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arXiv · 2404.17353

Large-scale atomistic study of plasticity in amorphous gallium oxide with a machine-learning potential

Jiahui Zhang·Junlei Zhao·Jesper Byggmästar·Erkka J. Frankberg·Antti Kuronen
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Abstract

Compared to the widely investigated crystalline polymorphs of gallium oxide (Ga2O3), knowledge about its amorphous state is still limited. With the help of a machine-learning interatomic potential, we conducted large-scale atomistic simulations to investigate the glass transition and mechanical behavior of amorphous Ga2O3 (a-Ga2O3). During the quenching simulations, amorphization of gallium oxide melt is observed at ultrahigh cooling rates, including a distinct glass transition. The final densities at room temperature have up to 4% variance compared to experiments. The glass transition temperature is evaluated to range from 1234 K to 1348 K at different cooling rates. Structural analysis of the amorphous structure shows evident similarities in structural properties between a-Ga2O3 and amorphous alumina (a-Al2O3), such as radial distribution function, coordination distribution, and bond angle distribution. An amorphous gallium oxide structure that contains approximately one million atoms is prepared for the tension simulation. A highly plastic behavior is observed at room temperature in the tension simulations, comparable to amorphous alumina. With quantitative characterization methods, we show that a-Ga2O3 can possibly has a higher nucleation rate of localized plastic strain events compared to a-Al2O3, which can increase the material's resistance to shear banding formation during deformation.

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Jiahui Zhang, Junlei Zhao, Jesper Byggmästar, Erkka J. Frankberg, Antti Kuronen. 2024-04-26. Large-scale atomistic study of plasticity in amorphous gallium oxide with a machine-learning potential. https://arxiv.org/abs/2404.17353

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