Prediction of osmotic coefficients for ionic liquids in various solvents with artificial neural network

Yu Cao, Shun Yao, Xianlong Wang, Tian Yao, Hang Song

Abstract


The relationship between the structural descriptions and osmotic coefficients of binary mixtures containing sixteen different ionic liquids and seven kinds of solvents has been investigated by back propagation artificial neural network (BP ANN). The influence of temperature for osmotic coefficients was considered and the concentrations of ionic liquids were close to 1mol kg-1 except which in acetonitrile. Multi linear regression (MLR) was used to choose variables for artificial neural network (ANN) model. A three layer BP ANN with seven variables containing structural descriptions of ionic liquids and solvent character was developed as input variable. Compared with experimental data, the calculated osmotic coefficients by ANN model had high squared correlation coefficient (R2) and low root mean squared error (RMSE). 


Keywords


binary mixture; BP ANN; MLR

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DOI: http://dx.doi.org/10.2298/JSC160725013D

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