Threshold displacement energy map of Frenkel pair generation in β-Ga₂ O₃ from machine-learning-driven molecular dynamics simulations

He, Huan1,2; Zhao, Junlei3; Byggmastar, Jesper2; He, Ru2; Nordlund, Kai2,4; He, Chaohui1; Djurabekova, Flyura2,4

2024-09-01

10.1016/j.actamat.2024.120087

ACTA MATERIALIA   影响因子和分区

1359-6454

1873-2453

-gallium oxide ( -Ga 2 O 3 ) shows great promise for electronics applications, particularly, in future space operating devices exposed to harsh radiation environments for extended times. This study focuses on crucial, yet not fully explored, aspects of radiation damage in this material, such as threshold displacement energies and formation of various radiation-induced Frenkel pairs. Analyzing over 5,000 molecular dynamics simulations based on our machine-learning potentials, we conclude that the threshold displacement energies for two Ga sites, the tetrahedral (22.9 eV) and octahedral (20 eV) ones, differ stronger than the same values for three different O sites, which range only between 17 eV and 17.4 eV. Mapping of threshold displacement energies unveils significant differences in displacements for all five atomic sites. Our newly developed defect identification methodology successfully classified multiple Frenkel pair types in-Ga 2 O 3 , with over ten different Ga and two primary O ones with a predominant O split interstitial at the O1 site. Finally, the calculated recombination energy barriers suggest that O Frenkel pairs are more likely to recombine upon annealing than Ga. These insights are pivotal for understanding the radiation damage and defect formation in Ga 2 O 3 , providing the basis for design of Ga 2 O 3-based electronics with high radiation resistance.

Gallium oxide Machine-learning interatomic potential Molecular dynamics Radiation damage Frenkel pair

SCI ; EI

英语

通讯

M-ERA.NET Program via GOFIB project["337627","352518"] ; National Natural Science Foundation of China[62304097] ; Guangdong Basic and Applied Basic Research Foundation[2023A1515012048] ; Shenzhen Fundamental Research Program[JCYJ20230807093609019] ; Research Council of Finland via SPATEC project[349690]

Materials Science ; Metallurgy & Metallurgical Engineering

Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering

WOS:001266832400001

PERGAMON-ELSEVIER SCIENCE LTD

20242716653999

Defects ; Gallium compounds ; Machine learning ; Radiation damage

Artificial Intelligence:723.4 ; Physical Chemistry:801.4 ; Materials Science:951

MATERIALS SCIENCE

Web of Science

1.Xi An Jiao Tong Univ, Sch Nucl Sci & Technol, Xian 710049, Shaanxi, Peoples R China
2.Univ Helsinki, Dept Phys, POB 43, FI-00014 Helsinki, Finland
3.Southern Univ Sci & Technol, Dept Elect & Elect Engn, Shenzhen 518055, Peoples R China
4.Univ Helsinki, Helsinki Inst Phys, POB 43, FI-00014 Helsinki, Finland

He, Huan,Zhao, Junlei,Byggmastar, Jesper,et al. Threshold displacement energy map of Frenkel pair generation in β-Ga₂ O₃ from machine-learning-driven molecular dynamics simulations[J]. ACTA MATERIALIA,2024,276.

He, Huan.,Zhao, Junlei.,Byggmastar, Jesper.,He, Ru.,Nordlund, Kai.,...&Djurabekova, Flyura.(2024).Threshold displacement energy map of Frenkel pair generation in β-Ga₂ O₃ from machine-learning-driven molecular dynamics simulations.ACTA MATERIALIA,276.

He, Huan,et al."Threshold displacement energy map of Frenkel pair generation in β-Ga₂ O₃ from machine-learning-driven molecular dynamics simulations".ACTA MATERIALIA 276(2024).