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This looks similar to the protein folding problem. Maybe an AlphaFold-like approach could work?
by fpordeig 3y ago
This looks similar to the protein folding problem. Maybe an AlphaFold-like approach could work?
- fock 3y agonot soo similar really, but yes, alphafold-style generative models could help find realistic structures for a specific composition. However a) data is much worse (I would say so at least...), b) the clever tricks of alphafold centered around strings of aminoacid don't really apply to particles in a box... and c) search space might be even larger if you go to interestingly sized systems. Also there's been some people arguing about the particles in a box situation for a loooong time and the most promising approach currently is diffusion.
- akasakahakada 3y agoWe exactly considering this since this year. But there are some major problems that cannot be solved in short term. Inorganic crystal structure database (and there is one database literally this name) is way smaller than what we have for proteins. Also by nature, Transformer is hardly useful for crystals because the crystal is repetitive. You don't throw the same sequence over and over to transformer and hope it will work like magic. My current understanding is that Graph Neural Network is perfect for this job because graph can exactly describe this kind of repetitive nature of crystal.
- rsfern 3y agoGNNs and graph transformers are the current state of the art methods for this kind of crystal property prediction task. One drawback is that they don’t seem to capture long range structure all that well, and the current generative models (which are really cool) based on GNNs don’t seem to take advantage of symmetry that well