Mechanistic Design of High-Capacity Cation-Rich Anion-Redox Cathodes with First-Principles Simulation, Compton Measurements and Scientific Machine Learning
Abstract
The overarching goal of this project is to use first principles density functional theory (DFT) simulations, X-ray compton measurements and scientific machine learning to build a mechanistic understanding of anionic redox enabled Li-rich TMO cathodes and leveragethis mechanistic understanding to build design rules to enable the identification of high-capacity cation-rich cathodes demonstrated experimentally. Current battery chemistries have come to a halt in improving energy density and higher-energy#density solutions iscritical for DoD applications. This proposal addresses the needs by exploiting redox phenomena otherwise unharnessed to increase the energy density of cathodes. The proposed work will provide the basis for exploiting anion redox in high specific energy cathodes and lead to high specific energy batteries. The project goals will be achieved by understanding the mechanisms and deriving descriptors for reversible anionic redox. Using these descriptors, we will search over the design space of candidate anion-redox cathodes using scientific machine learning that incorporates relevant symmetries in the system. Having down-selected candidates, we will use a combination of theory and experiment to validate the performance of high-capacity cathodes.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 12, 2023
- Source ID
- N000142312330
Entities
People
- Venkat Viswanathan
Organizations
- Carnegie Mellon University
- Office of Naval Research
- United States Navy