Hybrid data-driven and physics-based modeling for viscosity prediction of ionic liquids

作     者：Jing Fan Zhengxing Dai Jian Cao Liwen Mu Xiaoyan Ji Xiaohua Lu 

作者机构：State Key Laboratory of Materials-Oriented and Chemical EngineeringNanjing Tech UniversityNanjing211816China Energy EngineeringDivision of Energy ScienceLulea University of TechnologyLulea97187Sweden 

出 版 物：《Green Energy & Environment》 (绿色能源与环境（英文版）)

年 卷 期：2024年第9卷第12期

页      面：1878-1890页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China(21838004),STINT(CH2019-8287) the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23-1467) the financial support from Horizon-EIC and Pathfinder challenges,Grant Number:101070976 

主　　题：Viscosity Fundamental property Ionic liquids COSMO-RS Machine learning 

摘      要：Viscosity is one of the most important fundamental properties of ***,accurate acquisition of viscosity for ionic liquids(ILs)remains a critical *** this study,an approach integrating prior physical knowledge into the machine learning(ML)model was proposed to predict the viscosity *** method was based on 16 quantum chemical descriptors determined from the first principles calculations and used as the input of the ML models to represent the size,structure,and interactions of the *** strategies based on the residuals of the COSMO-RS model were created as the output of ML,where the strategy directly using experimental data was also studied for *** performance of six ML algorithms was compared in all strategies,and the CatBoost model was identified as the optimal *** strategies employing the relative deviations were superior to that using the absolute deviation,and the relative ratio revealed the systematic prediction error of the COSMO-RS *** CatBoost model based on the relative ratio achieved the highest prediction accuracy on the test set(R^(2)=0.9999,MAE=0.0325),reducing the average absolute relative deviation(AARD)in modeling from 52.45% to 1.54%.Features importance analysis indicated the average energy correction,solvation-free energy,and polarity moment were the key influencing the systematic deviation.