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  Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning

Bereau, T., DiStasio, R. A., Tkatchenko, A., & von Lilienfeld, O. A. (2018). Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning. The Journal of Chemical Physics, 148(24): 241706. doi:10.1063/1.5009502.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-DAA6-E Version Permalink: http://hdl.handle.net/21.11116/0000-0005-DA0C-9
Genre: Journal Article

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 Creators:
Bereau, Tristan1, 2, Author              
DiStasio, R. A., Author
Tkatchenko, A., Author
von Lilienfeld, O. Anatole3, Author              
Affiliations:
1Emmy Noether Group Bereau: Biomolecular Simulations, MPI for Polymer Research, Max Planck Society, ou_2344697              
2Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society, ou_1800287              
3Univ Basel, Inst Phys Chem and Natl Ctr Computat Design & Discovery Novel Mat (MARVEL), Dept Chem, CH-4056 Basel, Switzerland, ou_persistent22              

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Language(s): eng - English
 Dates: 2018
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1063/1.5009502
 Degree: -

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Title: The Journal of Chemical Physics
  Other : J. Chem. Phys.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Woodbury, N.Y. : American Institute of Physics
Pages: - Volume / Issue: 148 (24) Sequence Number: 241706 Start / End Page: - Identifier: ISSN: 0021-9606
CoNE: https://pure.mpg.de/cone/journals/resource/954922836226