期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 115, 期 20, 页码 E4569-E4576出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1714070115
关键词
autoionization; water; path sampling; machine learning; ab initio molecular dynamics
资金
- Research Council of Norway [237423, 250875]
- Faculty of Natural Sciences and Technology, Norwegian University of Science and Technology (NTNU)
- Norwegian Metacenter for Computational Science (NOTUR)
The pH of liquid water is determined by the infrequent process in which water molecules split into short-lived hydroxide and hydronium ions. This reaction is difficult to probe experimentally and challenging to simulate. One of the open questions is whether the local water structure around a slightly stretched OH bond is actually initiating the eventual breakage of this bond or whether this event is driven by a global ordering that involves many water molecules far away from the reaction center. Here, we investigated the self-ionization of water at room temperature by rare-event ab initio molecular dynamics and obtained autoionization rates and activation energies in good agreement with experiments. Based on the analysis of thousands of molecular trajectories, we identified a couple of local order parameters and show that if a bond stretch occurs when all these parameters are around their ideal range, the chance for the first dissociation step (double-proton jump) increases from 10(-7) to 0.4. Understanding these initiation triggers might ultimately allow the steering of chemical reactions.
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