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用于能源应用的晶相离子液体:基于混合基团贡献法的热容预测

Crystal Phase Ionic Liquids for Energy Applications: Heat Capacity Prediction via a Hybrid Group Contribution Approach.

作者信息

Shahin Moh'd Basel, Liaqat Shehzad, Nancarrow Paul, McCormack Sarah J

机构信息

Department of Chemical and Biological Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates.

Department of Civil, Structural and Environmental Engineering, Trinity College Dublin, D02 PN40 Dublin, Ireland.

出版信息

Molecules. 2024 May 3;29(9):2130. doi: 10.3390/molecules29092130.

Abstract

In the selection and design of ionic liquids (ILs) for various applications, including heat transfer fluids, thermal energy storage materials, fuel cells, and solvents for chemical processes, heat capacity is a key thermodynamic property. While several attempts have been made to develop predictive models for the estimation of the heat capacity of ILs in their liquid phase, none so far have been reported for the ILs' solid crystal phase. This is particularly important for applications where ILs will be used for thermal energy storage in the solid phase. For the first time, a model has been developed and used for the prediction of crystal phase heat capacity based on extending and modifying a previously developed hybrid group contribution model (GCM) for liquid phase heat capacity. A comprehensive database of over 5000 data points with 71 unique crystal phase ILs, comprising 42 different cations and 23 different anions, was used for parameterization and testing. This hybrid model takes into account the effect of the anion core, cation core, and subgroups within cations and anions, in addition to the derived indirect parameters that reflect the effects of branching and distribution around the core of the IL. According to the results, the developed GCM can reliably predict the crystal phase heat capacity with a mean absolute percentage error of 6.78%. This study aims to fill this current gap in the literature and to enable the design of ILs for thermal energy storage and other solid phase applications.

摘要

在为包括传热流体、热能存储材料、燃料电池以及化学过程溶剂等各种应用选择和设计离子液体(ILs)时,热容是一项关键的热力学性质。尽管已经进行了几次尝试来开发预测模型以估算离子液体液相的热容,但迄今为止,尚未有关于离子液体固相晶体相热容的预测模型报道。这对于离子液体将用于固相热能存储的应用尤为重要。首次开发了一种基于扩展和修改先前开发的用于液相热容的混合基团贡献模型(GCM)的模型,并将其用于预测晶体相热容。一个包含71种独特晶体相离子液体、超过5000个数据点的综合数据库被用于参数化和测试,该数据库包含42种不同的阳离子和23种不同的阴离子。除了反映离子液体核心周围分支和分布影响的派生间接参数外,这种混合模型还考虑了阴离子核心、阳离子核心以及阳离子和阴离子内子基团的影响。根据结果,所开发的GCM能够可靠地预测晶体相热容,平均绝对百分比误差为6.78%。本研究旨在填补当前文献中的这一空白,并为热能存储和其他固相应用的离子液体设计提供支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66e8/11085896/7bad62baf12e/molecules-29-02130-g001.jpg

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