Data-efficient machine learning for molecular crystal structure prediction
Author:
Affiliation:
1. Chair of Theoretical Chemistry
2. Technische Universität München
3. 85747 Garching
4. Germany
5. Engineering Laboratory
6. University of Cambridge
7. Cambridge CB2 1PZ
8. UK
9. Fritz-Haber-Institut der Max-Planck-Gesellschaft
Abstract
Using a cluster-based training scheme and a physical baseline, data efficient machine-learning models for crystal structure prediction are developed, enabling accurate structural relaxations of molecular crystals with unprecedented efficiency.
Funder
Deutsche Forschungsgemeinschaft
Publisher
Royal Society of Chemistry (RSC)
Subject
General Chemistry
Link
http://pubs.rsc.org/en/content/articlepdf/2021/SC/D0SC05765G
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