About this Abstract |
Meeting |
2023 TMS Annual Meeting & Exhibition
|
Symposium
|
Computational Discovery and Design of Materials
|
Presentation Title |
Developing an Ab Initio-Kinetic Passivation Model for High-throughput Screening of Material Stability |
Author(s) |
Rachel Gorelik, Arunima K. Singh |
On-Site Speaker (Planned) |
Rachel Gorelik |
Abstract Scope |
With corrosion remaining a significant economic issue, the ability to a priori predict the kinetics of material corrosion remains an important consideration in the field of materials discovery, which often lacks the ability to predict time-dependent corrosion behavior during high-throughput screening. To address this challenge, we have developed an ab initio-kinetic framework for predicting material stability by combining density functional theory and molecular dynamics simulations with a kinetic passivation model called the Point Defect Model (PDM). This non-empirical framework can predict the growth rate of passivation films in any elemental material without prior experimental knowledge. After developing and automating this workflow, we have evaluated its performance through two common metal case studies (Cu and W) and compared with available experimental literature. Finally, we have evaluated the viability of extending this framework to the more than 700 elemental materials which are currently available in the Materials Project database. |
Proceedings Inclusion? |
Planned: |
Keywords |
Computational Materials Science & Engineering, Other, Other |