AI 中文总结
研究人员结合原子簇展开机器学习势与增强采样技术，实现了碳酸钙沉淀早期阶段的反应性模拟，揭示了离子聚集与化学反应性在形核早期的紧密耦合关系。
AI 中文摘要
水溶液中碳酸钙的形成是生物矿化和通过矿化碳酸作用进行碳封存的核心过程。在近中性pH条件下，该过程具有高反应性，质子转移介导碳酸根物种之间的相互转化。迄今为止，大多数原子级模拟要么将碳酸根物种形态视为固定不变，要么仅在小簇中考虑质子转移。本文将从头训练的原子簇展开（ACE）机器学习势应用于分子动力学，并结合增强采样技术，实现了在以往难以企及的长度和时间尺度下对碳酸钙沉淀早期阶段的反应性模拟。我们研究了离子对、离子三聚体以及大量离子的集体聚集过程中的质子转移和碳酸根物种形态。对少量离子的模拟表明，离子缔合为质子转移提供了有利途径，促进了碳酸根、碳酸氢根和碳酸之间的相互转化。在多离子体系中，质子转移会随聚集过程自发发生，并且我们观察到模拟过程中物种演变时配位环境发生显著变化。这些结果表明，从溶液中形核的早期阶段，离子聚集与化学反应性可以紧密耦合。
英文摘要
Calcium carbonate formation from aqueous solution is central to biomineralization and to carbon sequestration through mineral carbonation. At near-neutral pH, the process is highly reactive, with proton transfer mediating the interconversion between carbonate species. Most atomistic simulations to date either treat carbonate speciation as fixed or consider proton transfer only in small clusters. Here, we combine an ab initio trained atomic cluster expansion (ACE) machine-learning potential for molecular dynamics with enhanced sampling to enable reactive simulations of the early stages of calcium carbonate precipitation at previously inaccessible length and time scales. We study proton transfer and carbonate speciation in ion pairs and triplets, as well as in the collective aggregation of many ions. Our simulations with few ions show that ion association provides a favorable pathway for proton transfer, facilitating interconversion between carbonate, bicarbonate, and carbonic acid. In many-ion systems, proton transfer occurs spontaneously alongside aggregation, and we observe significant changes in the coordination environments as species evolve during the simulations. These results show that ion aggregation and chemical reactivity can be strongly coupled during the early stages of nucleation from solution.
