|About this Abstract
||2023 TMS Annual Meeting & Exhibition
||Hume-Rothery Symposium on First-Principles Materials Design
||Holistic Integration of Experimental and Computational Data and Simple Empirical Models for Diffusion Coefficients of Metallic Solid Solutions
||Wei Zhong, Ji-Cheng Zhao
|On-Site Speaker (Planned)
Large amounts of both experimental and computational diffusion coefficients are available in the literature for careful assessments of the degree of agreements between the datasets. Such systematic assessments allow us to employ the best of both datasets and provide complementary data to establish the most reliable diffusion databases. The power of such holistic integration will be illustrated with unary and binary solid solutions. In addition, simple and yet generally applicable semi-empirical models of diffusion coefficients of binary and multicomponent metallic solid solutions are developed. Only one-fitting parameter is required to fully describe all the diffusion coefficients as a function of composition and temperature of a binary solution. Future calculations of this parameter and impurity (dilute) diffusion coefficients using first principles and machine-learning methods would be extremely valuable for the establishment of reliable diffusion (atomic mobility) databases for kinetic simulations of alloys.
||ICME, Computational Materials Science & Engineering, Magnesium