Molecular dynamics with on-the-fly machine learning of quantum-mechanical forces

HIGHLIGHTS

• who: . et al. from the Department, Strand, London WC R LS, United Kingdom University of have published the research: Molecular Dynamics with On-the-Fly Machine Learning of Quantum-Mechanical Forces, in the Journal: (JOURNAL) of 13/05/2014
• what: The authors propose an alternative machine-learning (ML) based scheme where the authors allow a stream of fresh quantummechanical (QM) calculations to augment the ML database during each MD simulation, enabling safe interpolation. The scheme could equally be viewed as an efficient FPMD approach where the authors seek to compute only the QM information necessary . . .
  

   

  

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