CrySPY enables anyone to easily perform crystal structure prediction simulations for materials discovery and design, and automates structure generation, structure optimization, energy evaluation, and efficiently selecting candidates using machine learning. Several searching algorithms are available such as random search, evolutionary algorithm, Bayesian optimization, and Look Ahead based on Quadratic Approximation. Machine learning is employed to efficiently select candidates for priority optimization. CrySPY automates the following: Structure generation Submitting jobs for structure optimization Collecting data for structure optimization Selecting candidates using machine learning
T. Yamashita, S. Kanehira, N. Sato, H. Kino, H. Sawahata, T. Sato, F. Utsuno, K. Tsuda, T. Miyake, and T. Oguchi, Sci. Technol. Adv. Mater.:Methods 1, 87 (2021).
, crystal structure prediction simulations,
Curator: qinyang