期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 113, 期 30, 页码 8368-8373出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1602375113
关键词
water structure; van der Waals interactions; neural network potentials; ab initio liquid water; density-functional theory
资金
- Cluster of Excellence RESOLV (Ruhr Explores Solvation) - Deutsche Forschungsgemeinschaft (DFG) [EXC 1069]
- DFG [Be3264/3-1, Be3264/6-1, Be3264/5-1]
- Studienstiftung des Deutschen Volkes
- Ruhr-University Research School Plus (DFG GSC) [98/3]
- VSC Research Center - Austrian Federal Ministry of Science, Research and Economy (bmwfw)
- Austrian Science Fund (FWF) [P24681-N20, SFB Vicom, F41]
- Austrian Science Fund (FWF) [P24681] Funding Source: Austrian Science Fund (FWF)
Whereas the interactions between water molecules are dominated by strongly directional hydrogen bonds (HBs), it was recently proposed that relatively weak, isotropic van der Waals (vdW) forces are essential for understanding the properties of liquid water and ice. This insight was derived from ab initio computer simulations, which provide an unbiased description of water at the atomic level and yield information on the underlying molecular forces. However, the high computational cost of such simulations prevents the systematic investigation of the influence of vdW forces on the thermodynamic anomalies of water. Here, we develop efficient ab initio-quality neural network potentials and use them to demonstrate that vdW interactions are crucial for the formation of water's density maximum and its negative volume of melting. Both phenomena can be explained by the flexibility of the HB network, which is the result of a delicate balance of weak vdW forces, causing, e.g., a pronounced expansion of the second solvation shell upon cooling that induces the density maximum.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据