Journal article
Heat capacity prediction of ionic liquids based on quantum chemistry descriptors
Zhengzhou University of Light Industry1
Department of Chemical and Biochemical Engineering, Technical University of Denmark2
KT Consortium, Department of Chemical and Biochemical Engineering, Technical University of Denmark3
Chinese Academy of Sciences4
University of California at Santa Barbara5
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 (SEP) 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 SEP 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 SEP descriptors are closely related to the heat capacity of ILs and can be potentially used to predict the properties of ILs.
| Language: | English |
|---|---|
| Publisher: | American Chemical Society |
| Year: | 2018 |
| Pages: | 16989-16994 |
| ISSN: | 15205045 and 08885885 |
| Types: | Journal article |
| DOI: | 10.1021/acs.iecr.8b03668 |
| ORCIDs: | 0000-0003-1224-1787 |
