Heat Capacity Prediction of Ionic Liquids Based on Quantum Chemistry Descriptors,Industrial & Engineering Chemistry Research

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Heat Capacity Prediction of Ionic Liquids Based on Quantum Chemistry Descriptors
Industrial & Engineering Chemistry Research ( IF 3.8 ) Pub Date : 2018-11-29 , DOI: 10.1021/acs.iecr.8b03668
Xuejing Kang _{1,

2} , Xinyan Liu ₃ , Jianqing Li ₄ , Yongsheng Zhao ₅ , Hongzhong Zhang _{1,

2}

Affiliation

Heat capacity is an important and fundamental physicochemical property of ionic liquids (ILs). Here, a new class of quantum chemical descriptor, namely electrostatic potential surface area (S_EP) descriptor, is employed to predict the heat capacity of ILs. In this study, 2416 experimental data points (254.0–1805.7 J mol^–1 K^–1) covering a wide temperature range (223.1–663 K) were employed. Multiple linear regression (MLR) and extreme learning machine (ELM) are applied to establish the linear and nonlinear models based on the S_EP descriptors, respectively. The obtained six-parameter models show good predictive performance. The R² of the linear MLR model is 0.988 for the entire set, while the ELM model has a higher value of R² = 0.999, indicating the robustness of the nonlinear model. The results suggest that the S_EP descriptors are closely related to the heat capacity of ILs and can be potentially used to predict the properties of ILs.

中文翻译：

基于量子化学描述子的离子液体热容预测

热容是离子液体（ILs）的重要而基本的理化性质。在这里，一类新的量子化学描述子，即静电势表面积（S _EP）描述子，被用来预测IL的热容。在这项研究中，采用了覆盖广泛温度范围（223.1–663 K）的2416个实验数据点（254.0–1805.7 J mol ^–1 K ^–1）。分别使用多元线性回归（MLR）和极限学习机（ELM）建立基于S _EP描述符的线性和非线性模型。所获得的六参数模型显示出良好的预测性能。的- [R ²整个集合的线性MLR模型的λ值为0.988，而ELM模型的R ²值为0.999较高，表明非线性模型的鲁棒性。结果表明，S _EP描述符与IL的热容密切相关，可潜在地用于预测IL的性质。

更新日期：2018-11-30

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