Orientation-Dependent Atomic-Scale Mechanism of $\beta$-$\mathrm{Ga}_{2}\mathrm{O}_{3}$ Thin Film Epitaxial Growth
Jun Zhang, Junlei Zhao, Junting Chen, Mengyuan Hua

TL;DR
This study uses large-scale machine-learning molecular dynamics simulations to uncover the orientation-dependent atomic-scale mechanisms governing the epitaxial growth of $eta$-Ga2O3 thin films, revealing the role of face-centered cubic stacking O sublattice migration.
Contribution
It systematically explores the growth mechanisms of $eta$-Ga2O3$ with four low Miller-index facets using advanced simulations, providing new atomic-scale insights into the epitaxial process.
Findings
Migration of face-centered cubic stacking O sublattice influences growth mechanisms.
Identification of stacking faults and twin boundaries consistent with experiments.
Insights into tailoring $eta$-Ga2O3$ properties for device applications.
Abstract
- has gained intensive interests of research and application as an ultrawide bandgap semiconductor. Epitaxial growth technique of the - thin film possesses a fundamental and vital role in the -based device fabrication. In this work, epitaxial growth mechanisms of - with four low Miller-index facets, namely (100), (010), (001), and (01), are systematically explored using large-scale machine-learning molecular dynamics simulations at the atomic scale. The simulations reveal that the migration of the face-centered cubic stacking O sublattice plays a predominant role in rationalizing the different growth mechanisms between (100)/(010)/(001) and (01) orientations. The resultant complex combinations of the stacking faults…
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Taxonomy
TopicsGa2O3 and related materials · ZnO doping and properties · Machine Learning in Materials Science
