A Radial Distribution Function Based Recognition Algorithm of Point Defects in Large-Scale β-Ga2O3 Systems

MZ Yan and JL Zhao and J Byggmästar and F Djurabekova and ZW Xu, JOURNAL OF PHYSICAL CHEMISTRY LETTERS, 15, 10677-10685 (2024).

DOI: 10.1021/acs.jpclett.4c02469

The atomic configurations and concentrations of intrinsic defects profoundly influence the electrical and optical properties of the semiconductor materials. This influence is particularly significant in the case of beta-Ga2O3, which is a highly promising ultrawide bandgap semiconductor characterized by highly complex intrinsic defect configurations. Despite its importance, there is a notable absence of an accurate method to recognize these defects in large-scale atomistic computational modeling. We design an effective algorithm for the explicit identification of various intrinsic point defects in the beta- Ga2O3 lattice, which constitutes the integration of the particle swarm optimization (PSO) and K-means clustering (K-MC) methods. Our algorithm attains the recognition accuracy exceeding 95%. Finally, the algorithm is applied to dynamic simulations, where the feasibility of dynamic real-time detection is explored.

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