Symbolic regression corrections added to Peng-Robinson equation-of-state predictions reduce vapor-liquid equilibrium errors for six nitrogen-n-alkane systems, with coefficients interpolated as functions of carbon number.
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Symbolic Machine Learning for Vapor-Liquid Equilibrium Prediction in Cx-N2 Binary Mixtures
Symbolic regression corrections added to Peng-Robinson equation-of-state predictions reduce vapor-liquid equilibrium errors for six nitrogen-n-alkane systems, with coefficients interpolated as functions of carbon number.