Colóquios da Nano – How Machine can help us learn about water: neural networks applied to liquids – Prof. Dr. Alexandre Rocha (IFT/UNESP)

  • Responsável: Pós-graduação em nanociências e materiais avançados
  • Câmpus: Evento Virtual
  • Local: nano.ufabc.edu.br/coloquios
  • Data: 07/10/2021
  • Horário: 16:00 às 18:00
  • Descrição:

    Palestrante: Prof. Dr. Alexandre R. Rocha
    Título: How Machine can help us learn about water: neural networks applied to liquids
    Data: 07/10 às 16h
    Link: https://youtu.be/Trz4v5SAAjA

    Resumo: Water is, undoubtedly, one of the most important substances known. It is a key resource required for the existence of life as we know. Albeit the liquid is formed by a seemingly simple molecule, the interplay between long and short range interactions at the atomic and molecular level leads to a set of properties that make this liquid so unique. In that sense, accurate microscopic theoretical predictions are hard to come by.
    On the one hand, classical force fields used to simulate the dynamics of the liquid, typically require some experimental input. In that sense, they are usually good for computing some physical quantities, while failing in other cases. On the other hand, first principles methods such as density functional theory, are usually limited to small systems and short times scales and good predictive capabilites are hindered by the approximations to the exchange and correlation approximations that are inherent to the method. In this talk I will address some of these issues, and how neural networks fitted on top of accurate density functional calculations can help us understand the properties of bulk water. In particular, I will show how we can obtain force fields that allow us to accurately simulate large systems and long time scales. I will argue that this is extremely important for obtaining good comparison with experimental results.

  • Necessita inscrição: Não
  • Link de divulgação: nano.ufabc.edu.br/coloquios

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