基于元动力学与机器学习分子动力学模拟的CaCl$_2$水系电解质溶剂化结构及离子动力学研究
Solvation Structures and Ion Dynamics of CaCl$_2$ Aqueous Electrolytes Using Metadynamics and Machine Learning Molecular Dynamics Simulations
AI总结：
本研究结合从头算与深度学习势分子动力学模拟，揭示CaCl₂水系电解质中Ca²⁺周围多种溶剂化结构共存的规律，明确离子配对对溶剂化水及离子动力学的影响，且模拟扩散系数与实验一致。
摘要：
本研究采用从头算分子动力学模拟与基于深度学习势的分子动力学模拟，探究了CaCl$_2$水系电解质的溶剂化结构与离子动力学。研究发现，Ca$^{2+}$离子周围可共存多种溶剂化结构，包括完全水合的单个Ca$^{2+}$离子、Ca-Cl接触离子对以及Ca-2Cl桥连离子对。离子配对状态对溶剂化壳层中水分子的平移与取向分布具有重要作用，且Ca$^{2+}$离子引发的局部有序性可延伸至第二溶剂化壳层。此外，研究发现溶剂化壳层中水分子的寿命对离子配对状态较为敏感。基于深度学习势的分子动力学模拟计算得到的离子与水分子自扩散系数，与实验测量结果吻合良好。最后，本研究通过分析角度概率分布直方图与van Hove关联函数，阐明了Ca$^{2+}$离子动力学在不同状态间的转变机制。
英文摘要：
The solvation structures and ion dynamics of CaCl$_2$ aqueous electrolytes have been investigated using ab initio molecular dynamics simulations and molecular dynamics simulations with deep learning potentials. We found multiple solvation structures around the Ca$^{2+}$ ion, including fully hydrated single Ca$^{2+}$ ion, Ca-Cl contact ion pair, and Ca-2Cl bridged ion pair, could coexist. The ion-pairing condition plays an important role in the translational and orientational distribution of water molecules in the solvation shell. And the local ordering introduced by the Ca$^{2+}$ ion can extend to the second solvation shell. Furthermore, we found the lifetime of water molecules in the solvation shell is sensitive to the ion-pairing conditions. The self-diffusivities of ions and water molecules, as calculated in molecular dynamics simulations with deep learning potentials, are in good agreement with experimental measurements. Finally, we elucidate the transition of Ca$^{2+}$ ion dynamics between different regimes by analyzing angle probability distribution histograms and van Hove correlation function.
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