Achieving optimized materials requires controlling atomic positions through painstaking trial-and-error in synthesis experiments.
When these efforts become too overwhelming for humans, various techniques from computational chemistry and machine learning,
including a recent approach called materials informatics, can be effective.
Our research focuses on developing methods to represent any material inside a computer so that they can be handled theoretically.