Reducing overprediction of molecular crystal structures via threshold clustering.

Published in: Proceedings of the National Academy of Sciences of the United States of America (2023)

Crystal structure prediction is becoming an increasingly valuable tool for assessing polymorphism of crystalline molecular compounds, yet invariably, it overpredicts the number of polymorphs. One of the causes for this overprediction is in neglecting the coalescence of potential energy minima, separated by relatively small energy barriers, into a single basin at finite temperature. Considering this, we demonstrate a method underpinned by the threshold algorithm for clustering potential energy minima into basins, thereby identifying kinetically stable polymorphs and reducing overprediction.

Keyphrases

crystal structure
single cell
climate change
human health
rna seq
deep learning
single molecule
room temperature