Scuola Normale Superiore, Piazza Dei Cavalieri 7, I-56126 Pisa, Italy.
Istituto Nazionale di Fisica Nucleare (INFN), Largo Pontecorvo 3, I-56127 Pisa, Italy.
J Chem Theory Comput. 2022 May 10;18(5):3164-3173. doi: 10.1021/acs.jctc.2c00181. Epub 2022 Apr 26.
Ion microsolvation is a basic, yet fundamental, process of ionic solutions underlying many relevant phenomena in either biological or nanotechnological applications, such as solvent reorganization energy, ion transport, catalytic activity, and so on. As a consequence, it is a topic of extensive investigations by various experimental techniques, ranging from X-ray diffraction to NMR relaxation and from calorimetry to vibrational spectroscopy, and theoretical approaches, especially those based on molecular dynamics (MD) simulations. The conventional microscopic view of ion solvation is usually provided by a "static" cluster model representing the first ion-solvent coordination shell. Despite the merits of such a simple model, however, ion coordination in solution should be better regarded as a complex population of dynamically interchanging molecular configurations. Such a more comprehensive view is more subtle to characterize and often elusive to standard approaches. In this work, we report on an effective computational strategy aiming at providing a detailed picture of solvent coordination and exchange around aqua ions, thus including the main structural, thermodynamic, and dynamic properties of ion microsolvation, such as the most probable first-shell complex structures, the corresponding free energies, the interchanging energy barriers, and the solvent-exchange rates. Assuming the solvent coordination number as an effective reaction coordinate and combining MD simulations with enhanced sampling and master-equation approaches, we propose a stochastic model suitable for properly describing, at the same time, the thermodynamics and kinetics of ion-water coordination. The model is successfully tested toward various divalent ions (Ca, Zn, Hg, and Cd) in aqueous solution, considering also the case of a high ionic concentration. Results show a very good agreement with those issuing from brute-force MD simulations, when available, and support the reliable prediction of rare ion-water complexes and slow water exchange rates not easily accessible to usual computational methods.
离子微溶是离子溶液的基本过程，也是许多生物或纳米技术应用中相关现象的基础，例如溶剂重组能、离子输运、催化活性等。因此，它是各种实验技术广泛研究的主题，从 X 射线衍射到 NMR 弛豫，从量热法到振动光谱学，以及理论方法，特别是基于分子动力学（MD）模拟的理论方法。离子溶剂化的传统微观观点通常由代表第一离子-溶剂配位壳的“静态”簇模型提供。然而，尽管这种简单模型具有优点，但是溶液中的离子配位应该被更好地视为动态相互交换的分子构象的复杂群体。这种更全面的观点更难以描述，并且通常难以通过标准方法来实现。在这项工作中，我们报告了一种有效的计算策略，旨在提供围绕水合离子的溶剂配位和交换的详细图像，从而包括离子微溶的主要结构、热力学和动力学性质，例如最可能的第一壳层配合物结构、相应的自由能、相互交换的能量势垒和溶剂交换速率。假设溶剂配位数作为有效反应坐标，并将 MD 模拟与增强采样和主方程方法相结合，我们提出了一种随机模型，该模型适合同时描述离子-水配位的热力学和动力学。该模型成功地应用于各种二价离子（Ca、Zn、Hg 和 Cd）在水溶液中的情况，也考虑了高离子浓度的情况。结果与可用的强力 MD 模拟结果非常吻合，并支持对罕见的离子-水配合物和通常计算方法难以获得的慢速水交换率的可靠预测。
