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Resolving Structural Avalanches in Amorphous Carbon with Arclength Continuation.

Fraser Birks1, Ibrahim Ghanem2, Lars Pastewka2

  • 1University of Warwick, Warwick Centre for Predictive Modelling, School of Engineering, Coventry CV4 7AL, United Kingdom.

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Summary
This summary is machine-generated.

Plastic deformation in amorphous solids occurs via shear transformations forming avalanches. Researchers used a machine-learned potential to analyze these events, revealing a latent structure and enabling event-driven dynamics for amorphous carbon.

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Area of Science:

  • Materials Science
  • Condensed Matter Physics
  • Computational Materials Science

Background:

  • Plastic deformation in amorphous solids is mediated by localized shear transformations.
  • These transformations self-organize into dynamic events known as avalanches.
  • Understanding the energetics and dynamics of these avalanches is crucial for predicting material behavior.

Purpose of the Study:

  • To investigate the energetics and organization of shear transformation avalanches in amorphous carbon.
  • To develop a method for resolving avalanche dynamics by analyzing the underlying energy landscape.
  • To establish an event-driven framework for studying plastic deformation in amorphous materials.

Main Methods:

  • Utilized a machine-learned interatomic potential to model amorphous carbon.
  • Employed a pseudoarclength numerical continuation framework to follow the energy landscape.
  • Decomposed avalanches into constituent shear transformations and determined their strain-dependent energetics.

Main Results:

  • Identified a latent structure of well-separated local minima preceding avalanche onset.
  • Demonstrated that pseudoarclength continuation can resolve avalanche energetics and organization.
  • Developed an event-driven framework for avalanche dynamics, removing time-step dependencies.

Conclusions:

  • The energy landscape provides a powerful tool for understanding plastic deformation in amorphous solids.
  • Pseudoarclength continuation offers a robust method for analyzing avalanche phenomena.
  • The developed framework facilitates accurate statistical analysis of avalanche properties, such as stress drop distributions.