Advanced Nano Manufacturing Enables Probing Fundamental Mechanical Behaviors of Materials Citation Zhang, Wenxin (2025) Advanced Nano Manufacturing Enables Probing Fundamental Mechanical Behaviors of Materials. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/fxq3-7817. https://resolver.caltech.edu/CaltechTHESIS:03132025-055626664 Abstract The trend of miniaturization has revolutionized modern technologies, with micro- and nanoscale materials driving transformative advancements in high-tech industries and scientific discovery. Among the various properties and applications enabled at these small scales, nanomechanical properties play a fundamental role, underpinning the integrity and functionality of any structures or systems. However, despite advancements in both conventional and emerging micro- and nano-manufacturing strategies, there has remained a lack of direct “bottom-up” experimental pathways to fabricate and probe the mechanical responses of submicron-sized monolithic nano-specimens with unconventional microstructures and/or 3D nano-architectures with submicron-sized features, particularly for non-carbon materials. In this work, I will present novel nano-fabrication and manufacturing strategies and their applications in addressing these nanomechanical challenges through three key studies. In Chapter 2, the deformation characteristic of organic ice is studied via cryogenic micro-compression and molecular dynamics simulations, providing insights into a benzene-ring re-orientation-mediated densification deformation route and offering new insights into planetary geology for celestial bodies such as Titan. In Chapter 3, we experimentally unveiled unprecedented two-regime size effects in additively manufactured metallic nanopillars with hierarchical microstructures, revealing a nanocrystallinity-, nanoporosity-mediated plasticity mechanism through atomistic insights. In Chapter 4, we extended this nano-manufacturing approach to explore nanoporosity-driven deformation behaviors in nano-architected metals with in situ experiments and finite element analysis. Together, these studies not only elucidate previously unprobed fundamental small-scale mechanical behaviors but also lay the groundwork for developing an advanced micro-to-nanoscale manufacturing platform, enabling complex systems and functional applications such as energy storage, biomedical microrobots, nanophotonics, and beyond, which I will briefly discuss in Chapter 5 as an outlook with a few examples from metal/oxide nanocomposites to interpenetrated pyrolytic carbon microarchitectures. Item Type: Thesis (Dissertation (Ph.D.)) Subject Keywords: Nanomechanics; Additive Manufacturing; Materials Characterization; Nanofabrication; Microstructure Degree Grantor: California Institute of Technology Division: Engineering and Applied Science Major Option: Mechanical Engineering Thesis Availability: Public (worldwide access) Research Advisor(s): Greer, Julia R. Thesis Committee: Ravichandran, Guruswami (chair) Pellegrino, Sergio Faber, Katherine T. Greer, Julia R. Defense Date: 12 March 2025 Funders: Funding Agency Grant Number NASA 80NM0018D0004 U.S. Department of Energy DE-SC0016945 Record Number: CaltechTHESIS:03132025-055626664 Persistent URL: https://resolver.caltech.edu/CaltechTHESIS:03132025-055626664 DOI: 10.7907/fxq3-7817 Related URLs: URL URL Type Description https://doi.org/10.1038/s41467-022-35647-x DOI Published doctoral work adapted for Chapter 2 https://doi.org/10.1021/acs.nanolett.3c02309 DOI Published doctoral work adapted for adapted for Chapter 3 https://doi.org/10.1038/s41467-024-52359-6 DOI Additional published doctoral work not adapted for the thesis https://doi.org/10.1002/adma.202308497 DOI Additional published doctoral work not adapted for the thesis https://doi.org/10.1038/s43586-025-00386-y DOI Published doctoral work adapted for Chapter 1 and 5 partly ORCID: Author ORCID Zhang, Wenxin 0000-0002-6318-0622 Default Usage Policy: No commercial reproduction, distribution, display or performance rights in this work are provided. ID Code: 17059 Collection: CaltechTHESIS Deposited By: Wenxin Zhang Deposited On: 15 Apr 2025 18:42 Last Modified: 15 Apr 2025 18:42 Thesis Files PDF (Redacted thesis - ch.4-5 omitted) - Final Version See Usage Policy. 13MB Video (AVI) (Movie 2.1) - Supplemental Material See Usage Policy. 105MB Video (AVI) (Movie 2.2) - Supplemental Material See Usage Policy. 45MB Video (AVI) (Movie 2.3) - Supplemental Material See Usage Policy. 69MB Video (AVI) (Movie 2.4) - Supplemental Material See Usage Policy. 51MB Video (AVI) (Movie 2.5) - Supplemental Material See Usage Policy. 70MB Video (AVI) (Movie 3.1) - Supplemental Material See Usage Policy. 4MB Video (AVI) (Movie 3.2) - Supplemental Material See Usage Policy. 16MB Video (AVI) (Movie 3.3) - Supplemental Material See Usage Policy. 9MB Repository Staff Only: item control page

Advanced Nano Manufacturing Enables Probing Fundamental Mechanical Behaviors of Materials Thesis by Wenxin Zhang In Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy CALIFORNIA INSTITUTE OF TECHNOLOGY Pasadena, California 2025 Defended March 12, 2025 ii © 2025 Wenxin Zhang ORCID: 0000-0002-6318-0622 All rights reserved iii 献给每一天 This work is dedicated to every day, and to you, who have taken the time to read this. May the spirit of curiosity, adventure, and persistence that guided this path inspire your own. :) iv ACKNOWLEDGEMENTS This thesis would not have been possible without the guidance, collaboration, and support of many incredible people. First and foremost, I would like to acknowledge my advisor, Prof. Julia R. Greer, for her mentorship, passion, and insights. I am also sincerely grateful to my thesis committee chair, Prof. Guruswami (Ravi) Ravichandran, and thesis committee members, Prof. Sergio Pellegrino and Prof. Katherine Faber, for their invaluable feedback, encouragement, and thought-provoking discussions that have strengthened my work. I have been incredibly fortunate to collaborate with a brilliant researcher and mentor—Prof. Huajian Gao—and his group, Dr. Zhi Li and Prof. Xuan Zhang. I also benefit tremendously from working with a number of Greer Group members: Prof. Rebecca A. Gallivan, Dr. Sammy Shaker, soon-to-be-Dr. Thomas Tran, and younger peers including Yingjin Wang and Kaiyu Zhao. I would like to thank many other co-authors listed in the Published Content and Contributions section. Your insights, discussions, and shared curiosity have made the journey all the more rewarding. I gratefully acknowledge the Jet Propulsion Laboratory’s Research and Technology Development Program and the Department of Energy, Office of Science’s Basic Energy Sciences program for funding the works. I express special thanks to the UC Irvine Materials Research Institute, especially Dr. Mingjie Xu, Dr. Toshihiro Aoki, and Dr. Jian-Guo Zheng, for their invaluable technical assistance and expertise. Beyond research, I am incredibly thankful for the friendships and companionships that have sustained me through this journey. v ABSTRACT The trend of miniaturization has revolutionized modern technologies, with micro- and nanoscale materials driving transformative advancements in high-tech industries and scientific discovery. Among the various properties and applications enabled at these small scales, nanomechanical properties play a fundamental role, underpinning the integrity and functionality of any structures or systems. However, despite advancements in both conventional and emerging micro- and nano-manufacturing strategies, there has remained a lack of direct “bottom-up” experimental pathways to fabricate and probe the mechanical responses of submicron-sized monolithic nano-specimens with unconventional microstructures and/or 3D nano-architectures with submicron-sized features, particularly for non-carbon materials. In this work, I will present novel nano-fabrication and manufacturing strategies and their applications in addressing these nanomechanical challenges through three key studies. In Chapter 2, the deformation characteristic of organic ice is studied via cryogenic microcompression and molecular dynamics simulations, providing insights into a benzene-ring reorientation-mediated densification deformation route and offering new insights into planetary geology for celestial bodies such as Titan. In Chapter 3, we experimentally unveiled unprecedented two-regime size effects in additively manufactured metallic nanopillars with hierarchical microstructures, revealing a nanocrystallinity-, nanoporositymediated plasticity mechanism through atomistic insights. In Chapter 4, we extended this nano-manufacturing approach to explore nanoporosity-driven deformation behaviors in nano-architected metals with in situ experiments and finite element analysis. Together, these studies not only elucidate previously unprobed fundamental small-scale mechanical behaviors but also lay the groundwork for developing an advanced micro-to-nanoscale manufacturing platform, enabling complex systems and functional applications such as energy storage, biomedical microrobots, nanophotonics, and beyond, which I will briefly discuss in Chapter 5 as an outlook with a few examples from metal/oxide nanocomposites to interpenetrated pyrolytic carbon microarchitectures. . vi PUBLISHED CONTENT AND CONTRIBUTIONS Chapter 1 and 5 have partly been adapted from: 1. Skliutas, E., Merkininkaite, G., Maruo, S., Zhang, W., Chen, W., Deng, W., Greer, J.R., von Freymann, G., Malinauskas, M. “Multiphoton 3D Lithography.” Nature Reviews Methods Primers 5, 15. (2025) DOI: https://doi.org/10.1038/s43586-025-00386-y Contributions: W.Z. wrote and revised sections of the manuscript. Chapter 2 has been adapted from: 2. Zhang, W., Zhang X., Edwards, B., Zhong, L., Gao, H., Malaska, M., Hodyss, R., Greer, J. “Deformation characteristics of solid-state benzene as a step towards understanding planetary geology.” Nature Communications 13, 7949. (2022) DOI: https://doi.org/10.1038/s41467-022-35647-x Contributions: W.Z. performed investigations and analysis and wrote and revised the manuscript. Chapter 3 has been adapted from: 3. Zhang, W., Li, Z., Dang, R., Tran, T.T., Gallivan, R.A., Gao, H., Greer, J.R. “Suppressed Size Effect in Nanopillars with Hierarchical Microstructures Enabled by Nanoscale Additive Manufacturing.” Nano Letters 23(17) 8162. (2023) DOI: https://doi.org/10.1021/acs.nanolett.3c02309 Contributions: W.Z. conceived the study, performed experimental investigations and analysis, and wrote and revised the manuscript. Chapter 4 has been adapted from: 4. Zhang, W., Li, Z., Gao, H., Greer, J.R. “Hydrogel-Infusion-Based Additive Manufacturing of Nano-Architected Metals – Exploring the Nanoporosity-Driven Deformation Regime.” Under review. (2025) Contributions: W.Z. conceived the study, performed experimental investigations and analysis, and wrote the manuscript. vii Section 5.1 has been adapted from: 5. Zhang, W., Greer, J.R. “Additively Manufactured Metal/Oxides Nanocomposites with Composition-dependent Microstructures and Strengths.” In preparation. Contributions: W.Z. conceived the study, performed experimental investigations and analysis, and wrote the manuscript. Chapter 6 has partly been adapted from: 6. Serles, P., Ji, Y., Zhang, W., et al. “Nanoscale Metals via Additive Manufacturing.” In preparation. Contributions: W.Z. wrote sections of the manuscript. Not directly adapted in this thesis: 7. Li, Z., Bhardwaj, A., He, J., Zhang, W., Tran, T.T., Li, Y., McClung, A., Nuguri, S., Watkins, J.J., Lee, S-W. “Nanoporous amorphous carbon nanopillars with lightweight, ultrahigh strength, large fracture strain, and high damping capability.” Nature Communications 15, 8151. (2024) DOI: 10.1038/s41467-024-52359-6. Contributions: W.Z. performed in situ nanomechanical experimental investigations. 8. Koch, T., Zhang, W., Tran, T.T., Wang, Y., Mikitisin, A., Puchhammer, J., Greer, J.R., Ovsianikov, A., Chalupa-Gantner, F., Lunzer, M. “Approaching Standardization: Mechanical Material Testing of Macroscopic Two ‐ Photon Polymerized Specimens.” Advanced Materials, 2308497. (2024) DOI: 10.1002/adma.202308497. Contributions: W.Z. performed parts of experimental investigations and analysis and revised the manuscript. viii TABLE OF CONTENTS Acknowledgements ........................................................................................... iv Abstract ...............................................................................................................v Published Content and Contributions ............................................................... vi Table of Contents ............................................................................................ viii List of Figures .................................................................................................... x List of Tables .................................................................................................... xv Chapter 1: Background ........................................................................................ 1 Chapter 2: Deformation Characteristics of Solid-State Benzene as a Step Towards Understanding Planetary Geology .................................................................... 13 2.1 Overview ............................................................................................... 13 2.2 Introduction .......................................................................................... 13 2.3 Methods ................................................................................................. 15 2.3.1 In situ nanomechanical experiments.............................................. 15 2.3.2 Microstructure Analysis via cryo-TEM ......................................... 18 2.3.3 Atomistic Simulations .................................................................... 18 2.4 Results .................................................................................................... 21 2.4.1 Mechanical response of benzene microcrystal under in situ compression ...................................................................................................................... 21 2.4.2 Crystallinity of the cryogenically formed solid-state benzene ..... 28 2.4.3 Atomistic densification mechanism of solid-state benzene ......... 29 2.5 Discussion & Conclusions ................................................................... 36 Chapter 3: Suppressed and Escalated Size Effect in Nanopillars with Hierarchical Microstructures Enabled by Nanoscale Additive Manufacturing .................... 40 3.1 Overview ............................................................................................... 40 3.2 Introduction .......................................................................................... 40 3.3 Methods ................................................................................................ 43 3.3.1 Sample fabrication ......................................................................... 43 3.3.2 Microstructure characterizations.................................................... 44 3.3.3 In situ nanomechanical experiments.............................................. 45 3.3.4 Molecular dynamics simulations ................................................... 46 3.4 Results ................................................................................................... 47 3.4.1 Microstructure characterizations.................................................... 47 3.4.2 In situ compression experiments ................................................... 51 3.4.3 Molecular dynamics simulations of Ni nanopillar in suppressed size effect regime .......................................................................................................... 54 3.5 Discussion ............................................................................................. 57 3.5.1 Kinetically- and chemically-driven microstructure ...................... 57 3.5.2 Size-dependent nanopillar strength................................................ 58 3.5.3 On Ni size effect (suppressed size effect regime) ......................... 60 3.6 Conclusion and outlook......................................................................... 63 ix Chapter 4: Hydrogel infusion-based Additive Manufacturing of Nano-architected Metals —Exploring the Nanoporosity-driven Deformation ........................................ 65 4.1 Overview................................................................................................ 65 4.2 Introduction .......................................................................................... 65 4.3 Methods ................................................................................................. 67 4.3.1 Fabrication ...................................................................................... 67 4.3.2 Nanomechanical experiments ........................................................ 68 4.3.3 Finite element simulations ............................................................. 69 4.4 Results .................................................................................................... 70 4.4.1 Two-photon-lithography-based additive manufacturing of metallic nanoarchitectures ......................................................................................... 70 4.4.2 In situ nano-compression unveiling structure-independent, size-dependent mechanical behaviors .................................................................................. 74 4.4.3 Size-dependent defect as the origin of nanomechanical behavior of nanoarchitectures ......................................................................................... 81 4.4.4 Multi-hierarchy finite element analysis of nanoarchitectures ....... 84 4.4.5 Nano-AM Ni nanoarchitectures with unprecedented structural integrity and specific strengths ........................................................................................ 91 4.5 Conclusions ........................................................................................... 93 Chapter 5: Outlook: a Micro-to-nanoscale Advanced Manufacturing Platform for Complex Systems and Energy Applications ..................................................................... 95 5.1 Composition-dependent microstructure and mechanical behavior in multi-element, additively manufactured metal/ceramic nanocomposites .......................... 97 5.2 Metal/carbon nanocomposites via vacuum HIAM — microstructure and magnetic perperties .................................................................................................... 111 5.3 Interpenetrated microlattices for battery ............................................. 120 5.4 Outlook ................................................................................................ 128 Chapter 6: Concluding Remarks ..................................................................... 131 Bibliography .................................................................................................... 136 Appendix A: Supplementary Information for Chapter 2 ................................ 154 Appendix B: Supplementary Information for Chapter 3 ................................ 157 x LIST OF FIGURES Figure 1.1: Novel nano-to-microscale functional applications enabled by nanoscale advanced manufacturing ...................................................................................................... 2 Figure 1.2: Micro-to-nanoscale mechanical studies enabled by multi-photon 3D lithiography advanced manufacturing ...................................................................................... 3 Figure 1.3: Nanomechanical discoveries in fcc metals ...................................... 5 Figure 1.4: Metal additive manufacturing from macro- to microscale .............. 6 Figure 1.5: Emerging field-assisted nano AM approaches ................................ 7 Figure 1.6: Schematics of electron interactions and signals in SEM ................. 9 Figure 1.7: Schematics of TEM in diffraction, imaging, & scanning mode .... 10 Figure 1.8: Electron scattering by a thin sample............................................... 11 Figure 1.9: Schematic of SEM-based in situ nanomechanical setup and comparison between stress-strain relationships measured by intrinsically displacement-controlled vs. loadcontrolled instruments ....................................................................................... 12 Figure 2.1: Schematics of cryogenic in situ nanomechanical experiment ....... 16 Figure 2.2: The load-time profiles of benzene microcrystal compression ...... 17 Figure 2.3: Benzene molecule orientations for MD simulations .................... 19 Figure 2.4: Deformation region cut-off criteria in MD .................................... 20 Figure 2.5: In situ nanomechanical experiment on benzene microcrystals ..... 22 Figure 2.6: Schematic of benzene microcrystal densification mechanisms .... 24 Figure 2.7: Identification of virgin-compression stiffness for higher-reload benzene microcrystal compression ................................................................................. 26 Figure 2.8: Identification of displacement bursts for higher-reload benzene microcrystal compression ....................................................................................................... 27 Figure 2.9: Estimation of longitudinal modulus of densified region in benzene microcrystal compression ....................................................................................................... 28 Figure 2.10: Microstructural and phase characterization of solid benzene...... 29 Figure 2.11: MD simulations on pyramidal benzene ....................................... 30 xi Figure 2.12: MD simulation showing collective re-orientation of benzene rings along the 45° local shear direction .................................................................................... 31 Figure 2.13: Atomistic deformation behavior in crystalline benzene .............. 32 Figure 2.14: Radial distribution function of densified region and solid benzene deformation mechanisms ........................................................................................................ 33 Figure 2.15: MD simulation showing the shear-strain evolution in a pyramidal benzene crystal ................................................................................................................. 34 Figure 2.16: Simulated contact pressure-normalized displacement relationship under different benzene pyramid orientations and temperatures ................................ 35 Figure 2.17: Radial distribution function of high-shear-strain region ............ 36 Figure 3.1: Additive manufacturing enables hierarchical microstructures at the nanopillar level .................................................................................................................... 42 Figure 3.2: Fabrication of nanoscale additively manufactured Ni .................. 43 Figure 3.3: Thermal treatment profiles for Ni ................................................. 44 Figure 3.4: Schematic of in situ nanopillar compression ................................ 46 Figure 3.5: Initial configuration of the MD-simulated pillars ......................... 47 Figure 3.6: Microstructural characterization of AM Ni nanopillars ................ 48 Figure 3.7: Size-dependent porosity in AM Ni nanopillars ............................. 50 Figure 3.8: Competing NiO nucleation mechanisms........................................ 51 Figure 3.9: In situ compression of Ni nanopillars — stress-strain relationships and failure behaviors ............................................................................................................ 52 Figure 3.10: Extrinsic size effects in Ni nanomechanics.................................. 53 Figure 3.11: Molecular dynamics simulation of Ni nanopillars compression . 54 Figure 3.12: Precursor-to-Weibull distribution fitting to nanopillar compression experimental results ........................................................................................... 59 Figure 3.13: Effect of porosity on compression strength of Ni nanopillars ..... 60 Figure 3.14: Deformation behavior of Ni nanopillars without internal voids . 61 Figure 3.15: Outlooks on the AM capability and applications......................... 64 Figure 4.1: Schematic of in situ compression using SEMentor ....................... 69 Figure 4.2: The size-dependent ultimate failure strengths of Ni nanopillars ... 70 xii Figure 4.3: Fabrication of nano-HIAM-Ni nanoarchitectures.......................... 71 Figure 4.4: Geometric properties of nanoarchitectures .................................... 73 Figure 4.5: In situ nanomechanical behaviors of nanoarchitectures. ............... 75 Figure 4.6: Precursor-to-Weibull distribution analysis of nano-HIAM-Ni nanopillar and nanoarchitecture ultimate strengths ................................................................... 81 Figure 4.7: Feature size-dependent nodal porosity in nanoarchitectures ......... 82 Figure 4.8: Material porosity properties in Schwarz-P nanolattice and spinodal-like nanoarchitecture ................................................................................................. 83 Figure 4.9: Material-level porosity properties from nano-HIAM-Ni nanopillars to nanoarchitectures ............................................................................................... 84 Figure 4.10: Mises stress distribution in nanoarchitectures ............................. 86 Figure 4.11: Correlation between the Mises stress distribution and geometric factors in spinodal-like architectures ................................................................................. 87 Figure 4.12: NN training results for the prediction of Mises stress distribution in Figure 4.11 ............................................................................................................................ 88 Figure 4.13: Finite element simulation of nanoarchitectures ........................... 89 Figure 4.14: Typical stress-strain curves from finite element simulations of octahedral nanolattices using beam-element models .......................................................... 90 Figure 4.15: Size dependence of the simulated lattice strengths ...................... 91 Figure 4.16: Mechanical performance of Ni nanoarchitectures ....................... 92 Figure 5.1: Relationship between Ni-to-Fe atomic ratio in infusion solution and that in oxide products ............................................................................................................ 100 Figure 5.2: Transmission electron microscopic characterizations of first-step thermal treatment products I ......................................................................................... 101 Figure 5.3: High-resolution TEM of Fe3O4 nanograins ................................ 102 Figure 5.4: Transmission electron microscopic characterizations of first-step thermal treatment products II ........................................................................................ 102 Figure 5.5: Composition-dependent microstructure in reduction products from the open-toair calcination samples ..................................................................................... 104 Figure 5.6: Phase assemblage characterization of AM nanocomposite ......... 106 xiii Figure 5.7: Electron energy loss spectroscopy mapping of metal/oxide nanocomposite .......................................................................................................................... 107 Figure 5.8: In situ Ni/magnetite nanocomposites micropillar compression .. 108 Figure 5.9: Composition-dependent strengths and deformability of Ni/magnetite nanocomposite micropillars............................................................................. 109 Figure 5.10: As-fabricated iron oxides nano-architectures ............................ 111 Figure 5.11: STEM characterizations of microstructures in vacuum HIAM metal-carbon nanocomposite microlattices ........................................................................... 114 Figure 5.12: STEM zoom-in view of phase assemblage and morphology variations in vacuum HIAM metal-carbon nanocomposites ............................................... 115 Figure 5.13: STEM-EDS map showing metal-carbon segregation at nanometer scale in the matrix phase ..................................................................................................... 115 Figure 5.14: High-resolution transmission electron microscopy characterizations of nanocrystalline-Ni/amorphous-C matrix......................................................... 116 Figure 5.15: High-resolution transmission electron microscopy characterizations of large area of graphitic carbon ................................................................................... 117 Figure 5.16: High-resolution transmission electron microscopy characterizations of interfacial area between large Ni nanograins and graphitic C regimes .......... 118 Figure 5.17: Magnetic hystersis comparison between CuNiFe via regular HIAM and vacuum HIAM ............................................................................................................... 119 Figure 5.18: Design and fabrication of interpenetrated microlattices ............ 122 Figure 5.19: Thermogravimetric analysis of photoresist decomposition ....... 122 Figure 5.20: Interpenetrated microlattices of pyrolytic hard carbon .............. 123 Figure 5.21: Mechanical response of pyrolytic hard carbon interpenetrated microlattice under compression ..................................................................................................... 124 Figure 5.22: Schematic of electroplating of lithium cobalt oxide .................. 126 Figure 5.23: SEM-EDS evidence of lithium cobalt oxide electroplating on hard carbon microlattice....................................................................................................... 127 Figure 5.24: Various materials treatment strategies to achieve multi-material and multifunctionality in nano-manufacturing . ............................................................. 128 xiv Figure 5.25: Diagram showing materials treatment strategies related to polymer 3D printing-based nano-manufacturing, expanding upon Figure 5.24. ............... 129 Figure 5.26: Development of hydrogel infusion-based advanced manufacturing platform for multi-material, functional applications. Micro-to-nanoscale coverage of HIAM for energy applications at distinc dimensions .................................................................. 130 Figure 6.1: Nanomechanical studies on nanoscale additively manufactured metals and metal oxides .............................................................................................................. 130 Figure A.1: Load & contact pressure-vs.-displacement relationships for the Same-Reload benzene microcrystal compression tests ........................................................ 148 Figure A.2: Load & contact pressure-vs.-displacement relationships for the Higher-Reload benzene microcrystal compression tests ......................................................... 149 xv LIST OF TABLES Table 2.1: Elastic constants of solid benzene ................................................... 37 Table 3.1: Difference in geometry and mechanical property of Ni nanopillars between the experiment and molecular dynamics simulation .............................................. 56 Table 4.1: Precursor-to-Weibull distribution least-square fitting results for nanoscale hydrogel infusion additive manufacturing (nano-HIAM) Ni nanopillars and nanoarchitectures ............................................................................................... 80 Table 5.1: Thermal treatment protocol comparison between regular HIAM and vacuum HIAM ............................................................................................................... 112 1 Chapter 1 BACKGROUND Why do we care about probing nanoscale properties of materials? The trend in miniaturizing almost every modern technology towards the micro- and nanoscale has transformed high-tech industries and fundamentally pushed forward the frontiers of scientific research. At these small dimensions, materials exhibit behaviors and properties distinctly distinguished from their bulk counterparts, unlocking novel functionalities and applications. For instance, quantum dots revolutionized imaging and display technologies through the nanoscale size-dependent, tunable optical properties(1); plasmonics harnesses free electron oscillations at metal-dielectric interfaces, allowing for light manipulation beyond the diffraction limit(2); furthermore, micro-robotics, nanofluidics, micro-photonics, nano-electronics, etc. leverage the unique size-enabled precision, controllability, tunability, enhanced performance, and complex functionalities in increasingly compact systems. These advancements are driving progresses in diverse fields, including targeted drug delivery(3), molecular synthesis(4), endoscopy(5), highperformance computing(6), and more. Understanding and harnessing the nanoscale properties of materials becomes more critical than ever before, which creates increasingly stringent demands on the advancement of nanomanufacturing towards smaller scales and greater precision. Figure 1.1 provides a glance at the nano-manufacturing capabilities for functional applications, exemplified by multi-photon lithography 3D printing (MP3DP) in micro-optics, nanomechanics, microrobots, catalysis, and cell mechanobiology with functional feature dimensions ranging 10s nanometers to 100s microns. 2 Figure 1.1 Novel nano-to-microscale functional applications enabled by nanoscale advanced manufacturing. Figures are adapted from (7–13) with permission. Copyright 2019 The Authors. AIP Publishing LLC. Copyright 2022 The Authors. Small published by WileyVCH GmbH. Copyright 2023 The Authors. Advanced Functional Materials published by Wiley-VCH GmbH. Copyright 2015 National Academy of Sciences. Copyright 2012 American Chemical Society. Copyright 2023 Optica Publishing Group. Copyright 2013 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Nanomechanical behaviors and properties are pivotal among all material characteristics, as the mechanical integrity of a structure underpins its functional application. Researchers have discovered unique mechanical enhancements in the micro-architectures of a variety of 3 materials including polymers, ceramics, metals, pyrolytic carbon, and polymer composites, as briefly summarized in Figure 1.1b and comprehensively detailed in Figure 1.2. Figure 1.2 Micro-to-nanoscale mechanical studies enabled by MP3DL advanced manufacturing. Figures are adapted from (10, 14–26) with permission. Copyright 2015 National Academy of Sciences. Copyright 2020 The Authors. Published by Wiley-VCH GmbH. Copyright 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. Copyright 2018 American Chemical Society. Copyright 2014 Natinoal Academy of Sciences. Copyright 2020 Natinoal Academy of Sciences. Copyright 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Copyright 4 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Copyright 2015 Elsevier Ltd. Copyright 2023 American Chemical Society. Copyright 2019, The Author(s), under exclusive licence to Springer Nature Limited. Copyright 2022 the Author(s). Published by PNAS. Copyright 2021, The Author(s), under exclusive licence to Springer Nature Limited. Copyright 2018, The Author(s). Published by Springer Nature. MP3DL uniquely enables bridging complex architectures and micro-to-nanoscale feature dimensions, paving the way for nanomechanical studies impossible otherwise. At the nanoscale, the mechanical properties and behavior of materials can significantly deviate from the macroscale due to size-induced mechanical enhancement. “Smaller is stronger” size effect discovered in metal nano/micropillars is manifested in MP3DL-derived copper microlattices whose strength at < 50% relative density past the bulk copper strength at full density (Figure 1.2I). For brittle materials, ceramics (for example, Al2O3), pyrolytic carbon, metallic glasses, etc., which MP3DL can derive with post-processing, as the characteristic feature dimension of the nano/micro-architecture decreases below the theoretical critical flaw size of the material, the nano-architecture gains flaw tolerance and improved deformability before catastrophic failure under mechanical loading. MP3DL/ALD-Al2O3 thin-shell microarchitectures with ~10–20 nm-thick walls and ~0.1–1% ultra-low relative density demonstrate extraordinary recoverability and resilience under cyclic compression for periodic lattices (Figure 1.2A) and stochastic geometries (Figure 1.2F). Core-shell polymerceramic/metal composite nanolattices are studied for flaw sensitivity and strengthrecoverability trade-offs (Figure 1.2A, C, and D). Pyrolytic carbon, whose micropillars could withstand 10 GPa at 40% compressive strain (Figure 1.2L), when MP3DL-fabricated into 3D lattices with submicron-sized features, have presented superior strengths (Figure 1.2M) and dynamic impact resilience (Figure 1.2N). Despite the remarkable discoveries in nanomechanical behaviors, fabrication has largely been constrained to micro-architectures. In many cases, achieving nanoscale dimensions relies on secondary templating treatments such as atomic layer deposition (ALD) and sputtering. These technical limitations hinder the fabrication of non-hollow, noncarbonaceous structures with submicron periodicity, which truly defines a nano-architecture. 5 Notably, the intriguing “smaller is stronger” phenomenon of metals has yet to be realized and harnessed until such nano-architectures can be experimentally fabricated. Conventionally, nanomechanical studies of metals have been realized with subtractive manufacturing, usually via focused-ion-beam (FIB) milling from a bulk stock material, which may contain different microstructures, including single-crystalline, nanocrystalline, nanotwinned, and nanoporous microstructures, each subject to their respective conventional manufacturing methods of thermal annealing, (pulsed) electrodeposition, and electrochemical de-alloying. As outlined in Figure 1.3, a “smaller is stronger” relationship— often referred to as the extrinsic size effect—is discovered in single-crystalline nanopillars of fcc metals, as explained by dislocation-surface-interaction-mediated plasticity mechanisms including dislocation starvation and nucleation and source truncation hardening; while nanocrystalline and nanotwinned metals exhibit the two-regime Hall-Petch (H-P) relation—or to be understood as an intrinsic size effect—explained by dislocation pile-up at grain boundaries in the classical H-P regime and grain boundary motions (rotation, sliding, annihilation, etc.) in the nanocrystalline inverse H-P regime. Besides, a nanoporous metal resembles an assembly of single-crystalline nano-ligaments, thus sharing similar surface dislocation nucleation and multiplication-mediated deformation mechanisms and benefit from the extrinsic size effect dictated by the nano-ligament dimension. Figure 1.3 Nanomechanical discoveries in fcc metals. Figures are adapted from (27–34) with permission. Copyright 2007 Springer Nature Limited. Copyright 2011 Elsevier Ltd. Copyright 2016 Taylor & Francis. Copyright 2019, The Author(s). Published by Springer Nature. Copyright 2014, The Author(s). Published by Springer Nature. Copyright 2006 6 American Chemical Society. Copyright 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Copyright 2009 American Association for the Advancement of Science. It is important to note that despite the extensive nanopillar studies of fcc metals, conventional experimental methodologies heavily rely on FIB preparation with Ga ions, the bombarding and embedding effects of often compromises the pristine nature of the nano-metal samples, potentially introducing artifacts such as altered dislocation density distributions. These effects could contribute to discrepancies between experimental conditions and results and computational/theoretical assumptions and predictions. Alternatively, nano-crystal or nanowire growth offer a damage-free approach but are highly restricted in terms of achievable microstructures, which are typically limited to single-crystalline forms. Advanced manufacturing, particularly additive manufacturing (AM), offers new “bottom-up” experimental opportunities by transforming traditional fabrication approaches. Metal AM is revolutionizing the conventional strategies such as subtractive manufacturing (e.g., milling, lathing), molding, and forging, while enabling unprecedented 3D freeform capabilities. Figure 1.4 highlights advancements in metal AM across length scales: from macroscale wirebased rapid plasma deposition of titanium (Figure 1.4A), to mesoscale powder-based electron beam melting of titanium alloys (Figure 1.4B), to tens-to-hundreds-of-microns-scale selective laser sintering of silver (Figure 1.4C), and to single-micron-scale laser-assisted direct ink writing (DIW) of silver (Figure 1.4D). Figure 1.4 Metal additive manufacturing from macro- to microscale. Figures are adapted from (35–38) with permission. Copyright 2009 Elsevier Ltd. Copyright 2019, The Author(s). Published by Springer Nature. Copyright 2016 National Academy of Sciences. 7 However, these methods are yet to approach the submicron-scale resolutions due to two major obstacles to further resolution refinement: (1) the finite size of metal precursors (from macro-wire to micro-powder to nanoparticle-loaded ink) and (2) the limited focusing strength of energy sources (laser or electron beam) and the size of DIW nozzles. Overcoming these challenges will require innovative developments in nano-manufacturing of metals, specifically towards continued miniaturization of the precursor form and the energy deposition mechanism, which this work will explore in detail. Granted, it is worth mentioning emerging nano-manufacturing strategies that have shown preliminary success in fabricating truly nanosized metal parts. These methods are commonly field-assisted, such as electrohydrodynamic redox 3D printing, electrohydrodynamic inkjet printing, and meniscus confined electrodeposition, as shown Figure 1.5A, B, and C, respectively. These methods are promising but may be limited in throughput or materials choices, which the present work aims at addressing through a vat-polymerization-based, field-free nano-manufacturing solution. Figure 1.5 Emerging field-assisted nano AM approaches. Figures are adapted from (39–41) with permission. Copyright 2019, The Author(s). Published by Springer Nature. Copyright 2012 American Chemical Society. Copyright 2021 The Authors. Electrochemical Science Advances published by Wiley‐VCH GmbH. Two experimental methods are fundamental to the present work on probing fundamental mechanical behaviors of materials enabled by advanced nano-manufacturing and will frequently make presence in the following Chapters 2–5: (1) electron microscopy and (2) in situ nanomechanical characterization. 8 Scanning electron microscopy (SEM). SEM is one of the most versatile instruments for material surface examination and analysis of microstructural morphology and chemical compositions at a superior resolution up to 1s nm.(42) Every SEM comprises an electron gun at the top of the electron column, which produces electrons and accelerates them to an energy level of 0.5–30 keV, a series of electromagnetic lenses and apertures through the column, which focuses and defines a highly focused electron spot under scanning motion on the specimen in the high-vacuum chamber underneath the column. The primary electrons (PE) from the electron column interact with the specimen in multiple ways and create multiple types of signals for detection. Illustrated in Figure 1.6A–C are the three primary interaction types of (A) inelastic collision, where low-energy secondary electrons (SE) are created, (B) elastic interaction, where PE are transformed into backscatter electrons (BSE) preserving most of their energy, and (C) characteristic X-ray emission, induced when an outer-shell electron fills an inner-shell vacancy created by inelastic collision of PE and emission of SE. Figure 1.6D shows how SE, BSE, and characteristic X-ray signals are collected by various detectors differently located in the high-vacuum specimen chamber. While SE primarily yields topographical contrast, BSE provides significant atomic number contrast due to the elastic electron-nucleus interaction nature of the backscatter event, and the characteristic Xray distinguishes the elemental composition based on the element-specific energy of the electron shells. 9 Figure 1.6 Schematics of electron interactions and signals in SEM. Figures are adapted from the presentation of Dr. Matthew Hunt at Kavli Nanoscience Institute at Caltech. Copyright 2019 Matthew Hunt. Transmission electron microscopy (TEM). TEM is a more sophisticated instrument compared to SEM. TEM comprises more electromagnetic lenses and apertures, which enable more operation modes for diffraction and imaging. While TEM has significantly more stringent requirement for vacuum conditions, vibration isolation, sample quality, and thickness (< 100 nm), it achieves extremely high spatial resolution of ~ 1–2 Å at electron accelerating voltages of 100-300 kV.(43) Figure 1.7A–B shows the beam diagram of TEM under diffraction mode and imaging mode, respectively, differed by the focusing strengths of the intermediate lens. In the diffraction mode, insertion of a selected-area-diffraction (SAD) aperture could allow for diffraction pattern acquisition of selected specimen area; in imaging mode, insertion of an objective aperture on the back focal plane could lead to brightfield (BF; aperture on the transmitted beam) or dark-field (DF; aperture on a diffraction spot) 10 mode imaging, enhancing the imaging contrast from crystallographic orientation difference and lattice defects (dislocations, stacking faults, etc.). Figure 1.7 Schematics of TEM in (A) diffraction mode, (B) imaging mode, and (C) scanning mode. Figures are adapted from (44, 45) with permission. Copyright 2006 Yougui Liao. Copyright 2021 Elsevier Inc. TEM may have the specialized function as a scanning transmission electron microscope (STEM) by incorporating a set of deflection scan coils (probe-forming lens in Figure 1.7C) and focusing the electron beam to an extremely fine spot. The spatial resolution of STEM is reported to be as high as 40.5 pm using 300 kV STEM equipped with fifth-order aberration corrector(46). As shown in Figure 1.7C, STEM mode involves a series of specialized detectors: BF-STEM detector located in the path of the transmitted electron beam, an annular DF-STEM detector to collect the (Bragg) scattered electrons, and a high-angle annular darkfield (HAADF) detector to collect very high-angle, incoherently (Rutherford-like) scattered electrons, suited for Z-contrast imaging. The placement of these detectors may be understood in the context of various types of interactions between an electron and a thin sample, as illustrated in Figure 1.8. As in SEM, the characteristic X-ray allows for energy dispersive Xray spectroscopy (EDS) in STEM, but STEM additionally enables electron energy loss spectroscopy (EELS) with the use of an EELS spectrometer consisting of energy selecting slits downstream of the BF-STEM detector which collects transmitted electrons and analyze 11 the energy loss of those who are inelastically scattered (Figure 1.8 – red) to unveil the element-specific core-loss fine-structures containing insights into the material’s (the element’s) electron structure, bonding, and local chemical environment. Figure 1.8 Electron scattering by a thin sample. The figure is adapted from (43) with permission. Copyright 2017 Springer Science+Business Media New York. In situ nanomechanics. SEM-based in situ nanomechanical characterization is a powerful method to measure the mechanical response (force and displacement) and simultaneously observe the deformation behavior of a specimen under different modes and setups including tension, compression, shear, fracture, and nanoindentation. These capabilities are commonly realized by the modular nanomechanical testing system, as shown in Figure 1.9. With a highly compact design, it can be directly mounted into an SEM chamber. The two primary components of the nanomechanical module are the indenter head and the sample stage. The indenter head has adjustable indenter tip geometries, including Berkovich tip for nanoindentation, flat punch for compression, micro-grips for tension, and so on and is confined to only axial motion, i.e., extension and retraction. The sample stage, on the other hand, holds the sample substrate perpendicular to the axial direction and is confined to lateral motion for specimen locating purposes. In typical systems, force and displacement are exerted or measured only in the axial direction through functions of the indenter head. The mainstream nanomechanical systems have two distinct control mechanisms (Figure 1.9): (1) the more traditional load-control mechanism is usually realized with a transducer where the force is applied through a voltage signal, the displacement is measured from 12 capacitance change, and displacement rate is controlled by adjusting loads through a feedback loop; it thus suffers from instability and artificial displacement bursts. (2) the emerging true displacement control is achieved by piezoelectric-driven mechanism, and the force is measured with a high-stiffness, in-series single-crystalline Si MEMS force sensor. It fundamentally precludes instability and avoids the artificial signature of the transducer-spring-compliance-induced displacement burst in load-controlled systems. Figure 1.9 Schematic of SEM-based in situ nanomechanical setup and comparison between stress-strain relationships measured by intrinsically displacement-controlled vs. loadcontrolled instruments. The combination of electron microscopy techniques, including SEM and TEM, with in situ nanomechanical characterization provides a powerful platform for in-depth investigation of the microstructural and mechanical properties of a wide spectrum of materials, including metals, carbonaceous materials, ceramcis, composites, and even organic ice, at the atomic to microscale. Fascinating research studies based around these experimental methods will be presented in the next chapters of this work. 13 Chapter 2 DEFORMATION CHARACTERISTICS OF SOLID-STATE BENZENE AS A STEP TOWARDS UNDERSTANDING PLANETARY GEOLOGY 2.1 Overview Small organic molecules, like ethane and benzene, are ubiquitous in the atmosphere and surface of Saturn’s largest moon Titan, forming plains, dunes, canyons, and other surface features. Understanding Titan’s dynamic geology and designing future landing missions requires sufficient knowledge of the mechanical characteristics of these solid-state organic minerals, which is currently lacking. To understand the deformation and mechanical properties of a representative solid organic material at space-relevant temperatures, we freeze liquid micro-droplets of benzene to form ~10 μm-tall single-crystalline pyramids and uniaxially compress them in situ. These micromechanical experiments reveal contact pressures decaying from ~2 to ~0.5 GPa after ~1 μm-reduction in pyramid height. The deformation occurs via a series of stochastic (~5–30 nm) displacement bursts, corresponding to densification and stiffening of the compressed material during cyclic loading to progressively higher loads. Molecular dynamics simulations reveal predominantly plastic deformation and densified region formation by the re-orientation and interplanar shear of benzene rings, providing a two-step stiffening mechanism. This work demonstrates the feasibility of in situ cryogenic nanomechanical characterization of solid organics as a pathway to gain insights into the geophysics of planetary bodies. 2.2 Introduction Simple organic molecules—e.g., ethane(47) and benzene(48)—exist in gas and liquid phases in Earth’s atmosphere and surface. These molecules are also found to be ubiquitous on another planetary body in the solar system, Titan, the largest moon of Saturn(49). The Cassini-Huygens mission—two spacecrafts, one for orbiting Saturn, the other for landing on Titan—has revealed that Titan’s thick nitrogen and methane-rich atmosphere enabled dynamic weathers, precipitation, and surface liquids. Many aeolian, pluvial, and fluvial geological processes, similar to Earth’s, have been observed on Titan to produce rivers, 14 canyons, lakes, and dunes(50). At the average temperature of ~94 K, Titan’s “hydrology” and landforms consist not of liquid water and silicates, but predominantly liquid methane and a mixture of water ice and solid organics that originated through complex photochemical processes in the upper atmosphere(51). Equipped with the instruments including the Radio Detection and Ranging instrument (RADAR) and Visual and Infrared Mapping Spectrometer (VIMS), Cassini-Huygens mapped the surface morphology of Titan, whose hazy organic atmosphere hinders visualbased observation of the surface. Titan’s surface was identified as being composed of multiple components, including 14% of hummocky/mountainous terrains which are the oldest on Titan, and 17% of dunes which are relatively young(52–54). Infrared spectral analysis(55) and microwave radiometry(56) reveal the dunes to be composed of organic materials. Limited data has led to the formulation of multiple competing theories to explain the fundamental mineralogy and geology of Titan. From dune sand transport distances(57, 58), eolian(59) and fluvial(60) erosion, karst(61) and yardang(62) formation, to putative cryovolcanic processes(63), many distinguishing mechanisms of these processes are dictated by the largely unexplored fundamental mechanical properties of the frozen organic minerals. Photochemical models have predicted the formation of benzene in Titan atmosphere(64) and through chemical transformation from acetylene in dunes(65). Single crystalline benzene (as well as its co-crystals with ethane(49), acetonitrile(66), and acetylene(67), etc.) has been proposed as a potential proxy candidate of the Titan surface mineralogy(51). Various solid benzene derivatives have demonstrated intriguing mechanical properties. For example, tens-of-micron-wide crystalline hexachlorobenzene exhibits ~360° bending with a local radius of curvature comparable to the width while retaining its macroscopic integrity, presumably enabled by anisotropic supramolecular interactions(68). Existing studies on solid benzene include high pressure solid phases of benzene(69–71), high-pressure hightemperature equation of state calculations(72) and phase diagram maps(73), superconductivity of solid benzene under high pressure(74), stress-induced amorphization(75), and polymerization of benzene into carbon nanothreads(76). However, 15 the basic mechanical properties and deformation mechanism of benzene (and of other molecular proxies) in the solid state and at space relevant temperatures remain open questions and hinder further understanding of the geophysics and surface topographies of Titan and other cold solar system bodies. In this work, we freeze liquid micro-droplets of benzene into micro-pyramids, perform uniaxial compression in situ, and corroborate with molecular dynamics simulations, unveiling that crystalline benzene plastically deforms via benzene rings densification, collective reorientation, and gliding according to the local shear direction. We demonstrate the significance of in situ cryogenic nanomechanical characterizations of solid organics towards insights on planetary geophysical studies. 2.3 Methods 2.3.1 In situ Nanomechanical Experiments The compression experiments were performed with an in situ nanomechanical instrument(77), which (i) enables applying mechanical loads with prescribed schedule, (ii) allows simultaneously collecting mechanical data and observing the deformation in a scanning electron microscope (SEM), and (iii) functions at a wide temperature range. The schematic of the experimental set-ups is shown in Figure 2.1a–c. During the experiment, the sample holder (Ted Pella standard pin mount aluminum SEM stub) was cooled to ~125 K with a copper cooling line (40 K to 400 K capability from Janis Research Company) chilled by liquid nitrogen in an SEM chamber (Quanta 200, ThermoFischer Scientific). The chamber is evacuated (~10-5 mbar) and equipped with a nanomechanical testing module (InSEMTM from Nanomechanics Inc.; force noise floor < 200 nN; displacement noise floor < 0.1 nm). After pre-cooling the sample holder, the chamber was then opened into an N2-purged glove bag (oxygen levels below 2% measured by an MSA ALTAIR® O2 Pro) to minimize water condensation onto the cooled components. Several milliliters of anhydrous benzene (Sigma Aldrich 99.8%) were dropped onto the sample holder tilted by ~30° relative to the floor. Until a visibly sufficient amount of benzene was frozen on the sample holder, the chamber was closed and re-evacuated. The stage temperature typically increased from ~125 K to ~180 K 16 during the short window when the chamber door was opened to freeze the sample and then decreased after the chamber was closed and re-equilibrated for ~2 hours. Figure 2.1 Schematics of cryogenic in situ nanomechanical experiment. (a) Schematic of in situ freezing of benzene droplet. (b) Schematic of the cryogenic in situ nanomechanical compression of benzene solid. (c) Picture of the in situ SEM nanomechanics instrument, attached to the glove bag and connected to the liquid nitrogen cryogenic cooling system. (d and e) SEM images of massive pyramidal benzene crystals and one zoom-in benzene pyramid with the nanomechanical indenter flat punch above (background is shaded, and the indenter and the crystallite are outlined for eye guide). 17 The sample was scanned with SEM to identify crystals whose cuboid-corner closely points towards the indenter; then, the corner orientation was manually adjusted to minimize possible misalignment (Figure 2.1d). Compressions of individual cuboid solid benzene crystals were performed with a ~7 µm-diameter diamond flat-punch indenter tip (Figure 2.1e). Two cyclic loading profiles were employed: repeated compressions to a particular load (referred to as same-reload tests) and successive compressions to progressively higher loads (referred to as higher-reload tests), as illustrated in Figure 2.2A–B. The same-reload experiments were conducted at temperatures of 123.39 ± 0.99 K, and the higher-reload ones at 144.40 ± 0.35 K, while the temperature effect is discussed in latter sections. The constant loading rates were 41 or 61 µN s-1 up to maximal loads of ≤ 1.5 mN. The data collection rate was 100 Hz. The results are summarized in Appendix A Figures A.1 and A.2. Note that the noisiness in the raw data primarily resulted from the liquid N2 influx and evaporation in the cryostat installed on one of the ports on the SEM chamber. Figure 2.2 The load-time profiles of benzene microcrystal compression for (A) samereload and (B) higher-reload tests. Calculation of contact pressure. The pyramidal sample geometry lends itself to the calculation of contact pressure, as representation of the compressive stress. Contact pressure Pcontact is defined as the ratio between the real-time load F and the instantaneous contact area Acontact between the indenter tip and the sample, or Pcontact = F/Acontact eq. 2.1 For an ideal cuboid-corner pyramidal geometry, at displacement h, Acontact = 33/2h2/2 eq. 2.2 18 Given minimal bulging was observed in SEM during compression, the self-similar crosssection assumption is valid. For the real experimental data, the finite curvature at the apex of the crystal is taken into account. The adjusted contact area is Acontact = 33/2(h+δ)2/2 eq. 2.3 With δ < 50 nm based on specific SEM observation. The contact pressure is then Pcontact = 2F/[33/2(h+δ)2] eq. 2.4 2.3.2 Microstructure Analysis via cryo-transmission electron microscopy Additional solid benzene sample was prepared for microstructural analysis via cryotramission electron microscopy (TEM) by first blotting 3 µL of liquid benzene on a lacey carbon TEM grid at a blot force setting of -15 at 10 °C for 0.5 s in an FEI Vitrobot Mark IV and then plunging it into liquid nitrogen. The sample was kept in liquid nitrogen during transfer to the TEM (Talos Arctica, ThermoFisher Scientific) and imaged at 77 K with the field emission gun operating at 200 kV and a 4k x 4k FEI Falcon II direct electron detector. A 10-µm selected area diffraction (SAD) aperture was used to isolate information from an individual crystal during diffraction pattern acquisition. 2.3.3 Atomistic Simulations We carried out a series of large-scale atomistic simulations to emulate the uniaxial compression of solid benzene corner using LAMMPS(78). In all simulations a reactive potential for hydrocarbons with intermolecular interactions, also called AIREBO potential(79), was used to describe both the intramolecular and intermolecular interactions. Such a force field can both describe the covalent bonding interactions and the torsion, dispersion, and nonbonded repulsion interactions via an adaptive treatment, which enables it to capture the chemical reactions, e.g., the breakage and formation of the carbon-carbon bonds, in the hydrocarbon system. The corner sample was extracted by cutting a triangular pyramid shape from a bulk solid benzene with the crystalline phase Pbca (lattice parameters of 7.644 Å, 9.514 Å, and 6.720 Å), approximately consistent with the experimental phase characterization. The heights of the corner samples were determined as 10 nm, 20 nm, and 30 nm separately, further to perform uniaxial deformation simulations. We selected three 19 loading directions: [010], [110], and [011], which were perpendicular to the base of the triangular pyramid. The orientation of the lateral faces was shown in Figure 2.3. Figure 2.3 Benzene molecule orientations for MD simulations. Shown are the benzene molecule orientations in the lateral face of the pyramidal sample for simulations under different loading directions. At the bottom of the sample, the section of one-tenth height was fully fixed; otherwise, the upper section was deformable. The corner sample was relaxed at 10 K for 200 ps under a canonical (NVT) ensemble. During deformation process, a rigid indenter was used to compress and release the corner sample at a loading rate 5×108 s-1 up to 40% of the total height. The temperature effect on the deformation process was also investigated. The temperature during the simulations was fixed at 10 K, 20 K, and 30 K separately to repeat all the simulations with samples of different heights and different loading directions described above. During the simulations, the force exerted on the indenter in the loading direction was outputted as the external force exerted on the overall sample so that the load-displacement curve for the simulation can be obtained. Subsequently, we used OVITO software to postprocess the simulation results(80). We transferred the load-displacement curves to the contact pressure-normalized displacement curves for convenient comparisons between simulation cases on different sample sizes. The contact area was determined by making a surface mesh from the full atomic models with the OVITO package. The contact pressure was calculated as the load divided by the contact area; the normalized displacement was calculated as the displacement divided by the initial height of the triangular pyramid. The shear strain was also calculated in OVITO for further coloring the atoms(81). 20 Calculation of Radial Distribution Functions from MD results. Based on observations, we isolated the molecules of the densification regions by selecting the atoms in OVITO that satisfy non-affine square displacement > 100 and shear strain < 0.5 with cut-off radius of 10 Å (example given in Figure 2.4). And then the radial distribution function (RDF) of C-C pairs was calculated in OVITO, setting the cut-off of 15 Å, and all curves are normalized by the height of the first peak. Figure 2.4 Deformation region cut-off criteria in MD. Selection of the densification region using parameters of non-affine square displacement > 100 and shear strain < 0.5 set in software OVITO. Calculation of Density Distributions from MD results. We used the following method to plot the density distribution: we calculated the coordination number (CN) of carbon atoms around one carbon atom within a cut-off of 8 Å and calculate the density of this position by the equation: 𝜌𝐴𝑡𝑜𝑚 = (CN+1)×13×𝑚 4/3×𝜋𝑅 3 eq. 2.5 Where m is the atomic mass constant, which is 1.66 × 10−27 kg, R is the cut-off radius. By substituting the initial lattice constants of the solid benzene for MD simulations, we can calculate the initial density of the sample as: 21 𝜌𝑖𝑛𝑖𝑡𝑖𝑎𝑙 = 24×13×𝑚 𝑎𝑏𝑐 = 1.05977 g cm−3 eq. 2.6 which is consistent with the initial density distribution in MD videos (Movies 2.2–2.4). 2.4 Results 2.4.1 Mechanical response of benzene microcrystal under in situ compression We performed in situ nanomechanical experiments and atomistic simulations on solid-state benzene micro-crystals, as the representative solid organic material. To create solid-state samples, liquid benzene droplets were first dispensed from a pipette onto a standard SEM stub mounted on a liquid nitrogen-cooled cryogenic sample stage in a scanning electron microscope (SEM) chamber within a custom-built nanomechanical instrument connected to a nitrogen-purged glove-bag (Figure 2.1a). The chamber was then immediately closed and pumped to ~10-5 mbar, while the droplets were flash-frozen on contact with a stage held at ~125 K to form multiple ~10 µm-tall cuboid pyramids (Figure 2.1b–e). The sample stage was then tilted to align the micro-pyramids to be amenable to uniaxial compression with initial contact at the apex, deforming uniformly towards the base (Figure 2.5a and Movie 2.1). The pyramidal shape of the benzene crystals is practically a non-standard geometry for mechanical measurements as explained in Methods. It was difficult to reshape or control the geometry as it was formed naturally when the droplets freely fell on the cryogenic stage; still, we need always keep in mind that the plots of posterior forcedisplacement curves and the ways for extracting the modulus are not standard. Monotonic and cyclical in situ quasi-static micro-compressions on the individual benzene pyramids were performed at a constant loading rate ~50 µN s-1 at ~125–145 K. We prescribed two distinct four-step loading schedules to each sample: (i) loading to a maximum load of ~1.0–1.2 mN, unloading to ~10% of the maximum load, followed by reloading to ~90% the maximum load for three cycles (Figure 2.5b) and (ii) loading to an initial load ~25% the same maximum load, unloading, and reloading to ~50%, 75%, and 100% of the maximum load in the three subsequent cycles (Figure 2.5c). 22 Figure 2.5 In situ nanomechanical experiment on benzene microcrystals. (a) SEM images of the same microcrystal pre/post-compression (the crystallite is outlined for eye guide). (b and c) Load/contact-pressure vs. displacement curves of the same-reload and higher-reload tests. (d) Displacement bursts during a higher-reload test. Figure 2.5a shows that the compressed pyramid was flattened from the apex, consistent with a maximum displacement of ~1 μm, with no observable deformation in its volume below the deformation front. The flattened top layer appears brighter in the SEM secondary-electron contrast, which is consistent with a localized densification-type of deformation observed in open-pore foams(82). Figures 2.5b and 2.5c contain two representative load/contact pressure versus displacement data of same-reload and higher-reload tests, where contact pressure is calculated by dividing the applied load by the contact area. Figure 2.5b demonstrates that during the initial compression on pristine benzene in the same-reload test, the compressive load increased linearly with displacement, and most of the deformation was permanent, with marginal elastic recovery (~15%) after unloading. The deformation behavior in the three subsequent cycles was consistent, exhibiting a common stiffness during reloading and 23 unloading, which suggests that the sequent deformation within the historical maximum was highly repeatable and predominantly elastic in both loading and unloading directions. The contact pressure peaked at ~2 GPa after establishing incipient contact and then monotonically decayed to ~0.4–0.6 GPa at ~1000-nm displacement with the continuously increasing contact area of the pyramid. Another characteristic of the same-reload experiments is the presence of ubiquitous, stochastically distributed, 5–30 nm displacement bursts, marked by arrows over the first loading cycle in Figure 2.5b. Despite the noises from cryogenic system vibrations, the displacement bursts could be distinguished through multiple thresholds for the displacement increment between adjacent data points collected at 100 Hz. In contrast, the displacement bursts are absent in the second-fourth reloading cycles in the same-reload test, where the deformation was mainly elastic with negligible hysteresis over a ~85% lower displacement than that in the first cycle. These observations indicate that the permanent densificationinduced microstructural deformation occurs nearly entirely during the first cycle, with the deformation in subsequent loading cycles restricted to the previously densified region. Stochastic displacement bursts have indeed been widely observed in nanomechanical studies of metal, especially in single-crystalline metallic nano-pillar compression experiments, where displacement bursts correspond to dislocation avalanches(77, 83–85). Post-mortem observations always show well-resolved slip lines on the pillar surface—as direct evidence to the deformation mechanism of crystallographic slip via dislocation avalanches. Differently, we did not observe any slip lines in the deformed solid benzene pyramids; instead, the pyramids’ top was flattened in a continuous manner, and the side slopes remained mostly unchanged throughout (Figure 2.5a and Movie 2.1), suggesting densification that is distinct from the volume-preserving dislocation plasticity in metallic systems, as illustrated in Figure 2.6. Our experiments can be viewed as a reversed classical indentation contact problem where a flat, stiff indenter tip is used to compress the compliant and deformable benzene pyramids. In the mechanical model for indentation, a parameter called reduced modulus, 𝐸𝑟 , is used to describe the stiffness contribution from both bodies through: 24 1 1−𝜐12 𝑟 𝐸1 = 𝐸 1−𝜐2 + 𝐸 2 2 eq. 2.7 where ν and E represent Poisson’s ratio and Young’s modulus, and “1” and “2” refer to the two bodies. The expression is symmetric with respect to “1” and “2,” suggesting that 𝐸𝑟 is insensitive to which body is more compliant and that classical nanoindentation theories are appliable to our reversed scenario(86). The elastic indentation mechanics theory predicts nonlinear load-displacement relation(86), while the plasticity events (e.g., the successive discrete displacement excursions, indicated by the pop-ins or displacement bursts) interrupt the nonlinear elastic solution and may explain the linear-like load-displacement relation in the Same-Reload test. Similar linear loading curve were widely observed in single crystalline nanoindentation tests in metals and small molecules(87–91). Figure 2.6 Schematic of pyramidal benzene microcrystal densification mechanisms. As for the higher-reload tests, we adopt the nomenclature from soil mechanics, where the preconsolidation (i.e., the historical maximum) stress dictates the transition from preceding (elastic) to virgin (plastic) consolidation (i.e., removal of pore volume)(92). The benzene pyramids experienced such tangent stiffness enhancement during each higher-reload reloading cycle (Figures 2.5b and 2.7) that the elastic compression from each previous cycle transitions to the onset of plasticity with further loading, and compression then progresses 25 into the deeper, undeformed layers of benzene (Figure 2.6). This transition is also evident in the scarcity of displacement bursts during preceding elastic compression and their emergence during further virgin compression (Figures 2.5d and 2.8). We observed systematic stiffening in each consecutive loading of the virgin material during higher-reload cycles, with the average stiffness progressively increasing by half, one-third, and one-eighth of the previous value, respectively. The increasing stiffness per cycle—indicating overall nonlinear loaddisplacement relation—is consistent with the elastic response of the densified region from preceding loading cycles. A similar stiffening phenomenon was observed during nanoindentation of hexachlorobenzene crystals(68). Calculation of Loading Stiffness for Virgin-compression in Higher-reload Experiments. For the first loading cycles, due to the linearity of the loading segment, the stiffness was taken as the best-fitted slope of the line, whereas for the reloading cycles, the virgincompression is considered as the loading segment from where the current load just surpassed the historical maximum to unloading. And the loading stiffness is then found as the best-fitted slope of this segment. Note that the displacement from the bursts is included in calculating the loading stiffnesses, which could cause these values to slightly underestimate the stiffness of the pre-burst pristine benzene (Figure 2.7). Identification of Displacement Bursts for the Loading Segments in Higher-reload Experiments. Based on the current loading rate, data acquisition frequency, and cryogenic system’s vibration magnitude, the criteria for displacement burst identification are (to simplify notation, total cumulative displacement is called h, and the incremental displacement per data point is called Δ): (a) Δ > δ = 0.7 nm, i.e., approximately twice median Δ (median instead of mean is considered because median is less sensitive to cryogenic vibrations) as well as the unit cell size of benzene; (b) the mean Δ from the adjacent five data points should be greater than δ/3; (c) for all data points identified by criteria a & b, the last identified point should be separated by no more than one data point from the current identified point; 26 (d) h at the current data point identified by criteria a, b, & c should be greater than h at the last data point identified by criterion a, b, & c; (e) the mean h of the adjacent seven data points is less than the mean h of the next seven data points. The criteria b-e partially serves for removing false identification caused by vibration. Still, very occasionally the criteria falsely identified artificial displacement bursts or omits likely real displacement bursts satisfying criteria a & b, in which case the relevant data points were visually examined and manually removed/reselected. The results are shown in Figure 2.8. Figure 2.7 Identification of virgin-compression stiffness for higher-reload experiments: (A) fitting results for individual datasets; (B) comparison of the stiffening effect over loading cycles. Error bars represent the standard deviation of each measurement. 27 Figure 2.8 Identification of displacement bursts (red) for higher-reload experiments. Estimation of the Longitudinal Modulus of the Densified Region. We estimated the longitudinal modulus of the densified region along the axial compression direction from the unloading segment of the load-displacement data and the post-mortem SEM images: El = kH(1 – Dpl/H)/A = ckH/2.6h eq. 2.8 where Dpl is the plastic displacement, H is total deformed height, k is the unloading stiffness, A is the cross-sectional area calculated at distance h from the initial apex location, and c = 1 – Dpl/H eq. 2.9 represents the densification ratio. Assuming linear elastic unloading and approximating cross-sectional area of the compressed pyramid as a constant (in reality, it had a slight variation over the height due to the small taper of the side), El is estimated as ~0.7–1.8 GPa for c ~ 0.4 ± 0.04 (Figure 2.9). 28 Figure 2.9 Estimation of the longitudinal modulus of densified region: (A) Extracting Dpl, H, k, and c from compression data (inset: post-mortem SEM image defining the dimensions); (B) Bounds of modulus as a function of densification ratio. Influence of Temperature on the Mechanical Properties. As applied in a previous roomtemperature nanoindentation study of a selection of candidate Titan minerals12, the Young’s modulus E scales as a function of temperature T as E(T) ≅ E0(1 – T/2Tm) eq. 2.10 where E0 is the Young’s modulus at 0 K, and Tm is the melting temperature. Applying this relation to the benzene crystallites in this work, whose melting temperature is 278.7 K (73), we find that E(94 K) ≅ 1.07 E(123.39 K) ≅ 1.12 E(144.40 K). This implies that the Young’s modulus at Titan’s surface temperature is only ~12% below the one measured in our work. The agreement should hold for the longitudinal modulus, as well because it is linearly related to the Young’s modulus through a geometric factor independent of temperature. Yu et al. also suggested the empirical relation between hardness H and Young’s modulus E through a power-law scaling, with a close-to-unity power coefficient(58), further suggesting that the hardness as well as the strength have similarly weak temperature-dependence and validates our measurements. 2.4.2 Crystallinity of the cryogenically formed solid-state benzene The microstructure of solid benzene was characterized using cryo-transmission electron microscopy (cryo-TEM) on similar droplets solidified directly on the lacey carbon TEM grid. 29 Due to the lower volume of liquid benzene needed in comparison to the in situ SEM sample preparation, the TEM sample contained smaller solid benzene particles. Nevertheless, the SEM and TEM samples shared comparable cryogenic temperature profiles, which is important in guaranteeing consistency in phase formation. Selected area diffraction (SAD) was performed for a single grain solidified on the TEM grid (Figure 2.10a). Using the lattice parameters of benzene, a = 7.384 Å, b = 9.416 Å, and c = 6.757 Å43, the diffraction spots (Figure 2.10a, inset) were indexed as (100), (021), and (121) with >97.5% match for the [012̅] zone axis. The findings suggest that the benzene pyramids are composed of single crystals, with the orthorhombic Pbca structure, identified as the only equilibrium crystalline phase of benzene under present SEM and TEM conditions23, i.e., ~77–145 K in vacuum (Figure 2.10b). It is notable that under the Pbca phase, each of the four benzene rings per unit cell (three at face centers and one at the corner) takes a dissimilar orientation, as indicated by the four colors in the inset of Figure 2.10b. Figure 2.10 Microstructural and phase characterization. (a) Cryo-TEM bright-field (BF) image of tens of benzene crystallites; inset: SAD determining the crystal structure. (b) The atomic model of one unit cell of Pbca-phase solid benzene, inset showing the four differently oriented benzene rings per unit cell. 2.4.3 Atomistic densification mechanism of solid-state benzene We employed large-scale molecular dynamics (MD) simulations to investigate the molecular-level origin and mechanism of the solid benzene’s plastic deformation and stiffening behaviors(78). The simulated samples consisted of periodically stacked Pbcaphase benzene crystals, consistent with the experimental characterization. Figure 2.11a shows the deformable region of the simulated pyramidal sample, with a height H, which resides on a fully clamped bottom layer. Figure 2.11b contains the load vs. displacement 30 response of three samples with different heights, H = 10, 20, and 30 nm under fixed [010] loading direction and 10-K temperature (Movies 2.2–2.4). This plot demonstrates that the initial load-displacement response, up to a displacement of ~4 nm, is linear-like and approximately identical for all samples, consistent with the experimental observations. All samples exhibit subsequent stiffening, which commences at lower displacements, 𝑑, as the sample height increases. Figure 2.11c conveys the contact pressure, calculated from the instantaneous contact area A, plotted against the normalized displacement 𝑑̅ , defined as the absolute displacement devided by the overall height, and reveals a roughly two-stage evolution during deformation: (1) a linear increase in contact pressure up to a normalized displacement of 0.12, with a virtually identical response among all samples up to the normalized displacement, and (2) a plateau stage, where the contact pressure remains relatively constant at ~150 MPa, with fluctuations that are caused by the sudden appearance of avalanche of densified benzene molecules (Figure 2.11d and Movie 2.4). Figure 2.11 MD simulations on pyramidal benzene. (a) Schematic of the simulation on pyramidal benzene. (b) Load vs. displacement and (c) contact-pressure vs. normalized displacement curves of the simulations on pyramidal benzene samples with the loading direction of [010] and the height H = 10, 20, and 30 nm. (d) Sequential snapshots of the density distribution of a cross-sectional slice cut from a 30 nm-height pyramidal benzene; insets in (iii) and (iv): reorientation-induced densification. 31 Figure 2.11d presents sequential snapshots of a cross-sectional slice from the sample with a height H = 30 nm during compression, colored by the local actual density, of which the calculation method based on the regional atom distributions are described in Methods, illustrating a heterogeneous densification profile. In all simulations, the initial densification region, marked by the arrow in Figure 2.11d(i), always nucleated at the apex of the pyramid and expanded roughly layer-by-layer with further compressive load, with a maximum density contour concentrated directly underneath the indenter ((i) in Figure 2.11d and Movies 2.2–2.4). The initial densification occurred at a normalized displacement of 0.12, within the first stage of contact pressure evolution for all sample heights. After the onset of stiffening, the densification region further extended from the edges of the flattened top towards the undeformed layers below, along the 45°-tilt lines (white arrows in (ii)–(iv) of Figure 2.11d) and progressively thickened (Figure 2.12). Figure 2.12 Collective re-orientation of benzene rings along the 45° local shear direction. The re-orientation process during compression in the local region in the black box is snapshotted and magnified in the lower zoomed-in images. 32 The mechanism of densified region formation appears to occur in two steps—firstly through collective re-orientation of benzene rings along the 45° local shear direction (Figure 2.11d (iii), circled region) and secondly through interplanar shear slipping between paralleled molecules (Figure 2.13 and Movie 2.5). The re-orientation front (black arrows in Figure 2.11d(iii), circled region) propagated primarily along the 45°-direction to extend the rows of coplanar benzene rings before deepening into the next parallel crystallographic plane (Figure 2.12). Two obvious, large drops are marked with (ii) and (iii) in Figure 2.11b and are related to the sudden reorientation-induced densification and propagation of the densified phase (Figure 2.11d and Figure 2.12). Figure 2.13 Atomistic deformation behavior in crystalline benzene. An intermolecular slip process in the black-boxed region in (iii) of Figure 2.11d. At the normalized displacements of 𝑑̅ ~ 35.4–36.5%, the interplanar shear front field (arrows in Figure 2.12) propagated analogously to dislocation in atomic crystals, driving offsets above and below the plane of shear in every column of benzene rings that it passed. At relative displacements greater than 𝑑̅ ~ 36.5% when the offset almost equated to half of the column spacing, the face-to-face π–π interactions between the stacked benzene rings(93) likely caused the front to expand into a slip band, which distributed the shear offset over multiple neighboring layers, relieving the high local strain and accommodating the increasing global strain while preserving the original ring-to-ring connectivity. The radial distribution function (RDF) analyses of the densified region is consistent with this mechanism (Figure 33 2.14; the selection of densified region is refered to Figure 2.4). During compression, the diffuse RDF peaks became sharp at 𝑑̅ ~ 8–12%, matching the onset of contact pressure plateau. The RDF peak shapes and positions remained stable until 𝑑̅ ~ 32–36%, suggesting stable propagation of the densification region. The highest RDF peak at a carbon-carbon pair distance of ~4.1 Å, which also experienced the most significant intensity increase, likely correlated to the interplanar spacing after the benzene rings’ re-orientation. Beyond 𝑑̅ ~ 32– 36%, the RDF peaks became diffuse again, which could be explained by interplanar shear slipping and distorting the columns of stacked benzene rings (Figure 2.13). Figure 2.14 Radial distribution function of the densified region at increasing normalized displacements in the 30 nm-height sample loading from [010]-direction, accompanied by the illustration of solid benzene deformation mechanisms. The red-arrowed dash line tracks the feature peak. The snapshots of the shear-strain evolution of the same slice, shown in Figure 2.15 and Movie 2.5, revealed that the high shear-strain region initiated from the apex and then propagated along an inverted triangular shape where the benzene molecules assumed a largely distorted arrangement—at 𝑑̅ ~ 10%, forming a 45°-shear band which guided the region above to slip along and plateaued at a contact pressure of 150 MPa ((2) to (3) in Figure 2.15). The reorientation-induced densification region appears to be located directly below 34 the shear band, which suggests that the role of the shear band is to facilitate the re-orientation of the benzene molecules and to thicken the densification region (comparing (iv) in Figure 2.11d and (4) in Figure 2.15). Distinctively, the interplanar slip/distortion in the densification region induced large shear strain evident in the contour maps (comparing (vi) in Figure 2.11d and (4) in Figure 2.15). Figure 2.15 The evolution of shear-strain distribution of the sliced sample. The formation of shear bands oriented at 45° with respect to the loading direction is caused by the motion of loosely stacked Van der Waals force-bonded benzene rings along the directions of maximum shear-compoenent that caused ring re-orientation. This phenomenon is distinct from shear slip in single crystalline metals, where dislocation glide on specific crystallographic slip systems defines plastic deformation, with minimal plane/lattice rotation, as evidenced by a similar compression experiment on single crystalline gold pyramids(84). The gold pyramid study reported conserved sample volume before and after compression, consistent with the dislocation glide mechanism; in contrast, the aromatic rings in solid benzene were loosely stacked and bonded by weaker Van der Waals forces, which enables densification via ring re-arrangements. The formation of densified region and shear band in MD simulations could explain the predominantly plastic deformation in experimental observation; meanwhile, the densified regions induced by reorientation and interplanar slip contribute to the stiffening behavior in the load-displacement curves. The molecular-level deformation behavior—re-orientation and interplanar shear of benzene rings with respect to the local stress field—is likely generalizable to different sample geometry and loading conditions. In simulations, varying the unit cell orientation inside the pyramid or the cryogenic temperature in the range of 10– 35 30 K barely affected the deformation behavior due to the highly responsive re-orientation of benzene molecules under the applied stresses (Figure 2.16). Figure 2.16 Simulated contact pressure-normalized displacement relationships using different (A) unit cell orientations and (B) temperatures in the range of 10-30 K. Our in situ SEM observations reveal the entire deformed pyramid, including the densified region at the top, to be thermodynamically stable after unloading because we did not detect any shape change. RDF evolution of high shear strain region with shear strain larger than 0.5 from MD simulations in Figure 2.17 reveals no obvious peaks, which is consistent with amorphous-like microstructure. To be noticed, the uniaxial pressures in our experiments (Pmax = 2.0 GPa) and simulations (Pmax = 0.2 GPa) were a factor of 8% (based on experiments) lower than those needed to trigger amorphization (Pamorphization ~ 25 GPa) and 20% below the pressure to initiate phase change from Pbca to P21/c(69, 75). This renders the discussion on whether amorphization or a phase change occurred in our experiments inconclusive; instead, we describe the microstructure as amorphous-like. 36 Figure 2.17 Radial distribution function in the region with high shear strain extracted from MD simulation using parameters of non-affine square displacement > 100 and shear strain ≥ 0.5 set in software OVITO. 2.5 Discussion & Conclusions We have demonstrated the feasibility of nanomechanical experiments on individual solid benzene micro-crystallites and the atomistic origin of the observed deformation behavior. The data provides insights into the mechanical properties of other simple organic materials representing surface mineralogy of cold solar system bodies like Titan. These materials are characterized by strong intermolecular forces, e.g., acetonitrile with two-dimensional hydrogen-bond networks(94), potentially coordinating the collective molecular responses in an analogous way as the π–π stacking in solid-state benzene dictates the re-orientation and shearing. In large-organic-molecule crystals, however, significant molecule rotation is typically hindered by steric constraints, with the deformation mechanisms dependent on the pre-existing interatomic forces in the original crystal structure: hexachlorobenzene, with column-stacked rings, is highly resilient to plastic bending(68); 1,3,5-trichloro-2,4,6triiodobenzene, with strong 2D networks, and crystals with intralayer/interlayer stacking sequences experience plastic shearing in-plane or along weak interlayers(95). On the other hand, the proton-disordered phase Ih ice microfiber with a diameter less than 10 microns, as a small-molecule inorganic crystal, can sustain an elastic limit up to 10.9% under bending deformation along with a pressure-induced phase transition from Ih to II(96). MD simulations of phase-Ih ice demonstrated that under compression, the column of oxygen atoms parallel to the compression direction would re-orient into a regular zigzag pattern(97), and that under 37 nanoindentation near the melting temperature, a quasi-liquid layer was formed at the iceindenter interface by pressure-induced amorphization(98). These previous studies suggest the clear difference between the deformation of small- versus large-molecule crystals and the special significance of intermolecular interactions in the nanomechanical response of smallmolecule crystals, organic or inorganic. Furthermore, the group of noble-gas solids, like hexagonal-close-packed (hcp) and body-centered cubic (bcc) 3He, hcp 4He, face-centered cubic (fcc) Ne and Ar etc., can only keep in solid phase with crystalline structure at low temperatures or high pressures, the same as benzene molecules(99, 100). By some mechanical experiments like pulling a ball through the solid hcp 4He (101), pulling a superconductive wire through bcc 4He (102), or uniformly shearing hcp 4He triggered by piezoelectric transducers(103), the solid helium always mechanically responded in plastic flow, phenomenologically similar as solid benzene in our experimental testing. Due to the metal-like atomic configuration, the plastic deformation can be explained by the avalanches of creation, multiplication, and interaction of dislocations in solid He. However, although the tested micro-crystallite benzene was also arranged in orthorhombic structure, the different orientations of the benzene molecules in one lattice and the tendency towards π–π stacking between benzene rings made it plastically deform in different underlying mechanisms compared to noble-gas solids, in which every atom is identical with no orientational characteristics. Table 2.1 Elastic constants of solid benzene(104). c11 c22 c33 c44 c55 c66 c12 c13 c23 170 K 8.01 9.26 7.88 3.18 5.53 1.95 3.85 4.80 5.08 138 K 8.61 10.01 8.63 3.56 6.13 2.10 4.15 5.10 5.38 Units: GPa Despite the nonstandard geometry of the micro-crystallite for extracting the modulus, hardness, etc., a longitudinal modulus of ~0.7–1.8 GPa is estimated for the densified region of solid-state benzene, by applying several approximations (Figure 2.9). The upper-bound value is ~55–70% lower than the Young’s modulus in the lattice-normal directions calculated from the elastic tensor measurement by an ultrasonic pulse method(104) (Table 38 2.1). This inconsistency in the modulus may be due, in part, to the differences in sample size, microstructures, crystallographic orientations, porosity, and fabrication methods used in the described measurement techniques. This range of the modulus is generally comparable to the nanoindentation-measured Young’s modulus of coronene (a polycyclic aromatic hydrocarbon) and biphenyl (two benzene molecules linked by a single bond). It is an order of magnitude lower than that of water ice at 94 K, laboratory Tholin (photochemically formed disordered polymer-like organics), and white gypsum sand, and two orders of magnitude lower than that of basalt and silica sand(58). While the modulus was relatively low, the solid benzene pyramids demonstrated substantial densification without fracture as flow stresses asymptotically approached a high value of ~0.4–0.6 GPa. At microscale, the shear band formation facilitating re-orientation and releasing local stress concentration might imply good resilience to fracture of small benzene micro-crystallites and viability of particle compaction and transport on cold planet surface. Additionally, densification could occur under the planet surface if benzene crystals were subjected to pressures during impact or burial(105) and/or subjected to higher pressures; the nonrecoverability after pressure removal as shown in the experiment would be of interest if materials at depth were eventually exposed (via geologic uplift(106)) onto the surface. With further studies and understanding on the plastic size effects, the present findings could help the development of continuum and discrete-element-method (DEM) models to simulate planetary geological processes, including the deposition, compaction, and lithification of solid organic materials and spacecraft landing missions on cold solar system bodies. While this study focused on small scale testing and simulations of solid-state benzene as a starting point, future studies could explore (i) the plastic size effects in these materials, (ii) the fracture toughness of solid-state benzene to further infer its robustness in more violent geological processes, and (iii) the fundamental mechanical properties of myriad small-molecule organic solids. Through revealing the deformation characteristics of solid-state benzene at the smallest scale, we suggest (i) the critical role of intermolecular forces in dictating a two-step (reorientation and shear) deformation mechanism of this representative small-molecule 39 single-crystal, in comparison to the dislocation-mediated plasticity in atomic singlecrystals consisting of nondirectional atoms and (ii) the potentially unique behaviors of the exotic simple-organic minerals compared to hard and stiff siliceous rocks of Earth. We anticipate that these implications will encourage future studies to advance the fundamental mechanics of small-molecule crystals and unveil the mysteries behind planetary geological processes. 40 Chapter 3 SUPPRESSED AND ESCALATED SIZE EFFECT IN NANOPILLARS WITH HIERARCHICAL MICROSTRUCTURES ENABLED BY NANOSCALE ADDITIVE MANUFACTURING 3.1 Overview Studies on mechanical size effects in nano-sized metals unanimously highlight both intrinsic microstructures and extrinsic dimensions for understanding size-dependent properties, commonly focusing on strengths of uniform microstructures, e.g., single-/nano-crystalline and nanoporous, as a function of pillar diameters, D. We developed a hydrogel infusionbased additive manufacturing (AM) technique using two-photon lithography to produce metals in prescribed 3D-shapes with ~100-nm feature resolution. We demonstrate hierarchical microstructures of as-AM-fabricated Ni nanopillars (D ~ 100–600 nm) to be nanoporous and nanocrystalline, with d ~ 30-50 nm nano-grains subtending each ligament in bamboo-like arrangements and pores with critical dimensions comparable to d. In situ nano-compression experiments unveil two size regimes with distinct deformation behaviors and strength size dependence at below and above D ~ 350 nm. In the D < 300 nm regime, the Ni nanopillar yield strengths, σ, reaches ~1-3 GPa, above single-/nano-crystalline counterparts in the D range, while demonstrating a suppressed size dependence, σ ∝ D-0.2, and localized-to-homogenized transition in deformation modes mediated by nanoporosity, uncovered by molecular dynamics simulations. In the D > 350 nm regime, however, the Ni nanopillars exhibited escalated size effect and lower strengths (10s–100s MPa) mediated by retained concentrated porosity. This work highlights hierarchical microstructures on mechanical response in nano-sized metals and suggests small-scale engineering opportunities through AM-enabled microstructures. 3.2 Introduction Microstructural engineering is an important enabler of enhanced performance of metals and alloys macroscopically, e.g., grain refinement within the Hall-Petch regime results in higher yield strengths(107). Microstructural features are recognized in nanomechanical studies as 41 key parameters that uniquely dictate specific plasticity mechanisms, with experimental studies delving deep into the influence of individual features/defects (nano-grains, nanotwins, dislocations, etc.) on strengths and their interactions with the extrinsic length scale (nanopillar diameters (D), free surfaces, etc.). “Smaller is stronger” power law strengthening with size reduction has been ubiquitously demonstrated in single-crystalline (sc) nano/micro-pillars produced via focused ion beam(83, 108) and templated electrodeposition(109, 110) and explained through various plasticity mechanisms, e.g., dislocation starvation and nucleation(111), source truncation hardening(112, 113), and weakest-link statistical models(114, 115). Bulk nanoporous metals, commonly produced via de-alloying, benefit from single crystalline nano-ligaments and exhibit superior mechanical strengths compared with materials of similar densities(32, 116–121). In contrast to the Hall-Petch relation(122), where the yield strength enhancement scales with grain size as ∆𝜎𝑦 ∝ 𝑑 −0.5 , describing hardening with reduced grain-boundary/twin-boundary (GB/TB) spacing caused by dislocation pile-ups against the boundaries in bulk crystals(123), nanocrystalline/nanotwinned (nc/nt) microstructures in nano-sized samples introduce a different behavior characterized by “D/d interplay” where surface/boundary-mediated plasticity competes with dislocation plasticity(124, 125). Such complex plasticity mechanisms are challenging to probe experimentally due to fabrication limitations in producing hierarchical microstructures within submicron-sized, individual specimens. Typically, these types of problems have been addressed via computations, e.g., molecular dynamics(126–129) and dislocation dynamics simulations(130, 131), and touched in some experimental studies(124, 125). The additive manufacturing (AM) technique of nano-sized metals and oxides with complex, hierarchical microstructures presented in this work renders these systems available for experimental investigation and for high-precision manufacturing of 3D-shaped, nano-sized metals and alloys. Figure 3.1 illustrates the nanoscale hydrogel infusion-based additive manufacturing process to produce Ni with 100s nm-sized features and hierarchical microstructures, which enables studying the operation and interactions among multiple nano-plasticity mechanisms. We 42 performed transmission electron microscopy, in situ nanomechanical experiments, and molecular dynamics simulations to contextualize the unique microstructural and mechanical behavior of these samples among submicron-regime Ni size effects. This investigation offers new insights into new microstructural parameter spaces that comprise fundamental buildingblocks of nano-architected materials. Figure 3.1 Additive manufacturing enables hierarchical microstructures at the nanopillar level. The multi-step, two photon lithography-based additive manufacturing method, forming intermediate products of blank polymer, Ni-infused polymer, and NiO along the way, enables the fabrication of Ni nanopillars with hierarchical microstructures. The complex microstructure leads to interplay between the signature plasticity mechanisms of individual microstructural characteristics (i.e., single-crystallinity, nanoporosity, nanocrystallinity, and nanotwinning). 43 3.3 Methods 3.3.1 Sample fabrication We prepared customized photoresists for two photon lithography (TPL) to produce samples with pre-designed geometries. The two-photon initiator 7-diethylamino-3-thenolcoumarin (DETC, Exciton) was dissolved in dimethyl sulfoxide (DMSO, Sigma-Aldrich) at 1-mg DETC per 75-μL DMSO. The solution was mixed with poly(ethylene glycol) diacrylate Mn = 575 (PEGda 575, Sigma-Aldrich) and deionized water at a volumetric ratio of 1:7.3:2.7, forming a yellow solution as the finished photoresist. TPL printing was performed on Photonic Professional GT (Nanoscribe GmbH) with a Zeiss Plan-Apochromat 63x/1.4 Oil DIC objective at a laser power of 50 mW and speed of 1.5 mm/s (Figure 3.2A). Pillars (diameter = 2 μm; aspect ratio = 3) on top of a 3 μm-tall one-layer square lattice support were printed on Si wafers. The printed samples were then developed in deionized water for 5 minutes to form the blank hydrogel templates and subsequently submerged into a 0.002–1 M aqueous solution of nickel nitrate hexahydrate (99.999%, Sigma-Aldrich) at 40°C for 60 minutes (Figure 3.2B) to form a Ni-infused hydrogel. Figure 3.2 Fabrication schematics of nanoscale additively manufactured Ni. Red dashed box represents thermal treatment in a tube furnace. 44 Then, the samples were moved from the solution to the tube furnace (MTI OTF-1500X) for two-step thermal treatment: (i) open-to-air calcination by heating at 1°C/min to 500 °C and cooling at 3°C/min back to the room temperature (Figure 3.2C); (ii) reduction by heating at 3°C/min to 590°C under vacuum, holding at 590°C for 3 min under 100-Torr forming gas (FG; 95% N2 and 5% H2), and cooling at 3°C/min back to the room temperature under vacuum (Figures 3.2D and 3.3). The final product was temporarily stored in Ar environment before transferred to high-vacuum conditions for further characterizations. Figure 3.3 Thermal treatment profiles during steps (C) calcination and (D) reduction. The varying background colors indicate different gas environments. 3.3.2 Microstructure characterizations Secondary electron micrographs were collected in a dual-beam focused-ion beam scanning electron microscope (FIB-SEM, Thermo Fisher Versa 3D) at the electron accelerating voltages of 10 and 20 keV. The same dual-beam instrument was used for cross-sectioning and preparing transmission electron microscope (TEM) lamellae using the focused-ion-beam (FIB) lift-out method(132) with a Ga-ion accelerating voltage of 30 keV and currents incrementally reduced from 5 nA to 10 pA. TEM (JEOL 2800) was conducted at 200 keV; the different crystal phases were identified based on the Fast Fourier Transformation (FFT) of relevant high-resolution TEM (HR-TEM) images with visible lattice fringes using Gatan DigitalMicrograph. Additional nanopillars, which were not used for in situ compression, were fabricated with the identical protocol for porosity estimation. Each cylindrical nanopillar was FIB-milled in 45 a top-down configuration (pillar axis parallel to ion beam) to remove one semicylinder of the volume so as to expose the longitudinal cross-section (in the electron-beam view), whose vertical dimension is the pillar height, and the lateral dimension is the pillar diameter. On each cross-section, horizontal lines were drawn evenly at 5%, 15%, …, 85%, and 95% of the pillar height: the line length corresponds to a diameter measurement, and the void length-tototal length ratio corresponds to a porosity measurement for the specific diameter. A total of N = 170 line porosity measurement were performed, and the diameter-to-porosity relation was summarized in Figure 3.7A in the latter section. 3.3.3 In situ nanomechanical experiments Uniaxial compression of individual nanopillars was performed in situ using the testing system FT-NMT04 (FemtoTools AG) mounted in the SEM (Thermo Fisher Versa 3D) sample chamber under high-vacuum conditions and an electron beam voltage of 20 keV. The instrument is intrinsically displacement-driven, precluding artificial displacement bursts common in intrinsically load-driven instruments usually as a combined result of mechanical instabilities, limited load-frame stiffness, and feedback control failures. The pillar diameter, D, and height, H, were measured via SEM immediately before the compression. A 10 µmdiameter diamond flat-punch nanoindenter tip was used for displacement-controlled tests with continuous stiffness measurement at a strain rate of 10-2 s-1 and a data collection rate of 200 Hz for load, P, and tip displacement, Δx; the system compliance is accounted for by the program’s built-in calibration procedure. From Δx, the pillar deformation, Δxpillar, was calculated by subtracting the local nanoindenter tip and substrate deformation using the Sneddon’s approach(133): (1−𝜐2 )∙𝑃 (1−𝜐2 )∙𝑃 ∆𝑥𝑝𝑖𝑙𝑙𝑎𝑟 = ∆𝑥𝑡𝑜𝑡𝑎𝑙 − 2𝐸 𝑆𝑖−𝑠𝑢𝑏𝑠𝑡𝑟𝑎𝑡𝑒∙𝑟 − 2𝐸 𝑑𝑖𝑎𝑚𝑜𝑛𝑑−𝑖𝑛𝑑𝑒𝑛𝑡𝑒𝑟∙𝑟 𝑆𝑖−𝑠𝑢𝑏𝑠𝑡𝑟𝑎𝑡𝑒 0 𝑑𝑖𝑎𝑚𝑜𝑛𝑑−𝑖𝑛𝑑𝑒𝑛𝑡𝑒𝑟 0 Uniaxial engineering stress σ is computed as: σ = 4P/πD2 eq. 3.2 And uniaxial engineering strain ε was computed as: ε = Δxpillar/H eq. 3.3 eq. 3.1 46 Figure 3.4 Schematic of in situ nanopillar compression. 3.3.4 Molecular dynamics simulations A series of large-scale molecular dynamics (MD) were performed to study the deformation behavior of nanocrystalline Ni nanopillars under uniaxial compression using the open-source code LAMMPS(78) and recently developed embedded atom method (EAM) potential(134). Pristine polycrystalline pillar samples with an average grain size of 14 nm were first cut from polycrystalline rectangular prism generated using Voronoi procedure(124). Random nanovoids with a characteristic diameter of 4 nm were subsequently generated near the internal GBs of the pristine nanopillars samples. We generated a series of nanopillar samples containing ~2–22 million atoms with aspect ratio fixed at 3, diameter ranging from 20 nm to 50 nm, and porosity varying between 8% and 22%. Before compressive loading, the nanopillar samples were equilibrated at 300 K for 200 ps under the isothermal–isobaric (NPT) ensemble. Periodic boundary condition was adopted for the axial direction and free boundary condition was used in the radial direction. The relaxed nanopillar samples were subsequently deformed along the axial direction to a compressive strain, e, of 0.3 at a constant strain rate 5x108 s-1. Dislocation structure analysis was performed and visualized using OVITO(80). 47 Figure 3.5 Initial configuration of the MD-simulated pillars. Pillars of (A) 20 nm diameter and (B) 50 nm diameter. Atoms in green are of fcc coordination; atoms in white are of unknown coordination, representing grain boundaries and void surfaces. 3.4 Results 3.4.1 Microstructural characterization Individual pillars experienced significant volumetric shrinkage, primarily during the aircalcination step and secondarily during the forming gas reduction step, while maintaining their shape integrity. Pillars printed with the prescribed diameter of 2 μm at the TPL step resulted in the final diameter, D, of ~130–550 nm and an aspect ratio of ~3-4. The crystallographic structure of the intermediate (post-calcination, NiO) and final (postreduction, Ni) products was characterized via high resolution TEM (HR-TEM) and indexed based on the corresponding FFTs. Post-calcination. The intermediate product was determined as a cubic-phase NiO with a lattice parameter of 4.17 Å and Fm3̅m symmetry(135) and contained uniformly distributed ~5–10 nm-sized grains (Figure 3.6A). These oxide pillars were mostly fully dense for diameters, D ≲ 350 nm; larger pillars inevitably contained an artifact void (Figure 3.7), which was continuous in the longitudinal direction, dividing the NiO pillar into a solid core and a shell. 48 Figure 3.6 Microstructural characterization of fabrication products. (A) (i): HR-TEM micrographs (scalebar = 10 nm) of a representative NiO lamella FIB-carved from a nanopillar; (i-Inset): SEM micrographs of a typical NiO nanopillar (scalebar = 250 nm); (ii) fast Fourier transformation (scalebar = 5 nm-1) of the image area in A(i). (B) (i): HR-TEM micrographs (scalebar = 10 nm) of a representative reduced Ni lamella; (i-Inset): SEM micrographs of a typical Ni nanopillar (scalebar = 250 nm); (ii) fast Fourier transformation (scalebar = 5 nm-1) of the dash-boxed area in B(i). (C) Center, SEM micrograph (scalebar = 200 nm) of a FIB-cut vertical cross-section of a typical Ni nanopillar; (i-ii) TEM micrographs of areas similar to the boxed areas displaying wall-ligament-pore microstructural features (scalebar = 200 nm and 50 nm, respectively). The redeposited Si(Ox) areas in (C(ii)) are shaded for clearer view. 49 Post-reduction. The final product was determined to be fcc Ni with a lattice parameter of 3.52 Å(136) (Figure 3.6B(i–ii)), with a grain size, d, ~30–50 nm, and finite porosity. All Ni pillars with D ≲ 300 nm were ~10% porous when reduced from fully dense NiO intermediate product. The vertical-cut cross-sectional lamella, shown in Figure 3.6C, demonstrates that these smaller pillars were typically comprised of a continuous exterior wall, as well as interior ligaments and pores. TEM image of a representative wall segment, shown in Figure 3.6C(ii), uncovers a bamboo-like microstructure, with individual nano-grain d ~ 30–50 nm, subtending the walls and ligaments, which are thus 1–2 grain-wide. The pores, which have critical dimensions comparable to d, are stochastically distributed throughout the sample, independent of pillar size, meaning that a larger pillar would on average have more ligaments than a smaller pillar, rather than being self-similarly scaled up. The labeled Si(Ox) in Figure 3.6C(i–ii) correspond to the TEM lift-out artifacts resulting from FIB-milled substrate Si redeposition and oxidation. We found that the larger pillars with D > 300–350 nm had greater porosity, which increased from 10% for D ~ 300 nm to ~20–25% for D ~ 550 nm (Figure 3.7A), and contained large, longitudinal core-shell voids retained through the FG-reduction. As-calcined NiO intermediate product is fully dense at smaller D (Figure 3.7B) but forming such longitudinal porosity defect at larger D (Figure 3.7C) which is retained through reduction (Figure 3.7D). Considering the microstructural inhomogeneity in the larger pillars, we gravitate our mechanical characterization and discussion (in situ nano-compression and MD simulations) on smaller pillars with D ≲ 350 nm, which are free of the core-shell voids, but we provide some discussion on the larger pillars as well. 50 Figure 3.7 Size-dependent porosity. (A) Porosity measured along horizontal lines on FIBprepared vertical cross-sections of Ni pillars. Every 17 measurements are binned into one black square for a clearer view, with error bars representing standard deviations along the corresponding axes. (B-C) FIB-cross-sectional-view SEM micrographs of NiO intermediate product, consistently showing ~fully dense microstructure at D ≲ 350 nm (B) and long vertical post-calcination voids at D ≳ 350 nm; (D) SEM micrograph of Ni final product showing retention of post-calcination voids in larger pillars, in contrast to stochastically distributed pores in smaller pillars (Figure 3.6). The cause of increasing porosity and the development of the core-shell structure with increasing D is elucidated by partial calcination experiments up to ~365°C rather than up to the final temperature of 500°C. As shown in Figure 3.8, the NiO nucleation occurs from the interior core at lower infusion concentrations around cNi ~ 0.002–0.015 M (leading to small D due to lower total Ni uptake; Figure 3.8A), manifested by HR-TEM in Figure 3.8B showing ~10 nm sized NiO nuclei (darker spots) precipitating from the Ni-infused polymer matrix (lighter ground), agreeing with the grain size distribution and microstructure observation in Figure 3.6A. In contrast, at higher infusion concentrations above cNi ~ 0.1 M (leading to small D due to lower total Ni uptake; Figure 3.8B), NiO nucleation occurs from the exterior first, forming a percolating oxide layer ~ 10s nm thick before any appreciable NiO formation on the interior. While subsequent polymer combustion and NiO formation may initiate at the interior core at higher temperature and later stages, this exterior NiO layer would form wrinkles due to conformal deformation along with the volumetric shrinkage of the interior. These two distinct nucleation routes from the exterior and the interior thus potentially explain the observed final core-shell structure with such longitudinal porosity. 51 Figure 3.8 Electron micrographs unveiling competing NiO nucleation mechanisms at partial calcination up to ~ 365°C: (A) SEM images (left: exterior view; right: FIB-cross-sectional view) of dominant NiO nucleation route at small diameters and/or low infusion concentrations; (B) HR-TEM showing NiO nuclei in polymer matrix upon partial calcination; (C) SEM images of dominant NiO nucleation route at large diameters and/or high infusion concentrations. 3.4.2 In situ compression experiments The compression of individual nanopillars was performed in an intrinsically displacementcontrolled system (FemtoTools AG) in the quasistatic regime. Figure 3.9 highlights three typical engineering stress-strain signatures, two from small-D regime and one from large-D regime. The smallest pillar, labeled D = 145 nm, contained an extensive linear regime, up to ε = 7%, with a least-square fitted longitudinal loading modulus of ~66 GPa, followed by a rapid load drop past the yield strength, σy ~ 3.2 GPa, calculated using the 0.2% strain offset criterion, consistent with the observed deformation via a single shear band at close-todiagonal orientation (Figure 3.9 inset – left; Movie 3.1). The “shoulder” in the data at ε ~ 9%, depicted by the blue arrow, may arise from the arrest of shear band propagation at an adjacent grain with a different crystallographic orientation. The second pillar in the small-D regime, labeled D = 211 nm, exhibited significant post-yield hardening and softening, reaching a maximum flow stress, σ ~ 3.0 GPa at ε = 15% strain and subsequent softening to 52 σ ~ 2.3 GPa which is then maintained until unloading at ε > 20%—accompanied by a homogeneous global compression profile (Figure 3.9 inset – middle; Movie 3.2). Figure 3.9 Engineering stress-strain relationships of three Ni nanopillars with representative D’s. From the data, the longitudinal loading modulus was calculated by least-square fitting from the linear loading segment, where the first 10% was not used due to nonlinearity from initial contact establishment; the yield strength was then chosen as the intersection point between the data and 0.2% strain-offset linear fitting line. The inset SEM micrographs show the pre-mortem and post-mortem status of the three representative pillars showing distinct failure mechanisms. Movies 3.1–3.3 contains the in situ videos of the nanopillar pillar compression synchronized with the stress-strain evolution; see Appendix B for the movie titles. As noted abvoe, these larger Ni pillars contain the retained calcination-induced defects (the continuous longitudinal core-shell voids), which dominated the deformation behavior. From the in situ compression experiment, these pillars were found to experience significantly lower σy ~ 0.2 GPa and deform via multiple cracking (Figure 3.9 inset – right; Movie 3.3), agreeing with influence from the continuous longitudinal voids. These cracking events were reflected in the stress-strain curve as multiple peaks and load drops. Size-dependence of nanopillar yield strengths. Based on compression results from N = 56 smaller nanopillars and N = 44 larger nanopillars, we observed two distinct “smaller is stronger” size-dependent regimes of their uniaxial yield strength, σ, plotted as a function of D on a log-log scale in Figure 3.10, accompanied by yield strength values from previous literatures on conventionally manufactured Ni nanopillars and nanocrystals with singlecrystalline (sc), nanocrystalline (nc) microstructures. Our experiments revealed σ-D scaling following: 53 𝑑𝑖𝑚 σ ∝ 𝐷− 𝑚 = 𝐷 −β eq. 3.4 where β = dim/m relates the scaling factor, β, to Weibull modulus, m, and dimensionality, dim (e.g., dim = 2 for surface-mediated plasticity)(137),(138). Smaller β, i.e., greater m at fixed dim, implies the presence of fewer and/or less severe defects in the Weibull distribution-characterized defect-dominated material strength model(137). A clear tworegime size effect is observed, where a segment-wise least-square fitting provides a value of β ~ 0.2 on D ≲ 350 nm, representing a suppressed extrinsic size effect for the smaller Ni nanopillars and a value of β ~ 4 on D ≳ 350 nm, representing an escalated extrinsic size effect for the larger Ni nanopillars. This significantly greater scaling factor of the latter indicates the presence of more defects or increasingly more severe defects with increasing D, agreeing with the positive correlation between porosity and D measured from pillar crosssections. Figure 3.10 Extrinsic size effects in Ni nanomechanics(83, 108–110, 139–141). A log-log plot of compressive uniaxial yield strengths of individual micro/nanosized Ni samples as a function of diameter. Shaded domains and dashed trend lines are used for eye guidance. 54 3.4.3 Molecular dynamics simulations of Ni nanopillar in suppressed size effect regime Figure 3.11 shows the compression simulation results of two typical nanopillars with diameters of 20 and 50 nm and the same porosity of 15% via stochastically distributed nanopores resembling the suppressed size-effect regime microstructures free of such weakening core-shell void structures to demonstrate distinct size-dependent plastic deformation behavior in such nanocrystalline, nanoporous microstructure-intrinsic regime. Figure 3.11 Molecular dynamics simulation of Ni nanopillars compression. (i) SEM micrographs of the original nanopillars in the suppressed size effect regime shown in Figure 3.9 labeled with a corresponding D, MD-simulated visualization of a representative nanopillar (ii) shortly after yielding, e = 0.025, and (iii) at a significant plastic strain, e = 0.3, and (iv) post-mortem SEM micrographs of the same pillars (all scalebars = 250 nm). Dislocations are colored by their types: Shockley partial dislocations (green), stair-rod dislocations (pink), and Hirth dislocations (yellow); atoms with hcp, bcc, and unknown coordination are colored red, blue, and white, respectively; in MD visualization, bulk fcc atoms are removed for clearer view; in (ii), atoms on the internal void surface are colored black, and blue arrows indicate the surface steps formed by grain boundary sliding. 55 Both specimens show the initiation of plastic deformation at a compressive strain e of around 0.025, characterized by a combination of surface grain boundary sliding and partial dislocation nucleation as shown in the insets in Figure 3.11 – upper (ii) & lower (ii), where blue arrows indicate the location of surface grain boundary sliding and green lines represent the Shockley partial dislocations. MD simulations reveal that in the smaller specimens, with D = 20 nm (Figure 3.11 – upper), partial dislocations predominantly nucleated from the outer surface; in larger pillars (D = 50 nm), a significant number of partial dislocations nucleated at the internal grains, especially those adjacent to voids (Figure 3.11 – lower(ii)). Upon further loading to e = 0.3, the smaller pillars formed localized shear bands in the middle of the nanopillar, as indicated by the dashed line in Figure 3.11 – upper(iii) along a preferably slip plane. Dislocation analysis(142) was performed for the nanopillar to obtain the total dislocation length in the shear band and a 30% increase of Shockley partial dislocation density was found in the localized deformed region within 5 nm of the slip plane, compared with the average density in the whole specimen. The larger pillar underwent a more homogenized plastic deformation (Figure 3.11 – lower(iii)), characterized by multiple activated slip systems throughout the entire volume and more uniformly distributed partial dislocations. The observed localized slip in the smaller pillar versus homogeneous plastic deformation in the larger pillar revealed by the MD simulations are in good agreement with the post-compression SEM images shown in Figure 3.11 – upper(iv) and lower(iv). Computational results demonstrate that the onset of yielding can be manifested by both surface GB sliding and partial dislocation nucleation, and that the large plastic strains are eventually accommodated by collective dislocation activity dictated by the interior nanoporosity. While gaining atomistic-level insights on qualitative trends based on MD simulations, we acknowledge that the intrinsic difference between the experimental parameters and the modeling setup may limit direct comparison between stress level, critical dimensions, and other quantitative results from the two, as discussed next. Limitations in using MD simulations for the present nanopillar compression experiment. 56 In this study, we have performed large scale MD simulations to gain atomic insights on the deformation mechanism and size effect of nanoporous nanocrystalline Ni nanopillars. While good qualitative agreement can be found between the experiments and simulations, there exist some discrepancy on the geometric parameters and quantitative results of the mechanical properties as detailed in Table 3.1. Table 3.1 Difference in geometry and mechanical property of Ni nanopillars between the experiment and MD simulation. Experiment Simulation Grain size 30–50 nm 14 nm Pillar diameter 130–330 nm 20–50 nm Pore size ~30–50 nm 4 nm Porosity ~10% ~10–20% Strain rates 10-2 s-1 5*108 s-1 Yielding strain ~5% ~3% Modulus 51 ± 17 GPa ~70–100 GPa Yield stress 1–3 GPa 1.5–2.5 GPa Those quantitative discrepancies can be understood from the following intrinsic assumptions and constraints in our MD simulations: (1) Limitation in length scale and time scale because of computational power. In our case, our largest MD model contains 22 million atoms (D = 50 nm) and is still much smaller than the smallest pillar in the experiment (D ~ 130nm). Our strain rate in the simulation is around ten orders of magnitude higher than in the experiment. The difference in length and time scales could affect a series of deformation behaviors (i.e., grain boundary sliding, dislocation nucleation/interaction), and thus shift the balance between different deformation mechanisms (i.e., grain boundary meditated plasticity vs. dislocation meditated plasticity). (2) Simplified microstructures of the simulation model. MD simulations were performed on nanopillars with relatively clean grain boundaries and spherical pores, while the grain boundary structure in the experiment might be defective with larger free volume or decorated with solutes, and the non-spherical nanopores in experiment could have higher 57 stress concentration than the simulation model at the same porosity. The difference in grain boundary structure and pore geometry could both affect the dislocation nucleation and transmission behavior in the nanopillars. (3) Accuracy of interatomic potential. We have adopted the widely used EAM potential for Ni in our MD simulations. However, the accuracy of the dislocation nucleation energy barrier at grain boundary/free surface and dislocation core structure might not be guaranteed, which can be another error source for the discrepancy between experiments and simulations. While we hold good confidence that the atomic mechanism revealed by our MD simulations on the transition of deformation modes (localized shear banding vs. homogenized deformation) and reduced size dependence of the yield strength of the nanopillars should function similarly in the experiments, we acknowledge that the critical pillar size for the transition and the scaling factor β could be different in simulations and experiments due to the constraints discussed above. The modulus and yield stress of the nanopillars in MD simulations both decrease with increasing porosity and are within the similar range of the values from the experiment—although greater variance is observed in experiments due to the more complex microstructures (i.e., grain boundary structure and irregular pore morphology) of the AM-fabricated nanopillars. 3.5 Discussion 3.5.1 Kinetically- and chemically-driven microstructure The present AM method forms a natural ground for comparison with the sol–gel synthesis, which has been the process of choice to produce loose powders of nanocrystalline metal oxide nanoparticles and macroscale samples with sintered nano-grains(143–146). Distinctly, the present method produced NiO intermediate product with pronounced shape integrity and density retention at ~100’s nm sample sizes and with grain sizes of 5–10 nm, approximately an-order-of-magnitude smaller than sol–gel-produced grains(146). In situ environmentalTEM study by Jeangros et al. described the submicron-sized NiO-to-Ni reduction mechanism to occur via simultaneous nucleation and growth of multiple Ni grains on the surface of the sample, gradually moving the Ni/NiO interface inward, with concomitant formation of pores 58 and irregularities to accommodate the oxygen volume loss(147). The model explains the presently observed porosity formation, surface roughening, and poly(nano)crystallinity. 3.5.2 Size-dependent nanopillar strength From the compression experiments, the decreasing pillar strength as well as the decreasing strength variance with increasing D suggest a stochastic defect-driven deformation mechanism, likely dominated by interior pore volumes. Defect-dominated mechanical properties are typically understood to be size-dependent, e.g., by the weakest link statistics(137). Larger samples are (i) statistically more likely to trap a more detrimental defect, leading to reduced strengths, and (ii) representative of more homogenized systems, leading to reduced specimen-to-specimen variation. The size-dependent transition in plastic deformation mode (from localized shearing to homogenized compression) may be accounted for as well: while GB junctions present themselves as the weak points for dislocation nucleation and thus plastic deformation, with constant grain size but increased D/d ratio, larger pillars contain a greater number of the weak point across the width to facilitate dislocation plasticity and prevent localized plastic instability by shear banding. In contrast, the smaller pillars with fewer pore surface-GB triple junctions underwent single shear banding, where the close-to-diagonal orientation is dictated by the higher resolved shear stress under uni-axial compression. Moreover, applying the precursor-to-Weibull (PWBL) distribution specifically suggested for nano-structures by Bernal(148) to the present experimental data, we estimated a Weibull modulus of 5.8, a representative-element area of ~10s nm2, and a characteristic strength approximating the theoretical strength of Ni. Nanopillar compression results in the context of Precursor-to-Weibull (PWBL) distribution. We adapted the expression for the failure probability based on the PWBL distribution discussed by Bernal46 to the present experimental results of Ni nanopillar compression: 𝜎 𝑃𝑓𝑗 = 1 − (1 − (𝜎𝑗 )𝑚 )𝑁𝑗 0 where: eq. 3.5 59 (i) Pfj is the failure probability of pillar #j; (ii) σj is the yield strength of pillar #j measured by the experiment; (iii) σ0 is the distribution parameter for characteristic stress; (iv) m is the distribution parameter for Weibull modulus; (v) Nj is the number of representative element in pillar #j: we consider the surface-mediated dislocation plasticity as the source of yielding, and thus we take a 2D representative element and A0 as the distribution parameter for the size (i.e., area) of the element; therefore, Nj = Aj/A0 with Aj approximated as the cylindrical side-surface area of pillar #j. We performed least-square fitting for N = 56 pillars, where the experimental value of Pf(σ) is approximated by the proportion of tested pillars whose yield strength was < σ. Results are summarized in Figure 3.12, where we obtained the PWBL parameters to be: A0 = 31 nm2, σ0 = 12.7 GPa, and m = 5.8. Note that approximating Aj using the exterior surface area is an underestimation due the surface roughness and the presence of interior pores; therefore, A0 may be underestimated as well. Note that the deviation from a Sigmoid-shaped curve of the experimental data, which rather appears approximately piece-wise linear, may suggest the presence of more than one governing failure mechanisms, which possibly correlate to the quasi-brittle, shearing banding failure vs. the homogeneous plastic flow-kind deformation dominant at different pillar size ranges with some cross-over. Figure 3.12 PWBL distribution fitting to nanopillar compression experimental results. 60 3.5.3 On Ni size effect (suppressed size effect regime) When comparing the uniaxial yield strength as a function of extrinsic dimensions, the present additively manufactured nanoporous, nanocrystalline pillars exhibit similar uniaxial yeild strengths to the sc-pillars, nanowires, and nanocrystalline pillars, while as-grown scnanoparticles are approaching the theoretical strength of Ni, due to their lack of pre-existing defects (Figure 3.10). Compared to β ~ 0.6-0.7 for the well-known “smaller is stronger” in single-crystalline fcc nano/micro-pillars, the present Ni nanopillars with hierarchical microstructure exhibit a reduced size effect, with β ~ 0.2. The universally observed exponent, β ~ 0.6-0.7, for single crystals is commonly associated with dislocation source truncationinduced hardening, typically observed for FIB-carved samples with high pre-existing dislocation density, which commonly undermines their yield strength(149, 150). When initial dislocation densities are lower or when dislocations are easily driven out by gliding on nonintersecting slip planes during compression experiments on low-symmetry-oriented samples, dislocation starvation and nucleation-mediated plasticity lead to suppressed size dependence(151). Figure 3.13 Effect of porosity on compression strength of Ni nanopillars. (A) Initial microstructures of typical Ni nanopillars in MD simulations with 10% and 18% porosity. Spherical voids are generated along the internal grain boundaries. Atoms with FCC and unknown coordination structures (at surface and grain boundaries) are colored green and white. (B) Compression strength of Ni nanopillars as a function of initial void volume fraction. Data points are colored by pillar diameter: 20 nm (black), 30 nm (green), 40 nm (blue), and 50 nm (red). 61 This scenario matches the present system because (i) the thermal treatment and FIB-free fabrication result in low initial dislocation densities, and (ii) interior pore volumes reduce the dislocation mean free paths and facilitate dislocation nucleation from pore surface-GB junctions. This porosity-mediated deformation behavior is well-captured by our MD simulations, and strength of nanopillars was shown in Figure 3.13 to be affected more by nanoporosity than pillar size. The suppressed size effect due to nanoporosity is demonstrated further in Figure 3.14 where the compressive yield strength of small and large pillars determined by 1% strain offset shows significantly lessened size dependence in nanoporous pillars than pristine counterparts. Figure 3.14 Deformation behavior of Ni nanopillars without internal voids. (A) Stressstrain curves of Ni nanopillars with different porosity and diameter. Dashed magenta lines show the 1% offset using elastic modulus at given porosity. Snapshots from MD simulations showing the compressive deformation process of typical Ni nanopillars with diameters of (B) 20 nm and (C) 40 nm with increasing strain. Atoms with fcc, hcp, bcc, and unknown coordination are colored green, red, blue, and white, respectively. In deformed samples, bulk fcc atoms are removed for clearer view. The dashed black line in (B) indicates the location of localized slip band. 62 In the present D regime, our nanopillars are consistently stronger than electrodeposited nanocrystalline counterparts with comparable grain sizes (30 nm)(139), despite the former being nanoporous and the latter fully dense. The strengthening mechanisms in the present experiments may include: (i) GB pinning by residual oxygen-rich impurities, (ii) GB roughness due to the grain growth and interlocking upon reduction, and (iii) interior pores decreasing the probability of preferred GB orientaiton at junctions for easy deformation. In nanocrystalline nanopillars of Pt, Gu et al. discovered that accompanying surface GB sliding, the interior plasticity was dominated by dislocation nucleation from GB triple junctions, intragranular propagation, and absoprtion at GBs of the same grain(124). In the present nanoporous scenario, while pore surface-GB junctions serve a similar role as their GB triple junctions, dislocations may escape at pore surfaces across the grain and relax the stress concentration instead of being trapped at GB, intensifying the stress concentration, and facilitating secondary dislocation nucleations—this argument suggests the observed plastic flow stress enhancement due to nanoporosity. Experimental studies on nanoporous metals have predominantly focused on Au or Ag at typical porosity > 50%, precluding direct comparison to the present study. Nevertheless, several studies have indicated the strong influence of ligament sizes on the yield strength: inkjet-printed nanoporous, nanocrystalline Ag (~25% relative density) demonstrated nanoindentation hardness decrease by 70% with increasing ligament size from 80 to 230 nm(117); de-alloyed, annealed nanoporous Au exhibited similar nanoindentation hardness drop with the increased ligament diameter ranging 5–126 nm(152); macro-sized nanoporous Au possessed 80 MPa yield strength at ~35% relative density, benefitted from 37 nm-sized ligaments(120). These literatures and the present work both highlight the de-coupling between the extrinsic dimension of the specimen and the characteristic dimension of the microstructural feature so that larger samples could benefit from high strengths inherent to finer features. Experimental control over microstructural dimensions and the influence on the nanopillar yield strength. From our experience with sample fabrication, prolonging the reduction step can cause grain coarsening to > 150 nm. Meanwhile, the grain growth leads 63 towards a morphology of faceted grains and uneven pillar diameter, where the product starts to resemble a stack of a few grains and would not be suitable for uniaxial compression. For such microstructure, we would expect the mechanical response to resemble that of a bicrystalline counterpart whose pillar diameter and grain size become comparable, whose yield strength (i.e., the stress required for dislocation plasticity) could be lowered as the dislocation nucleation/activation stress is in general inversely related to the free-surface radius of curvature. And this indeed has been preliminarily observed in our ongoing, unpublished work on compression of Ni nanolattices fabricated with different reduction treatment—the specimens with the coarsened grains exhibited observable decrease in yield strength. Estimating the ligament strength using the Suquet upper bound (SU)51: 𝜎𝑦𝑆𝑈 = 6𝜎𝑦𝑠 𝜌̅ /√69 − 33𝜌̅ eq. 3.6 where 𝜎ys represents the constituent material, i.e., individual ligaments, yield strength, and 𝜌̅ represents the relative density. Using 𝜌̅ ~ 90%, we obtain the ligament yield strength to be 16% higher than the pillar strength while not approaching the theoretical limit, suggesting two-fold effects of pore surfaces: (i) strengthening by dislocation escape at pore surfaces and (ii) facilitated dislocation nucleation at pore surface-GB junctions. Hakamada and Mabuchi examined the ligament yield strength-size dependence for nanoporous Au with ligament sizes of 5–126 nm using eq. 4 and obtained β = 0.20, which they attributed to dislocation nucleation at free surfaces, supporting our present argument on pore surfaces-mediated deformation50. 3.6 Conclusion and outlook In the present work, we established a multi-step additive manufacturing technique for printing metals with ~100 nm features and demonstrated the as-fabricated Ni nanopillars to possess hierarchical microstructure, exhibiting nanoporosity and nanocrystallinity with single grain-thick walls and interior ligaments. At D ≲ 350 nm, the nanopillars are mechanically robust, reaching 1–3 GPa yield strengths, higher than most other reported scand nc-Ni nanopillars. MD simulations unveiled the atomistic understanding of the 64 nanoporosity-meditated plastic deformation giving rise to the size-dependent shift in deformation modes and suppressed size effect. The present study on nanopillars—the fundamental building block of nano-architected structures—sheds light on designing the mechanical response of complex small-scale 3D designs and alternative material systems uniquely enabled by the method. Figure 3.15 takes a glimpse at the AM capabilities using the present method: NiO and Ni cuboctahedral lattices with 1-µm unit cell and 100-nm smallest feature size (Figure 3.15A–D), patterned iron oxides (Figure 3.15E), and shell-based Schwarz-P structure of metallic silver (Figure 3.15F), while work by Saccone & Gallivan et al. further suggests the potential of alloying(153). In contrast, popular commercialized metal AMs does not reach the present length scale(37, 154), and previous submicron-resolution breakthroughs are commonly hindered by complicated chemical synthesis(26, 155, 156) or low throughputs(157–159). We anticipate the AM method can facilitate high-end applications in micro-biomedical devices, in situ catalytical studies, nanophotonics, and more by combining complex microstructures and geometries. Figure 3.15 Outlooks on the AM capability and applications: SEM micrographs of cuboctahedral nanolattices of (A, C) NiO (scalebars = 1 and 2 μm, respectively) and (B, D) Ni (scalebars = 1 and 2 μm, respectively), (E) hexagonal beam pattern of Fe2O3 (scalebar = 5 μm), (F) Schwarz-P shell structure of Ag (scalebar = 3 μm). 65 Chapter 4 HYDROGEL-INFUSION-BASED ADDITIVE MANUFACTURING OF NANO-ARCHITECTED METALS—EXPLORING THE NANOPOROSITY-DRIVEN DEFORMATION 4.1 Overview The emergence of 3D printing methods for small-scale metals has enabled attaining a unique dimensional niche, on the order of 10-100 nm, at the nexus of the functional feature sizes, the critical microstructural detail, and atomic-level defects. This convergence fundamentally challenges the conventional relationships across structural hierarchies and has significant nanomechanical implications. We introduce a metal nano-printing system that combines two-photon-lithography, hydrogel infusion-based additive manufacturing, and in situ mechanical experiments on 3D nano-architected Ni, with critical dimensions of ~100 nm, surface roughness on the order of 10 nm, and a broad range of geometries (periodic vs. nonperiodic, beam-based vs. shell-based), and demonstrate their superior specific strengths of ~100 MPa.g-1cm3, enabled by an unambiguous “smaller is stronger” size effect. Experiments identified regions of concentrated porosity to serve as primary deformation initiation sources and quantified the concentrated porosity distributionembargoed.] as an input allowing us to perform [This chapter is temporarily physics-informed, multi-scale finite-element simulations to accurately predict the sizedependent mechanical properties of nano-architected Ni governed by nanoporosity-induced deformation mechanisms. Our work introduces a generalizable framework that integrates experimental and computational approaches for the fabrication, characterization, and evaluation of nano- and micro-architected metals and ceramics across structural hierarchies, applicable to the broad fields of nanotechnology and nanoscale manufacturing systems. 4.2 Introduction The field of nanotechnology has seen explosive growth, driven by the unique potential of nano-scale-enabled material properties and phenomena. These include a high surface-areato-volume-ratio for adhesion(160), nanoscale mechanical enhancement(23, 84, 161), quantum effects(162), and subwavelength optical properties(163). Metals and ceramics, 66 traditional engineering materials widely used for their superior mechanical, thermal, and electronic properties, have become central to the exploration of nanoscale technologies. This “downsizing adventure” has led to (1) intriguing discoveries in plasmonics(164), microoptics(165), and nanomechanics(21) and (2) promising opportunities in energy storage, catalysis, and biomedical applications, which in turn collectively calls for advancements in nanofabrication techniques for metals in the nano-scale regime. Despite significant advances in the additive manufacturing (AM) of metals with complex microstructures and geometries(153, 166), the direct fabrication of designed-for-function metal parts remains a challenge. This limitation arises from the insufficient resolution of > 1s μm of the mainstream laser-powder-bed-fusion-based metal AM methods(37, 167), as well as from the throughput and structural complexity and integrity constraints of emerging nano-printing methods, most of which are field-assisted or nanocluster-based(15, 41, 168–170). A critical need exists to develop a nanoscale additive manufacturing (nano-AM) method that combines superior 3D freeform capability with high-resolution precision to enable the fabrication of complex 3D metallic parts. [This chapter is temporarily embargoed.] Emerging nano-AM technologies, including two-photon-lithography-based 3D printing(170), electrohydrodynamic jet printing(39), and electrochemical nano-printing(41), have made it possible to attain the dimensional space where the functional/structural feature dimensions (e.g., the beam diameter of a wood-pile nanolattice), the characteristic microstructural length scale (e.g., nanocrystalline grain size), and the defects’ size (e.g., processing-induced porosity) all meet at ~10-100 nm. This convergence of characteristic lengths fundamentally alters the conventional paradigm for evaluating structural material response because (1) we can no longer assume a clear separation of scales or rely on homogenization approaches for lower hierarchy elements when assessing mechanical reliability, which is critical for the efficacy of nano-architectures in practical applications, and (2) the properties of the “building blocks” directly influence the performance of the overall “architecture” across higher structural hierarchies. Despite its importance, this unique feature of nano-architectures has not been systematically investigated. Practical challenges, including limitations in the precision, throughput, and reproducibility of current nano-AM 67 technologies, as well as constraints in achieving geometrical and mechanical robustness, have hindered comprehensive investigation. In this work, we demonstrate a two-photon-lithography-based hydrogel infusion nano-AM strategy (nano-HIAM) that is sufficiently versatile to produce complex 3D geometries from diverse materials systems, including metals (nickel, silver, etc.), ceramics (iron oxides, titania, etc.), and nanocomposites. Leveraging on the fabrication of monolithic metal nanopillars, which can serve as the nano-building blocks with superior strengths(171), we fully develop nano-HIAM process for complex 3D nano-architectures with 100-nm-fine feature dimensions and 10s-nm-scale surface roughness. A series of periodic beam-based and shell-based Ni nanolattices and non-periodic spinodal-like Ni nano-architectures are fabricated and reveal their unprecedented structural integrity and superior specific strengths of ~100 MPa.g-1cm3, serving as a model system to investigate the unique nanomechanical behavior arising from the converging structural and microstructural characteristic length scales. In situ nano-experiments and multi-hierarchy finite-element simulations collectively identify nanoporosity as the key factor controlling the size-dependent strength of the nano[This chapter is temporarily embargoed.] architectures and bridging the nano/micro-mechanical behaviors across structural hierarchies. These findings demonstrate an effective pathway for the fabrication and diagnosis of high-integrity nano-architected metals for nanoengineering applications. 4.3 Methods 4.3.1 Additive manufacturing sample fabrication A photoresist was prepared with mixing three components: (A) poly(ethylene glycol) diacrylate Mn = 575 crosslinker (PEGda 575, Sigma-Aldrich) in deionized water solvent at a 2.67:1 volumetric ratio, (B) a two-photon initiator solution (1.33w/v% 7-diethylamino-3thenolcoumarin (DETC, Exciton) in dimethyl sulfoxide (DMSO, Sigma-Aldrich)), and (C) a photosensitizer solution (0.05wt.% methylene blue in water, Sigma-Aldrich) at an A:B:C volumetric ratio of 100:10:2. Polymeric 3D structures were fabricated via two-photon lithography (TPL) on a Photonic Professional GT system (Nanoscribe GmbH) with a Zeiss Plan-Apochromat 63x/1.4 Oil DIC objective, at a laser power of 50 mW and speed of 7.5 mm/s, directly printed onto a Si wafer substrate. The as-TPL-printed samples were developed 68 in deionized water for 5 minutes for solvent exchange and subsequently immersed in 0.005 M aqueous solution of nickel nitrate hexahydrate (99.999%, Sigma-Aldrich) at 20°C for 12 hours to form Ni-ion-infused hydrogel 3D structures. The samples were then removed from the solution, dip-rinsed with deionized water for 1 second, air-dried for 1 minute, and transferred into a tube furnace (MTI OTF-1500X). The thermal treatment profile followed the protocol in our preceding work on additive manufacturing of Ni: the sample was opento-air calcined up to 500°C at +1°C/min, cooled down to room temperature at -3°C/min, and reduced using 100 Torr forming gas (FG; 95% N2 and 5% H2) at 590°C for 3 minutes(22). The final product was immediately transferred into high-vacuum conditions for subsequent testing or temporarily in Ar-glovebox for storage until testing. 4.3.2 Nanomechanical experiments In situ compression of Ni nanoarchitectures was performed in a scanning electron microscope (SEM; Quanta 200, Thermo Fisher Scientific) equipped with an intrinsically load-controlled nanomechanical testing module (InSEMTM from Nanomechanics Inc. and Inforce-50 actuator from KLA) under high vacuum of ~1x10-4 Pa, room temperature of 294 [This chapter is temporarily embargoed.] K, and an electron accelerating voltage of 20 kV (Figure 4.1). Pseudo-displacementcontrolled compression was performed using an 170 µm-diameter diamond flat-punch nanoindenter at a strain rate of 10-3s-1 and a data collection frequency of 200 Hz for load, P, and tip displacement after contact, Δx, which is corrected for system compliance by the module’s built-in calibration function. The height, H, and lateral dimension, L, of the nanoarchitectures as well as the feature size, t, were measured from the pre-mortem SEM micrograph. Uni-axial, nominal engineering stress, σ, and engineering strain, ε, were calculated: σ = P/L2 and ε = Δx/H. Structural relative density, 𝜌̅ , of each specimen was estimated individually based on SEM-measured dimensions using the computer-aided design (CAD) software nTopology. Note that structural relative density, 𝜌̅ , does not take into account the microstructural porosity, i.e., the presence of hollow volumes at the interior of the continuous feature surface. Such material porosity of the octahedral nanolattice is estimated separately via focused-ion-beam milling to reveal the full vertical cross-section at the middle plane of each unit cell layer and by counting the area percentage of interior pores. 69 Figure 4.1 Schematic of in situ compression using SEMentor. 4.3.3 Finite element (FE) simulations Two series of FE simulations were performed using the commercial package Abaqus(172) (Dassault Systèmes SE) to investigate the mechanical response of the unit cell and 6x6x4 unit cell array, respectively. For the simulation of stress distribution in the unit cells of the beam-based octahedral nanolattice, shell-based Schwarz-P nanolattice, and shell-based spinodal-like nanoarchitecture, models generated from 3D print files (nTopology Robust Tetrahedral Mesh) were directly meshed with C3D4 solid elements. These models were [This chapter is temporarily embargoed.] placed on a rigid substrate and subjected to compression loading from a rigid flat indenter using the Abaqus/Standard module. A typical unit cell simulation consisted of approximately 800,000 elements, assigned a linear elastic material model with a Young's modulus of 70 GPa and a Poisson's ratio of 0.3 for Ni. To model the ultimate strength prior to structural collapse, a series of 6x6x4 beam-based octahedral nanolattices with varying feature dimensions and relative densities were simulated using B31 beam elements in the Abaqus/Explicit module. These models, containing approximately 10,000 elements each, were also placed on a rigid substrate and subjected to compression loading from a rigid flat indenter. Damage accumulation in the nanolattice was modeled by element removal at critical strain. An elastic-perfect plastic material model was adopted for baseline Ni, with a Young's modulus of 70 GPa, a Poisson's ratio of 0.3, a yield strength of 3 GPa, and a failure strain of 0.05. These properties were derived from the stress-strain curves of Ni nanopillars with a diameter of 145 nm, which was mentioned in Chapter 3. To account for size effects, the failure strain was set to increase with the feature dimension, reaching 0.2 at a diameter of 70 300 nm, as suggested by nanopillar experiments. For the scaling of strength, we have adopted two different treatments: (1) The first is directly adopting the scaling law of the fracture strength of a nanopillar when modeling the nanolattices with different feature dimensions. The size-dependent scaling relationship is directed adopted from the Ni nanopillar experiments in the work of Chapter 3, where the ultimate failure strengths of the nodal elements have a scaling factor of -2 (i.e., the defect-driven regime) and the non-nodal elements have a scaling factor of ~ -0.2 (i.e., the microstructure-intrinsic regime), as shown in Figure 4.2. [This chapter is temporarily embargoed.] Figure 4.2 The size-dependent ultimate failure strengths of the present additive manufactured Ni nanopillars (Chapter 3) under uniaxial compression. (2) In the second treatment, we explicitly consider the experimentally measured sizedependent average porosity and porosity distribution in the nodal area. Linear interpolation is used to determine the average porosity at the given feature dimension, and the porosity distribution at the nodal elements is described with a gamma distribution. The size effect of the strength is modeled with the porosity-induced material degradation. The ultimate strength from FE simulation is defined as the maximum strength in the stress-strain curve. 4.4 Results 4.4.1 Two-photon-lithography additive manufacturing of metallic nanoarchitectures Figure 4.3 presents a schematic of the two-photon-lithography (TPL) fabrication process, showing the custom photoresist formulation, the glass-photoresist-silicon sandwich setup, and CAD model of the three distinct representative structures of interest: (1) a beam-based 71 periodic octahedral nanolattice, (2) a shell-based periodic Schwarz-P nanolattice, and (3) a shell-based non-periodic spinodal-like nano-architecture. In the hydrogel infusion AM approach (HIAM) developed by the authors(171), the pre-designed, as-printed organogel structures are treated with aqueous solutions of metal salts to transform into metal-infused hydrogels, which can then be calcined, reduced, and/or pyrolyzed to form replicas of the originally designed structures made of metals, metal alloys, metal oxides, and composites with great versatility enabled by tunable infusion and thermal treatment recipes. An improved photoresist formulation, with a 2 vol% of a photosensitizer solution increased the TPL printing speed by 10x and solved multiple detrimental issues including local overheating, delamination, and solvent evaporation without compromising the spatial resolution of the printed part, thereby ensuring its reliability, precision, and throughput for producing large, complex 3D geometries. [This chapter is temporarily embargoed.] Figure 4.3 Fabrication of nano-architected Ni. (A) Schematic of the two-photon lithography setup and CAD model of the printed architecture. The bottom square lattice and the spring layer are sacrificial and are incorporated into the design to ensure structural integrity and to accommodate for significant shrinkage during thermal post-processing. (BD) Fabricated nano-architectures: (i) SEM micrographs of as-fabricated octahedral, Schwarz-P, and spinodal-like nano-architectures, respectively; (ii) a zoom-in view of the 2 µm x 2 µm area outlined by a dashed rectangle in (i); (iii) corresponding CAD models with the experimentally quantified dimensions based on SEM images used for relative density 72 estimation. Dashed boxes in Bii and Cii indicate the periodic unit cells. Scale bars: Bi = 3 µm; Ci = 5 µm; Di = 5 µm. Here, we explore the nano/micro-mechanical-microstructural interplay of propertycontributing characteristic length scales between 10s and 100 nm using HIAM-fabricated 3D nano-architected Ni as a model system. Figure 4.3B–D show the fabricated nano-architected Ni products, characterized by a structural relative density, 𝜌̅ , of ~20–40%, structural feature dimensions, d, in the range of hundreds of nanometers, and surface roughness on the order of 10 nm. These results highlight the fabrication strategy’s precise feature resolution and structural definition. The microstructure of the nano-architected Ni parts is nanoporous and nanocrystalline, with ~50 nm grains and ~10% uniform nanoporosity at diameters of d ≲ 350 nm (Figures 3.6 and 3.7), consistent with what was reported by the authors for monolithic Ni nanopillars fabricated using the same protocol and exhibited strength enhancement up to ~2-4 GPa with decreasing d down to < 150 nm(171). At greater d, we observed additional regions of concentrated porosity, which brought about a two-regime dependence of the nanopillar strengths on d and on the overall nanomechanical response. [This chapter is temporarily embargoed.] Structural geometry characterizations of 3D metallic Ni nano-architectures. Figure 4.3BDiii shows the CAD model constructed according to the feature dimensions measured from pre-mortem SEM micrograph of each specimen for the purpose of structural relative density estimation. The influence of the elliptical voxel shape of the TPL laser beam on the resolved feature aspect ratio in the octahedral nanolattice is taken into account: the beam is assumed to be elliptical; both the major (Z-axis) length, a, and minor (X or Y-axis) length, b, are measured at ~10 beams; the characteristic feature size for the nanolattice specimen is then ̅̅̅̅̅̅. For the shell-based nano-architectures, the influence of the elliptical estimated as d ~ √𝑎𝑏 TPL laser voxel shape is insignificant; thus, the wall-thickness, t, is measured at 10 locations, and the characteristic feature size for the specimen is then estimated as d ~ 𝑡̅. As such, it is determined that: doctahedral varied between 163 and 445 nm with 𝜌̅ ~ 26.6% ± 3.4%; dSchwarz-P varied between 114 and 231 nm with 𝜌̅ ~ 26.6% ± 5.8%; and dspinodal-like varied between 102 and 506 nm with 𝜌̅ ~ 33.3% ± 5.1%. These d values fall within the diameter 73 range of nanoHIAM-Ni nanopillars that have been examined by the authors in their recent work for detailed nanomechanical characterizations (Chapter 3), thus enabling physicsinformed modeling of the mechanical behavior of these nano-architectures at the next structural hierarchy. [This chapter is temporarily embargoed.] Figure 4.4 Geometric properties of nanoarchitectures computed using experimentally measured parameters via SEM and subsequent CAD remodeling. The relative density is set equal 21.7% for the three nanoarchitectures used for this plot for fair comparison. 74 Furthermore, Figure 4.4 provides a comparison of the geometric properties of the three chosen nanoarchitectures, showing that under equal 𝜌̅ , the beam-based octahedral nanolattice tends to skew towards greater local curvature, the non-periodic, shell-based spinodal-like nanoarchitecture tends to skew towards greater local feature thickness, while the shell-based Schwarz-P nanolattice possesses both local curvatures and feature thicknesses following bell-shaped normal distributions. Overall, from the bar plots, it is evident that while the three geometries possess considerably different local curvature distribution with distinct means, medians, quartiles, and ranges, their local feature thickness distribution have highly comparable means and medians despite increasing range from Schwarz-P, to octahedral, and to spinodal-like geometries. This purely geometric perspective could provide potential implications for the size-dependent mechanical behaviors, the stress concentration, and potential failure modes of the nano-sized structures, which will be discussed in greater detail in latter sections. 4.4.2 In situ nano-compression unveiling structure-independent, size-dependent mechanical behaviors [This chapter is temporarily embargoed.] Figures 4.5A–C present the results of in situ nano-compression experiments on nanoarchitected Ni samples (schematics in Figure 4.1), which unveil their characteristic failure mechanism, coined “material failure” in this context, characterized by a catastrophic global collapse (②–③) that occurred in samples of all nano-architecture geometries and sizes, with structural feature dimensions ranging from d ~ 100–500 nm and relative densities, 𝜌̅ ~ 20–40%. This “material failure” mode is characterized by an extended linear loading regime, occasionally interrupted by short strain bursts in the periodic nanolattices caused by premature failure of the processing shrinkage-induced distorted base layers, followed by a single catastrophic strain burst of ~40–50%. In the octahedral nanolattice (Ai–iii, Bi–ii, and Ci–ii), this is evidenced by localized fracture events simultaneously occurring in the vicinity of the nodes across multiple unit cells. In some rare cases, we also observed a secondary failure type, a “structural failure” mode Biii and Ciii), which manifests as gradual, layer-bylayer buckling and densification (①–④/⑤). We attribute this “structural failure” to the inevitable fabrication-induced imperfections, and these samples exhibit at least ~30–50% lower nominal strengths at comparable relative density and structural feature sizes. We were 75 able to easily identify these samples by their signature of having visual defects (e.g., cracked or wrinkled walls) and low compressive stiffness during initial loading and not include them in the analysis. [This chapter is temporarily embargoed.] Figure 4.5 In situ nanomechanical response of nano-architected Ni samples. Stressstrain relations from in situ compression of nano-architectures: (A) octahedral nanolattices, (B) Schwarz-P nanolattices, and (C) spinodal-like architectures. Insets (i–iii) for (A–C) show snapshots of the corresponding nano-architectures under compression at specific compressive strains, numbered and colored to match the data. Scale bars: A: (i) = 3 µm; (ii) = 2 µm; (iii) = 10 µm; B: (i) = 4 µm; (ii) = 4 µm (upper) and 10 µm (lower); (iii) = 4 µm; C: (i) = 4 µm; (ii) = 5 µm; (iii) = 5 µm. (D and E) Ultimate strengths (corresponding to cross markers on the stress-strain curves in A–C) of the nanolattices (D, marked by squares; pink for octahedral unit cell and black for Schwarz-P unit cell) and spinodal-like nanoarchitectures (E, marked by green diamonds) as a function of feature dimension, d, plotted with estimated 𝜎𝑓𝑒𝑎𝑡𝑢𝑟𝑒 (𝑑), marked by crosses, and ultimate strength references of nanobuilding blocks, marked by grey triangles. 76 Stress-strain response, deformation behavior, and failure. Figure 4.5A presents the characteristic engineering stress-strain responses of the beam-based octahedral nanolattices, with representative in situ snapshots in insets Figure 4.5Ai–iii. Irrespective of the characteristic feature dimension, d, the octahedral lattices experienced similar deformation stages during compression. Contact establishment was immediate, suggested by the stable longitudinal modulus starting from the onset of loading. The subsequent small strain bursts ≲ 1% and ones ≲ 10% were attributed to premature failure and densification of the sacrificial base support and bottom layer(s) immediately adjacent to the base, as manifested by the difference between snapshots Figure 4.5Ai①–②, ii①–②, and iii①–②. Note that the largest nanolattice, between iii②–③, experienced additional strain burst equivalent to the height of two and one lattice layers, respectively, due to the premature collapse of the bottom layers which are tapered in geometry due to shrinkage mismatch during fabrication, leading to their lesser load-bearing capability in comparison to the upper intact layers. The ultimate lattice failure, indicated with the cross symbol, occurred via catastrophic global collapse and densification of the nanolattice layers, amounting to a total strain of ~ 40-50%, as in i②-③, ii②–③, and iii③–④. [This The ultimate failure mode was consistently observed across the chapter is temporarily embargoed.] feature dimension range ~ 150–500 nm and attributed to materials failure, meaning the loadbearing features in each repeating unit cell have reached their critical strength limit. The corresponding nominal stress level is then defined as the ultimate compressive strength of the nanolattice. Minimal recovery strain was observed upon unloading. Despite the similar deformation characters, the lattice strength was considerably higher at smaller d— approximately 10-time increase from d ~ 445 nm (Figure 4.5Aiii) decreasing to d ~ 163 nm (Figure 4.5Ai). Figure 4.5B presents the stress-strain responses of the shell-based Schwarz-P nanolattices, whose early deformation behaviors qualitatively resemble those of the beam-based octahedral counterparts (Figure 4.5Bi①–②, ii①–②, and iii①–②). Upon larger compressive strain, the majority of the Schwarz-P nanolattices, represented by the dark and light grey curves, exhibit the dominant failure mode of catastrophic global collapse attributed to materials failure, consistent with the octahedral nanolattices (Figure 4.5Bi②–③ and ii②–③). Curiously, the yellow curve demonstrates an alternative failure mode, which is 77 less catastrophic—wall buckling propagates gradually layer-by-layer (Figure 4.5Biii②– ④), followed by densification past a cumulative compressive strain of 0.6. The layer-bylayer buckling initiated from the top layer where the as-fabricated unit cells exhibit geometric distortion and pre-existing crack openings, suggesting a structural failure route occurring at lower stress level premature to meeting the materials failure criterion. Despite the similar shell wall aspect ratios between the specimens in Figure 4.5Bii and iii, their absence and presence of structural imperfections exemplify the universal competition between material failure versus structural failure at the nanoscale. Figure 4.5C presents the stress-strain responses of the non-periodic spinodal-like architecture, demonstrating similar signatures of rapid contact establishment and catastrophic collapse as the periodic nanolattice counterparts. The dark and light green curves (Figure 4.5Ci and ii) represent the materials failure-dictated nano-architecture response, showing ~ linear loading up to ~ 10% compressive strain uniformly distributed throughout the nanoarchitecture (Figure 4.5Ci①–② and ii①–②), then catastrophic collapse by ~ 60% strain via full fracture of the nano-architecture shells (Figure 4.5Ci②–③ and ii②–③), and [This chapter is temporarily embargoed.] finally minimal recovery upon unloading. On the other hand, the grey curve represents the structural failure-dictated failure via gradual shell wall buckling and densification (Figure 4.5Ciii②–⑤), similar to the Schwarz-P nanolattice specimen in Figure 4.5Biii. Note that the specimens that experienced such premature structural failure are excluded from the following analysis of the size-dependent lattice strengths, so that only specimens that experienced materials failure are considered for a clear correlation between the nanoarchitecture strengths and the “building block” material strengths. Size-dependent strengths of nanoarchitectures. For the majority of nano-architectures, which underwent “material failure,” the ultimate compressive strengths, 𝜎𝑎𝑟𝑐ℎ𝑖𝑡𝑒𝑐𝑡𝑢𝑟𝑒 , ranged from 20 to 200 MPa, and appear to depend on two independent variables: structural feature size, d, and relative density, 𝜌̅ , as 𝜎𝑎𝑟𝑐ℎ𝑖𝑡𝑒𝑐𝑡𝑢𝑟𝑒 (𝑑, 𝜌̅ ) = 𝑓(𝜌̅ )𝜎𝑓𝑒𝑎𝑡𝑢𝑟𝑒 (𝑑) eq. 4.1 78 The 𝜌̅ -dependence has been widely discussed in the context of cellular solids, micro-tomacro-lattices and their mechanical attributes; the d-dependence has been largely overlooked in literature on metal lattices, most likely due to the lack of appreciable size effects in metals at the commonly studied, previously manufacturing-viable (meso-to-macro) length scales, as well as to the limited findings of size dependence in carbon nanostructures(24, 173). This ddependence plays a critical role in the observed mechanical properties of metallic nanoarchitectures manufactured in this work, owing to the strong nanoscale size effect arising from the nano-building blocks of the nanostructures. We adopt the widely used Suquet upper bound (SU)(174) for porous solids to represent the 𝜌̅ -dependence of various nanoarchitectures in this work: 𝑓(𝜌̅ ) ∝ 𝑓𝑆𝑈 (𝜌̅ ) = ̅ 2𝜌 11 √4+ (1−𝜌 ̅) 3 eq. 4.2 We assume a power-law scaling with the exponent 𝛽 to describe the d-dependence agreeing with a common approach in discussions of nanopillar size effects(84, 171, 175): 𝜎𝑓𝑒𝑎𝑡𝑢𝑟𝑒 (𝑑) ∝ 𝑑 −𝛽 eq. 4.3 The nominal compressive[This strengths nano-architecture as a function of these two chapterofis atemporarily embargoed.] parameters can then be formulated as: 𝜎𝑎𝑟𝑐ℎ𝑖𝑡𝑒𝑐𝑡𝑢𝑟𝑒 (𝑑, 𝜌̅ ) ∝ ̅ 2𝜌 11 √4+ (1−𝜌 ̅) 3 𝑑 −𝛽 eq. 4.4 Figure 4.5D-E summarize the ultimate compressive strengths, 𝜎𝑎𝑟𝑐ℎ𝑖𝑡𝑒𝑐𝑡𝑢𝑟𝑒 , of periodic and non-periodic nano-architectures, together with the ultimate compressive strengths of their nano-building block, 𝜎𝑏𝑢𝑖𝑙𝑑𝑖𝑛𝑔 𝑏𝑙𝑜𝑐𝑘 (𝑑) , as well as the size-dependent term of nanoarchitectures’ ultimate compressive strengths, 𝜎𝑓𝑒𝑎𝑡𝑢𝑟𝑒 (𝑑) ∝ 𝜎𝑎𝑟𝑐ℎ𝑖𝑡𝑒𝑐𝑡𝑢𝑟𝑒 (𝑑, 𝜌̅ )/𝑓(𝜌̅ ) . The 𝜎𝑏𝑢𝑖𝑙𝑑𝑖𝑛𝑔 𝑏𝑙𝑜𝑐𝑘 (𝑑) data exhibits two distinct size effect regimes: (1) a suppressed size effect regime at d ≲ 350 nm (𝛽 ~ 0.2) and (2) an escalated size effect regime at d ≳ 350 nm (𝛽 ~ 2.0) We attribute the suppressed size effect in regime (1), characterized by the absolute strengths of ~3 GPa to the dislocation plasticity-mediated size dependence of strengths in nanoporosity-induced reduction in the dislocation mean free path across the grains, which renders the microstructural characteristic dimension insensitive to d. Regime (2), characterized by a power law reduction of strength from > 2 GPa to ~ 0.5 GPa represents the 79 defect-driven size dependence of strengths, attributed to increasing concentration of porosity-mediated mechanical degradation at greater dimensions. Both types of periodic nano-architectures studied in this work, the beam-based octahedral and shell-based SchwarzP nanolattices, exhibit a single power law size effect regime, with 𝛽 ~ 1.5. The non-periodic, spinodal-like nano-architectures are also described by a single size effect, with a lower 𝛽 ~ 0.7. This difference in 𝛽 exponents between the periodic and non-periodic architectures is also reflected in the fitted Weibull modulus(148), m, with mperiodic ~ 5 vs. mnon-periodic ~ 7. This difference suggests the prevalence of more (severe) defects in periodic nano-architectures, which are consistent with the short, localized strain bursts prior to global failure during compression. Non-periodic nano-architectures, which do not exhibit such bursts, imply a less defect-driven distribution of strength, with fewer critical defects acting as “weakest links.” The 𝛽 exponents for both periodic and non-periodic nano-architectures fall within the 𝛽 range of the two nanopillar size effect regimes—microstructure-intrinsic regime (1) with dislocation plasticity-mediated suppressed size dependence and defect-driven regime (2) with concentrated porosity-mediated escalated size dependence. The results suggest that the structural response of the [This nano-architectures is governed by the contribution from the nanochapter is temporarily embargoed.] building blocks, which exhibit both microstructure-intrinsic and defect-driven mechanical behaviors, with distinct relative contributions in periodic vs. non-periodic nano-architectures. Weibull modulus fitting from experimental results. Considering the potentially finite number of representative element contained in each nanoscale specimen, we adapted the expression for the failure probability based on the precursor-to-Weibull (PWBL) distribution discussed by Bernal(148) to the present experimentally measured ultimate strengths of Ni nanopillar and nano-architectures under compression: 𝜎 𝑃𝑓𝑗 = 1 − (1 − (𝜎𝑗 )𝑚 )𝑁𝑗 0 eq. 4.5 where: (i) Pfj is the failure probability of pillar #j; (ii) σj is the yield strength of pillar #j measured by the experiment; (iii) σ0 is the distribution parameter for characteristic stress; (iv) m is the distribution parameter for Weibull modulus; 80 (v) Nj is the number of representative elements in pillar #j: we consider the volume defectmediated failure mechanism. Thus, we take a 3D representative element and V0 as the distribution parameter for the size (i.e., volume) of the element; therefore, Nj = Vj/V0 with Vj approximated as the cylindrical volume for nanopillar #j or as the nominal volume of the architectures equaling the product of the bulk width cubed with the structural relative density. Table 4.1 Precursor-to-Weibull distribution least-square fitting results for nano-HIAM-Ni nanopillars and nanoarchitectures. V01/3 (nm) σ0 (MPa) m Nanopillar (regime 1: microstructure-intrinsic) 1.6E1 5.2E3 10.6 Nanopillar (regime 2: defect-driven) 0.7E1 11.9E3 5.4 Periodic nano-architecture 1.1E2 3.4E2 5.1 Non-periodic nano-architecture 1.7E3 5.4E1 7.1 [This chapter is temporarily embargoed.] We performed least-square fitting for nanopillars (regime 1 of β ~ 0.2: N = 65; regime 2 of β ~ 2.0: N = 35), periodic nanoarchitectures (N = 31), and non-periodic nano-architectures (N = 37), separately, where the experimental value of Pf(σ) is approximated by the proportion of tested specimens in each category whose yield strength was < σ. Results are summarized in Table 4.1 and Figure 4.6. 81 Figure 4.6 PWBL analysis of nano-HIAM-Ni nanopillar and nanoarchitecture ultimate strengths for fitting of their respective Weibull modulus, m. 4.4.3 Size-dependent defect as the origin of nanomechanical behavior of nanoarchitectures [This chapter is temporarily embargoed.] As the properties of the nano-building block exhibit two distinct size-effect regimes, governed by the different deformation mechanisms, with a transition at d ~350 nm, we conducted a close examination of local feature dimensions in the octahedral nanolattices to elucidate the origins of their mechanical responses. We observed multiple highly concentrated pore regions localized exclusively at the nodal junctions, where the effective local feature d is greater than the reported characteristic feature d of the nanolattice, i.e., the average beam diameter. The locally increased d near nodal junctions is also visualized by the color mapping contrast in Figure 4.7A in CAD models based on experimental measurements. This suggests that the mechanical response and the consequent strength were different for the nodal junctions and the beam segments. The concentrated porosity among nodal junctions varies within individual nanolattices and across nanolattices with different d. This variation was characterized using gamma distributions with d-dependent parameters showing an increase in mean porosity in nanolattices with larger d (Figure 4.7B). 82 [This chapter is temporarily embargoed.] Figure 4.7 Feature dimension-dependent nodal porosity in nano-architectures. (A) (i) a cross-sectional view of the feature dimension distribution in a representative octahedral nanolattice; (ii) SEM micrograph of a representative cross-section, with yellow arrows pointing to large voids concentrated at features with greater local dimensions, such as nodal junctions in periodic nanolattices; (iii) a zoom-in view SEM micrograph of a few nodes with concentrated porosity. (B) Experimentally measured size-dependent nodal porosity distributions for octahedral nanolattice with three characteristic feature dimensions, fitted using Gamma distribution. (C and D) (i) a cross-sectional view of the feature dimension distribution and (ii) SEM micrograph of a representative cross-section for Schwarz-P nanolattice in (C) and spinodal-like nano-architecture in (D); Scale bars: Aii, Cii, Dii: 5 µm. Aiii: 500 nm. Dashed boxes in Ai and Ci indicate the periodic unit cells. 83 We also observed ordered patterning of concentrated porosity in samples with the other periodic architecture, the shell-based Schwarz-P nanolattice, specifically in areas with greater effective d (Figures 4.7C and 4.8A). This type of porosity patterning is absent in the non-periodic, spinodal-like nano-architectures because of their intrinsic stochastic shell thickness variation (Figures 4.7D and 4.8B). The Weibull modulus of periodic nanoarchitectures closely aligns with that of the defect-driven-regime nano-building blocks (5.1 vs. 5.4), further highlighting the dominant role of concentrated nodal porosity in governing the global failure of periodic nano-architectures. The distinct size-dependent distributions of defects between periodic and non-periodic nano-architectures also rationalize the differences in their strength vs. size scaling. This finding underscores the critical role of defects at the peculiar convergence regime of microstructures and structures, bridging the size-dependent properties of the nano-building blocks to the higher-level response of nano-architected materials. [This chapter is temporarily embargoed.] Figure 4.8 Material porosity properties in Schwarz-P nanolattice and spinodal-like nanoarchitecture. (A) SEM micrographs of FIB-milled cross-sections of Schwarz-P nanolattice, insets show the Ga-ion FIB micrograph of the corresponding top-down view at three representative locations (i–iii). (B) SEM micrographs of FIB-milled cross-sections of spinodal-like nanoarchitecture, insets show the Ga-ion FIB micrograph of the corresponding top-down view at three representative locations (i–iii). 84 Gamma distribution fitting of the porosity distribution at lattice nodal region. As shown in Figure 4.7, concentrated porosity is observed at the nodal junction area in octahedral nanolattices and the porosity distribution can be approximated by a gamma function with feature dimension (d), dependent shape parameter (k), and scale parameter (𝜃). Based on the observation on the experimental and fitted distribution functions for three nanolattices with increasing d (Figure 4.7B), the mean porosity (𝑘𝜃) and k of the distribution function increases steadily with d, suggesting the existence of larger porosity at nodal junction areas while the change in 𝜃 is less significant especially for nanolattice with larger d. Thus, for the interpolation of gamma function parameters for any given d, 𝜃 is chosen to keep at constant values of 0.02 while k is determined from the linear interpolation of the mean porosity (𝑘𝜃) as a function of d. The fitted gamma distribution is further adopted in the finite element analysis to assign the porosity-based material properties in the nodal elements (Figure 4.9C). [This chapter is temporarily embargoed.] Figure 4.9 Material-level porosity properties from nano-HIAM-Ni nanopillars to nanoarchitectures. (A) nanopillar porosity (i) distribution and (ii) TEM micrograph, adapted from Zhang and Li, et al. Nano Letters, 2023(22) (Chapter 3). (B) SEM micrograph of porosity concentration at nodal junctions in octahedral nanolattice corresponding to d~350 nm in Figure 4.7B; inset showing FIB micrograph of the top-down view. (C) A schematic view of finite-element partitioning for an octahedral unit cell, with circular and square symbols representing the vertices of the beam elements and the nodes of the lattice, respectively, and the boxed regions indicating near-node beam elements. 4.4.4 Multi-hierarchy finite element analysis of the AM-nanoarchitectures We conducted Finite element (FE) analysis using experimentally obtained nano-building block properties and the microstructural features of the nanostructures to investigate the unique deformation mechanisms of the AM-nano-architectures. The von Mises stress 85 distributions in typical unit cells of octahedral nanolattices, Schwarz-P nanolattices, and spinodal-like nano-architectures are presented in Figures 4.10Ai, Bi, and Ci, respectively. In the octahedral and Schwarz-P units with periodic structures, we observed smoothly varying stress distributions with well-defined high- and low-stress regions. The stress field in the spinodal-like nano-architectures was more heterogeneously distributed, with the isolated stress-concentrated regions caused by their stochastic topography. Notable stress concentrations are found around the nodal junctions in periodic nanolattices (Figures 4.10Aii and Bii), which suggests their propensity for driving material failure. Histograms of von Mises stress (Figures 4.10Aiii, Biii, and Ciii) quantitatively convey that the spinodal-like nano-architectures have a broader stress distribution with longer tails in the high stress region, consistent with a higher degree of structural heterogeneity and localized stress concentrations. This increased heterogeneity suggests that material failure in non-periodic nano-architectures is dependent on site-specific local microstructure, resulting in ultimate strength that is less sensitive to feature dimensions or apparent defect distributions. This behavior aligns with the reduced scaling factor observed in Figure 4.5E. On the other hand, the shape of the von Mises[This stresschapter distribution of the periodic nanolattices qualitatively agrees is temporarily embargoed.] with those of their geometric properties, where greater skewness is consistently identified in the octahedral nanolattice compared to the Schwarz-P nanolattice in terms of local feature dimensions, local curvatures, and local von Mises stresses, suggesting a direct correlation between the “building block”-level local features and the architectural mechanical behaviors. 86 [This chapter is temporarily embargoed.] Figure 4.10 Stress distribution in (A) Octahedral nanolattices, (B) Schwarz-P nanolattice, and (C) Spinodal-like architecture: (i) exterior and (ii) cross-sectional view of the Mises stress distribution and concentrations; (iii) statistical distribution of Mises stress in the nanoarchitectures. Stress distribution in unit cell of spinodal-like architecture. Further analysis was performed to understand the effects of the geometric factors including the local curvature and shell thickness on the heterogeneous stress distribution in the spinodal-like unit cells (Figure 4.10C). The stress of one thousand randomly picked material points on the surface of the unit 87 cell was extracted from FE simulations and plotted against their local curvature and shell thickness in Figure 4.11. Figure 4.11 Correlation between the Mises stress distribution and geometric factors in spinodal-like architectures. (A) stress-curvature plot. (B) stress-thickness plot. No strong correlation was observed between the stress field and these local geometric factors suggesting that the stress field in the spinodal-like unit cells cannot be solely determined by [This chapter is temporarily embargoed.] the local structure but is also affected by the complex surrounding microstructures. This is further confirmed by our machine learning analysis using TensorFlow(176) where a neural network with 64x64x1 dense layers and ReLU activation functions was trained to learn the distribution of the stress field of the unit. The neural network could not correctly predict the stress field with only inputs of the local geometry parameters, i.e., curvature and shell thickness (Figure 4.12A) suggesting a lack of key knowledge in the input information. With the additional inputs of nodal coordinates, the neural network with the same structure started to develop the ability to predict the stress field (Figure 4.12B). These analyses further demonstrate the non-local features of the heterogeneous stress field in the spinodal-like unit cells, which leads to potentially more complex fracture behavior. 88 Figure 4.12 NN training results for the prediction of Mises stress distribution in Figure 4.11: (A) with only curvature and thickness as inputs and (B) with additional information of node coordinates. Reduced model of full lattice. The periodic octahedral nanolattice was taken as the example to illustrate the capability of capturing the structural response of the nano-architecture based [This chapter is temporarily embargoed.] on lower-hierarchy nano-building block properties. We first incorporated the lowerhierarchical-level information, including the presence of nanovoids and the experimental building block-level stress-strain response (see Methods; adopted from the work in Chapter 3), into the fracture-failure modeling of the unit cell (Figure 4.13A). We observed a concentrated plastic strain and fracture initiation at the nodal junctions (Figure 4.13Aii), consistent with the stress distribution analysis in Figure 4.10AThis feature was then integrated into the reduced FE modeling of full lattices by introducing degraded material properties into the nodal elements (Figure 4.13B). 89 Figure 4.13 Finite-element simulations of nano-architectures. (A) Stress distribution in 3D-element models of (i) octahedral, (ii) Schwarz-P and (iii) spinodal-like unit cells, which exhibit smooth transition and well-defined higher stress concentrations around nodal junctions in periodic nanolattices, in contrast to the more heterogeneous stress field in spinodal-like cell. (B) Simulations of nanoporous unit cells: (i) 3D-element model of an octahedral unit cell with randomly distributed nanopores. (ii) Plastic strain distribution in [This chapter is temporarily embargoed.] the nanoporous unit cell, simulated using materials properties extracted from nanopillar experiments. White arrows indicate regions with strain localization. (C) Reduced beam element lattice model of the full octahedral lattice: (i) 6x6x4 unit cell array of the octahedral nanolattice; Mises stress distribution at (ii) the initial deformation stage and (iii) structure failure; (iv) simulated lattice strength as a function of feature dimension, with data points colored according to the structural relative density, 𝜌̅ . The failure of a typical lattice was observed to initiate from random local nodal elements, followed by catastrophic global collapse (Figure 4.13Bi–iii), in agreement with the in situ experimental observations. We implemented each of the two independent models that describe materials property degradation into modeling the ultimate nano-architected material strength dependence on the relative density and feature dimensions: (1) homogeneous degradation of the nodal element strength, based on the experimentally measured two-regime size-effect relationship of nanopillar ultimate strengths (Figure 4.5D) and (2) random degradation from the microstructure-intrinsic regime baseline, using nodal porosity sampling based on the experimentally fitted d-dependent gamma distribution of nanoporosity. Both models successfully captured the experimentally observed size effects of the periodic 90 nanolattices (Figure 4.13Biv), which demonstrates the effectiveness of predicting the mechanical properties of nano-architected materials by leveraging the unique nanoporositygoverned deformation mechanism at the nano-building block and microstructural levels. Comparison of different material models in the FE analysis of the ultimate strength of octahedral nanolattices. Two material models were used in this work to demonstrate the capability of utilizing the building block information to predict the mechanical response of the nanoarchitecture. The baseline material properties for Ni were extracted from the compression stress-strain curve of the nanopillar with a diameter of 145 nm, and the yield strength was determined to be 3 GPa. When this value was used in both the homogeneous degradation model and the porosity-based model for the evaluation of the ultimate strength of the nanolattice, the scaling factors obtained from both models match the experimental results (Figure 4.14), while the porosity-based model yields lower values of the ultimate strength. The lower strength from the porosity-based model is attributed to strong degradation at nodal elements with large porosity, as sampled from the gamma distribution (Figure 4.7B). The porosity-based model can match embargoed.] both the scaling factor and values of [This chapter is temporarily the experimental data with a scaled yield strength, which can be interpreted as the reference strength of defect-free nanocrystalline material. Figure 4.14 Typical stress-strain curves from finite element simulations of octahedral nanolattices using beam-element models. (A) homogenized reduction model. (B) nanoporosity based model. (C) nanoporosity based model with scaled material parameters. The major difference between the homogeneous model and the porosity-based model is that the latter considers the real porosity distribution and the associated local material 91 fracture in the nanoarchitectures. The typical stress-strain curves of nanolattices with different feature dimensions and relative densities simulated with both models are presented in Figure 4.14, which clearly demonstrates a prolonged non-linear region prior to the ultimate stress in the porosity-based model, resulting from the local damage at nodal elements with large porosity. As a consequence of the modeling of real porosity distribution, the porosity-based model predicts an increased magnitude of the scaling factor with larger feature dimensions (Figure 4.15), suggesting a stronger effect of the building block defects on the mechanical response of the nanoarchitecture. [This chapter is temporarily embargoed.] Figure 4.15 Size dependence of the simulated lattice strengths. 4.4.5 Nano-AM Ni nanoarchitectures with unprecedented structural integrity and specific strengths Figure 4.16A shows the specific strengths of our current nanoarchitectures compared to metallic lattices fabricated using other AM methods, such as powder bed fusion for titanium alloy meso-lattices and indirect templating for hollow-beam nanolattices of fcc-metals. In the mesoscale regime of metallic lattices, there exists a strong “smaller is weaker” trend, decreasing from ~200 to ~1 MPa.g-1cm3 with feature dimensions decreasing from ~1 to ~0.05 mm, likely due to compromised manufacturing integrity with decreasing dimensions, as opposed to in the submicron feature dimension regime. The present work defines an 92 unoccupied area in the parameter space by achieving specific strengths that are (1) comparable to meso-to-macro-lattices of titanium alloys(177–180) and steels(181–183), while being 1000 times smaller, and (2) 10 times higher than previous additively manufactured Ni nanolattices(26), benefitting from the significant resolution and structural integrity improvement of the present nano-AM method and the nanocrystalline, nanoporousmicrostructure-intrinsic nanomechanical enhancement. Figure 4.16B places the present Ni nanopillars and nanoarchitectures in the broad context of the nominal strength-density relation of various material categories. For the present nano-AM Ni architectures, periodic nanolattices lie above the domains of porous metals and metal composites as well as dealloyed nanoporous metals, while the present non-periodic nanoarchitectures fall inside those domains characteristic of stochastic topologies, e.g., via spinodal decomposition during dealloying. The distinction re-emphasizes the chosen periodic architectures’ greater axial loadbearing capacity. [This chapter is temporarily embargoed.] Figure 4.16 Mechanical performance of Ni nanoarchitectures. (A) Specific strengths as a function of feature dimensions, compared with data from prior studies(21, 26, 177–189); (B) Relationship between density and nominal strength for various categories of materials, highlighting the performance of Ni nanoarchitectures relative to existing material systems(22–24, 190). While the present Ni nano-architectures fit within the strength-density regime of conventional metals, the monolithic Ni nano-building blocks from the authors’ previous work(171) exhibit superior strengths > 1 GPa. This observation highlights the importance of 93 cautious extrapolation of building block-level mechanical properties to higher structural hierarchies. This caution is warranted due to the strong nanoscale size effect in metallic materials, which are associated with transitions in fundamental deformation mechanisms(28, 151), as well as with the introduction of defects with dimensions comparable to the pristine building blocks in larger architectures. These factors highlight the need to directly probe the mechanical performance of nano-architectures to properly assess functionality of the components they comprise and to validate any computational model. Both the building block properties and the unique higher-structure-level-specific features (e.g., defects) are essential for developing high-fidelity numerical evaluations and computational predictions of the mechanical response in nano-architected and hierarchical materials (i.e., natural materials such as bone, nacre, organs, as well as engineered materials such as nanoelectromechanical system devices, nanorobots, etc.). Neglecting critical features, such as the presence of concentrated porosity at nodal intersections, could cause false overestimation of the strength and a wrong prediction of failure stress, especially under fatigue loading as expected in biomedical implants, flexible electronics, and aerospace micro-structures. Our work showcases the necessity and the utility of a physics-informed framework that bridges [This chapter is temporarily embargoed.] structural hierarchies, providing essential guidance for diagnosing, predicting, and designing complex architectures at the nanoscale. 4.5 Conclusions We demonstrate the fabrication of nano-architected metals with superior resolution and structural integrity enabled by a novel nanoscale additive manufacturing approach based on two-photon lithography and hydrogel infusion (nano-HIAM). The produced nickel nano-architectures – beam-based and shell-based, periodic and non-periodic – exhibit remarkable specific mechanical strengths, achieving ~10-100 MPa.g-1cm3 at feature dimensions of ~100-500 nm. These structures surpass the fabrication precision and structural complexity limitations of all existing metal additive manufacturing methods today. In situ nano-compression experiments unveiled unique nanomechanical behaviors in the regime where structural, functional, and microstructural dimensions converge, ~10-100nm. 94 A predominant global “material failure” mechanism allows for a direct correlation between the structural response and the experimentally measured strength of nano-building blocks that comprise the nano-architected materials. Through integrated experimental characterizations and physics-informed, multi-hierarchy finite element analysis, nodal nanoporosity is identified as the key factor controlling deformation modes and sizedependent strength, which ultimately links the nano-building block properties to the structural response of representative octahedral nanolattices. This study highlights nano-architected Ni as a model system to demonstrate the capability of nano-HIAM for fabricating complex 3D geometries with high resolution. Future work could explore the application of the nano-HIAM method to more complex material systems and microstructures, including multi-principal elements alloys, ceramics, doped carbon composites, hetero-structured nanostructures, and muti-stable nano-architecture. The versatile infusion and thermal treatment processes of nano-HIAM, combined with its superior 3D-freeform capability, could enable wide multifunctional applications in nanotechnology. The nano-defect-meditated size-dependent structure properties identified [This chapter is temporarily embargoed.] here likely extend to other nano-architectures with converging characteristic dimensions, posting new challenges for developing high-fidelity multi-hierarchy modelling frameworks for evaluating and designing nano-architectures with superior target properties. Our work demonstrates a novel additive manufacturing strategy for complex nanoarchitectures and establishes a platform that couples experiments and modelling for the characterization and evaluation of nano-architectural properties across structural hierarchies. This versatile nano-HIAM technology for creating intricate 3D nanoarchitectures is readily generalizable to various nanoscale additive manufacturing schemes and hierarchical systems and offers broad applicability in emerging nanotechnology fields, including Nano-MEMS, nanorobotics, and sustainable manufacturing. 95 Chapter 5 OUTLOOK: A MICRO-TO-NANOSCALE ADVANCED MANUFACTURING PLATFORM FOR COMPLEX SYSTEMS AND ENERGY APPLICATIONS 90% of global CO2 emissions come from fossil fuels combustion. The global goal of Net Zero Emissions by 2050 invokes significant demand for air CO2 capture and conversion, renewable electricity, and clean fuel technologies. The development of these surging industrial sectors critically requires the advancement of electrochemical materials widely used for CO2 reduction for hydrocarbon fuels, for water electrolysis for green H2 fuel, for fuel cells for clean electricity, and so on. Among the wide selections, the major categories include metals/alloys (Pt, Ni, etc.) for their electrical conductivity and distinct catalytic activity for CO2 reduction, O2 reduction, and/or H2 evolution; ceramics (perovskites, IrO2, transition metal oxides, etc.) for their ion conductivity, O2 evolution/reduction catalytic activity, Li-ion storage capacity, etc.; hard carbons; composites (Pt-graphene, Fe-NC, etc.); and emerging polymer-inorganic composite electrolyte materials. In many cases, the electrochemical active phases are in the form of nano-to-micro fine particles, whether loaded in a slurry (matrix) or not, forming a nano/micro-porous network allowing, e.g., gas diffusion and targeting for high specific area and activity. However, such nanoparticle form factors typically lead to compromised mechanical strengths and thermal stability; consequently, conventional energy cell designs are highly subject to trade-offs between electrochemical activity and thermal/mechanical reliability, e.g., in proton exchange membrane electrolyzers or fuel cells and solid oxide fuel cells. Similar trade-off between energy density and power density exists in conventional Li batteries slurry electrode design concerning ion transport. Further, the incorporation of catalytic nanoparticles such as platinum group metals and derivatives demand improvements as well towards lower loading but higher catalytic efficiency. Enabling controlled 3D free-form structures to energy materials will decouple electrochemical activity & structural integrity, decouple extrinsic dimensions & intrinsic 96 electron/ion transport distances, and lead to potential breakthroughs in performance and stability enhancement of energy systems. Advanced additive manufacturing thus represents a new opportunity addressing the challenges while providing further benefits: e.g., submicron feature dimensions for high catalytic efficiency, extraordinary mechanical strength and thermal durability, enhanced charge species transport, and improved gas diffusion via lowtortuosity structural designs, hierarchical porosity networks, and topological optimization. Additive manufacturing (AM) represents a variety of techniques that allow, commonly layerby-layer, fabrication of 3D structures with wide materials selection, e.g., polymers, metals, and ceramics. In conventional metal AM techniques (powder bed fusion (PBF), i.e., selective laser melting (SLM), and alike), a mobile high-intensity laser locally melts metallic powders to fuse into larger geometries. The technique is inherently energy-intensive, due to hightemperature requirements for melting (typically > 1000°C)(191) and plasma atomization (~10000°C)(192) for high-quality powder preparation. Besides, 10s-µm powder sizes hamper the spatial resolution refinement of conventional metal AM to emulate feature dimensions in widely used electrochemical materials, and high-temperature processing may further undermine the AM metal’s catalytic activity. While potentially adaptable for composites, the associated plasma-assisted ball milling process for composite powder preparation is also costly and energy-demanding. On the other hand, typical AM methods for ceramics also include direct ink writing, stereolithography using photosensitive ceramic slurry, and so on, which may have compromised 3D freeform-ability (i.e., being 2.5D) and/or rarely achieve comparable spatial resolution comparable to typical 10s-µm thicknesses of non-architected conventional electrode. Consequently, despite enormous enthusiasms from academia, research labs, and industries in AM and energy materials, the integration of the two themes—AM of energy materials—has lagged behind and requires new AM strategies to guide its way, where hydrogel infusion additive manufacturing (HIAM)—the core technique in Chapter 3 and Chapter 4—is a great candidate. In comparison to conventional metal AM, HIAM overcomes resolution limits, mitigates fine particle handling risks, encompasses wider materials categories, and reduces energy 97 requirements (e.g., polymer-to-oxide conversion at below ~ 400°C). Thus, there is indeed a solid foundation for the explorations of HIAM as a platform for energy materials, bringing key innovations to electrode designs and applications: (1) Free 3D design: tunable solid-pore networks for machine learning-driven conductivity, diffusion, and stability optimization. (2) Microstructure control: HIAM decouples microstructural and structural hierarchies, untying the functional performance vs. stability trade-offs. (3) Enhanced strength and interfacial bonding: chemically derived composites offer increased robustness against thermal and mechanical stresses for improved operational stability. With these bright pictures, Chapter 5 aims at providing an outlook, through the demonstration of three preliminary progresses in Sections 5.1 to 5.3 to showcase the development of an additive manufacturing platform for versatile electrochemical materials fabrication and motivate the exploration of the AM-enabled performance enhancement by the revolutionary 2D-to-3D transformation in the design and manufacturing of functional materials, laying a robust playground to address scientific challenges such as ion conductivity influenced by tunable electrolyte-electrode interfaces and topologies. Additionally, this chapter highlights broader implications for precision manufacturing, resource circularity, and sustainability. 5.1 Composition-dependent microstructure and mechanical behavior in multi-element, additively manufactured metal/ceramic nanocomposites Progress in additive manufacturing has brought new opportunities to fundamental studies and novel applications of ceramics. With nanoscale hydrogel infusion additive manufacturing, two-photon lithography-prepared polymer 3D structures are infused with aqueous metal ions (Fe and Ni) chapter and thermally treated in multiple gas conditions sequentially [This is temporarily embargoed.] for conversion into nano-crystalline metal/oxide composites with < 1000 nm structural dimensions and ~ 10-100 nm microstructural grain sizes. By varying the Ni/Fe atomic ratio at the infusion step, subsequent air calcination could lead to a variety of oxide phase 98 assemblages and microstructures, including wüstite-, magnetite-, and hematite-based phases, all having Fe partially substituted with varying concentrations of Ni. Additional thermal treatment with 5% H2 gas further leads to reduction and sintering, forming unique nanocomposites with Fe-dominant magnetite and Ni-dominant metallic dual matrices, which exhibit composition-dependent phase distributions and mechanical behaviors transitioning from ceramics-dominant to metal-dominant characteristics. 5.1.1 Methods Additive manufacturing fabrication. Following the nanoscale hydrogel infusion additive manufacturing (nano-HIAM) fabrication protocols in Chapter 3 and Chapter 4, a photoresist was mixed with poly(ethylene glycol) diacrylate Mn = 575 crosslinker (PEGda 575, SigmaAldrich), deionized water, two-photon initiator solution (1.33w/v% 7-diethylamino-3thenolcoumarin (DETC, Exciton) in dimethyl sulfoxide (DMSO, Sigma-Aldrich)), and photosensitizer solution (0.05wt.% methylene blue in water, Sigma-Aldrich) at 73:27:10:2 volumetric ratio. Polymeric architectures were fabricated on a single-crystalline silicon wafer as the substrate via two-photon lithography (TPL) on Photonic Professional GT (Nanoscribe [This chapter is temporarily embargoed.] GmbH) with a Zeiss Plan-Apochromat 63x/1.4 Oil DIC objective at a laser power of 50 mW and laser speeds of 1.5–15 mm/s. The printed samples were developed in deionized water for 5 minutes for solvent exchange and subsequently immersed in 0.01–1 M aqueous solution of ammonium iron (II) sulfate hexahydrate (99.997%, Sigma-Aldrich), or iron (III) nitrate nonahydrate (99.95%, Sigma-Aldrich) and nickel nitrate hexahydrate (99.999%, SigmaAldrich)) at 40°C for 1–3 hours to form a hydrogel infused with Fe (and Ni). The samples were then removed from the solution and transferred into a tube furnace (MTI OTF-1500X) for thermal treatment under various gas environments, including argon, forming gas (FG; 95% N2 and 5% H2), and air. For the first-step thermal treatment of converting the metalinfused hydrogel into a ceramic, the temperature profile includes ramping up at 1°C/min to 500°C (used when flowing air at 1 atm) or 600°C (used when flowing argon or FG at 0.02 atm), no holding, and ramping down at -3°C/min back to room temperature. For air-calcined samples, a second-step thermal treatment followed for further reduction; its temperature profile includes ramping up at 5°C/min to 700°C under vacuum (0.0003 atm), holding at 700°C for 20 min under 0.53 atm FG, ramping down at 5°C/min back to room temperature 99 under vacuum (0.0003 atm). The thermally treated samples were immediately transferred into argon glovebox until characterizations. Microstructure characterizations. Secondary-electron micrographs were collected in Versa 3D (Thermo Fisher), a dual-beam focused-ion beam scanning electron microscope (FIBSEM), which was also used for cross-sectioning and preparing transmission electron microscope (TEM) lamellae using the FIB lift-out method. TEM and scanning transmission electron microscopy (STEM) were conducted at 200 keV using JEM-2800 (JEOL) for STEM-mode energy dispersive X-ray spectroscopy (EDS) and at 300 keV using JEMARM300F (JEOL) for STEM-mode electron energy loss spectroscopy (EELS). The TEM data acquisition and analysis were performed using Gatan DigitalMicrograph software (AMETEK, Inc.). The near-edge X-ray absorption spectrum (NEXAS) was performed at beamline 5.3.2.2 at the Advanced Light Source (ALS) at the Lawrence Berkeley National Laboratory (LBNL). In situ nanomechanical experiments. in situ uniaxial compression of individual [This chapterSEM-based is temporarily embargoed.] nanopillars was performed using the FT-NMT04 system (FemtoTools AG) inside Versa 3D (Thermo Fisher). A quasistatic strain rate of 0.005 s-1 was used. The pillar diameter, D, and height, H, were measured via SEM immediately before testing; load, P, and tip displacement, Δx were recorded by the system during testing at 100 Hz. Engineering stress, σ, and strain, ε, were computed: σ = 4P/πD2 and ε = Δx/H. 5.1.2 Results Infusion. Due to differential affinity between the hydrogel polymer and the metal ion species, when more than one metal species is introduced at the infusion step, the differential/preferential uptake of competing metal species has to be taken into account. Proper adjustment of the Ni-to-Fe ratio of the infusion solution is required to produce the desired Ni-to-Fe ratio in the final ceramic/metal product. Figure 5.1 shows the relationship where the slope of ~0.82 of the fitted line suggests that in a mixed solution of iron (III) nitrates and nickel (II) nitrates, iron (III) is more preferentially infused than nickel (II). 100 Figure 5.1 Relationship between Ni-to-Fe atomic ratio in infusion solution and that in oxide products. Note that this relationship is specific to the infusion solution contains iron (III) nitrates and nickel (II) nitrates at the designated ratios. Calcination or pyrolysis. Different first-step thermal treatment conditions lead to qualitatively similar phase assemblage and microstructures regardless of the gas species and pressure, as manifested in Figure 5.2A–C, particularly for systems infused with Fe(II) only, Fe(III) only, or cFe(III) > cNi(II). Whether the metal infused hydrogel is directly treated with low-pressure (0.02 atm) FG or Ar or ambient-pressure (1 atm) ambient atmosphere, the gel is transformed into a nanoporous, nanocrystalline matrix of iron oxides. Under the more [This chapter is temporarily embargoed.] reducing pyrolysis environment of FG in which case a Fe(II) precursor was chosen with special considerations rather than the more commonly used Fe(III) precursor, the nanocrystalline oxide grain size (equivalently, the nanoporous oxide ligament size) was 29.9 ± 6.6 nm, moderately greater than that from the inert pyrolysis environment of Ar (15.2 ± 2.1 nm) or that from open-to-air calcination (16.5 ± 2.6 nm). From high-resolution TEM (HR-TEM) at ~ six-million-time magnification and the corresponding FFT, the crystallographic assemblages under the three distinct conditions are found to be comparable—showing diffraction signatures from both the hematite (Fe2O3) and magnetite (Fe3O4) phases. Figure 5.3 highlights the selected areas of Figure 5.2A(i) and (ii), clearly exhibiting the atomic arrangement of the magnetite phase along the respective zone axes and thus providing direct evidence of the presence of the magnetite phase after the first-step direct hydrogel-ceramic conversion reaction. Furthermore, STEM-EDS as the inset in Figure 5.2CHAADF shows a homogeneous distribution of the small amount of Ni in the Fe-dominant compositions in these calcination/pyrolysis products. 101 Considering the highly similar calcination/pyrolysis results from the different attempted recipes, subsequent reduction experiments and further sample preparation for mechanical characterizations is carried out from the open-to-air calcination recipe due to the simplicity of material handling and the greater stability and consistency of the processing conditions, quality, and results. [This chapter is temporarily embargoed.] Figure 5.2 Transmission electron microscopic characterizations of first-step thermal treatment products I: (A) 0.02-atm FG-treated Fe(II)-infused hydrogel; (B) 0.02-atm Artreated Fe(III)-infused hydrogel; (C) 1-atm air-treated Fe(III)-and-Ni(II)-infused hydrogel at cFe(III) >> cNi(II); 102 Figure 5.3 High-resolution TEM of Fe3O4 nanograins corresponding to white-dash-boxed areas (i) and (ii) in Figure 5.2A. Insets show the corresponding crytal lattice structure projection along the determined zone axis (Z.A.) with green atoms representing Fe and red atoms representing oxygen. However, when applying the identical open-to-air calcination experiment to metal-infused hydrogels whose infusion composition approaches embargoed.] equal-molarity between Fe(III) and [This chapter is temporarily Ni(II), the microstructure and the phase assemblage become fundamentally different, as shown by Figure 5.4 in contrast to Figure 5.2C. Figure 5.4 Transmission electron microscopic characterizations of first-step thermal treatment products II: 1-atm air-treated Fe(III)-and-Ni(II)-infused hydrogel at cFe(III) = cNi(II). 103 The product becomes increasingly nanocrystalline but less openly nanoporous. It achieved an average grain size of 4.8 ± 0.8 nm, which is significantly lower than those from Fedominant compositions. Furthermore, the phase assemblage is completely altered from the dual presence of hematite and magnetite to a single-phase solid solution of wüstite (FeO) and NiO, as evidenced by the FFT of HR-TEM in Figure 5.4. This observation is highly consistent with the fact that wüstite and NiO crystalline lattices share the same space group of Fm ̅ 3m (the same space group as face-centered-cubic, fcc, metals) and possess highly similar lattice parameters with a = 4.26 Å for wüstite and a = 4.19 Å for NiO. The solidsolution conclusion is further supported by the STEM-EDS mapping (inset to the HR-TEM in Figure 5.4) demonstrating identical spatial elemental distribution of Fe and Ni at a scale below the 5-nm-grain-size and using a < 1-nm high resolution. Interestingly, recall that, in Chapter 3, the microstructure and grain size of the open-to-air NiO intermediate product is highly similar to the present result, suggesting that Ni-infused and Fe-infused hydrogels could share different nucleation kinetics under concerted the air/oxygen combustion of the hydrogel polymer and the thermal decomposition of the metal nitrate salts. [This chapter is temporarily embargoed.] Reduction. The open-to-air calcination products with varying Ni-to-Fe compositions were subsequently reduced under an identical protocol to examine the composition-dependent microstructure evolution. The identical reduction profile led to the same phase assemblage of a magnetite-based oxide phase and a Ni-based metallic phase, while the varying final oxide phase composition with Ni/(Ni+Fe) ranging 7% to 80% led to a spectrum of the dual phase distribution and thus characteristically different microstructure morphologies. These results are summarized in Figure 5.5, showing a transition from a magnetite-matrix-dominant microstructure at low Ni content to a metallic Ni-matrix-dominant microstructure at high Ni content (left to right) with an intertwined “dual-matrix” signature at intermediate compositions, whose mechanical implication was explored and is discussed towards the end of this section. 104 Figure 5.5 Composition-dependent microstructure in reduction products from the open-to-air calcination samples. Top row: HAADF; second row: STEM-EDS; third row: Fe signal count map; fourth row: Ni signal count map. All labeled Ni/Fe ratios are elemental [This chapter is temporarily embargoed.] atomic ratios. White arrows indicate Ni nanograins dispersed in the oxide matrix; yellow arrows indicate the Fe elemental segration to grain boundaries of metallic Ni in Ni-matrixdominant compositions. At low Ni percentage (7% - Figure 5.5), metallic Ni are present as ~ 10 nm-sized dispersed grains in the magnetite matrix, which has ~ 100 nm grain sizes. Besides residing in the form of segragated Ni grains, the rest Ni content is dissolved in the magnetite matrix, as suggested by the atomic ratio Ni/Fe ~ 1/12 measured inside the matrix regimes. This Ni incorporation is likely in the form of partial substitution of Fe(II) with Ni(II) in the magnetite phase, forming (Fe,Ni)Fe2O4, which retains the crystallographic signatures of the original Fe3O4 magnetite. As Ni percentage increases, metallic Ni grains grow in irregular shapes which trace the magnetite grain boundaries with ~ 10s nm widths. The STEM-EDS mapping if the specimen with 33% Ni percentage suggests potential locally saturated substitution of Fe(II) with Ni(II) in the magnetite matrix, whose atomic Ni/Fe approaches 1/2, indicating a chemical 105 composition of NiFe2O4; meanwhile, Ni/Fe ~ 40 was found in the adjacent metallic Ni phase, indicating a solid solution of small amounts of Fe in the metallic phase as well. As the Ni percentage continues to increase and surpasses that of Fe, metallic Ni becomes a continuous matrix enclosing the magnetite-based oxide grains, whose size decreases from ~ 100 nm to 10s nm with decreasing Fe percentage. The Ni/Fe ratios in both the metallic Ni matrix and the now segragated oxide grains do not experience large changes at global Ni percentage > 33%. Although, at global Ni percentage > 50%, it may be more frequently identified that additional Fe content are segregated into the grain boundary areas between metallic Ni grains (yellow arrows in Figure 5.5). At all compositions, the reduction product possesses some volume of interior nanopores due to limited diffusion and volumetric shrinkage during the H2 reduction. Meanwhile, the grain size of the matrix phase and interior porosity are not sensitive to Ni/Fe compositional changes. Figure 5.6 focuses on the[This Ni percentage 50% sample in Figure 5.5 and in detail examines chapter is=temporarily embargoed.] the phase assemblage, confirming the ubiquitous presence of the magnetite phase and the metallic Ni phase. The STEM-EDS mapping is juxtaposed with the TEM imaging of the same ~150 nm x 300 nm area, showing the interesting microstructure of two Fe-dominant grains enclosed in a continuous Ni-dominant matrix with additional thin areas of Fe segragation to the Ni grain boundaries and triple junctions. HR-TEM, FFT, and diffraction pattern simulation in the Ni-dominant area, (i), and the Fe-dominant area, (ii), were carefully collected and analyzed, confirming that the phases are indeed fcc-Ni nad magnetite, respectively. Note that the volume of the Fe segragation at Ni grain boudaries is below the spacial resolution of the characterizations; thus, it is unclear whether this unique interfacial Fe content is present in a crystalline form or an amorphous ordering in accordance with the typical amorphous nature of non-special grain boudaries. The latter possibility of a potentially disordered interfacial presence may be the more plausible explanation. 106 [This chapter is temporarily embargoed.] Figure 5.6 Phase assembalge characterization with HR-TEM images, FFT of the full image, and simulated diffraction patterns. The two rows of results correspond to the labeled (i) and (ii) areas in the juxtaposed STEM-EDS mapping and TEM images. Figure 5.7 provides additional evidence on the phase assemblage of the Ni/magnetite nanocomposite at the intermediate Ni ~ Fe compositions. The shift in the peak position of the Fe L-edge fine structure measured by both the electorn energy loss spectroscopy and the near-edge X-ray absoprtion spectroscopy acts as direct indication of the valence state of the Fe center(193–196). The reference Fe(III) L-edge XANES profile (black dashed line) of the Fe(III)-infused hydrogel sample shows a peak position of 710.7 eV, which is characteristic of Fe(III) valency. The Fe L-edge EELS profiles taken from the Ni and Fe-rich areas (blue and green solid lines, respectively) exhibit peak positions around 708 eV, which is 107 characteristic of Fe with zero valence, thus confirming that Fe is likely present in a solid solution state in metallic fcc-Ni matrix and occasionally forms metallic Fe grains, which are likely bcc-Fe. Note that the present results does not exclude the possibility of medium or short-range order formation between Ni nad Fe atoms in the metallic phases . On the other hand, the Fe L-edge EELS profile taken from the O-rich area (red solid line) with a peak position of 709.6 eV clearly distinguishes the present phase from hematite containing Fe(III) only and instead suggests the presence of Fe(II) and Fe(III) in accordance with magnetite. The presence of a lower-eV shoulder peak for hematite vs. the lack of such a shoulder peak for magnetite assures that the oxide matrix is magnetite-dominant without remnants of unreduced hematite. [This chapter is temporarily embargoed.] Figure 5.7 Electron energy loss spectroscopy mapping showing phase assembalge in the reduction product with intermediate Ni ~ Fe atomic compositions. Note that the dashed line is XANES rather than EELS. 108 From the Ni L-edge EELS spectra, while Ni and Ni(II) have been demonstrated to have indistinguishable core-loss peak positions(197), we identify clear distinctions in the positions and intensities of the pre-edge ~ 844 eV and post-edge peaks ~ 865 eV and 871–872 eV between the metallic Ni-dominant area (blue solid line) and the O-rich area (red solid line), suggesting the presence of Ni in a non-metallic, oxidized form, likely as Ni(II) at low concentrations substituting Fe(II) in the magnetite phase. From the above phase assemblage and microstructure characterizations, we have discovered a unique Ni/magnetite nanocomposite AM product, with particularly interesting “dual matrix” morphology at the intermediate compositions. Figure 5.8 shows the composition-dependent, microstructure-dependent mechanical responses of as-AM-fabricated Ni/magnetite nanocomposite micropillars with diameters ~ 1 μm examined via SEM-based, intrinsically displacement-controlled, quasi-static in situ compression. [This chapter is temporarily embargoed.] Figure 5.8 In situ compression of micropillars of Ni/magnetite nanocomposites showing composition-dependent mechanical responses (SEM images are pre- and post-failure snapshots of the same micropillar corresponding to the top-row engineerings stress-strain relationships at the indicated Ni atomic percentages). From oxide-dominant to metal-dominant compositions, the stress-strain relation transitions from a rapid load drop to plateauing and to typical strain hardening behavior in metals; the deformation behavior transitions from brittle, simultaneous global fracturing (yellow arrows), suggesting intergranular fracture along grain boundaries in the oxide matrix at low Ni percentages, to crack propagation arrested by the metallic “dual matrix” at intermediate Ni 109 percentages, and to localized plasticity via shear banding through the metallic matrix (pink arrows) at high Ni percentages. Figure 5.9 summarizes the composition-dependent ultimate strengths and yield strengths as well as the deformation (assessed by the flow stress level retainment past yielding point) of the as-AM-fabricated nanocomposite micropillars. The yield strength is determined as the earlier of either the first load drop or the 0.2%-strain-offset strengths past the linearity regime. In many cases, the two criteria lead to the same yield strength determination. The ultimate strengths is determined as the maximum stress reached prior to any catastrophic load drop or structural failure event. The flow stress past yielding point is considered non-zero only when no catastrophic load drop or structural failure event occurs within the post-yielding strain interval. [This chapter is temporarily embargoed.] Figure 5.9 Composition-dependent (A) strengths and (B) deformability of Ni/magnetite nanocomposite micropillars. While at all compositions, the micropillars show consistent GPa-scale high strengths, the low-Ni-percentage, magnetite-matrix-donimant micropillars show the greatest srengths scattering, including a lower-yield strength tail approaching < 400 MPa, exemplying the characteristic brittleness of cemaric materials. The strength scattering and weak outliers are 110 rarely seen at > 50% Ni percentage, benefitting from the plasticity and deformability of the increased and increasing continuous metallic component. Stochastic microstructure (with no texturing but stochastic placement of the metallic component) as well as the small Dpillar/dgrain ratio result in fracturing events at various stress levels and cause large standard deviation of the pillar strengths, especially at low Ni percentages. Figure 5.9B clearly reveals the positive correlation between the flow stress retainment and the metallic phase presence. At low Ni percentages (8%–22% and 30%–36%), few micropillars remain load-bearing at 10% strain past the yielding point; at intermediate Ni percentages (50%–67%), ~ half of the examined micropillars could sustain > 0.5 GPa flow stress at 10% strain past yielding, and ~ half of them could further sustain > 0.5 GPa flow stress at 20% strain past yielding. At high Ni percentages (~80%), most micropillars could sustain > 1 GPa flow stress at 10% strain past yielding, which continue to carry > 0.5 GPa flow stress at 20% strain past yielding. Thus, we have demonstrated: [This chapter is temporarily embargoed.] - Two photon lithography enables additive manufacturing of Fe/Ni (oxides) nanoarchitectures with tunable compositions. - Pyrolysis or calcination of Fe(Ni)-infused hydrogel nano-structures leads to nanocrystalline hematite/magnetite assemblage at low Ni percentages and singlephase FeO/NiO solid solution at cNi ≳ cFe. - H2-reduced nanocomposite’s microstructure transitions from magnetite matrix with dispersed Ni nanograins at low Ni content to Ni matrix with dispersed magnetite as nanograins or Fe at grain boundaries at high Ni content. - Micropillars under compression transitions from brittle fracturing to localized shearing with increasing metallic composition, consistently achieving ~ 0.6–2.0 GPa. The present multi-step, nanoscale additive manufacturing provides a robust pathway to simultaneously tune the composition, microstructure, and structural dimensions of metal oxides-based materials with submicron resolutions (Figure 5.10). Future studies are encouraged to target examining their properties, e.g., magnetic, and expanding the 111 framework for alternative ceramics systems, paving the way toward functional applications at nano-to-micro length scales. [This chapter is temporarily embargoed.] Figure 5.10 As-fabricated iron oxides nano-architectures. 5.2 Metal/carbon nanocomposites via vacuum HIAM—microstructure and magnetic perperties 5.2.1 Methods Hydrogel infusion additive manufacturing. Different from nano-HIAM discussed in this work up to this point, the HIAM product in this section is 3D-printed via digital light processing (DLP), a microscale technique, rather than two photon lithography, a nanoscale technique. The photoresist formula as well as the infusion recipe were reported by Saccone et al.(153), representing slight variaton from those used in Chapter 3 and Chapter 4 of the present work. As nano-HIAM does, the regular HIAM incorporates a similar two-step thermal treatments of calcination and reduciton. However, here, we explore an alternative thermal treatment route, referred to as vacuum HIAM, in order to achieve an unconventional metal/carbon nanocomposite micro-architecture, possessing a uniquely complex hierarchical 112 microstructure and phase assemblage. The thermal treatment protocols of two-step regular HIAM and single-step vacuum HIAM are compared in Table 5.1. Table 5.1 Thermal treatment protocols comparison between regular HIAM and vacuum HIAM. Regular HIAM Vacuum HIAM First step Gas environment 50 sccm air Vacuum (~ 0.0025 atm Ar) Peak temperature 700 °C 900 °C Gas environment 150 sccm forming gas - Peak temeprature 900 °C - Second step The vacuum HIAM strategy was motivated by the attempt to retain carbon in a constructive fashion in the predominantly metallic product of regular HIAM. Notably, the HIAM procedure has the potential to produce these carbon phases via catalytic graphitization(198) and circumvent high-temperature processes which are normally required. Under the vacuum HIAM thermal processing, the formation of metal carbides at ~ 900 °C and subsequent decomposition of the metal carbide upon cooling at lower temperatures could result in graphitic carbon phase formation, which typically require temperatures exceeding 2000 °C via the alternative synthesis route of the pyrolysis of organic precursors. Thus, suitable modificaiton of the regular HIAM for pyrolysis could (1) open a novel pathway of graphitic carbon formation at lower-than-tranditional temperatures and (2) allow for the integral incorporation of hard carbon with metallic micro-architectures for functional adaptations with superior mechanical integrity. This section mainly focuses on a vacuum HIAM sample with a composition of C, Ni, and Fe at a Ni-to-Fe atomic ratio of 80:20 for microstructural characterizations and another vacuum HIAM sample with a composition of C, Cu, Ni, Fe at a Cu-to-Ni-to-Fe atomic ratio of 60:20:20, commonly referred to as cunife, for magnetic property measurements. 113 Microstructure characterizations. The experiemental protocols and instrumentations remain the same as those for the work of section 5.1. Magnetic properties characterization by vibraing sample magnetometry (VSM). The measurement involves firstly applying a powerful magnetic field to the sample of interest in order to magnetize and erase any previous magnetic memory from past exposure to magnetic or electric fields. As measurements are taken on the magnetism induced by the sample, the applied field is decreased stepwise until it becomes of equal magnitude but in the opposite direction; then, the field is increased back to the initial applied conditions. For a ferromagnetic material, this process traces a hysteresis loop in the magnetic moment-vs.applied field relationship. The intercept with the applied field axis is known as the remnant magnetization; the intercept with the magnetic moment axis is known as the coercivity, measuring the resistance to demagnetization. These two quantities act as benchmark properties for determining the usage and performance of a magnetic materail. For this section, the magnetic hysteresis measurement was performed at 293 K using a Quantum Design Physical Property Measurement System over a magnetic field sweep between 5000 oersted (Oe) and -5000 Oe (Figure 5.17). 5.2.2 Results Microstructures of vacuum HIAM metal/carbon nanocomposites. Figure 5.11 provides an overview of the microstructures via STEM-EDS and HAADF. There are three primary noticeable features, distinguished by distinct EDS signal intensity of Ni and C as well as by the dark-field imaging contrast: (1) The brightest area with the highest Ni signal and the lowest C signal indicates a metallic Ni phase, in 10s-200 nm-sized “new moon” shapes; note that these metallic grains are primarily Ni and does not show concentrated prensence of Fe based on the STEM-EDS result. (2) The darkest area with elevated C signal indicates a graphitic carbon phase, which are closely bound to the metallic Ni phase as if a “shadow” complementing the “new moon.” (3) The rest area represents the majority phase, which is interconnected, with an intermediate brightness and intermediate Ni, C, and Fe signal levels. It is attributed to the 114 matrix phase consisting of amorphous carbon and nanocrystalline metals containing both Ni and Fe. Figure 5.12 provides a higher-magnification view showing the co-existence of the three microstructural morphologies. Figure 5.11 Scanning transmission electron microscopy characterizations of microstructures in vacuum HIAM metal-carbon nanocomposite microlattices. 115 Figure 5.12 A scanning transmission electron microsocpy zoom-in view of phase assemblage and morphology variations in vacuum HIAM metal-carbon nanocomposites. Figure 5.13 STEM-EDS map showing metal-carbon segregation at nanometer scale in the matrix phase. Figures 5.14, 5.15, and 5.16 demonstrate the high-resolution view of the three representative microstructural morphologies in vaccum HIAM metal-carbon nanocomposites: (I) nanocrystalline-Ni(Fe)/amorphous-C matrix as elementally mapped with STEM-EDS in Figure 5.13 evidencing postive correlation between Ni vs. Fe presence and negative correlation between Ni/Fe vs. C presence, (II) a large area of graphitic carbon clearly showing the stacking and folding of the graphitic layers, and (III) an atomically sharp inerface between large Ni nanograins and graphitic carbon. These three images are among my favorite HR-TEM images that I have had the pleasure of capturing. To me, they represent 116 the extraordinary beauty and delicacy of atomic structures at the nanoscale. They always evokes my feelings of peacefulness and fulfillment as I had always wanted to “see” atoms since my primary school years. 1 0 n m Figure 5.14 High-resolution transmission electron microscopy characterizations of individual microstructural morphologies in vaccum HIAM metal-carbon nanocomposites I: nanocrystalline-Ni/amorphous-C matrix. Both Figures 5.15 and 5.16 belong to the first two microstructural morphologies segregrated from the 10-nm nanocrystalline matrix and are clue of the potential metallic carbide 117 composition reaction forming metallic Ni and graphitic carbon, with Ni acting as a selfcatalyst (but not Fe despite its moderate bulk content). The presence of large grains of Ni and graphitic carbon (10s–200 nm) in close proximity, and their conformal geometries, as well as the folding of graphitic layers around the Ni nanograin facets (Figure 5.16) provide strong evidence supporting the hypothesis. 1 0 n m Figure 5.15 High-resolution transmission electron microscopy characterizations of individual microstructural morphologies in vaccum HIAM metal-carbon nanocomposites II: large area of graphitic carbon. 118 Figure 5.16 High-resolution transmission electron microscopy characterizations of individual microstructural morphologies in vaccum HIAM metal-carbon nanocomposites: atomically sharp inerface between large Ni nanograins and graphitic carbon regimes. With the understanding of the bimodal nanocrystalline grain size distribution of the metallic phases dictated by Ni in these metal/ceramic nanocomposites, we characterized the magnetic hysterisis of a slightly different system of vacuum HIAM CuNiFe (in terms of phase assemblage, microstructure, and grain sizes), such that due to the unique self-catalytic effect of Ni in graphitization via carbide decomposition and the absence of equally proniment effects for Cu or Fe, the CuNiFe lacks the strongly bimodal metallic grain size distribution 119 and predominantly comprises of the ~ 10nm grain matrix phase. The performance of vacuum HIAM CuNiFe is also compared to that of regular HIAM CuNiFe whose phase assemblage and microstructures are drastically different, such that: regular HIAM CuNiFe (1) does not form a nanocomposite but a single fcc metallic phase and (2) does not have a bimodal nanocrystalline grain size distribution but a unimodal microcrystalline grain size distribution around ~1s μm. These microstructural differences contribute to the difference in their magnetic properties, as shown in Figure 5.17. Figure 5.17 Magnetic hystersis characterizations: comparison between CuNiFe via regular HIAM (calcination + reduction) and vacuum HIAM (pyrolysis), together shown are a schematic of VSM and a micrograph of the microlattice. The figure is partly adapted from (199) with permission. The vacuum HIAM CuNiFe has a coercivity (Hc) value of 17.7 Oe, much lower than that of the regular HIAM CuNiFe (47.0 Oe). This difference is explained by the grain size (D) dependence of coercivity(200). There exists a classical scaling regime of 𝐻𝑐 ∝ 𝐷−1 for D > 100 nm and an inverse scaling regime of 𝐻𝑐 ∝ 𝐷6 for D < 100 nm. Thus, the vacuum HIAM and regular HIAM CuNiFe belong to the inverse and classical scaling regimes, respectively. Further owing to the significantly sharper scaling factor of the inverse scaling regime, the vacuum HIAM CuNiFe possesses a much lower effective coercivity. 120 However, despite the lack of measurement for the magnetic properties of the 80%Ni-20%Fe (NiFe) system, it is highly anticipated that the vacuum HIAM NiFe system would possess enhanced coercivity in comparison to the regualr HIAM NiFe system, due to the unique ~100 nm sizes of the Ni grains from catalytic carbide decomposition—this size sits at the transition point between the classical regime of increasing coercivity with decreasing grain sizes (> 100 nm) and the inverse regime of decreasing coercivity with further decreasing nanocrystalline grain sizes (< 100 nm)(200). 5.3 Interpenetrated microlattices for enhanced battery energy- and power-density While additive manufacturing has enabled 3D-microarchitected electrodes for lithium ion batteries to achieve enhanced energy density(201, 202), the way the architected electrodes are assembled into a coin cell as the conventional batteries slurry electrode designs does not fundamentally decrease the charged species transport distance by the introduction of the regular array of 3D micro-channels due to the physical spacing between the cathode and anode by the full thickness of the electrolyte plus the height of the 3D cathode and anode, which are now further thickned. Therefore, to simultaneously achieve enhanced energy density and power density of lithium ion batteries, the 3D microarchitecture is in demand of revolutionary re-design, for instance, via interpenetrated cathode-anode microlattices. Hard carbon anode and lithium ion transition metal cathode represent a pair of widely used electrodes for lithium ion batteries. The following section will delineate an early stage attempt in fabricating interpenetrated microlattices of pyrolytic carbon anode and lithium cobalt oxide (LCO) cathode to redefine battery designs. 5.3.1 Methods Digital light processing. The 3D printing was performed with the digital light processing (DLP) method on Micro-2 DLP printer (MicroSLA) using the commercial 3DSR UHR photoresist (MicroSLA). A Z-layer slicing thickness of 5 μm was used, while the X-Y pixel dimension of the light projection was 5 μm x 5 μm over an rectangular area of 9.6 mm x 5.4 mm. An exposure time profile of 20 sec/layer for first 10 layers and 5 sec/layer for subsequent layers was chosen, while the exposure light intensity was set to be under the default current of the instrument’s UV LED (365 nm). 121 Thermogravimetric analysis (TGA). The analysis was performed with TGA 500 (TA Instruments) directly on the as-3D-printed UHR micro-architectures (1.715 mg). A N2 flow rate of 25 mL/min and a temperature ramp rate of 4 °C/min from ambient temperature to 1000 °C were implemented. Pyrolysis. The pyrolysis was performed inside a tube furnace (MTI OTF-1500X) to convert the polymer into hard carbon. A N2 Environment of 0.0003 atm was maintained through the entire thermal treatment process, which includes ramping up from ambient temperature to 1000 °C at 4 °C/min and ramping back down at 5 °C/min. Electroplating. The electroplating of lithium cobalt oxides on the hard carbon microlattice was performed following the protocol in(203). A electroplating bath was prepared in an Arglovebox by mixing KOH and LiOH at 5:1 weight ratio. The mixture was heated at 315 °C until melting and turning transparent. Then, ~ 2 wt.% of CoO was added to the melt. The hard carbon microlattice was electrically connected with Cu wires and intergrated to the electrochemical cell as the working electrode (WE), while Co and Ni wires were used as the reference electrode (RE) and the counter electrode (CE), respectively. A pulsed waveform was applied btween WE and RE (1.1 V pulse for 4 sec and open-circuit potential for 1 min) for 1 hour. After electroplating, the microlattice sample was washed with deionized water and air dried. 5.3.2 Results Interpenetrated microlattices. Figure 5.18A shows the design of the interpenetrated cathodeanode microlattices design made with nTopology. The blue and pink colors indicate the two interpenetrated but nontouching microlattices with the identical beam-based “diamond” unit cell structure and the identical unit cell size of 1330 μm and beam diameter of 105 μm. A base microlattice (grey) is printed underneath the functional components for structural supporting purposes. The As-printed polymer micro-architecture is imaged in Figure 5.18B, showing its high structural integrity and small size compared to a quarter dollar coin. 122 Figure 5.18 Design and fabrication of interpenetrated microlattices. TGA. The thermal decomposition behavior of the UHR photoresist was characterized. Figure 5.19 shows that the thermal decomposition of UHR photoresist comprises of a primary peak at ~ 400 °C, leading to > 85% mass loss at this single event. This feature could suggest designing a isotherm holding or decreased temperature ramp rate in the furnace pyrolysis treatment around ~ 400 °C to prevent explosive gas escape events to distort the geometry. However, that was not needed for the present microarchitecture design likely due to the small beam diameter and short gas diffusion length. Figure 5.19 Thermogravimetric analysis of UHR photoresist thermal decomposition. Pyrolytic hard carbon product. Based on the TGA result, the furnace pyrolysis experiment was performed, whose results are provided in Figure 5.20. The two interpenetrated microlattices remained unconnected and kept uniform spacing. The beam diameter 123 experienced considerable linear shrinkage by ~ 60–70% to a final beam diameter of ~ 30–40 μm in the pyrolytic carbon microlattice (Figure 5.20A–C). Note that despite the surface stepmarks (Figure 5.20D) as a remnant of the 5 μm slicing thickness as part of the DLP printing mechanism, the surface morphology of the pyrolytic carbon is highly smooth (Figure 5.20E), free of air bubble or pockets or any hint of a nanoporous microstructure. These geometrical and morphological signatures suggests the structural and mechanical integrity of the pyrolytic carbon microlattices, which can serve both as the functional electrode as well as the micro-scaffold hosting other mechanically weak electrochemically active materials. Figure 5.20 Interpenetrated microlattices of pyrolytic hard carbon: (A) optical image; (B and C) scanning electron micrographs of the microlattice; (D) scanning electron micrograph showing step marks due to layer slicing; (E) higher magnification scanning electron micrograph showing smooth surface morphology of pyrolitic hard carbon. In situ quasistatic compression experiment with a dynamic mehcanical analysis system (DMA; TA Instruments) demonstrated the superior mechanical robustness of the asfabricated interpenetrated microlattices, as shown in Figure 5.21. The microarchitecture, 124 after pyrolysis, achieves a uniform beam diameter of 38 µm and a unit cell edge length of 416 µm, leading to an 8.3% relative density considering the presence of two identical but offseted interpenerated microlattices. The interpenetrated region, with a nominal crosssectional area of 1.20 mm x 1.85 mm and a height of 1.76 mm was glued to a 1 mm-thick microglass using a minimal amount of colloidal graphite of negligible thickness; then, the supporting structures was cut off with a razor blade to isolate the interpenetrated region for mechanical compression at a strain rate of 0.1% per second. Figure 5.21 Mechanical response of pyrolytic carbon interpenetrated microlattices under compression. (A) SEM-based dimension measurements and CAD-model relative density, 𝜌̅ , estimation of the tested specimen in top-down view; the shadowed portion of the microarchitecture was cut off prior to the compression test; (B) in situ compression result nominal stress-vs.-engineering strain relationship; (C) optical microscopic snapshots during compression in correspondence to the stress-strain relationship. The dashed lines in B and dashed boxes in Ci–vi with identical dimensions are for eye guidance purposes only. The microarchitecture exhibited high nominal stress (engineering stress calculated as the total load divided by the area of 1.20 mm x 1.85 mm without taking into account 𝜌̅ ) of at least 7 MPa while showing minimal sign of global damage (Figure 5.21C i vs. vi). The 125 multiple unloading and re-loading events shown in Figure 5.21B are explained by the abrupt load drop caused by catastrophic fracture failure of individual beam members causing the load head to instantaneously lose contact with the sample in a displacement-controlled mode. In these load drops, however, the bulk microarchitecture structure experience only elastic recovery and remain intact, as suggested by the stable longitudinal modulus over the reloading cycles, which shows no sign of degradation. The significant mechanical imrpovement compared to conventional slurry electrodes for Li-ion batteries spares the demand of separators, thus lightweighting the battery design and further facilitating the power-density and energy-density enhancement. It is notable that between Figure 5.21Ciii–iv, the interpenetrated microlattices experienced an abrupt reconfiguration, transforming from an independent compression of the two laterally offsetted microarchitectures to concerted compression likely due to global latticeto-lattice contact establishement. The reconfigured pattern was maintained through higher compressive strain level until the instruments load limit was triggered. It is interesting that the longitudinal loading modulus before and after the reconfiguration was not distinguishable. The present experiment not only manifests the superior mechanical properties of the pyrolytic carbon microarchitecture as both an electrode and a scaffold for electrochemical applications but also elucidates on potential enhanced flexibility and flaw tolerance via an interpenetrated design of 3D architectures. As shown in Figure 5.22, to achieve electroplating of lithium cobalt oxides (LCO), the interpenetrated microarchitecture was first electrically connected to the electrochemical cell with a 50 µm-diameter Cu wire on one of the two legs (thus only one of the two interpenetrated microlattices is electrically connected and will be electroplated), where the connection between the microarchitecture and the Cu wire was secured with a conductive colloidal graphite paste. The microarchitecture was then secured to a microglass substrate with a non-conductive, thermally stable glue of colloidal alumina. Once secured in place, the other leg of the microarchitecture is cut off by a razor blade to isolate the non-electrically connected microlattice form the base support and from the rest of the electrical circuit. 126 Figure 5.22 Schematic of electroplating of LCO and an optical view of the actual carbon microarchitecture electrically connected to the working electrode and adhered to a microglass substrate with non-conductive alumina paste. Figure 5.23 shows the results of LCO electroplating, characterized with SEM-EDS, which clearly shows the attachement of Co-rich phase uniformly and conformally on the microlattice surface. However, the preliminary electroplating attempt failed to keep the electrically disconnected half of the microarchitecture free from electroplating, likely due to undesired contact between the two interpenetrated microlattices upon handling. Thus, future studies are encouraged to design additional insulating mechanisms or better interpenetrated design while maintaining the desired 10s µm microlattice spacings to uphold the objectives of simultaneous high energy density, high power density, and high mechanical strengths. 127 Figure 5.23 LCO electroplating on hard carbon microlattice. (A-C) SEM-EDS mapping; red = carbon; magenta = cobalt. (D-E) EDS spectrum and calculated atomic ratio. (F-G) secondary electron micrographs at higher magnification showing flacky LCO nano-crystals. As an outlook, upon success electroplating of one of the two interpenetrated microlattices, the system will be washed and annealed in an inert environment to allow for the formation of continuous LCO layer on the cathode microlattice with enhanced conformity. Then, a photopolymerizable electrolyte will be introduced and cured into the open volume inbetween the hard carbon anode microlattice and the LCO-coated cathode microlattice. Further processes such as wirebonding and soldering may be required to fully fabricate a full battery cell for performance assessment. 128 5.4 Outlook Sections 5.1–5.3 have demonstrated three exciting preliminary accomplishments in hydrogel infusion-based nano-to-micro-manufacturing for complex systems and applications. In a broader scope, Figures 5.24 and 5.25 summarize various treatment strategies adaptable to the large family of vat-photopolymerization platform technologies, including multi-photon lithography, digital light processing, stereolithography, volumetric printing, holographic lithography, and more. These treatment strategies include photoresist modification, precursor infusion, post-printing deposition (i.e., surfacement treatment and infiltration), and heat treatments to achieve complex materials, e.g., oxides, nitrides, metallic glass, and high entropy alloys, as well as functionalities, e.g., biocompatibility, wettability, anti-bacteria properties, and high refractive index. Figure 5.24 Various materials treatment strategies to achieve multi-material and multifunctionality in nano-manufacturing. Figures are adapted from (21, 204) with permission. Copyright 2015 Elsevier Ltd. Copyright 2023 Wiley-VCH GmbH. 129 Figure 5.25 Diagram showing materials treatment strategies related to polymer 3D printing-based nano-manufacturing, expanding upon Figure 5.24. Figure 5.26 provides a broader perspective towards the development of a micro-to-nanoscale, vat photopolymerization-based advanced manufacturing platform for energy applications. A spectrum of conventional and novel strategies could be organically incorporated for (1) post treatment—dealloying to enhanced specific area and interfacial properties, coating and infiltration with electrochemically active phases, as well as decoration with catalyst nanoparticle, etc., and (2) application-targeted integration—thin film embedding of nanoarchitectures, lattice interpenetration, and topological optimization for charged species and gas transport, etc.. These manufacturing innovations will enable versatile energy materials systems that are multi-material, electrochemically active, mechanically robust, and structurally sound—providing solutions for global decarbonization by enabling futuregenetration fuel cells, electrolyzers, energy storage, CO2 reduction, critical mineral extraction, and more. 130 Figure 5.26 Development of hydrogel infusion-based advanced manufacturing platform for multi-material, functional applications. Micro-to-nanoscale coverage of HIAM for energy applications at distinc dimensions. The figure is partly adapted from (26, 153, 202, 205) with permission. Copyright 2024 Yuchun Sun ORCID: 0000-0002-7028-3523. Copyright 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. Copyright 2022, The Author(s), under exclusive licence to Springer Nature Limited. Copyright 2018, The Author(s). Published by Springer Nature. 131 Chapter 6 CONCLUDUING REMARKS On nanomechanical studies of nano-AM metals and oxides The nanomechanical characterizations of nanoscale additively manufactured products of metals and metal oxides have mostly extensively focused on scanning electron microscopybased in situ compression testing of as-AM-fabricated monolithic pillars, whose diameters range from ~100 nm to 1s um. As shown in Figure 6.1A to G, the compressive deformation behaviors of these nanopillars of different chemistry could be categorized into localized shearing, splitting, and homogenized deformation, which may be understood in relation to their respective microstructures. Distinct from macroscopic mechanical behaviors, the nanomechanical behaviors of nanopillars are highly sensitive to the relative ratio between microstructural feature dimensions, e.g., grain size (d) and the extrinsic dimension, i.e., the nanopillar diameter (D). Such D/d effect has been investigated in nanocrystalline metal nanowires conventionally manufactured (via templated electrodeposition)(110, 206), elucidating a transition – with decreasing D/d – from dislocation-mediated to grain boundary-mediated plasticity and sometimes from more ductile to brittle failure behaviors. It is notable that the microstructure of most additively manufactured metal and metal oxides nanopillars are highly similar to that in the D/d studies, i.e., usually nanocrystalline (derived from AM methods including FEBID, FIBID, HIAM, LED, TPL-thermal, LDP, LED, EHD-redox, etc.)(22, 39, 207–209) and sometimes ultra-fine-grained or microcrystalline (derived from localized force-controlled electroplating)(210). The almost universal nanocrystallinity among products of the various nanoscale additive manufacturing routes should be emphasized and may be rationalized by high solidification rates, non-equilibrium nature of processing, and limited thermal annealing or diffusion facilitating nucleation over grain growth, as well as grain boundary pinning and stabilization. 132 Figure 6.1 Nanomechanical studies on nanoscale additively manufactured metals and metal oxides(22, 39, 169, 170, 207–214). FIBID = focused ion beam-induced deposition. FEBID = focused electron beam-induced deposition. TPD = two-photon deposition. HIAM = hydrogel infusion additive manufacturing. LDP = laser direct printing. LED = localized electrodeposition. EHD = electrohydrodynamic. TPL = two-photon lithography. Figures are adopted from (22, 169, 209–212, 214) with permission. Copyright 2023 American Chemical Society. Copyright 2022 The Authors. Published by Elsevier Ltd. Copyright 2018 WILEYVCH Verlag GmbH & Co. KGaA, Weinheim. Copyright 2023 IOP Publishing Ltd. Copyright 2024, The Author(s), under exclusive licence to Springer Nature Limited. Copyright Royal Society of Chemistry 2017. Copyright 2023, The American Association for the Advancement of Science. 133 The D/d perspective could partly account for the transition between the three major failure modes in these additively manufactured nanopillars, from localized shearing events at small D/d to homogenized deformation at greater D/d. Gallivan et al. further explained in their work on additively manufactured ZnO nanopillars (Figure 6.1A) that the critical stress necessary for shear banding scales with the square-root of (shear-band surface energy) * (Young’s modulus) / (pillar diameter)(214), which may only be achieved in the smallest nanopillars, considering that the presence of flaws in larger pillars tends to provide alternative low-stress deformation pathways. Zhang et al. examined their nanocrystalline, nanoporous Ni nanopillars additively manufactured via HIAM with molecular dynamics simulations, unveiling a nanoporosity-mediated dislocation nucleation plasticity mechanism, explaining both localized plasticity (shearing, Figure 6.1D) from exteriorsurface dislocation nucleation at smaller D and homogenized deformation (Figure 6.1F) from multiple interior-pore-surface dislocation nucleation at larger D(22). Besides microstructure and size effects, the nanomechanical behaviors of the additively manufactured products are highly dependent on their chemistry – whether metals belonging to face-centered-cubic (fcc) structure, body-centered-cubic (bcc), or else or oxides with cubic or non-cubic lattices. The different symmetry and slip systems and the electron structure unique to different elements can collectively influence nanomechanics of the additively manufactured nano-structures. Fcc metals, e.g., Pt, Ni, and Cu (Figure 6.1E, F, and G, respectively), could exhibit greater deformability – plastically deforming by over 10-20% under compression without fracturing, while bcc metals, e.g., Mo (Figure 6.1H), fracturing at 1.5% tensile strain, and, oxide ceramics (Figure 6.1A and B), undergoing splitcracking, exhibit greater brittleness. It should be noted that few studies investigated tensile performance of the products, which leaves a knowledge gap hindering comprehensive evaluation of the multiple AM approaches, since the assumption of tension-compression symmetry may not hold true in these nanoscale nanocrystalline materials, where fabrication defects, particularly voids, may be detrimental under tension, which future studies are encouraged to study. Despite the multitude of burgeoning nanoscale additive manufacturing approaches, very few studies have mechanically characterized these products for non-monolithic, complex 134 architectures. Figure 6.1I and J represent two notable studies exploring the deformation behaviors of Co and Ni nanolattices, respectively(169, 215). The Co nanolattice demonstrated significant strain recovery upon unloading while sustaining 1s MPa nominal stresses. The Ni nanolattices exhibited superior strengths up to 200 MPa at relative densities ~ 20%–40% and of a variety of architectural geometries (Figure 6.1K), providing the first evidence of the mechanical robustness of additively manufactured metal 3D structures and paving the way for the utilization of their combined nanoscale dimensions, 3D freeform ability, and high strengths for functional applications. Figure 6.1K summarizes the strength vs. density relationship of the nanoscale additively manufactured metals and metal oxides in the big-picture context of conventional materials categories. Most of these AM metal and metal oxides nano-pillars/wires stand on the higher end or above the domain of conventional metals, owing to the universal “smaller is stronger” rule. No single AM approach appears to outperform the rest in terms of pillar strengths, likely due to the generally comparable nanocrystalline microstructure and similar degree of defects causing the strengths to be primarily microstructure- and material-driven. However, nanoscale HIAM seem the most feasible approach to achieve mechanical robustness in complex 3D architectures. It should be acknowledged that nanoscale additively manufactured metals and metal oxides may not possess as high strengths as nanoscale additively manufactured pyrolytic carbon counterparts, who can achieve nominal strengths > 3000 MPa at < 1 g/cm3, owing to the flawless nature as well as the low material relative density of the latter. However, the comparison should not overshadow the significantly greater material variability and functionality in the category of metals and metal oxides, while more nanomechanical studies on complex AM architectures of them are highly encouraged to develop a framework for their characterization, modeling, and prediction of the nanomechanical performance to better integrate mechanical design to the functional applications of these emerging nano-AM capabilities. A few more thoughts Together, we have visited the five chapters that chronicle an exciting journey—beginning with not knowing how to approach the fundamental mechanical properties of uncommon 135 material systems and arriving at accomplishing an experimental platform for novel nanomanufacturing and characterization. Along the way, we have uncovered so many fascinating insights into unprecendented materials, microstructures, and nanoarchitectures that were inaccessible or even unimagined before us. Over the years, I have frequently been asked, “what is the application of your work?” Initially, I would frown and reply, “You mean today? Not much. And I don’t really care.” But as I delved deeper into developing nano-manufacturing recipes for increasingly complex material systems, my perspective began to shift. Establishing a micro-to-nanoscale advanced manufacturing platform means more than my personal curiosity about making and seeing serendipitous creations; it holds great potential for both fundamental scientific discoveries and transformative engineering applications. While techniques like multi-photon lithography might be critiqued for their low throughputs and impracticality, they remain an unparalleled tool for prototyping: to create new microstructures and phase assemblages, tune interfacial characteristics, and optimize complex 3D topologies. These capabilities will establish a solid foundation for continued study to achieve scalability, by integrating approaches like proximity field nano-patterning or meta surface-enabled holographic lithography(216, 217) with inverse architectural designs and unlocking opportunities in energy and quantum materials and beyond. My perspective has also evolved regarding my first PhD project on benzene micropyramids. What once felt like a long and tenuous connection to the planetary geology of an icy moon now feels like a delightful, cute “nano”-step among the 15.5 billion miles of humanity’s excursion(218) that continues farther. Through this work at the smallest scales, I hope to ignite your curiosity about dimensions of our world that you may have never felt connected to before. May it inspire you to see beyond your immediate surroundings and think beyond conventional limits—for the future and for fun. 136 BIBLIOGRAPHY 1. L. Jacak, P. Hawrylak, A. 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Movie 2.5 The shear-strain evolution of a slice sample cut from 30-nm height pyramidal benzene in parallel with contact pressure vs. normalized displacement curve. 157 Appendix B SUPPLEMENTARY INFORMATION FOR CHAPTER 3 Titles for Movies 3.1-3.3 Movie 3.1 In situ SEM mechanical test on a representative Ni pillar (D = 145 nm). The video is at real-time speed. See Figure 3.9 for pre- and post-mortem images. Movie 3.2 In situ SEM mechanical test on a representative Ni pillar (D = 211 nm). The video is at real-time speed. See Figure 3.9 for pre- and post-mortem images. Movie 3.3 In situ SEM mechanical test on a large Ni pillar (D = 508 nm). The video is at 10x speed. See Figure 3.9 for pre- and post-mortem images.