# Crystal Diffusion Variational Autoencoder for Periodic Material Generation

@article{Xie2021CrystalDV, title={Crystal Diffusion Variational Autoencoder for Periodic Material Generation}, author={Tian Xie and Xiang Fu and Octavian-Eugen Ganea and Regina Barzilay and T. Jaakkola}, journal={ArXiv}, year={2021}, volume={abs/2110.06197} }

Generating the periodic structure of stable materials is a long-standing challenge for the material design community. This task is difficult because stable materials only exist in a low-dimensional subspace of all possible periodic arrangements of atoms: 1) the coordinates must lie in the local energy minimum defined by quantum mechanics, and 2) global stability also requires the structure to follow the complex, yet specific bonding preferences between different atom types. Existing methods…

## 33 Citations

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- Computer ScienceArXiv
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A class of models that are equivariant with respect to crystalline symmetry groups are introduced, by generalization of the message passing operations that can be used with more general permutation groups, or that can alternatively be seen as deﬁning an expressive convolution operation on the crystal graph.

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