Modeling and Control of Solid-State Batteries for the Regulation of Morphogenic Interfaces
Students: Keith Ng, Maxwell Wu
Due to the demand for higher-performing batteries, particularly in consumer products, solid-state batteries present an encouraging next-generation technology for their advantages in energy density, reduced flammability risk, and charging capability. However, compared to current conventional batteries with a liquid electrolyte, the interfaces (i.e., between the electrodes and electrolyte) are currently unstable and poorly controlled, resulting in severe degradation and failure of the cell. This project aims to develop a control and decision-making framework to: 1) provide real-time regulation of the interface by driving dynamic morphogenic processes; and 2) use off-line learning to identify performance trends and metrics to guide the interface design.