Contents lists available at ScienceDirect Fuel journal homepage: www.elsevier.com/locate/fuel Full Length Article Towards estimating surface tension of biodiesels: Application to thermodynamic and intelligent modeling Yan Cao a, ⁎ , Jiang Du a , Yu Bai a , Mahdi Ghadiri b,c, ⁎ , Samira Mohammadinia d a School of Mechatronic Engineering and Shaanxi Key Laboratory of Non-Traditional Machining, Xian Technological University, Xian 710021, China b Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam c The Faculty of Environment and Chemical Engineering, Duy Tan University, Da Nang 550000, Vietnam d Chemical Engineering Department, Islamic Azad University, Mahshahr, Iran GRAPHICAL ABSTRACT ARTICLE INFO Keywords: Surface tension Fatty acid esters Biodiesel Artificial intelligence Sensitivity analysis ABSTRACT Recently, increasing demands for energy accelerates the study on renewable energy resources so biodiesels become one of interesting topics for the researchers. Due to wide and user-friend applications of artificial in- telligence methods, in this study, an artificial intelligence method based on support vector machine algorithm optimized by Grey wolf optimization algorithm is suggested to estimate the surface tension of biodiesels. To this end, the experimental surface tension dataset has been collected and divided into two datasets of 59 and 19 points for training and testing randomly. After various comparisons with the real surface tension dataset for the proposed artificial intelligence method, three existing models including UNIFAC, Kay and Dalton models have been participated in the comparisons. The determined R-squared values for Kay, Dalton, UNIFAC, and support vector machine are 0.627, 0.6462, 0.8483, and 0.9905, respectively. According to these results, developed model is the best predictive tool for calculation of surface tension of biodiesels. Additionally, the accuracy of biodiesel surface tension databank has been investigated. On the other hand, the impacts of contributed vari- ables in the models on surface tension of biodiesel fuels have been investigated as an another novel point. It explains that the heaviest fractions have been known as the most effective variables on determination of surface tension of biodiesels. Therefore, this study involves a novel and accurate tool for prediction of surface tension of biodiesels and also sensitivity analysis on effective parameters to help researchers in production of cleaner fuels. https://doi.org/10.1016/j.fuel.2020.118797 Received 12 April 2020; Received in revised form 17 June 2020; Accepted 21 July 2020 ⁎ Corresponding authors. E-mail addresses: caoyan@xatu.edu.cn (Y. Cao), mahdighadiri@duytan.edu.vn (M. Ghadiri). Fuel 283 (2021) 118797 0016-2361/ © 2020 Elsevier Ltd. All rights reserved. T