| About this Abstract |
| Meeting |
2023 TMS Annual Meeting & Exhibition
|
| Symposium
|
Hume-Rothery Symposium on First-Principles Materials Design
|
| Presentation Title |
Dynamic Stability Design of Materials for Solid-state Batteries |
| Author(s) |
Xin Li |
| On-Site Speaker (Planned) |
Xin Li |
| Abstract Scope |
Solid state battery in operation is a dynamically coupled device under local mechanical constriction. The growth of lithium dendrite and crack in battery cycling can be stopped by self-limited local decompositions between lithium dendrite and certain solid electrolytes, enabling the battery to be cycled at high current densities. The functional decomposition here is a type of dynamic stability, which needs a delicate balance of sufficient decomposition energy to generate the decomposition and appropriate self-limiting ability to passivate it. We thus constructed a constrained ensemble computational platform to describe the unique local environment under mechanical constriction. High-throughput computation was then used to collect the two metrics for describing the dynamic stability under constrained ensemble, by also utilizing the ab initio data for all the inorganic materials in the Materials Project. Machine learning was used to extract the correlation between material composition and dynamic stability for the design of new solid electrolytes. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Energy Conversion and Storage, Machine Learning, Computational Materials Science & Engineering |