De Novo Atomistic Discovery of Disordered Mechanical Metamaterials by Machine Learning

Han Liu*, Liantang Li, Zhenhua Wei, Morten M. Smedskjaer, Xiaoyu Rayne Zheng, Mathieu Bauchy*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

2 Citations (Scopus)
20 Downloads (Pure)

Abstract

Architected materials design across orders of magnitude length scale intrigues exceptional mechanical responses nonexistent in their natural bulk state. However, the so-termed mechanical metamaterials, when scaling bottom down to the atomistic or microparticle level, remain largely unexplored and conventionally fall out of their coarse-resolution, ordered-pattern design space. Here, combining high-throughput molecular dynamics (MD) simulations and machine learning (ML) strategies, some intriguing atomistic families of disordered mechanical metamaterials are discovered, as fabricated by melt quenching and exemplified herein by lightweight-yet-stiff cellular materials featuring a theoretical limit of linear stiffness–density scaling, whose structural disorder—rather than order—is key to reduce the scaling exponent and is simply controlled by the bonding interactions and their directionality that enable flexible tunability experimentally. Importantly, a systematic navigation in the forcefield landscape reveals that, in-between directional and non-directional bonding such as covalent and ionic bonds, modest bond directionality is most likely to promotes disordered packing of polyhedral, stretching-dominated structures responsible for the formation of metamaterials. This work pioneers a bottom-down atomistic scheme to design mechanical metamaterials formatted disorderly, unlocking a largely untapped field in leveraging structural disorder in devising metamaterials atomistically and, potentially, generic to conventional upscaled designs.

Original languageEnglish
Article number2304834
JournalAdvanced Science
Volume11
Issue number13
Number of pages13
DOIs
Publication statusPublished - 3 Apr 2024

Bibliographical note

© 2024 The Authors. Advanced Science published by Wiley‐VCH GmbH.

Keywords

  • Bayesian optimization
  • cellular materials
  • interparticle interactions
  • molecular dynamics simulation
  • stiffness-density scaling

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