Sharif Digital Repository

(Liquid + liquid) equilibrium (LLE) data for the ternary systems (heptane + toluene + 1-ethyl-3-methylpyridinium ethylsulfate) and (heptane + benzene + 1-ethyl-3-methylpyridinium ethylsulfate) were measured at T = 298.15 K and atmospheric pressure. The selectivity and aromatic distribution coefficients, calculated from the equilibrium data, were used to determine if this ionic liquid can be used as a potential extracting solvent for the separation of aromatic compounds from heptane. The consistency of tie-line data was ascertained by applying the Othmer-Tobias and Hand equations  

Liquid-liquid equilibrium (LLE) data for the ternary systems (heptane. +. p-xylene. +. 1-ethyl-3-methylpyridinium ethylsulfate) and (n-octane. +. p-xylene. +. 1-ethyl-3-methylpyridinium ethylsulfate) were measured at . T=. 313.15. K and atmospheric pressure. The selectivity and aromatic distribution coefficients, calculated from the equilibrium data, were used to determine if this ionic liquid can be used as a potential extracting solvent for the separation of p-xylene from heptane and n-octane. The consistency of tie-line data was ascertained by applying the Othmer-Tobias and Hand equations  

Absorption of carbon dioxide (CO2) in aqueous solutions can be improved by the addition of other compounds. However, this requires a large amount of equilibrium data for solubility estimation in a wide ranges of temperature, pressure and concentration. In this paper, a model based on an artificial neural network (ANN) was proposed and developed with mixtures containing monoethanolamine (MEA), diethanolamine (DEA), methyldiethanolamine (MDEA), 2-amino-2-methyl-1-propanol (AMP), methanol, triethanolamine (TEA), piperazine (PZ), diisopropanolamine (DIPA) and tetramethylensulfone (TMS) to predict solubility of CO2 in mixed aqueous solution (especially in binary and ternary mixtures) over wide... 

Ionic liquids (ILs) have been considered as a good candidate to be replaced by the conventional solvent in recent years due to their potential consumptions and unique properties. In the present study, artificial neural network was used to predict the ternary viscosity of mixtures containing ILs. A collection of 729 experimental data points were gathered from the previously public shed literatures. Different topologies of a multilayer feed forward artificial neural network (MFFANN) were examined and optimum architecture was determined. Ternary viscosity data from the literature for 5 ILs with 547 data points have been used to train the network. In addition, to differentiate dissimilar...