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Title
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Phase Equilibrium of Binary System Carbon Dioxide - Methanol at High Pressure Using Artificial Neural Network
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Type
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JournalPaper
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Keywords
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Artificial neural network, Thermodynamic, carbon dioxide, methanol, high pressure
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Abstract
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Interest in supercritical fluids extraction (SFE) is increasing throughout many scientific and industrial fields. The common solvent for use in SFE is carbon dioxide. However, pure carbon dioxide frequently fails to efficiently extract the essential oil from a sample matrix, and modifier fluids such as methanol should be used to enhance extraction yield. A more efficient use of SFE requires quantitative prediction of phase equilibrium of this binary system, carbon dioxide – methanol. The purpose of the current research is modeling carbon dioxide – methanol system using artificial neural network (ANN). Results of ANN modeling has been compared with experimental data as well as thermodynamic equations of state. The comparison shows that the ANN modeling has a higher accuracy than thermodynamic models.
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Researchers
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Tahmasb Hatami (Third Researcher), Afshin Maleki (Fourth Researcher), hiua Daraei (Second Researcher), Fariborz Nasri (First Researcher)
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