Using Neural Network Force Fields to Ascertain the Quality of Ab Initio Simulations of Liquid Water

Autor(es)

Torres, Alberto ^[1] ; Pedroza, Luana S. ^[2] ; Fernandez-Serra, Marivi ^[3] ; Rocha, Alexandre R. ^[1]

Afiliação do(s) autor(es)

^[1] Sao Paulo State Univ UNESP, Inst Theoret Phys, BR-01140070 Sao Paulo - Brazil

^[2] Univ Fed ABC, Ctr Ciencias Nat & Humanas, BR-09210580 Santo Andre, SP - Brazil

^[3] SUNY Stony Brook, Stony Brook, NY 11790 - USA

• Tipo de documento: Artigo Científico
• Fonte: Journal of Physical Chemistry B; v. 125, n. 38, p. 10772-10778, SEP 30 2021.
• Citações Web of Science: 0

Resumo

Accurately simulating the properties of bulk water, despite the apparent simplicity of the molecule, is still a challenge. In order to fully understand and reproduce its complex phase diagram, it is necessary to perform simulations at the ab initio level, including quantum mechanical effects both for electrons and nuclei. This comes at a high computational cost, given that the structural and dynamical properties tend to require long timescales and large simulation cells. In this work, we evaluate the errors that density functional theory (DFT)-based simulations routinely incur into due time- and size-scale limitations. These errors are evaluated using neural-network-trained force fields that are accurate at the level of DFT methods. We compare different exchange and correlation potentials for properties of bulk water that require large timescales. We show that structural properties are less dependent on the system size and that dynamical properties such as the diffusion coefficient have a strong dependence on the simulation size and timescale. Our results facilitate comparisons of DFT-based simulation results with experiments and offer a path to discriminate between model and convergence errors in these simulations. (AU)

• Processo FAPESP: 17/02317-2 - Interfaces em materiais: propriedades eletrônicas, magnéticas, estruturais e de transporte
• Beneficiário: Adalberto Fazzio
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 16/01343-7 - ICTP Instituto Sul-Americano para Física Fundamental: um centro regional para física teórica
• Beneficiário: Nathan Jacob Berkovits
• Modalidade de apoio: Auxílio à Pesquisa - Projetos Especiais
• Processo FAPESP: 17/10292-0 - Simulações atomísticas em eletroquímica
• Beneficiário: Luana Sucupira Pedroza
• Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores