Unified Model for Crystalline Material Generation

Unified Model for Crystalline Material Generation

Astrid Klipfel, Yaël Frégier, Adlane Sayede, Zied Bouraoui

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
AI for Good. Pages 6031-6039. https://doi.org/10.24963/ijcai.2023/669

One of the greatest challenges facing our society is the discovery of new innovative crystal materials with specific properties. Recently, the problem of generating crystal materials has received increasing attention, however, it remains unclear to what extent, or in what way, we can develop generative models that consider both the periodicity and equivalence geometric of crystal structures. To alleviate this issue, we propose two unified models that act at the same time on crystal lattice and atomic positions using periodic equivariant architectures. Our models are capable to learn any arbitrary crystal lattice deformation by lowering the total energy to reach thermodynamic stability. Code and data are available at https://github.com/aklipf/GemsNet.
Keywords:
AI for Good: Multidisciplinary Topics and Applications
AI for Good: Machine Learning