Predicting failure in disordered solids from structural metrics

 · Invited

Abstract

Under applied shear, amorphous solids flow via a succession of plastic rearrangements of localized particles. Numerous numerical and experimental studies have shown that plastic instabilities in glasses are triggered by spatially localized soft spots in direct analogy with dislocations present in crystalline solids, although the population and microscopic structure of the former are significantly different from the latter. In addition, many research groups have developed methods for identifying such defects, although these methods have not been systematically compared. Here we use a swap Monte Carlo algorithm to prepare equilibrium amorphous configurations with very different stabilities that exhibit a range of behaviors under shear, from ductile flow to brittle failure. We compute various structural indicators ranging from purely structural to highly non-linear metrics that require the knowledge of the interactions between constituents. We compare these metrics on the same data sets, quantifying how well these metrics perform in predicting plastic deformation across this range of glass stabilities. Moreover, we use these structural metrics to quantify the spatial distribution of plastic defects for different preparation protocols, as well as the evolution of these defects across the yielding transition, allowing us to precisely characterize how the microscopic structure encodes the differences between ductile and brittle materials.

*This work was supported by the Simons Foundation Grant No. 454947.

Presenters

  • David Richard

    • Univ of Amsterdam

Authors

  • David Richard

    • Univ of Amsterdam
  • Misaki ozawa

    • Ecole Normale Superieure
    • ens
  • Sylvain Patinet

    • PMMH, ESPCI Paris
    • Physique de Mécanique des Milieux Hétérogènes laboratory
    • PMMH, CNRS UMR 7636, ESPCI Paris, PSL University, Sorbonne Université, Université de Paris, F-75005 Paris, France
    • espci Paris
  • Ethan Stanifer

    • Syracuse University
  • Baoshuang Shang

    • University of Grenoble
  • Sean Ridout

    • University of Pennsylvania
    • Physics, Unversity of Pennsylvania
  • Bin Xu

    • Beijing Computational Science Research Center
    • Beijing computational science research center
  • Ge Zhang

    • Univ of Pennsylvania
    • University of Pennsylvania
  • Peter Morse

    • Duke University
  • Jean-Louis BARRAT

    • Université Grenoble Alpes, Liphy, CNRS, France
    • University of Grenoble
  • Ludovic Berthier

    • University of Montpellier
    • Universite Montpellier
  • Eran Bouchbinder

    • Weizmann Institute of Science
  • Michael Falk

    • Johns hopkins university
    • Johns Hopkins University
  • Pengfei Guan

    • Beijing Computational Science Research Center
    • Beijing Computational Science Res Ctr
    • Beijing computational science research center
  • Andrea Jo-Wei Liu

    • Univ of Pennsylvania
    • University of Pennsylvania
    • Department of Physics and Astronomy, University of Pennsylvania
    • Physics, University of Pennsylvania
    • Physics and Astronomy, University of Pennsylvania
  • Kirsten Martens

    • University of Grenoble
  • Srikanth Sastry

    • Jawaharlal Nehru Centre for Advanced Scientific Research
    • Jawaharlal Nehru Ctr Adv Sci
    • Theoretical Sciences Unit, Jawaharlal Nehru Centre For Advanced Scientific Research, Bangalore, India
    • JNCASR
  • Damien Vandembroucq

    • PMMH, ESPCI Paris
    • PMMH, CNRS UMR 7636, ESPCI Paris, PSL University, Sorbonne Université, Université de Paris, F-75005 Paris, France
    • espci Paris
  • Edan Lerner

    • University of Amsterdam
    • Univ of Amsterdam
  • M. Lisa Manning

    • Syracuse University
    • Physics, Syracuse University
    • Department of Physics, Syracuse University