Prediction of Vapor-Liquid Equilibrium for Aqueous Solutions of Electrolytes Using Artificial Neural Networks

2008 ◽  
Vol 8 (4) ◽  
pp. 615-621 ◽  
Author(s):  
A. Ghaemi ◽  
Sh. Shahhosein ◽  
M. Ghannadi M ◽  
M. Farrokhi
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Aqueous Solutions ◽  
Liquid Equilibrium ◽  
Vapor Liquid Equilibrium ◽  
Solutions Of Electrolytes ◽  
Artificial Neural ◽  
Vapor Liquid

scholarly journals Experimental and an electrolyte non-random two-liquid model to predict the vapor–liquid equilibrium of CO2 in aqueous solutions of diethylenetriamine

2020 ◽  
pp. 174751982096417
Author(s):  
Ruilei Zhang ◽  
Yandong Tang ◽  
Weifeng Shan ◽  
Haijun Liu ◽  
Haijun Li ◽  
...  
Keyword(s):  
Aqueous Solutions ◽  
Saturated Vapor ◽  
Physical Parameters ◽  
Liquid Equilibrium ◽  
Absolute Deviation ◽  
Vapor Liquid Equilibrium ◽  
Liquid Theory ◽  
Equilibrium Data ◽  
Experimental Values ◽  
Vapor Liquid

The absorption and desorption data of CO2 in aqueous solutions with a mass fraction of 10% and 20% of diethylenetriamine are measured at 313.15, 343.15, 373.15, and 393.15 K. The electrolyte non-random two-liquid theory is developed using Aspen V9.0 to correlate and predict the vapor–liquid equilibrium of CO2 in aqueous diethylenetriamine solutions. The model predicted the heat capacity and saturated vapor pressure data of diethylenetriamine, the mixed heat of a diethylenetriamine–H2O binary system, and the vapor–liquid equilibrium data of a diethylenetriamine–H2O–CO2 ternary system. The physical parameters and the interaction parameters of the model system are calculated. The model predicted CO2 solubility showing a 10% average absolute deviation from experimental data. The calculated values of the model are basically consistent with the experimental values.

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