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  • 标题:Ab initio theory and modeling of water
  • 本地全文:下载
  • 作者:Mohan Chen ; Hsin-Yu Ko ; Hsin-Yu Ko
  • 期刊名称:Proceedings of the National Academy of Sciences
  • 印刷版ISSN:0027-8424
  • 电子版ISSN:1091-6490
  • 出版年度:2017
  • 卷号:114
  • 期号:41
  • 页码:10846-10851
  • DOI:10.1073/pnas.1712499114
  • 语种:English
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:Water is of the utmost importance for life and technology. However, a genuinely predictive ab initio model of water has eluded scientists. We demonstrate that a fully ab initio approach, relying on the strongly constrained and appropriately normed (SCAN) density functional, provides such a description of water. SCAN accurately describes the balance among covalent bonds, hydrogen bonds, and van der Waals interactions that dictates the structure and dynamics of liquid water. Notably, SCAN captures the density difference between water and ice I h at ambient conditions, as well as many important structural, electronic, and dynamic properties of liquid water. These successful predictions of the versatile SCAN functional open the gates to study complex processes in aqueous phase chemistry and the interactions of water with other materials in an efficient, accurate, and predictive, ab initio manner.
  • 关键词:water ; ab initio theory ; hydrogen bonding ; density functional theory ; molecular dynamics
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