Diffusion coefficients calculations of 110mAg in ZrC at very high temperature using machine-learning interatomic potential
Year: 2024
Type: article
Abstract: The ternary machine-learning interatomic potential for a Zr–C–Ag system was developed using first-principles calculations, moment tensor potential, and molecular dynamics simulations to calculate the diffusion coefficient of Ag in ZrC. The developed potential was utilized to investigate the vacancy formation energy, Ag substitutional energy, binding energy between Ag and vacancy, Ag interstitial energy in ZrC, and thermal expansion of ZrC. The results conformed to previously reported experimental and computational results, thereby validating the accuracy of the developed potential. The diffusion coefficients of Ag in ZrC0.94 and ZrC0.97 in the temperature range of 2800–3200 K were calculated using molecular dynamics simulations with the developed machine-learning interatomic potential. These calculation results can aid the safety analysis of radioactive 110mAg release in nuclear thermal propulsion reactors.
Source: Journal of Nuclear Materials
Authors: Jae Joon Kim, Eung-Seon Kim, Hyun Woo Seong, Ho Jin Ryu
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,510
OpenAlex ID: W4404642035