Large-scale atomistic study of plasticity in amorphous gallium oxide with a machine-learning potential
arxiv(2024)
摘要
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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