Inverse-designed growth-based cellular metamaterials

Mechanics of Materials, Год журнала: 2023, Номер 182, С. 104668 - 104668

Опубликована: Май 2, 2023

Advancements in machine learning have sparked significant interest designing mechanical metamaterials, i.e., materials that derive their properties from inherent microstructure rather than just constituent material. We propose a data-driven exploration of the design space growth-based cellular metamaterials based on star-shaped distances. These two-dimensional are periodically-repeating unit cells consisting material and void patterns with non-trivial geometries. Machine models exploiting large datasets then employed to inverse for tailored anisotropic stiffness. Firstly, forward model is created bypass growth homogenization process accurately predict given finite set parameters. Secondly, an used invert structure–property maps enable accurate prediction designs stiffness query. successfully demonstrate frameworks' generalization capabilities by chosen outside domain space.

Язык: Английский

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Topology optimization of irregular multiscale structures with tunable responses using a virtual growth rule

Computer Methods in Applied Mechanics and Engineering, Год журнала: 2024, Номер 425, С. 116864 - 116864

Опубликована: Март 25, 2024

Many applications demand tunable structural responses through tailored organic microstructural distributions and spatially varied material properties. Notable progress has been made in discovering optimized designs using periodic patterns fixed phases to achieve unusual responses. To enable the capability of exploring non-periodic architectures with continuous phase design space, we propose a topology optimization methodology that leverages virtual growth rule for designing unique multiscale structures irregular architectures, while naturally ensuring manufacturability. Our approach exploits algorithm create database, delineating constitutive relations between homogeneous frequency hints building blocks responsible generating microstructures resultant homogenized elasticity tensors. We then employ neural network yield differentiable relation. Subsequently, framework is introduced optimize both macroscale layout local block distribution. Finally, generalize account heterogeneous grow yet at microscale. present four examples showcase our proposed programming several types responses, including displacement cloaking, strain energy density, global stiffness, two three dimensions. The structures, characterized by their stochastic demonstrate programmed closely match desired targets. These also ensure connectivity offer flexibility select guaranteed minimal features. Consequently, leverage such features manifest manufacturability 3D printing. computational strategy, which precisely realizes facilitates manufacturing feasibility, can be beneficial prioritize exemplifying disorderedness, non-uniformity, heterogeneity.

Язык: Английский

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Modulate stress distribution with bio-inspired irregular architected materials towards optimal tissue support

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Май 21, 2024

Abstract Natural materials typically exhibit irregular and non-periodic architectures, endowing them with compelling functionalities such as body protection, camouflage, mechanical stress modulation. Among these functionalities, modulation is crucial for homeostasis regulation tissue remodeling. Here, we uncover the relationship between functionality irregularity of bio-inspired architected by a generative computational framework. This framework optimizes spatial distribution limited set basic building blocks uses to assemble heterogeneous, disordered microstructures. Despite being non-periodic, assembled display spatially varying properties that precisely modulate towards target values in various control regions load cases, echoing robust capability natural materials. The performance generated experimentally validated 3D printed physical samples — good agreement observed. Owing its redirect loads while keeping proper amount stimulate bone repair, demonstrate potential application stress-programmable support orthopedic femur restoration.

Язык: Английский

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Wireless electronic-free mechanical metamaterial implants

Materials Today, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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Additively manufactured biodegradable Zn metamaterials with tunable Poisson’s ratio and enhanced mechanical properties

Virtual and Physical Prototyping, Год журнала: 2025, Номер 20(1)

Опубликована: Фев. 6, 2025

Язык: Английский

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Data-driven topology optimization of mechanical metamaterials via deep neural network and material-field function

Mechanics of Advanced Materials and Structures, Год журнала: 2025, Номер unknown, С. 1 - 17

Опубликована: Фев. 12, 2025

Data-driven methods offer an innovative way to explore high-performance mechanical metamaterials, accelerating their engineering applications. However, most existing approaches use image pixel values (e.g. element densities) as input, leading the curse of dimensionality, resulting in high storage, memory demands, computational costs, and long training times. This article presents a novel lightweight data-driven approach using material field series expansion (MFSE) function deep neural network (DNN) non-iteratively design optimal metamaterials. By describing distribution with material-field instead elemental densities, number variables is significantly reduced. A multi-layer perceptron was trained map coefficients boundary conditions, principal component analysis (PCA) applied reduce output dimensions. Once trained, instantly generates topology optimization designs for optimizing bulk modulus, shear or minimizing Poisson's ratio (PR), demonstrated through numerical examples. The proposed method achieves accuracy minimal amount data. Compared density-based models, MFSE-DNN reduces time, allowing on personal PCs lower resources. not limited studied metamaterial can be further extended various metamaterials extreme specific functionalities.

Язык: Английский

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Anisotropic Nature of Lightweight Wooden Metamaterials with Mechanical/Thermomechanical Multistability

Advanced Functional Materials, Год журнала: 2023, Номер 33(51)

Опубликована: Авг. 8, 2023

Abstract Nanoengineered wood provides a renewable structural material with 3D micro and nanoarchitectures, exhibiting many beneficial characteristics such as being lightweight in nature, mechanically strong, eco‐friendly, thermally insulation, low carbon footprint. Most nanocellulose aerogels lack sufficient mechanical strength, while nanowood involves trade‐off between strength insulation performance. Here, nanowood‐derived product mechanical/thermomechanical multistability called wooden metamaterial, which is ultrastiff yet lightweight, designed synthesized. The self‐healing behaviors of cellulose nanofibrils originally present the cell walls their combination microscale constraints are utilized to form directional porous frameworks (porosity ≥98%) encapsulated empty fiber lumen predesigned macroscopic architectures. metamaterials showing ultrahigh specific (207.7 MPa cm 3 g −1 ), anisotropy an approximate factor 4. Wooden have overcome deficiencies existing building materials advanced aerospace thermal insulators, great potential for revolutionizing architecture manufacturing industries, particularly scalable, energy‐efficient, cost‐effective.

Язык: Английский

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A novel bio-inspired design method for porous structures: Variable-periodic Voronoi tessellation

Materials & Design, Год журнала: 2024, Номер 243, С. 113055 - 113055

Опубликована: Май 31, 2024

This paper introduces a novel approach, namely Variable-Periodic Voronoi Tessellation (VPVT), for the bio-inspired design of porous structures. The method utilizes distributed points defined by variable-periodic function to generate tessellation patterns, aligning with wide diversity artificial or natural cellular In this VPVT method, truss-based architecture can be fully characterized variables, such as frequency factors, thickness factors. approach enables optimal structures both mechanical performance and functionality. varied, anisotropic cell shapes sizes provide significantly greater flexibility compared typical isotropic addition, not only micro-macro multiscale materials, but is also applicable meso-macro scale structures, constructions, biomedical implants, aircraft frameworks. work employs Surrogate-assisted Differential Evolution (SaDE) perform optimization process. Numerical examples experiments validate that proposed achieves about 51.1% 47.8% improvement in compliance damage strength, respectively, than existing studies.

Язык: Английский

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Enhanced elastic stability of a topologically disordered crystalline metal–organic framework

Nature Materials, Год журнала: 2024, Номер 23(9), С. 1245 - 1251

Опубликована: Июль 23, 2024

Abstract By virtue of their open network structures and low densities, metal–organic frameworks (MOFs) are soft materials that exhibit elastic instabilities at applied stresses. The conventional strategy for improving stability is to increase the connectivity underlying MOF network, which necessarily increases material density reduces porosity. Here we demonstrate an alternative paradigm, whereby enhanced in a with aperiodic topology. We use combination variable-pressure single-crystal X-ray diffraction measurements coarse-grained lattice-dynamical calculations interrogate high-pressure behaviour topologically system TRUMOF-1, compare against its ordered congener MOF-5. show topology former quenches instability responsible pressure-induced framework collapse latter, much as irregularity shapes sizes stones acts prevent cooperative mechanical failure drystone walls. Our results establish aperiodicity counter-intuitive design motif engineering properties relevant MOFs larger-scale architectures alike.

Язык: Английский

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Dislocation Distribution, Crystallographic Texture Evolution, and Plastic Inhomogeneity of Inconel 718 Fabricated by Laser Powder Bed Fusion

Advanced Engineering Materials, Год журнала: 2024, Номер unknown

Опубликована: Май 6, 2024

Plastic inhomogeneity, particularly localized strain, is one of the main mechanisms responsible for failures in engineering alloys. This work studies spatial arrangement and distribution microstructure (including dislocations grains) their influence plastic inhomogeneity Inconel 718 fabricated by additive manufacturing (AM). The bidirectional scanning strategy with no interlayer rotation results highly ordered alternating arrangements coarse Goss‐like {110}<001> textured grains separated fine Cube‐like {100}<001> grains. also an overall high density geometrically necessary (GNDs) that are dense Although texture desirable isotropy dominant, it gradually weakens during deformation undesirable component (second most dominant as‐built microstructure) increases. clustered bimodal grains, textures, GND densities causes fast roughening deformation, along line row However, chessboard a lower comparatively more random crystallographic GNDs, (and much texture) remains stable throughout deformation. uniform reducing inhomogeneity.

Язык: Английский

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