Estimation of the Heat Capacity of Ionic Liquids: A Quantitative Structure鈥揚roperty Relationship Approach

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• 作者：Mehdi Sattari ; Farhad Gharagheizi ; Poorandokht Ilani-Kashkouli ; Amir H. Mohammadi ; Deresh Ramjugernath
• 刊名：Industrial & Engineering Chemistry Research
• 出版年：2013
• 出版时间：September 11, 2013
• 年：2013
• 卷：52
• 期：36
• 页码：13217-13221
• 全文大小：306K
• 年卷期：v.52,no.36(September 11, 2013)
• ISSN：1520-5045

文摘

In this paper, a quantitative structure鈥損roperty relationship model is developed using genetic function approximation (GFA) to predict the liquid heat capacity at constant pressure (C_pL) for ionic liquids at atmospheric pressure. The NIST Standard Reference Database was used to prepare a data set of C_pL data consisting of 3726 experimental data points comprised of 82 ionic liquids. The data set was split into two subsets, with 80% of the data used as a training set and 20% as a test set. Instead of using nonlinear modeling like artificial neural networks and a support vector machine, the GFA method was used to determine a model by a binary combination of descriptors rather than using single ones. Statistical analysis of the model shows that it has an overall AARD % of 1.70%, a coefficient of determination (R²) of 0.993, and a root mean square of error of 15.11 J mol^鈥? K^鈥?.