An international consortium of scientists has mapped out a framework for a centralized battery data hub. Invoking the Human Genome Project of the 1990s, the proposed Battery Data Genome is a large-scale undertaking to unify data acquisition and sharing practices across the wide-ranging battery community — and accelerate engineering of the next generation of batteries.

The project architects aim to compile data from all types of batteries across all stages of development and throughout their useful life cycles, from discovery to manufacturing to deployment. They believe that universal data management standards will enable the community to unleash the power of artificial intelligence on the pressing need for better energy storage. Using these data, novel algorithms will be able to uncover possible new battery materials, increase energy storage density and improve cell lifetimes.

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A group of 28 scientists, including ChemE professor David Beck and 2022 Ph.D. recipients Erica Eggleton, Victor Hu, and Linette Teo, laid out the idea in a recent paper published in the journal Joule. The effort grew out of an Electrochemical Society hack week led by Beck, ChemE professor Dan Schwartz, and Matt Murbach (Ph.D. ’18). Eggleton, Hu, Murbach and Teo all completed the Advanced Data Science degree option in ChemE.