Neural-network-based molecular dynamics simulations reveal that proton transport in water is doubly gated by sequential hydrogen-bond exchange: Neural network potentials training data

Neural network potentials of an excess proton in bulk water, training data This dataset contains 2188 configurations labeled at two hybrid DFT levels (revPBE0-D3 and B3LYP-D3). The configurations are given as a single XYZ file: configurations.xyz The box dimensions are written in box.txt The energies for all configurations at a given level of theory are written in energies_LEVEL.txt (one configuration per line) The atomic forces for each configuration at a given level of theory are gathered in a XYZ file: forces_LEVEL.xyz The relative displacements of the Wannier centroids, with respect to the closest oxygen atom, for each configuration at a given level of theory, are in the following XYZ file: wannier-centroids-displacements_LEVEL.xyz体相水中过剩质子的神经网络势能训练数据集。本数据集包含2188个构型，均通过两种杂化密度泛函理论（DFT）级别（revPBE0-D3与B3LYP-D3）完成标注。所有构型存储于单个XYZ文件：configurations.xyz。模拟盒的尺寸信息记录于box.txt文件中。特定理论级别下所有构型的能量数据均存储于energies_LEVEL.txt文件中，每行对应一个构型。特定理论级别下每个构型的原子受力数据汇总于XYZ文件forces_LEVEL.xyz内。特定理论级别下每个构型的万尼尔（Wannier）质心相对于最近邻氧原子的相对位移数据，存储于以下XYZ文件：wannier-centroids-displacements_LEVEL.xyz。