Five Steps Change the Cost Curve of Crystal Structure Prediction
TL;DR for operators When a materials-screening pipeline must generate structures for thousands of compositions, the practical question is not only which model is most accurate, but how many sequential model calls are required to obtain that accuracy. Dey and colleagues’ uFlowCSP1 shifts that tradeoff sharply. On MP-20 with 20 candidates, five-step uFlowCSP reaches an 83.64% match rate using 100 model calls, compared with 78.34% for CrystalFlow using 2,000 and 77.93% for DiffCSP using roughly 20,000. Even one-step uFlowCSP reaches 78.38% with only 20 calls. ...