پديدآورندگان :
Khashei Fatemeh f.khashee@yahoo.com Department of Physical Chemistry, University of Isfahan, Isfahan, Iran; , Daneshvar Azadeh Faculty of Chemistry, Department of Physical Chemistry, University of Isfahan, Isfahan, Iran , Moosavi Majid Faculty of Chemistry, Department of Physical Chemistry, University of Isfahan, Isfahan, Iran
كليدواژه :
Dicationic ionic liquid , Viscosity , Shear rate , Artificial neural network
چكيده فارسي :
In this work, the viscosity of three imidazolium-based dicationic ionic liquids with short alkyl chain length have been measured at different temperatures and shear rates. An artificial neural network method has been developed to model simultaneously the shear-, temperature-, and the number of carbons in alkyl chain of cation dependencies of the viscosities in the studied dicationic ionic liquids. Total number of experimental data used to design the stated network were 546 data points. The results show that the optimal number of neurons in the hidden layer was 18 and the best network topology was obtained as (3-18-1).
