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Artificial Intelligence for Materials Design

Меню

  • About
  • News
  • People
    • Alexander Shapeev
    • Evgeny Podryabinkin
    • Ivan Novikov
    • Max Hodapp
    • Tatiana Kostyuchenko
    • Edgar Makarov
    • Vadim Sotskov
    • Timofey Miryashkin (MIPT)
    • David Demuriia (MIPT)
    • Evgeny Krylov (MIPT)
    • Evgeny Sorkin (MIPT)
    • Olga Kovalyova (MIPT)
    • Alexey Kotykhov (MIPT)
    • Nikita Bogdanov (MIPT)
    • Past members
      • Evgenii Tsymbalov
      • Konstantin Gubaev
      • Vera Islamova
      • Milad Asgarpour Khansary
  • Research
    • Machine-Learning Interatomic Potentials
      • Machine Learning for Computational Materials Discovery
      • First-principles calculations of alloy phase diagrams using Machine Learning
      • Prediction of chemical reaction rates using Machine Learning
      • Modelling cathodes using Machine Learning
    • Machine Learning for Elastic Strain Engineering
    • Atomistic-to-Continuum Coupling
    • List of Publications
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News and Events

  • Patent is published

    April 16, 2020
  • RFBF grant: Machine learning the thermodynamics of complex materials with ab initio accuracy

    February 5, 2020
  • Our paper is on the cover of Journal of Chemical Physics issue

    December 14, 2019
  • Konstantin Gubaev defense

    October 2, 2019
  • MSc student defenses

    June 24, 2019

Our paper is in the top-cited list of Journal of Chemical Physics

21/05/2020

Our article “Machine learning of molecular properties: Locality and active learning” (K. Gubaev, E. V. Podryabinkin, and Alexander V. Shapeev) has appeared in the list of the top-cited papers of The Journal of Chemical Physics.

Top-cited papers list

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