Thermal Conductivity Estimation of Diverse Liquid Aliphatic Oxygen-Containing Organic Compounds Using the Quantitative Structure–Property Relationship Method

• Published in: ACS omega Vol. 5; no. 15; pp. 8534 - 8542
• Main Authors: Lu, Haixia, Liu, Wanqiang, Yang, Fan, Zhou, Hu, Liu, Fengping, Yuan, Hua, Chen, Guanfan, Jiao, Yinchun
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 21-04-2020
• ISSN: 2470-1343; 2470-1343
• DOI: 10.1021/acsomega.9b04190

Thermal conductivity is an essential thermodynamic data in chemical engineering applications. Liquid aliphatic oxygen-containing organic compounds are important organic intermediates and raw materials. As a result, estimating thermal conductivity of liquid aliphatic oxygen-containing organic compounds is of significance in industry production. In this study, the genetic function approximation method was applied to screen descriptors and develop a 6-descriptor linear quantitative structure–property relationship model. The entire data set of these compounds covering 1064 thermal conductivity values was divided into 694-member training set, 298-member test set, and 72-member prediction set. The average absolute relative deviation of the training set, test set, and prediction set were 4.14, 4.41, and 4.16%, respectively. Model validation and Y-randomization test proved that the developed model has goodness-of-fit, predictive power, and robustness. In addition, the applicability domain of the developed model was visualized by the Williams plot. This study can provide a convenient method to estimate the thermal conductivity for researchers in chemical engineering production.