Development of artificial neural network models for supercritical fluid solvency in presence of co-solvents

다국어 초록 (Multilingual Abstract)

This paper presents the application of artificial neural networks (ANN) to develop new models of liquidsolvent dissolution of supercritical fluids with solutes in the presence of cosolvents. The neural network model of theliquid solvent dissolution of CO2 was built as a function of pressure, temperature, and concentrations of the solutesand cosolvents. Different experimental measurements of liquid solvent dissolution of supercritical fluids (CO2) withsolutes in the presence of cosolvents were collected. The collected data are divided into two parts. The first part wasused in building the models, and the second part was used to test and validate the developed models against the Peng-Robinson equation of state. The developed ANN models showed high accuracy, within the studied variables range,in predicting the solubility of the 2-naphthol, anthracene, and aspirin in the supercritical fluid in the presence and absenceof co-solvents compared to (EoS). Therefore, the developed ANN models could be considered as a good tool in predictingthe solubility of tested solutes in supercritical fluid.

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