Research ArticlePHYSICS

Machine learning unifies the modeling of materials and molecules

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Science Advances  13 Dec 2017:
Vol. 3, no. 12, e1701816
DOI: 10.1126/sciadv.1701816

Article Information

vol. 3 no. 12

Online ISSN: 
History: 
  • Received for publication May 30, 2017
  • Accepted for publication November 14, 2017

Author Information

  1. Albert P. Bartók1,
  2. Sandip De2,3,
  3. Carl Poelking4,
  4. Noam Bernstein5,
  5. James R. Kermode6,
  6. Gábor Csányi7 and
  7. Michele Ceriotti2,3,*
  1. 1Scientific Computing Department, Science and Technology Facilities Council, Rutherford Appleton Laboratory, Oxfordshire OX11 0QX, UK.
  2. 2National Center for Computational Design and Discovery of Novel Materials (MARVEL), Lausanne, Switzerland.
  3. 3Laboratory of Computational Science and Modelling, Institute of Materials, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
  4. 4Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
  5. 5Center for Materials Physics and Technology, U.S. Naval Research Laboratory, Washington, DC 20375, USA.
  6. 6Warwick Centre for Predictive Modelling, School of Engineering, University of Warwick, Coventry CV4 7AL, UK.
  7. 7Engineering Laboratory, University of Cambridge, Cambridge, UK.
  1. *Corresponding author. Email: michele.ceriotti{at}epfl.ch.

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