Generating Symmetric Materials using Latent Flow Matching
Authors: Anmar Karmush, Cedric Mathieu Brandenburg, Soheil Ershadrad, Johanna Rosén, Michael Felsberg, Filip Ekström Kelvinius
Organizations: Department of Electrical Engineering (ISY) & AI4x, Linköping University · Department of Physics, Chemistry and Biology (IFM), Linköping University · Wallenberg Initiative Materials Science for Sustainability (WISE), Linköping University · Department of Computer and Information Science (IDA), Linköping University
Tackling the task of materials generation, we aim to enhance the previously proposed All-atom Diffusion Transformer (ADiT) by introducing SymADiT, a symmetry-aware variant. To do so, we use a representation of materials based on Wyckoff positions. We follow ADiT and perform generative modelling in latent space, adapted to our symmetry-aware representation. By forcing the output of the generative model to adhere to the symmetry restrictions imposed by the generated crystal's space group and each atom's Wyckoff-position, the generated materials exhibit more realistic symmetry properties. We benchmark our method against both symmetry-aware and symmetry-agnostic models for materials generation and show competitive performance, generating stable, symmetric materials with a simple Transformer architecture.