Machine learning based energy-free structure predictions of molecules, transition states, and solids
- Author(s)
- Dominik Lemm, Guido Falk von Rudorff, O. Anatole von Lilienfeld
- Organisation(s)
- Computational Materials Physics
- External organisation(s)
- Universität Basel
- Journal
- Nature Communications
- Volume
- 12
- No. of pages
- 10
- ISSN
- 2041-1723
- DOI
- https://doi.org/10.1038/s41467-021-24525-7
- Publication date
- 07-2021
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 103006 Chemical physics
- Keywords
- ASJC Scopus subject areas
- Physics and Astronomy(all), Chemistry(all), Biochemistry, Genetics and Molecular Biology(all)
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/machine-learning-based-energyfree-structure-predictions-of-molecules-transition-states-and-solids(ee23cc48-b9e2-4209-a53e-37e9b74fb359).html