Structuro-elasto-plasticity model for large deformation of disordered solids

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

7 Scopus Citations
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Author(s)

  • Hongyi Xiao
  • Entao Yang
  • Robert J. S. Ivancic
  • Sean A. Ridout
  • Robert A. Riggleman
  • Douglas J. Durian
  • Andrea J. Liu

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number043026
Journal / PublicationPhysical Review Research
Volume4
Issue number4
Online published13 Oct 2022
Publication statusPublished - Dec 2022

Link(s)

Abstract

Elastoplastic lattice models for the response of solids to large-scale deformation typically incorporate structure only implicitly via a local yield strain that is assigned to each site. However, the local yield strain can change in response to a nearby or even distant plastic event in the system. This interplay is key to understanding phenomena such as avalanches in which one plastic event can trigger another, leading to a cascade of events, but is typically neglected in elastoplastic models. To include the interplay one could calculate the local yield strain for a given particulate system and follow its evolution, but this is expensive and requires knowledge of particle interactions that aren't necessarily pairwise additive or possible to extract from experiments. Instead, we use a structural quantity, "softness,"obtained using machine learning to correlate with imminent plastic rearrangements. We show that softness correlates with local yield strain and use it to construct a "structuro-elasto-plasticity"model that reproduces particle simulation results reasonably well for several observable quantities, confirming that we capture the influence of the interplay of local structure, plasticity, and elasticity on material response.

Research Area(s)

  • RELAXATION, CRYSTALS

Citation Format(s)

Structuro-elasto-plasticity model for large deformation of disordered solids. / Zhang, Ge; Xiao, Hongyi; Yang, Entao et al.
In: Physical Review Research, Vol. 4, No. 4, 043026, 12.2022.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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