Work

A Radial Distribution Function Based Recognition Algorithm of Point Defects in Large-Scale β-Ga 2 O 3 Systems

Year: 2024

Type: article

Abstract: 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 β-Ga 2 O 3, 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 β-Ga 2 O 3 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.

Source: The Journal of Physical Chemistry Letters

DOI: 10.1021/acs.jpclett.4c02469

Authors: Mengzhi Yan, Junlei Zhao, Jesper Byggmästar, Flyura Djurabekova, Zongwei Xu

Institutions: Tianjin University, Southern University of Science and Technology, University of Helsinki, Helsinki Institute of Physics

Language: English

Topic: Ga2O3 and related materials

Subfield: Electronic, Optical and Magnetic Materials

Field: Materials Science

Domain: Physical Sciences

Open Access status: green