Extracting Electrolyte Design from Interpretable Data-Driven Methods
- 2025
- ACS Spring 2025
Andy Tek
Title
Staff Research Scientist, Accelerated Discovery
Publications
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
- 2023
- ACS Fall 2023
Accelerated Electrolyte Discovery using Data Driven Approach
- 2023
- ACS Fall 2023
Oxygen Assisted Lithium-Iodine Batteries: Towards Practical Iodine Cathodes and Viable Lithium Metal Protection Strategies
- Maxwell J. Giammona
- Jangwoo Kim
- et al.
- 2023
- Advanced Materials Interfaces
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
Oxidizing gas enhancement of lithium-iodine batteries: Towards practical iodine cathodes and viable lithium metal protection strategies
- Maxwell Giammona
- Linda Sundberg
- et al.
- 2022
- ACS Fall 2022
Patents
- IN
- 496832
- US
- 10695724
- US
- 10584191
- CN
- ZL201610086205.5
- US
- 10293308
- US
- 10086338
- US
- 9931598
Projects
Leveraging our expertise in materials science, AI, quantum and high performance computing, we're developing a more powerful, sustainable, and energy-efficient battery.
Top collaborators
YN
Young-Hye Na
Manager & PRSM, Accelerated Discovery of Sustainable Battery Materials
MG
Max Giammona
Research Staff Member
VS
Vidushi Sharma
Staff Research Scientist
MZ
Murtaza Zohair
Research Scientist