Research ArticlePHYSICS

Machine learning unifies the modeling of materials and molecules

See allHide authors and affiliations

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

Article Information

vol. 3 no. 12

Online ISSN: 
  • 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}


Article usage

Article usage: December 2017 to December 2018

Dec 201728456901339
Jan 2018804448668
Feb 2018454358383
Mar 2018393355308
Apr 2018315315303
May 2018320341277
Jun 2018278286246
Jul 2018216252247
Aug 20184503249
Sep 20180461220
Oct 20180509263
Nov 20180521227
Dec 2018022986

Navigate This Article