Concepedia

Machine Learning Potentials

Machine Learning Potentials is a computational interatomic potential model that leverages machine learning techniques to approximate quantum-mechanical accuracy in predicting material properties while significantly reducing computational cost compared to first-principles methods.

827

Publications

64.2K

Citations

2.1K

Authors

716

Institutions

Publications per year

2017–2026

797

Variants

Mlps

Parents

Publications

827

The PseudoDojo: Training and grading a 85 element optimized norm-conserving pseudopotential table

Michiel J. van Setten, Matteo Giantomassi, Éric Bousquet et al. · Computer Physics Communications · 2018 · 2.1K citations · Full text

, , +5

ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

Justin S. Smith, Olexandr Isayev, Adrián E. Roitberg · Chemical Science · 2017 · 2K citations · Full text

, , +17

E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials

Simon Batzner, Albert Musaelian, Lixin Sun et al. · Nature Communications · 2022 · 1.7K citations · Full text

, , +17

Perspective: Machine learning potentials for atomistic simulations

Jörg Behler · The Journal of Chemical Physics · 2016 · 1.5K citations · Full text

, , +13

Atomic cluster expansion for accurate and transferable interatomic potentials

Ralf Drautz · Physical review. B./Physical review. B · 2019 · 918 citations

, , +16

1–5 of 827

Authors

2.1K

  1. GC
    Gábor Cśanyi

    University of Cambridge, United Kingdom

    33 publications · 4.5K citations

    31

    h-index

  2. JB
    Jörg Behler

    Ruhr University Bochum, Germany

    31 publications · 5.7K citations

    25

    h-index

  3. OI
    Olexandr Isayev

    Carnegie Mellon University, United States

    25 publications · 5.8K citations

    20

    h-index

  4. VL
    Volker L. Deringer

    RWTH Aachen University, Germany

    20 publications · 2.7K citations

    19

    h-index

  5. AV
    Alexander V. Shapeev

    Skolkovo Institute of Science and Technology, Russia

    20 publications · 2.2K citations

    19

    h-index

1–5 of 2.1K

Institutions

716

  1. University of Cambridge

    Cambridge, United Kingdom

    39 h-index

    107 publications

    14.5K citations

  2. Skolkovo Institute of Science and Technology

    Skolkovo, Russia

    23 h-index

    61 publications

    6.2K citations

  3. University of Stuttgart

    Stuttgart, Germany

    22 h-index

    65 publications

    4.3K citations

  4. École Polytechnique Fédérale de Lausanne

    Lausanne, Switzerland

    21 h-index

    70 publications

    8.1K citations

  5. Ruhr University Bochum

    Bochum, Germany

    21 h-index

    55 publications

    8.5K citations

  6. Carnegie Mellon University

    Pittsburgh, United States

    20 h-index

    64 publications

    4.7K citations

  7. Los Alamos National Laboratory

    Los Alamos, United States

    18 h-index

    99 publications

    11.3K citations

  8. University of Vienna

    Vienna, Austria

    18 h-index

    46 publications

    7.8K citations

1–8 of 716

Venues

  1. The Journal of Chemical Physics

    85 publications · 8.6K citations

    42

    h-index

  2. Journal of Chemical Theory and Computation

    JCTC · 55 publications · 3.8K citations

    35

    h-index

  3. npj Computational Materials

    44 publications · 3.6K citations

    34

    h-index

  4. Physical review. B./Physical review. B

    PRB · 46 publications · 4.6K citations

    30

    h-index

  5. Physical Review Materials

    32 publications · 1.8K citations

    23

    h-index

1–5