A Density-Functional Theory-Based Neural Network Potential for Water Clusters Including van der Waals Corrections
A Density-Functional Theory-Based Neural Network Potential for Water Clusters Including van der Waals Corrections
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DOI：
10.1021/jp401225b
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发表时间：
2013-08-15
影响因子：
2.9
通讯作者：
Behler, Joerg
中科院分区：
文献类型：
--
作者：
Morawietz, Tobias;Behler, Joerg
水对于许多化学过程的根本重要性促使人们开发出无数高效但近似的水势，用于大规模分子动力学模拟，从简单的经验力场到非常复杂的灵活水模型。准确且普遍适用的水势应满足许多要求。它们应该具有接近量子化学方法的质量，它们应该明确依赖于所有自由度，包括所有相关的多体相互作用，并且它们应该能够描述分子解离和重组。在这项工作中，我们提出了一种基于密度泛函理论 (DFT) 计算的水团簇的高维神经网络 (NN) 潜力，该网络是使用包含多达 10 个单体的分散体构建的，原则上能够满足所有这些要求。我们使用两种常用的广义梯度近似 (GGA) 交换相关函数 PBE 和 RPBE 作为参考方法来研究特定参数化的可靠性。我们发现，神经网络势相对于 DFT 的结合能误差明显低于由于交换相关函数的选择而产生的 DFT 计算的典型不确定性。此外，我们还研究了范德华相互作用的作用，而 GGA 泛函并未正确描述范德华相互作用。具体来说，我们将 Grimme (J. Chem. Phys. 2010, 132, 154104) 建议的 D3 方案纳入我们的势中，并证明它可以以与 DFT 计算相同的方式应用于基于 GGA 的 NN 势，无需修改。我们的结果表明，如果包含范德华相互作用，RPBE 泛函提供的小水簇的描述会显着改善，而众所周知，PBE 泛函产生的结合力比 RPBE 更强，范德华校正会导致结合能被高估。
The fundamental importance of water for many chemical processes has motivated the development of countless efficient but approximate water potentials for large-scale molecular dynamics simulations, from simple empirical force fields to very sophisticated flexible water models. Accurate and generally applicable water potentials should fulfill a number of requirements. They should have a quality close to quantum chemical methods, they should explicitly depend on all degrees of freedom including all relevant many-body interactions, and they should be able to describe molecular dissociation and recombination. In this work, we present a high-dimensional neural network (NN) potential for water clusters based on density-functional theory (DFT) calculations, which is constructed using dusters containing up to 10 monomers and is in principle able to meet all these requirements. We investigate the reliability of specific parametrizations employing two frequently used generalized gradient approximation (GGA) exchange-correlation functionals, PBE and RPBE, as reference methods. We find that the binding energy errors of the NN potentials with respect to DFT are significantly lower than the typical uncertainties of DFT calculations arising from the choice of the exchange-correlation functional. Further, we examine the role of van der Waals interactions, which are not properly described by GGA functionals. Specifically, we incorporate the D3 scheme suggested by Grimme (J. Chem. Phys. 2010, 132, 154104) in our potentials and demonstrate that it can be applied to GGA-based NN potentials in the same way as to DFT calculations without modification. Our results show that the description of small water clusters provided by the RPBE functional is significantly improved if van der Waals interactions are included, while in case of the PBE functional, which is well-known to yield stronger binding than RPBE, van der Waals corrections lead to overestimated binding energies.