[1Ip01-08] Low-dimensional Material/Nanostructure/Nanomaterial (LD/NS/NM)

[1Ip03] Analysis of S defect structures in WS₂ thin films using neural network potential

*Ryuji Otsuka¹, Koji Shimizu¹, Hitoshi Wakabayashi², Satoshi Watanabe¹ (1. Department of Materials Engineering, The University of Tokyo, 2. Department of Electrical and Electronic Engineering, Tokyo Institute of Technology)

In recent years, two-dimensional transition metal dichalcogenides (TMDCs) like WS₂ have attracted attention for their potential in thermoelectric materials and MISFETs due to high mobility and Seebeck coefficient. WS₂ stands out for its stability and mobility, but understanding its structural disorder, which affects device performance, by experiments remains a challenge. This study employs high-dimensional neural network potential (HDNNP) to investigate S defects and structural disorder in WS₂ thin films by computational calculation. Molecular dynamics (MD) simulations using HDNNP were conducted on WS₂ slabs at different temperatures and S/W ratios. Introduced S vacancies transformed into non-six-membered ring structures (e.g., 5-membered and 9-membered rings) during MD simulations, proving more stable than atomic vacancy structures. The study also explores correlations between neighboring defect structures.