Machine learning models for materials discovery
Innovative materials are needed to tackle current major challenges in energy storage and generation. However, the design of new materials largely relies on experimental trial and error, limiting the number explored compounds relative to the entire space of possible compounds. In this presentation, I will discuss our approach to materials design, which integrates machine learning (ML) techniques with quantum mechanics-based computations.