Foundation Models Enabling Multi-Scale Battery Materials Discovery: From Molecules To Devices
- Vidushi Sharma
- Andy Tek
- et al.
- 2025
- NeurIPS 2025
Publications
11 results for Khanh Nguyen
Chemical Foundation Model-Guided Design of High Ionic Conductivity Electrolyte Formulations
- Murtaza Zohair
- Vidushi Sharma
- et al.
- 2025
- npj Computational Materials
Extracting Electrolyte Design from Interpretable Data-Driven Methods
- 2025
- ACS Spring 2025
Improving electrolyte performance for target cathode loading using an interpretable data-driven approach
- Vidushi Sharma
- Andy Tek
- et al.
- 2024
- Cell Reports Physical Science
Formulation Graphs for Mapping Structure-Composition of Battery Electrolytes to Device Performance
- 2023
- J. Chem. Inf. Model.
AI-directed discovery of high entropy electrolyte formulations for batteries using interhalogen cathodes and lithium metal anodes
- 2023
- ACS Fall 2023
Understanding the role of mass transport and lithium interphase design in enabling conversion batteries
- Murtaza Zohair
- Maxwell Giammona
- et al.
- 2023
- ACS Fall 2023
Accelerated Electrolyte Discovery using Data Driven Approach
- 2023
- ACS Fall 2023
Going beyond High Throughput Screening towards AI in Accelerated Electrolyte Discovery
- 2022
- MRS Fall Meeting 2022
Transfer Learning Enabled Deep Learning Model for the Prediction of Battery Performance from Electrolyte Formulations
- 2022
- ECS Meeting 2022