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Title: Learning local, quenched disorder in plasticity and other crackling noise phenomena

Abstract

When far from equilibrium, many-body systems display behavior that strongly depends on the initial conditions. A characteristic such example is the phenomenon of plasticity of crystalline and amorphous materials that strongly depends on the material history. In plasticity modeling, the history is captured by a quenched, local and disordered flow stress distribution. While it is this disorder that causes avalanches that are commonly observed during nanoscale plastic deformation, the functional form and scaling properties have remained elusive. In this paper, a generic formalism is developed for deriving local disorder distributions from field-response (e.g., stress/strain) timeseries in models of crackling noise. We demonstrate the efficiency of the method in the hysteretic random-field Ising model and also, models of elastic interface depinning that have been used to model crystalline and amorphous plasticity. We show that the capacity to resolve the quenched disorder distribution improves with the temporal resolution and number of samples.

Authors:
Publication Date:
Research Org.:
Johns Hopkins Univ., Baltimore, MD (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1439912
Alternate Identifier(s):
OSTI ID: 1501822
Grant/Contract Number:  
SC0014109
Resource Type:
Published Article
Journal Name:
npj Computational Materials
Additional Journal Information:
Journal Name: npj Computational Materials Journal Volume: 4 Journal Issue: 1; Journal ID: ISSN 2057-3960
Publisher:
Nature Publishing Group
Country of Publication:
United Kingdom
Language:
English
Subject:
36 MATERIALS SCIENCE

Citation Formats

Papanikolaou, Stefanos. Learning local, quenched disorder in plasticity and other crackling noise phenomena. United Kingdom: N. p., 2018. Web. doi:10.1038/s41524-018-0083-x.
Papanikolaou, Stefanos. Learning local, quenched disorder in plasticity and other crackling noise phenomena. United Kingdom. doi:10.1038/s41524-018-0083-x.
Papanikolaou, Stefanos. Thu . "Learning local, quenched disorder in plasticity and other crackling noise phenomena". United Kingdom. doi:10.1038/s41524-018-0083-x.
@article{osti_1439912,
title = {Learning local, quenched disorder in plasticity and other crackling noise phenomena},
author = {Papanikolaou, Stefanos},
abstractNote = {When far from equilibrium, many-body systems display behavior that strongly depends on the initial conditions. A characteristic such example is the phenomenon of plasticity of crystalline and amorphous materials that strongly depends on the material history. In plasticity modeling, the history is captured by a quenched, local and disordered flow stress distribution. While it is this disorder that causes avalanches that are commonly observed during nanoscale plastic deformation, the functional form and scaling properties have remained elusive. In this paper, a generic formalism is developed for deriving local disorder distributions from field-response (e.g., stress/strain) timeseries in models of crackling noise. We demonstrate the efficiency of the method in the hysteretic random-field Ising model and also, models of elastic interface depinning that have been used to model crystalline and amorphous plasticity. We show that the capacity to resolve the quenched disorder distribution improves with the temporal resolution and number of samples.},
doi = {10.1038/s41524-018-0083-x},
journal = {npj Computational Materials},
number = 1,
volume = 4,
place = {United Kingdom},
year = {2018},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1038/s41524-018-0083-x

Citation Metrics:
Cited by: 2 works
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Figures / Tables:

Fig. 1 Fig. 1: Possible scenario of size effects and stochasticity in uniaxial compression of crystalline nano and micro pillars. a Uniaxial stress–strain curves have been shown to be increasingly stochastic —with clear bursts—and with higher apparent strength, as the sample/probe volume decreases, in the range where the probed volume has effectivemore » diameter 0.5, 10, or 100 μm.3–5,7 The yield stress in such samples ranges from 50 to 500 MPa. (inset): Avalanche bursts, quantified through their strain magnitude S, have been shown to follow power-law distributions with a cutoff that decreases with sample volume.3,5 b Increased strength and stochasticity at nanopillars could possibly originate into a nanoscale quenched yield distribution with non-trivial wide form, where the “most probable” yield is displaced from the bulk yield point. This distribution should evolve into a normal distribution as sample volume increases, according to the central limit theorem. The very existence of quenched disorder manifests in stochastic events that are common to describe through avalanches.4 The green arrows display the direction of increasing representative volume that is being deformed« less

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    Works referencing / citing this record:

    From Statistical Correlations to Stochasticity and Size Effects in Sub-Micron Crystal Plasticity
    journal, July 2019


    Machine learning plastic deformation of crystals
    journal, December 2018


      Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.