The isobaric phase equilibrium data for the binary systems of ethanol + cyclopentanone, propyl butanoate + 4-methylphenol, and cyclopentanone + propane-1,2-diol at atmospheric pressure were measured using a modified distillation apparatus. The Herington and Van Ness tests were employed to confirm the thermodynamic consistency of the experimental data. In addition, the Wilson, NRTL, and UNIQUAC models were used to correlate experimental vapor–liquid equilibrium data. The corresponding binary interaction parameters (BIPs) for the three models, which are useful for the modeling and designing separation processes involving biofuel, were obtained using a maximum likelihood objective function. It has been confirmed that when appropriate BIPs are used in each model, the outputs are consistent with each other and with experimental data.

Process modeling and feasibility studies for biofuel production require accurate phase equilibria data. Binary mixtures of common biofuel compounds butan-2-one + 2-methylpropan-1-ol, butan-2-one + cyclopentanone, 2-methylpropan-1-ol + cyclopentanone, and a ternary system of all three components were studied to obtain vapor−liquid equilibrium data at atmospheric pressure. The experimental data were validated and verified thermodynamically by employing the modified McDermott−Ellis, Van Ness, and Herington methods. The binary vapor−liquid equilibrium (VLE) data were successfully correlated with the Wilson, NRTL, and UNIQUAC activity coefficient models and predicted with the PSRK model. Further, the PSRK model and NRTL with the obtained binary interaction parameter (BIP) model were applied to forecast VLE data for the ternary system of butan-2-one + 2methylpropan-1-ol + cyclopentanone. Both PSRK and NRTL models showed good accuracy in predicting the equilibrium temperature. At the same time, the PSRK model outperformed the NRTL model in predicting the composition of the vapor phase. The PSRK model was quite accurate for predicting the VLE of these biofuel components, even without any experimental data.

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