The aim of this research area is to help revolutionize materials science, and to identify new components of advanced batteries that can power future zero-emissions and carbon-neutral vehicles. The challenges in this area include highly nonlinear phenomena in active particles and across electrodes due to coupled physics; emergent behavior due to interaction between quantum, atomistic, particle and electrode scales; and the need for predictive capability requiring data-driven communication across scales. One of the goals of the group is to integrate machine learning into this research.
For more information, contact micde-contact@umich.edu.