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首页> 外文期刊>International Journal of Heat and Mass Transfer >Modeling heat capacity of ionic liquids using group method of data handling: A hybrid and structure-based approach
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Modeling heat capacity of ionic liquids using group method of data handling: A hybrid and structure-based approach

机译：使用分组数据处理方法对离子液体的热容量进行建模：基于结构的混合方法

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摘要

Ionic liquids (ILs) are a significant class of chemicals with applications in solar cells, sensors, capacitors, batteries, plasticizers and thermal fluids. These compounds have attracted wide attention due to their low vapor pressure, tunable viscosity, non-flammability, wide liquid region phase diagrams and substantial chemical and thermal stability. Moreover, ILs structures can be easily modified leading to highly tunable physicochemical properties, which widen the application of these compounds. Heat capacity of ILs is an essential property for heat transfer evaluation as well as the estimation of widely used thermodynamic properties. Establishing a generalized and accurate model for predicting the heat capacity of ILs is valuable for their further development. In this manuscript, a hybrid group method of data handling (GMDH) was employed to establish a model estimating the ILs heat capacities. The database employed is an all-inclusive source of data taken from NIST standard, which includes the heat capacities of 56 ILs as a function of temperature and four structural parameters. About 80% of the database was assigned for building the model, and the remainder was used for evaluating the model performance. Statistical parameters and graphical techniques revealed that the model developed in this study is very accurate, with an R-2 value of 0.982 and an average absolute percent relative error (AAPRE) of 1.84%. Moreover, the sensitivity analysis showed that the chemical structure of the cation has the highest impact on the heat capacity of ILs. (C) 2018 Elsevier Ltd. All rights reserved.
机译：离子液体（ILs）是一类重要的化学物质，应用于太阳能电池，传感器，电容器，电池，增塑剂和导热液中。这些化合物由于其低蒸气压，可调节的粘度，不易燃性，宽的液相区域相图以及重要的化学和热稳定性而备受关注。此外，IL的结构易于修饰，可产生高度可调节的物理化学性质，从而拓宽了这些化合物的应用范围。 IL的热容是传热评估以及广泛使用的热力学性质评估的基本属性。建立一个通用且准确的模型来预测IL的热容量对于它们的进一步发展是有价值的。在此手稿中，采用数据处理的混合组方法（GMDH）建立估算IL的热容量的模型。所使用的数据库是从NIST标准获取的全面数据来源，其中包括56 ILs的热容随温度的变化和四个结构参数。大约80％的数据库被分配用于构建模型，其余部分用于评估模型性能。统计参数和图形技术表明，本研究开发的模型非常准确，R-2值为0.982，平均绝对相对误差百分比（AAPRE）为1.84％。此外，敏感性分析表明，阳离子的化学结构对离子液体的热容影响最大。 （C）2018 Elsevier Ltd.保留所有权利。

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