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混合热力学性质对索雷特效应的作用。

Role of mixing thermodynamic properties on the Soret effect.

作者信息

Kiyosawa Tomohiro, Shimizu Masahiro, Matsuoka Jun, Nakashima Kento, Sato Kenzo, Nishi Masayuki, Shimotsuma Yasuhiko, Miura Kiyotaka

机构信息

Department of Material Chemistry, Graduate School of Engineering, Kyoto University, Katsura, Nishikyo-ku, Kyoto 615-8510, Japan.

School of Engineering, The University of Shiga Prefecture, Hikone 522-8533, Japan.

出版信息

J Chem Phys. 2022 Nov 7;157(17):174501. doi: 10.1063/5.0122015.

DOI:10.1063/5.0122015
PMID:36347674
Abstract

We demonstrate that the modified Kempers model, a recently developed theoretical model for the Soret effect in oxide melts, is applicable for predicting the composition dependence of the Soret coefficient in three binary molecular liquids with negative enthalpies of mixing. We compared the theoretical and experimental values for water/ethanol, water/methanol, water/ethylene glycol, water/acetone, and benzene/n-heptane mixtures. In water/ethanol, water/methanol, and water/ethylene glycol, which have negative enthalpies of mixing across the entire mole fraction range, the modified Kempers model successfully predicts the sign change of the Soret coefficient with high accuracy, whereas, in water/acetone and benzene/n-heptane, which have composition ranges with positive enthalpies of mixing, it cannot predict the sign change of the Soret coefficient. These results suggest that the model is applicable in composition ranges with negative enthalpies of mixing and provides a framework for predicting and understanding the Soret effect from the equilibrium thermodynamic properties of mixing, such as the partial molar volume, partial molar enthalpy of mixing, and chemical potential.

摘要

我们证明,改进的肯佩斯模型(一种最近开发的用于描述氧化物熔体中索雷特效应的理论模型)适用于预测三种具有负混合焓的二元分子液体中索雷特系数的组成依赖性。我们比较了水/乙醇、水/甲醇、水/乙二醇、水/丙酮和苯/正庚烷混合物的理论值和实验值。在整个摩尔分数范围内具有负混合焓的水/乙醇、水/甲醇和水/乙二醇中,改进的肯佩斯模型成功地高精度预测了索雷特系数的符号变化,而在具有正混合焓组成范围的水/丙酮和苯/正庚烷中,它无法预测索雷特系数的符号变化。这些结果表明,该模型适用于具有负混合焓的组成范围,并为从混合的平衡热力学性质(如偏摩尔体积、偏摩尔混合焓和化学势)预测和理解索雷特效应提供了一个框架。

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