1
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Deng W, Kumar S, Vallone A, Kochmann DM, Greer JR. AI-Enabled Materials Design of Non-Periodic 3D Architectures With Predictable Direction-Dependent Elastic Properties. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2308149. [PMID: 38319025 DOI: 10.1002/adma.202308149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 01/08/2024] [Indexed: 02/07/2024]
Abstract
Natural porous materials have exceptional properties-for example, light weight, mechanical resilience, and multi-functionality. Efforts to imitate their properties in engineered structures have limited success. This, in part, is caused by the complexity of multi-phase materials composites and by the lack of quantified understanding of each component's role in overall hierarchy. This challenge is twofold: 1) computational. because non-periodicity and defects render constructing design guidelines between geometries and mechanical properties complex and expensive and 2) experimental. because the fabrication and characterization of complex, often hierarchical and non-periodic 3D architectures is non-trivial.
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Affiliation(s)
- Weiting Deng
- Division of Engineering and Applied Sciences, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Siddhant Kumar
- Department of Materials Science and Engineering, Delft University of Technology, Delft, 2628 CD, The Netherlands
| | - Alberto Vallone
- Department of Mechanical and Process Engineering, ETH Zurich, Zurich, 8092, Switzerland
| | - Dennis M Kochmann
- Department of Mechanical and Process Engineering, ETH Zurich, Zurich, 8092, Switzerland
| | - Julia R Greer
- Division of Engineering and Applied Sciences, California Institute of Technology, Pasadena, CA, 91125, USA
- Kavli Nanoscience Institute at Caltech, Pasadena, CA, 91125, USA
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2
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Meekel EG, Partridge P, Paraoan RAI, Levinsky JJB, Slater B, Hobday CL, Goodwin AL. Enhanced elastic stability of a topologically disordered crystalline metal-organic framework. NATURE MATERIALS 2024:10.1038/s41563-024-01960-7. [PMID: 39043928 DOI: 10.1038/s41563-024-01960-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 06/27/2024] [Indexed: 07/25/2024]
Abstract
By virtue of their open network structures and low densities, metal-organic frameworks (MOFs) are soft materials that exhibit elastic instabilities at low applied stresses. The conventional strategy for improving elastic stability is to increase the connectivity of the underlying MOF network, which necessarily increases the material density and reduces the porosity. Here we demonstrate an alternative paradigm, whereby elastic stability is enhanced in a MOF with an aperiodic network topology. We use a combination of variable-pressure single-crystal X-ray diffraction measurements and coarse-grained lattice-dynamical calculations to interrogate the high-pressure behaviour of the topologically aperiodic system TRUMOF-1, which we compare against that of its ordered congener MOF-5. We show that the topology of the former quenches the elastic instability responsible for pressure-induced framework collapse in the latter, much as irregularity in the shapes and sizes of stones acts to prevent cooperative mechanical failure in drystone walls. Our results establish aperiodicity as a counter-intuitive design motif in engineering the mechanical properties of framework structures that is relevant to MOFs and larger-scale architectures alike.
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Affiliation(s)
- Emily G Meekel
- Inorganic Chemistry Laboratory, Department of Chemistry, University of Oxford, Oxford, UK
| | - Phillippa Partridge
- Centre for Science at Extreme Conditions and EaStCHEM School of Chemistry, University of Edinburgh, Edinburgh, UK
| | - Robert A I Paraoan
- Inorganic Chemistry Laboratory, Department of Chemistry, University of Oxford, Oxford, UK
| | - Joshua J B Levinsky
- Centre for Science at Extreme Conditions and EaStCHEM School of Chemistry, University of Edinburgh, Edinburgh, UK
| | - Ben Slater
- Department of Chemistry, University College London, London, UK
| | - Claire L Hobday
- Centre for Science at Extreme Conditions and EaStCHEM School of Chemistry, University of Edinburgh, Edinburgh, UK
| | - Andrew L Goodwin
- Inorganic Chemistry Laboratory, Department of Chemistry, University of Oxford, Oxford, UK.
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3
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Jia Y, Liu K, Zhang XS. Modulate stress distribution with bio-inspired irregular architected materials towards optimal tissue support. Nat Commun 2024; 15:4072. [PMID: 38773087 PMCID: PMC11109255 DOI: 10.1038/s41467-024-47831-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 04/12/2024] [Indexed: 05/23/2024] Open
Abstract
Natural materials typically exhibit irregular and non-periodic architectures, endowing them with compelling functionalities such as body protection, camouflage, and mechanical stress modulation. Among these functionalities, mechanical stress modulation is crucial for homeostasis regulation and tissue remodeling. Here, we uncover the relationship between stress modulation functionality and the irregularity of bio-inspired architected materials by a generative computational framework. This framework optimizes the spatial distribution of a limited set of basic building blocks and uses these blocks to assemble irregular materials with heterogeneous, disordered microstructures. Despite being irregular and non-periodic, the assembled materials display spatially varying properties that precisely modulate stress distribution towards target values in various control regions and load cases, echoing the robust stress modulation capability of natural materials. The performance of the generated irregular architected materials is experimentally validated with 3D printed physical samples - a good agreement with target stress distribution is observed. Owing to its capability to redirect loads while keeping a proper amount of stress to stimulate bone repair, we demonstrate the potential application of the stress-programmable architected materials as support in orthopedic femur restoration.
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Affiliation(s)
- Yingqi Jia
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Ke Liu
- Department of Advanced Manufacturing and Robotics, Peking University, Beijing, 100871, China.
| | - Xiaojia Shelly Zhang
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA.
- Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA.
- National Center for Supercomputing Applications, Urbana, USA.
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4
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Yin P, Li B, Hong J, Jing H, Li B, Liu H, Chen X, Lu Y, Shao J. Design Criteria for Architected Materials with Programmable Mechanical Properties Within Theoretical Limit Ranges. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2307279. [PMID: 38084485 PMCID: PMC10916576 DOI: 10.1002/advs.202307279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 11/30/2023] [Indexed: 12/20/2023]
Abstract
Architected materials comprising periodic arrangements of cells have attracted considerable interest in various fields because of their unconventional properties and versatile functionality. Although some better properties may be exhibited when this homogeneous layout is broken, most such studies rely on a fixed material geometry, which limits the design space for material properties. Here, combining heterogeneous and homogeneous assembly of cells to generate tunable geometries, a hierarchically architected material (HAM) capable of significantly enhancing mechanical properties is proposed. Guided by the theoretical model and 745 752 simulation cases, generic design criteria are introduced, including dual screening for unique mechanical properties and careful assembly of specific spatial layouts, to identify the geometry of materials with extreme properties. Such criteria facilitate the potential for unprecedented properties such as Young's modulus at the theoretical limit and tunable positive and negative Poisson's ratios in an ultra-large range. Therefore, this study opens a new paradigm for materials with extreme mechanical properties.
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Affiliation(s)
- Peng Yin
- Key Laboratory of Education Ministry for Modern Design and Rotor‐Bearing SystemXi'an Jiaotong UniversityXi'anShaanxi710049China
| | - Baotong Li
- Key Laboratory of Education Ministry for Modern Design and Rotor‐Bearing SystemXi'an Jiaotong UniversityXi'anShaanxi710049China
| | - Jun Hong
- Key Laboratory of Education Ministry for Modern Design and Rotor‐Bearing SystemXi'an Jiaotong UniversityXi'anShaanxi710049China
| | - Hui Jing
- Key Laboratory of Education Ministry for Modern Design and Rotor‐Bearing SystemXi'an Jiaotong UniversityXi'anShaanxi710049China
| | - Bang Li
- Key Laboratory of Education Ministry for Modern Design and Rotor‐Bearing SystemXi'an Jiaotong UniversityXi'anShaanxi710049China
| | - Honglei Liu
- Key Laboratory of Education Ministry for Modern Design and Rotor‐Bearing SystemXi'an Jiaotong UniversityXi'anShaanxi710049China
| | - Xiaoming Chen
- State Key Laboratory for Manufacturing Systems EngineeringXi'an Jiaotong UniversityXi'anShaanxi710049China
| | - Yang Lu
- Department of Mechanical EngineeringThe University of Hong KongPokfulamHong KongSAR999077China
| | - Jinyou Shao
- State Key Laboratory for Manufacturing Systems EngineeringXi'an Jiaotong UniversityXi'anShaanxi710049China
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5
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Lee D, Chen WW, Wang L, Chan YC, Chen W. Data-Driven Design for Metamaterials and Multiscale Systems: A Review. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2305254. [PMID: 38050899 DOI: 10.1002/adma.202305254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 09/15/2023] [Indexed: 12/07/2023]
Abstract
Metamaterials are artificial materials designed to exhibit effective material parameters that go beyond those found in nature. Composed of unit cells with rich designability that are assembled into multiscale systems, they hold great promise for realizing next-generation devices with exceptional, often exotic, functionalities. However, the vast design space and intricate structure-property relationships pose significant challenges in their design. A compelling paradigm that could bring the full potential of metamaterials to fruition is emerging: data-driven design. This review provides a holistic overview of this rapidly evolving field, emphasizing the general methodology instead of specific domains and deployment contexts. Existing research is organized into data-driven modules, encompassing data acquisition, machine learning-based unit cell design, and data-driven multiscale optimization. The approaches are further categorized within each module based on shared principles, analyze and compare strengths and applicability, explore connections between different modules, and identify open research questions and opportunities.
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Affiliation(s)
- Doksoo Lee
- Dept. of Mechanical Engineering, Northwestern University, Evanston, IL, 60208, USA
| | - Wei Wayne Chen
- J. Mike Walker '66 Department of Mechanical Engineering, Texas A&M University, College Station, TX, 77840, USA
| | - Liwei Wang
- Dept. of Mechanical Engineering, Northwestern University, Evanston, IL, 60208, USA
| | - Yu-Chin Chan
- Siemens Corporation, Technology, Princeton, NJ, 08540, USA
| | - Wei Chen
- Dept. of Mechanical Engineering, Northwestern University, Evanston, IL, 60208, USA
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6
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Wang T, Xiao Y, King JL, Kats MA, Stebe KJ, Lee D. Bioinspired Switchable Passive Daytime Radiative Cooling Coatings. ACS APPLIED MATERIALS & INTERFACES 2023; 15:48716-48724. [PMID: 37812501 DOI: 10.1021/acsami.3c11338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/11/2023]
Abstract
Passive daytime radiative cooling (PDRC) relies on simultaneous reflection of sunlight and radiation toward cold outer space. Current designs of PDRC coatings have demonstrated potential as eco-friendly alternatives to traditional electrical air conditioning (AC). While many features of PDRC have been individually optimized in different studies, for practical impact, it is essential for a system to demonstrate excellence in all essential aspects, like the materials that nature has created. We propose a bioinspired PDRC structure templated by bicontinuous interfacially jammed emulsion gels (bijels) that possesses excellent cooling, thinness, tunability, scalability, and mechanical robustness. The unique bicontinuous disordered structure captures key features of Cyphochilus beetle scales, enabling a thin (130 μm) bijel PDRC coating to achieve high solar reflectance (≳0.97) and high longwave-infrared (LWIR) emissivity (≳0.93), resulting in a subambient temperature drop of ∼5.6 °C under direct sunlight. We further demonstrate switchable cooling inspired by the exoskeleton of the Hercules beetle and mechanical robustness in analogy to spongy bone structures.
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Affiliation(s)
- Tiancheng Wang
- Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Yuzhe Xiao
- Department of Electrical and Computer Engineering, Department of Materials Science and Engineering, and Department of Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Department of Physics, University of North Texas, Denton, Texas 76203, United States
| | - Jonathan L King
- Department of Electrical and Computer Engineering, Department of Materials Science and Engineering, and Department of Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Mikhail A Kats
- Department of Electrical and Computer Engineering, Department of Materials Science and Engineering, and Department of Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Kathleen J Stebe
- Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Daeyeon Lee
- Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
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7
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Wang Z, Dabaja R, Chen L, Banu M. Machine learning unifies flexibility and efficiency of spinodal structure generation for stochastic biomaterial design. Sci Rep 2023; 13:5414. [PMID: 37012266 PMCID: PMC10070414 DOI: 10.1038/s41598-023-31677-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 03/15/2023] [Indexed: 04/05/2023] Open
Abstract
Porous biomaterials design for bone repair is still largely limited to regular structures (e.g. rod-based lattices), due to their easy parameterization and high controllability. The capability of designing stochastic structure can redefine the boundary of our explorable structure-property space for synthesizing next-generation biomaterials. We hereby propose a convolutional neural network (CNN) approach for efficient generation and design of spinodal structure-an intriguing structure with stochastic yet interconnected, smooth, and constant pore channel conducive to bio-transport. Our CNN-based approach simultaneously possesses the tremendous flexibility of physics-based model in generating various spinodal structures (e.g. periodic, anisotropic, gradient, and arbitrarily large ones) and comparable computational efficiency to mathematical approximation model. We thus successfully design spinodal bone structures with target anisotropic elasticity via high-throughput screening, and directly generate large spinodal orthopedic implants with desired gradient porosity. This work significantly advances stochastic biomaterials development by offering an optimal solution to spinodal structure generation and design.
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Affiliation(s)
- Zhuo Wang
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Rana Dabaja
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Lei Chen
- Department of Mechanical Engineering, University of Michigan-Dearborn, Dearborn, MI, 48128, USA.
| | - Mihaela Banu
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
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8
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Cheng X, Fan Z, Yao S, Jin T, Lv Z, Lan Y, Bo R, Chen Y, Zhang F, Shen Z, Wan H, Huang Y, Zhang Y. Programming 3D curved mesosurfaces using microlattice designs. Science 2023; 379:1225-1232. [PMID: 36952411 DOI: 10.1126/science.adf3824] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/25/2023]
Abstract
Cellular microstructures form naturally in many living organisms (e.g., flowers and leaves) to provide vital functions in synthesis, transport of nutrients, and regulation of growth. Although heterogeneous cellular microstructures are believed to play pivotal roles in their three-dimensional (3D) shape formation, programming 3D curved mesosurfaces with cellular designs remains elusive in man-made systems. We report a rational microlattice design that allows transformation of 2D films into programmable 3D curved mesosurfaces through mechanically guided assembly. Analytical modeling and a machine learning-based computational approach serve as the basis for shape programming and determine the heterogeneous 2D microlattice patterns required for target 3D curved surfaces. About 30 geometries are presented, including both regular and biological mesosurfaces. Demonstrations include a conformable cardiac electronic device, a stingray-like dual mode actuator, and a 3D electronic cell scaffold.
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Affiliation(s)
- Xu Cheng
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P.R. China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, P.R. China
| | - Zhichao Fan
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P.R. China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, P.R. China
- College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, P.R. China
| | - Shenglian Yao
- School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing 100083, P.R. China
| | - Tianqi Jin
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P.R. China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, P.R. China
| | - Zengyao Lv
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P.R. China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, P.R. China
| | - Yu Lan
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P.R. China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, P.R. China
| | - Renheng Bo
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P.R. China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, P.R. China
| | - Yitong Chen
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P.R. China
- Department of Automation, Tsinghua University, Beijing 100084, P.R. China
| | - Fan Zhang
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P.R. China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, P.R. China
| | - Zhangming Shen
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P.R. China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, P.R. China
| | - Huanhuan Wan
- College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, P.R. China
| | - Yonggang Huang
- Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, IL 60208, USA
- Departments of Civil & Environmental Engineering, Mechanical Engineering, and Materials Science & Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Yihui Zhang
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P.R. China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, P.R. China
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9
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Zeng Q, Duan S, Zhao Z, Wang P, Lei H. Inverse Design of Energy-Absorbing Metamaterials by Topology Optimization. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2204977. [PMID: 36504452 PMCID: PMC9896075 DOI: 10.1002/advs.202204977] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 11/18/2022] [Indexed: 05/27/2023]
Abstract
Compared with the forward design method through the control of geometric parameters and material types, the inverse design method based on the target stress-strain curve is helpful for the discovery of new structures. This study proposes an optimization strategy for mechanical metamaterials based on a genetic algorithm and establishes a topology optimization method for energy-absorbing structures with the desired stress-strain curves. A series of structural mutation algorithms and design-domain-independent mesh generation method are developed to improve the efficiency of finite element analysis and optimization iteration. The algorithm realizes the design of ideal energy-absorbing structures, which are verified by additive manufacturing and experimental characterization. The error between the stress-strain curve of the designed structure and the target curve is less than 5%, and the densification strain reaches 0.6. Furthermore, special attention is paid to passive pedestrian protection and occupant protection, and a reasonable solution is given through the design of a multiplatform energy-absorbing structure. The proposed topology optimization framework provides a new solution path for the elastic-plastic large deformation problem that is unable to be resolved by using classical gradient algorithms or genetic algorithms, and simplifies the design process of energy-absorbing mechanical metamaterials.
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Affiliation(s)
- Qingliang Zeng
- Beijing Key Laboratory of Lightweight Multi‐functional Composite Materials and StructuresBeijing Institute of TechnologyBeijing100081P. R. China
| | - Shengyu Duan
- Beijing Key Laboratory of Lightweight Multi‐functional Composite Materials and StructuresBeijing Institute of TechnologyBeijing100081P. R. China
| | - Zeang Zhao
- Beijing Key Laboratory of Lightweight Multi‐functional Composite Materials and StructuresBeijing Institute of TechnologyBeijing100081P. R. China
| | - Panding Wang
- Beijing Key Laboratory of Lightweight Multi‐functional Composite Materials and StructuresBeijing Institute of TechnologyBeijing100081P. R. China
| | - Hongshuai Lei
- Beijing Key Laboratory of Lightweight Multi‐functional Composite Materials and StructuresBeijing Institute of TechnologyBeijing100081P. R. China
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10
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Zheng X, Chen TT, Jiang X, Naito M, Watanabe I. Deep-learning-based inverse design of three-dimensional architected cellular materials with the target porosity and stiffness using voxelized Voronoi lattices. SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS 2023; 24:2157682. [PMID: 36620090 PMCID: PMC9815236 DOI: 10.1080/14686996.2022.2157682] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 11/26/2022] [Accepted: 12/04/2022] [Indexed: 05/27/2023]
Abstract
Architected cellular materials are a class of artificial materials with cellular architecture-dependent properties. Typically, designing cellular architectures paves the way to generate architected cellular materials with specific properties. However, most previous studies have primarily focused on a forward design strategy, wherein a geometry is generated using computer-aided design modeling, and its properties are investigated experimentally or via simulations. In this study, we developed an inverse design framework for a disordered architected cellular material (Voronoi lattices) using deep learning. This inverse design framework is a three-dimensional conditional generative adversarial network (3D-CGAN) trained based on supervised learning using a dataset consisting of voxelized Voronoi lattices and their corresponding relative densities and Young's moduli. A well-trained 3D-CGAN adopts variational sampling to generate multiple distinct Voronoi lattices with the target relative density and Young's modulus. Consequently, the mechanical properties of the 3D-CGAN generated Voronoi lattices are validated through uniaxial compression tests and finite element simulations. The inverse design framework demonstrates potential for use in bone implants, where scaffold implants can be automatically generated with the target relative density and Young's modulus.
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Affiliation(s)
- Xiaoyang Zheng
- Graduate School of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan
- Research Center for Structural Materials, National Institute for Materials Science, Tsukuba, Japan
| | - Ta-Te Chen
- Graduate School of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan
- Research Center for Structural Materials, National Institute for Materials Science, Tsukuba, Japan
| | - Xiaoyu Jiang
- Department of Engineering Mechanics and Energy, University of Tsukuba, Tsukuba, Japan
| | - Masanobu Naito
- Graduate School of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan
- Research and Services Division of Materials Data and Integrated System (MaDIS), National Institute for Materials Science, Tsukuba, Japan
| | - Ikumu Watanabe
- Graduate School of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan
- Research Center for Structural Materials, National Institute for Materials Science, Tsukuba, Japan
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11
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Liu K, Sun R, Daraio C. Growth rules for irregular architected materials with programmable properties. Science 2022; 377:975-981. [PMID: 36007025 DOI: 10.1126/science.abn1459] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Biomaterials display microstructures that are geometrically irregular and functionally efficient. Understanding the role of irregularity in determining material properties offers a new path to engineer materials with superior functionalities, such as imperfection insensitivity, enhanced impact absorption, and stress redirection. We uncover fundamental, probabilistic structure-property relationships using a growth-inspired program that evokes the formation of stochastic architectures in natural systems. This virtual growth program imposes a set of local rules on a limited number of basic elements. It generates materials that exhibit a large variation in functional properties starting from very limited initial resources, which echoes the diversity of biological systems. We identify basic rules to control mechanical properties by independently varying the microstructure's topology and geometry in a general, graph-based representation of irregular materials.
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Affiliation(s)
- Ke Liu
- Department of Mechanical and Civil Engineering, California Institute of Technology, Pasadena, CA 91125, USA.,Department of Advanced Manufacturing and Robotics, Peking University, Beijing 100871, China
| | - Rachel Sun
- Department of Mechanical and Civil Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Chiara Daraio
- Department of Mechanical and Civil Engineering, California Institute of Technology, Pasadena, CA 91125, USA
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