Quantifying the Features of an Amorphous Solid's Local Yield Surface

Fuente: arXiv
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Main Authors: Fajardo, Spencer, Desmarchelier, Paul, Patinet, Sylvain, Falk, Michael L.
Format: Preprint
Published: 2026
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author Fajardo, Spencer
Desmarchelier, Paul
Patinet, Sylvain
Falk, Michael L.
author_facet Fajardo, Spencer
Desmarchelier, Paul
Patinet, Sylvain
Falk, Michael L.
contents In two-dimensional Lennard-Jones glasses, mechanical probing reveals that local yield surfaces are dominated by regions with a positive second derivative of the yield stress with respect to the loading angle. Each feature corresponds to a shear transformation zone and a characteristic non-affine displacement field at yield. Most features are well described by a combined Schmid-Mohr-Coulomb criterion parameterized by a weak-plane orientation, a critical stress, and a pressure sensitivity. The resulting parameter statistics clarify how the onset of plastic flow is governed by the population of discrete yielding features encoded in the amorphous structure.
format Preprint
id arxiv_https___arxiv_org_abs_2603_16905
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Quantifying the Features of an Amorphous Solid's Local Yield Surface
Fajardo, Spencer
Desmarchelier, Paul
Patinet, Sylvain
Falk, Michael L.
Soft Condensed Matter
Disordered Systems and Neural Networks
Materials Science
In two-dimensional Lennard-Jones glasses, mechanical probing reveals that local yield surfaces are dominated by regions with a positive second derivative of the yield stress with respect to the loading angle. Each feature corresponds to a shear transformation zone and a characteristic non-affine displacement field at yield. Most features are well described by a combined Schmid-Mohr-Coulomb criterion parameterized by a weak-plane orientation, a critical stress, and a pressure sensitivity. The resulting parameter statistics clarify how the onset of plastic flow is governed by the population of discrete yielding features encoded in the amorphous structure.
title Quantifying the Features of an Amorphous Solid's Local Yield Surface
topic Soft Condensed Matter
Disordered Systems and Neural Networks
Materials Science
url https://arxiv.org/abs/2603.16905