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arXiv 2102.02836physics.chem-ph
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储氢应用中密度泛函预测Potential Energy曲线的性能评价

Assessment of the Performance of Density Functionals for Predicting Potential Energy Curves in Hydrogen Storage Applications

Srimukh Prasad Veccham, Martin Head-Gordon

摘要:

用于建模和模拟的精确计算工具的可用性对于加速发现能够在给定的压力摆动和温度参数下储存氢(H2)的材料至关重要。之前,我们编译了由平衡几何结构组成的H2 Bind 275数据集,并评估了该数据集上55个密度泛函的性能(Veccham,S. P的;海德戈登,M。化学理论计算杂志,2020,16,4963- 4982)。由于计算工具准确模拟整个势能曲线(PEC)至关重要,除了平衡几何形状外,我们还扩展了这个数据集,增加了389个新的数据点,包括沿着78个PEC的两个压缩和三个拉长的几何形状,用于H2结合,形成H2 Bind 78 x7数据集。在这个明显更大和更全面的H2 Bind 78 × 7数据集上评估55个密度泛函的性能,我们已经确定了H2结合应用的最佳性能密度泛函:PBE 0-DH、$ω$ B 97 X-V、$ω$ B 97 M-V和DSD-PBEPBE-D3(BJ)。此外,Hartree Fock交换提高了密度泛函的性能,尽管在整个PEC中并不均匀。我们推荐使用wB 97 X-V和wB 97 M-V密度泛函,因为它们对几何和能量都有很好的性能。此外,我们还确定了B 97 M-V和B 97 M-rV是预测平衡几何下H2结合能的最佳半局域密度泛函。

英文摘要:

The availability of accurate computational tools for modeling and simulation is vital to accelerate the discovery of materials capable of storing hydrogen (H2) under given parameters of pressure swing and temperature. Previously, we compiled the H2Bind275 dataset consisting of equilibrium geometries and assessed the performance of 55 density functionals over this dataset (Veccham, S. P.; Head-Gordon, M. J. Chem. Theory Comput., 2020, 16, 4963--4982). As it is crucial for computational tools to accurately model the entire potential energy curve (PEC), in addition to the equilibrium geometry, we have extended this dataset with 389 new data points to include two compressed and three elongated geometries along 78 PECs for H2 binding, forming the H2Bind78x7 dataset. Assessing the performance of 55 density functionals on this significantly larger and more comprehensive H2Bind78x7 dataset, we have identified the best performing density functionals for H2 binding applications: PBE0-DH, $ω$B97X-V, $ω$B97M-V, and DSD-PBEPBE-D3(BJ). Addition of Hartree Fock exchange improves the performance of density functionals, albeit not uniformly throughout the PEC. We recommend the usage of wB97X-V and wB97M-V density functionals as they give good performance for both geometries and energies. In addition, we have also identified B97M-V and B97M-rV as the best semi-local density functionals for predicting H2 binding energy at its equilibrium geometry.

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