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甲基硫酸酯和对甲苯磺酸酯咪唑鎓离子液体的高压研究。

High-pressure study of the methylsulfate and tosylate imidazolium ionic liquids.

作者信息

Aparicio Santiago, Alcalde Rafael, García Begoña, Leal José M

机构信息

Departamento de Quimica, Universidad de Burgos, 09001 Burgos, Spain.

出版信息

J Phys Chem B. 2009 Apr 23;113(16):5593-606. doi: 10.1021/jp9003467.

Abstract

The considerable interest aroused in recent years by the unique properties and industrial applications of ionic liquids has given rise to the need for a detailed statement of the linkage between their molecular features and the observed macroscopic behavior. A combined experimental/computational approach to the study of ionic liquids is submitted here and applied to the relevant, nonhalogenated ionic liquids 1,3-dimethylimidazolium methylsulfate and 1-ethyl-3-methylimidazolium tosylate. To establish a reliable equation of state pertinent to these fluids, density data over wide pressure (0.1-60 MPa) and temperature (318.15-428.15 K) ranges, along with high pressure (1-70 MPa) viscosities and other selected ambient pressure properties were measured to assemble sufficient experimental information for the seek of predictive models for process design. A computational method based on ab initio and classical molecular dynamics yielded a deal of structural information, borne out by the experimental readings. Likewise, the predictive ability of the force field applied in molecular dynamics simulations was faced with the measured properties. The pictorial description of the selected ionic liquids reached this way may become widespread to other relevant examples in order to infer valuable structure/property relationships.

摘要

近年来,离子液体独特的性质和工业应用引发了人们极大的兴趣,这就需要详细阐述其分子特征与所观察到的宏观行为之间的联系。本文提出了一种结合实验与计算的方法来研究离子液体,并将其应用于相关的非卤化离子液体硫酸甲酯1,3 - 二甲基咪唑鎓和对甲苯磺酸1 - 乙基 - 3 - 甲基咪唑鎓。为了建立适用于这些流体的可靠状态方程,测量了在宽压力(0.1 - 60 MPa)和温度(318.15 - 428.15 K)范围内的密度数据,以及高压(1 - 70 MPa)下的粘度和其他选定的常压性质,以收集足够的实验信息来寻找用于过程设计的预测模型。一种基于从头算和经典分子动力学的计算方法产生了大量的结构信息,这些信息得到了实验数据的证实。同样,分子动力学模拟中应用的力场的预测能力也与测量性质进行了对比。通过这种方式获得的所选离子液体的图像描述可能会推广到其他相关实例,以便推断出有价值的结构/性质关系。

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