Zhuang Bilin, Ramanauskaite Gabriele, Koa Zhao Yuan, Wang Zhen-Gang
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
Yale-NUS College, Singapore 138527, Singapore.
Sci Adv. 2021 Feb 12;7(7). doi: 10.1126/sciadv.abe7275. Print 2021 Feb.
Liquid mixtures are ubiquitous. Miscibility and dielectric constant are fundamental properties that govern the applications of liquid mixtures. However, despite their importance, miscibility is usually predicted qualitatively based on the vaguely defined polarity of the liquids, and the dielectric constant of the mixture is modeled by introducing mixing rules. Here, we develop a first-principles theory for polar liquid mixtures using a statistical field approach, without resorting to mixing rules. With this theory, we obtain simple expressions for the mixture's dielectric constant and free energy of mixing. The dielectric constant predicted by this theory agrees well with measured data for simple binary mixtures. On the basis of the derived free energy of mixing, we can construct a miscibility map in the parameter space of the dielectric constant and molar volume for each liquid. The predicted miscibility shows remarkable agreement with known data, thus providing a quantitative basis for the empirical "like-dissolves-like" rule.
液体混合物无处不在。混溶性和介电常数是决定液体混合物应用的基本性质。然而，尽管它们很重要，但混溶性通常是基于液体模糊定义的极性进行定性预测的，而混合物的介电常数则通过引入混合规则来建模。在这里，我们使用统计场方法为极性液体混合物开发了一种第一性原理理论，而不依赖于混合规则。利用该理论，我们得到了混合物介电常数和混合自由能的简单表达式。该理论预测的介电常数与简单二元混合物的测量数据吻合良好。基于推导出的混合自由能，我们可以在每种液体的介电常数和摩尔体积的参数空间中构建一个混溶图。预测的混溶性与已知数据显示出显著的一致性，从而为经验性的“相似相溶”规则提供了定量依据。
