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Modeling of CO2 absorbtion by amino acid salts blended with amine solutions

ABSTRACT In this work, the goal is modeling of carbon dioxide loading capacities by exploiting artificial neural network model in two applicable amino acid salt solutions blended with amine solutions as an additive in wide ranges of temperature and pressure. In this regard a group of 740 experimental data points for CO2 loading capacity has been collected from recent literature work. Results of a developed network show the good capability to predict CO2 loading capacity in solutions with Average Relative Deviation equal to 3.8608, Mean Square Error value of 0.0045 and correlation coefficient equal to 0.9976.