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离子液体熔点的基团贡献估算：现有模型的关键评估与改进。

Group Contribution Estimation of Ionic Liquid Melting Points: Critical Evaluation and Refinement of Existing Models.

机构信息

Department of Chemical Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates.

Department of Biology, Chemistry and Environmental Sciences, American University of Sharjah, Sharjah 26666, United Arab Emirates.

出版信息

Molecules. 2021 Apr 22;26(9):2454. doi: 10.3390/molecules26092454.

DOI:10.3390/molecules26092454
PMID:33922374
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8122861/
Abstract

While several group contribution method (GCM) models have been developed in recent years for the prediction of ionic liquid (IL) properties, some challenges exist in their effective application. Firstly, the models have been developed and tested based on different datasets; therefore, direct comparison based on reported statistical measures is not reliable. Secondly, many of the existing models are limited in the range of ILs for which they can be used due to the lack of functional group parameters. In this paper, we examine two of the most diverse GCMs for the estimation of IL melting point; a key property in the selection and design of ILs for materials and energy applications. A comprehensive database consisting of over 1300 data points for 933 unique ILs, has been compiled and used to critically evaluate the two GCMs. One of the GCMs has been refined by introducing new functional groups and reparametrized to give improved performance for melting point estimation over a wider range of ILs. This work will aid in the targeted design of ILs for materials and energy applications.

摘要

虽然近年来已经开发出了几种基团贡献方法（GCM）模型来预测离子液体（IL）的性质，但在其有效应用中仍然存在一些挑战。首先，这些模型是基于不同的数据集开发和测试的；因此，基于报告的统计措施进行直接比较是不可靠的。其次，由于缺乏官能团参数，许多现有的模型在其可以使用的 IL 范围上受到限制。在本文中，我们研究了两种最具多样性的 GCM 来估算 IL 的熔点；这是在材料和能源应用中选择和设计 IL 的关键性质。已经编译了一个包含超过 1300 个数据点和 933 个独特 IL 的综合数据库，并用于对这两种 GCM 进行严格评估。通过引入新的官能团和重新参数化，其中一种 GCM 得到了改进，从而在更广泛的 IL 范围内提高了熔点估算的性能。这项工作将有助于有针对性地设计用于材料和能源应用的 IL。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/97c517f817f2/molecules-26-02454-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/4750a225d844/molecules-26-02454-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/6f196bfbb742/molecules-26-02454-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/3ed84c973c54/molecules-26-02454-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/83c5c54f4e85/molecules-26-02454-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/f9bb7f0b479f/molecules-26-02454-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/08aa2ee1089f/molecules-26-02454-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/7ebdda55348a/molecules-26-02454-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/389e1a632a0f/molecules-26-02454-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/97c517f817f2/molecules-26-02454-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/4750a225d844/molecules-26-02454-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/6f196bfbb742/molecules-26-02454-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/3ed84c973c54/molecules-26-02454-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/83c5c54f4e85/molecules-26-02454-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/f9bb7f0b479f/molecules-26-02454-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/08aa2ee1089f/molecules-26-02454-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/7ebdda55348a/molecules-26-02454-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/389e1a632a0f/molecules-26-02454-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce4a/8122861/97c517f817f2/molecules-26-02454-g009.jpg

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