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基于SCAN元广义梯度近似密度泛函的水的状态方程。

Equation of state of water based on the SCAN meta-GGA density functional.

作者信息

Zhao Gang, Shi Shuyi, Xie Huijuan, Xu Qiushuang, Ding Mingcui, Zhao Xuguang, Yan Jinliang, Wang Dehua

机构信息

School of Physics and Optoelectronic Engineering, Ludong University, Yantai 264025, P. R. China.

出版信息

Phys Chem Chem Phys. 2020 Feb 26;22(8):4626-4631. doi: 10.1039/c9cp06362e.

Abstract

Based on the newly developed SCAN meta-GGA and the widely used PBE-GGA functionals, ab initio molecular dynamics are performed on water. It is proved that, although the SCAN meta-GGA is not as good as the TIP4P/2005 model potential in describing the equation of state of water, it is much better than the PBE-GGA, the ST2 model potential, and ab initio trained neural network potentials. Moreover, the SCAN meta-GGA predicts a first-order liquid-liquid transition from high- to low-density water at negative pressure, in which the structures are qualitatively consistent with experimental observations, and the spinodal point of high-density water is very close to Speedy's stability limit line.

摘要

基于新开发的SCAN元广义梯度近似(meta-GGA)和广泛使用的PBE-GGA泛函,对水进行了从头算分子动力学研究。结果表明,虽然SCAN元广义梯度近似在描述水的状态方程方面不如TIP4P/2005模型势,但比PBE-GGA、ST2模型势和从头算训练的神经网络势要好得多。此外,SCAN元广义梯度近似预测在负压下高密度水到低密度水会发生一级液-液转变,其结构在定性上与实验观测结果一致,并且高密度水的旋节线点非常接近斯皮迪(Speedy)稳定性极限线。

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