Battery Intelligence from the Inside Out

Batteries are increasingly central to transportation and the electric grid, yet many of the processes that determine their lifetime, safety, and performance remain hidden from conventional measurements. In this talk, I will discuss two complementary approaches for gaining access to this hidden information. First, cryogenic electron microscopy enables direct visualization of battery interfaces and degradation processes at the nanoscale. Second, machine-learning-based virtual sensing can infer internal electrode states from measurements available outside the battery, creating a “virtual reference electrode” that can improve state estimation, detect lithium plating, and enable smarter charging. Together, these approaches point toward a future in which batteries are not only better understood from the inside, but also become increasingly intelligent in how they are monitored and controlled from the outside.

Speaker: Yuzhang Li, UC Los Angeles