Earlier quoted context omitted.
Not an expert but it just happen that my lab is full of DFT folks so I heard a lot about those everyweek. As people above already answered the questions, I gonna talk some extras. 1. Computation cost is large. 1 compute task for a small scale ~100 atoms last about 3 days to 1 week on supercomputer. 2. Search space is hugh. For each composition you can have different atomic (or crystal) structure. And here we are talk…
This looks similar to the protein folding problem. Maybe an AlphaFold-like approach could work?
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.