AI-assisted design of 3D NPR lattice materials with programmable mechanical properties using irregular unit cells

Materials Horizons 2026 Open access

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Authors: Zewen Gu, Yalong Liu, Xiaoxuan Ding, Jianwei Zhao, Aoyu Xiao, Xiangqing Kong, Jianlin Liu, Xiaonan Hou
DOI: 10.1039/d5mh02188j
Cited by: 3
References: 53

Abstract

and quasi-static compression tests, we experimentally validate the programmable NPR effects across varied materials and scales. Micro-DIC analysis reveals the strain localization patterns governing microscale deformation and pinpoints the critical buckling instabilities in compressed architectures. Our approach enables the inverse design of 3D lattice metamaterials composed of irregular unit cells with tailored mechanical properties, unlocking new possibilities for applications in lightweight structures, energy absorption, and beyond.

Fields of Study & Subjects

Cellular and Composite Structures Topology Optimization in Engineering Shape Memory Alloy Transformations

Publication details

Journal / source
Materials Horizons
Publisher
Royal Society of Chemistry (RSC)
Volume
13
Issue
6
Pages
3103–3116
Publication date
1 January 2026
Language
EN