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首页> 外文期刊>Chemical Engineering Science >Estimation of densities of ionic liquids using Patel-Teja equation of state and critical properties determined from group contribution method
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Estimation of densities of ionic liquids using Patel-Teja equation of state and critical properties determined from group contribution method

机译:使用Patel-Teja状态方程和基团贡献法确定的临界特性估算离子液体的密度

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摘要

In this paper, the Valderrama and Robles group contribution model for the critical properties is extended to the prediction of densities of ionic liquids (ILs) at varying temperatures and pressures, where the critical properties of ILs are represented by the modified Lydersen-Joback-Reid group contribution method, and the density is predicted by virtue of the Patel-Teja (PT) equation of state (EOS). The group increments for totally 47 groups with respect to the extended Group Contribution Patel-Teja (GC-PT) model were determined on the basis of experimental density data for 747 pure ILs at atmospheric pressure and ambient temperature. The group increments are suitable for both the GC-PT model and the original Valderrama and Robles model for the density prediction of ILs. The correlation accuracy in terms of overall average absolute relative deviation (AARD) is 4.4% for 918 data points of density at ambient temperature and atmospheric pressure. The applicability of the GC-PT model is justified by predicting the densities of imidazolium-, pyridinium-, and phosphonium-based ILs containing various anions over a wide range of temperatures and pressures and the vapor pressures of five alkylimidazolium-based ILs at varying temperatures, which implied the rationality of the group increments and the critical properties of ILs, as well as the potential uses of the GC-PT model for the thermodynamic modeling of IL-containing systems.
机译:本文将Valderrama和Robles临界特性的贡献模型扩展到预测在不同温度和压力下离子液体(ILs)的密度,其中ILs的临界特性由改进的Lydersen-Joback-Reid表示组贡献法,并通过状态(EOS)的Patel-Teja(PT)预测密度。相对于扩展的Group Contribution Patel-Teja(GC-PT)模型,基于747个纯IL在大气压力和环境温度下的实验密度数据,确定了总共47个组的组增量。组增量适用于GC-PT模型以及原始的Valderrama和Robles模型,用于IL的密度预测。对于环境温度和大气压下的918个数据密度点,根据总体平均绝对相对偏差(AARD)的相关精度为4.4%。通过预测在各种温度和压力范围内包含各种阴离子的咪唑鎓,吡啶鎓和phospho类IL的密度以及五种烷基咪唑鎓类IL在不同温度下的蒸气压,可以证明GC-PT模型的适用性,这暗示了基团增量的合理性和IL的关键性质,以及GC-PT模型在含IL系统的热力学建模中的潜在用途。

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