Data-driven classification of elementary rearrangement events in silica glass. (December 2021)

• Record Type: Journal Article
• Authors: Bamer, Franz; Alshabab, Somar Shekh; Paul, Arghadwip; Ebrahem, Firaz; Markert, Bernd; Stamm, Benjamin
• Is Part Of: Scripta materialia. Number 205(2021)
• Publication Date: 2021-12
• Subjects: Silica glass -- Shear transformations -- Atomic-scale rearrangements -- Nanoscale plasticity -- Polynomial regression; Materials -- Periodicals; Metallurgy -- Periodicals; Metalen; Legeringen; Materiaalkunde; Metals, metalworking and machinery industries; Metals; Electronic journals; 620.11
• DOI: 10.1016/j.scriptamat.2021.114179
• Languages: English
• ISSNs: 1359-6462

Abstract

Graphical abstract: Abstract: Reliable classification and prediction of elementary rearrangement events is a crucial step towards a profound understanding of the mechanical behavior of silica glass. Using various cyclic athermal quasistatic shear deformation protocols, we detect angle-changing and bond-breaking events in silica glass, both of which do or do not recover within a defined deformation protocol. We show in this contribution that data-driven approaches using rigorous statistical analyses and polynomial regression provide valuable insights into the mechanics of the marginally stable strain state of silica glass. We classify if a particular event recovers within a defined deformation protocol with up to 90% accuracy and predict the recovering strain with up to 95% accuracy.