The Governing Council of the University of Toronto

Purpose

The main objective of this Project is to conduct a computational study of novel battery materials using computer models, simulations, and machine learning. The Recipient will perform density functional theory (DFT) simulations and machine learning to design and create proof-of-concept battery materials, including cathode and electrolyte materials. The designed materials will be screened by the Recipient to identify promising candidates for exploration in a high-throughput system, influencing the workflow development by the NRC. The role of the Recipient is to perform theoretical and machine learning calculations to predict new materials with superior properties and qualify them for further development by the NRC. The NRC will synthesize the proposed electrode and electrolyte materials and engage in an iterative loop with the Recipient to identify the best-performing materials for further development.