Deep learning in mechanical metamaterials: from prediction and generation to inverse design

X Zheng, X Zhang, TT Chen, I Watanabe - Advanced Materials, 2023 - Wiley Online Library
Mechanical metamaterials are meticulously designed structures with exceptional
mechanical properties determined by their microstructures and constituent materials …

Data‐Driven Design for Metamaterials and Multiscale Systems: A Review

D Lee, W Chen, L Wang, YC Chan… - Advanced …, 2024 - Wiley Online Library
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 …

3d-ldm: Neural implicit 3d shape generation with latent diffusion models

G Nam, M Khlifi, A Rodriguez, A Tono, L Zhou… - arXiv preprint arXiv …, 2022 - arxiv.org
Diffusion models have shown great promise for image generation, beating GANs in terms of
generation diversity, with comparable image quality. However, their application to 3D …

Nature-inspired architected materials using unsupervised deep learning

SC Shen, MJ Buehler - Communications Engineering, 2022 - nature.com
Nature-inspired material design is driven by superior properties found in natural architected
materials and enabled by recent developments in additive manufacturing and machine …

[HTML][HTML] ShipHullGAN: A generic parametric modeller for ship hull design using deep convolutional generative model

S Khan, K Goucher-Lambert, K Kostas… - Computer Methods in …, 2023 - Elsevier
In this work, we introduce ShipHullGAN, a generic parametric modeller built using deep
convolutional generative adversarial networks (GANs) for the versatile representation and …

TPMS-infill MMC-based topology optimization considering overlapped component property

S Zhang, D Da, Y Wang - International Journal of Mechanical Sciences, 2022 - Elsevier
Engineering designs involving multiple materials suffer either difficult interface modeling or
finding physically meaningful transition domains with a clear or even optimal structural …

Controlling auxeticity in curved-beam metamaterials via a deep generative model

G Felsch, N Ghavidelnia, D Schwarz… - Computer Methods in …, 2023 - Elsevier
Lattice-based mechanical metamaterials are known to exhibit quite a unique mechanical
behavior owing to their rational internal architecture. This includes unusual properties such …

[HTML][HTML] Inverse design of 3D cellular materials with physics-guided machine learning

M Abu-Mualla, J Huang - Materials & Design, 2023 - Elsevier
This paper investigates the feasibility of data-driven methods in automating the engineering
design process, specifically studying inverse design of cellular mechanical metamaterials …

New families of triply periodic minimal surface-like shell lattices

Y Xu, H Pan, R Wang, Q Du, L Lu - Additive Manufacturing, 2023 - Elsevier
Triply periodic minimal surface (TPMS)-based shell lattices are increasingly recognized for
their exceptional geometric and mechanical attributes. Their open-cell configuration further …

Deep learning-enabled design for tailored mechanical properties of SLM-manufactured metallic lattice structures

O Eren, N Yüksel, HR Börklü, HK Sezer… - … Applications of Artificial …, 2024 - Elsevier
The lattice structures obtained by combining repetitive light cellular forms provide superior
high strength to weight capabilities compared to monolithic solid bodies. These properties of …