INVESTIGATION OF THE RELATIONSHIP BETWEEN INTERMOLECULAR INTERACTIONS AND COMPOSITION-DEPENDENCE OF VISCOSITY IN BINARY MIXTURES OF 1-BUTYL-3- METHYLIMIDAZOLIUM HEXAFLUOROPHOSPHATE AND SOME ALCOHOLS

In this work, the viscosity of four different binary mixtures of 1-butyl-3-methylimidazolium tetrafuoroburate and poly ethylene glycol with average molecular weights of 200, 400, 600 and 1000 have been measured at different compositions, temperatures and shear rates. An artificial neural network method has been developed to model simultaneously the shear-, temperature-, composition- and average molecular weight of poly ethylene glycol dependencies of the viscosities in the studied mixtures. Total number of experimental data used to design the stated network were 615 data points. The results show that the optimal number of neurons in the hidden layer was 24 and the best network topology was obtained as (4-24-1).