Effects of interstitial water and alkali cations on the expansion, intercalation potential, and orbital coupling of nickel hexacyanoferrate from first principles
Effects of interstitial water and alkali cations on the expansion, intercalation potential, and orbital coupling of nickel hexacyanoferrate from first principles
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DOI：
10.1063/5.0080547
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发表时间：
2022-03
影响因子：
3.2
通讯作者：
Sizhe Liu;Kyle C. Smith
中科院分区：
文献类型：
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作者：
Sizhe Liu;Kyle C. Smith
普鲁士蓝类似物（PBAs）由于其可逆嵌入一价阳离子的能力而成为一类重要的水溶液电化学分离和能量储存材料。然而，在PBAs的从头算研究中引入间隙分子[分子式：见正文]在技术上是具有挑战性的，尽管对于理解间隙水、间隙阳离子和影响插层电位和阳离子插层选择性的框架晶格之间的相互作用至关重要。因此，我们引入并使用一种方法，该方法将机器学习模型的效率与从头计算的准确性相结合，以阐明（1）不同大小的阳离子嵌入时的晶格膨胀机制，（2）对嵌入大尺寸疏水阳离子的选择性偏差，以及（3）从无水到水合晶格的超导体-导体转变。我们分析PBA六氰合铁酸镍[[式：见正文]]，因为它在含水电解质中具有结构稳定性和电化学活性。在这里，巨势分析用于确定给定插层阳离子（Na[式：见正文]、K[式：见正文]或Cs[式：见正文]）的水合平衡度和[式：见正文]氧化态，基于借助机器学习和模拟退火确定的压力平衡结构。这些结果为未来阳离子嵌入电极材料的合理设计提供了新的方向，这些材料在各种电化学应用中优化了性能，并且它们表明了选择适当的计算框架来准确预测PBA晶格性质的重要性。
Prussian blue analogs (PBAs) are an important material class for aqueous electrochemical separations and energy storage owing to their ability to reversibly intercalate monovalent cations. However, incorporating interstitial [Formula: see text] molecules in the ab initio study of PBAs is technically challenging, though essential to understanding the interactions between interstitial water, interstitial cations, and the framework lattice that affect intercalation potential and cation intercalation selectivity. Accordingly, we introduce and use a method that combines the efficiency of machine-learning models with the accuracy of ab initio calculations to elucidate mechanisms of (1) lattice expansion upon intercalation of cations of different sizes, (2) selectivity bias toward intercalating hydrophobic cations of large size, and (3) semiconductor–conductor transitions from anhydrous to hydrated lattices. We analyze the PBA nickel hexacyanoferrate [[Formula: see text]] due to its structural stability and electrochemical activity in aqueous electrolytes. Here, grand potential analysis is used to determine the equilibrium degree of hydration for a given intercalated cation (Na[Formula: see text], K[Formula: see text], or Cs[Formula: see text]) and [Formula: see text] oxidation state based on pressure-equilibrated structures determined with the aid of machine learning and simulated annealing. The results imply new directions for the rational design of future cation-intercalation electrode materials that optimize performance in various electrochemical applications, and they demonstrate the importance of choosing an appropriate calculation framework to predict the properties of PBA lattices accurately.