Battery Informatics in Devices & Discovery

The increasing accessibility of battery data, both on the device and materials level, is driving exciting new questions in battery science and engineering. These span the full materials life-span, from how fleet-level users can best leverage on-vehicle diagnostic data to how R&D scientists can identify promising new materials. In this talk, I will highlight recent work which explores both device prediction tasks related to vector databases for batteries and history-agnostic degradation prediction as well as data-driven discovery of new principles in cathode design. Attention will be paid to the ways in which industrial, governmental, and academic labs can complement each other's strengths in the collection and use of data.