Investigating the atomic structures and electronic properties of WS2 thin films with sulfur vacancies via a neural network potential-aided first-principles study

Autor: Ryuji Otsuka, Koji Shimizu, Hitoshi Wakabayashi, Satoshi Watanabe
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Applied Physics Express, Vol 17, Iss 11, p 115501 (2024)
Druh dokumentu: article
ISSN: 1882-0786
DOI: 10.35848/1882-0786/ad8b0c
Popis: Transition metal dichalcogenides are promising materials for high-performance electronics, whereas the impact of defects on their electronic properties remains elusive. Here, we employ neural network potentials (NNPs) constructed from density functional theory (DFT) data to investigate defect-laden WS _2 thin films. Molecular dynamics simulations reveal that at low defect concentrations (S/W ratio of 1.9), single sulfur vacancies are predominant. Conversely, at high defect concentrations (S/W ratio of 1.7), complex defects with short lifetimes appear. Additionally, DFT results indicate that the band gap persists at S/W = 1.9 but disappears at 1.7, aligning with observed device degradation at high defect concentrations.
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