How is Machine Learning Transforming Computational Crystallography?
Machine learning is increasingly being integrated into computational crystallography to overcome some of these challenges. By training algorithms on existing data, researchers can quickly predict the properties of new crystal structures without the need for exhaustive simulations. This approach accelerates the discovery of new catalysts and optimizes existing ones.
