Molecular dynamics and machine learning study of tensile behavior in single-crystal tungsten containing He bubbles - Pan-dong Lin; Yan Lin; Hong-guang Li; Shu-gang Cui; Jun-feng Nie; Bai-wen Zhong; Yu-peng Lu (Materials & Design)
Tungsten is commonly used in nuclear fusion plants, where irradiation defects (e.g., He bubbles) are frequently generated. This study investigates the impact of He bubbles on the tensile behavior of single-crystal tungsten through molecular dynamics (MD) simulations. The analysis considers varying He bubble sizes, He/V ratios (the number of helium atoms with respect to the number of vacancies in helium bubble), temperatures, and strain rates. The findings indicate that He bubbles significantly affect the material’s mechanical properties, with larger bubble sizes reducing tensile strength. Dislocation emission initiates from the void surface during tensile deformation. While the He/V ratio slightly influences peak stress values, it does not alter the overall stress–strain curve. Elevated temperatures lower peak stress, whereas higher strain rates increase it. Additionally, machine learning models predict the combined effects of bubble size, He/V ratio, strain rate, and temperature on the peak stress of tungsten, utilizing MD simulation data. This work offers important insights into tungsten’s behavior under irradiation conditions.