Simulated multi-component metallic glasses akin to experiments

Author:

Rene Alvarez-Donado, Silvia Bonfanti, Mikko Alava

Keyword:

Condensed Matter, Disordered Systems and Neural Networks, Disordered Systems and Neural Networks (cond-mat.dis-nn), Materials Science (cond-mat.mtrl-sci)

journal:

date:

2023-09-10 16:00:00

Abstract

We study a three-component metallic glass system by means of a hybrid Monte Carlo and Molecular Dynamics algorithm which allows the generation of equilibrated samples for temperatures below the conventional glass transition accessible by conventional methods. Using a realistic potential for the atomic interactions we explore the kinetics, thermodynamics, and rheology of a Cu-Zr-Al metallic glass composition in the ultrastable glass regime, showing in particular how the configurational entropy depends on the temperature, and compare it to the ubiquitous Cu-Zr one. Our results pave the way for theoretical studies of complex metallic glasses and comparisons with experiments.

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