Abstract

The density of binary biofuel mixtures significantly influences fuel properties, directly affecting internal combustion engine performance. This research aims to develop correlational models to calculate densities in binary biofuel mixtures, leveraging the Gibbs energy mixing rule. Two correlation models are proposed: the ideal Gibbs energy mixing rule and the Gibbs energy quadratic mixing rule. These models aim to enhance the cross-interaction of Gibbs energy of activation (ΔG<inf>12</inf>) to improve predictive performance. Importantly, the constants of the existing models are directly related to thermodynamic parameters. To assess the accuracy of the models, observed densities were collected from four different binary systems: biodiesel + diesel, pure fatty acid ethyl ester + alcohol, biodiesel + alcohol, and alcohol binary mixtures, amounting to 2242 data points obtained from the literature. Based on mole fractions, both models were compared to earlier approaches. The examination revealed that the equation formulated by the quadratic mixing rule exhibited heightened precision and efficacy. Our data demonstrate that the extended ΔG<inf>12</inf> provided the most accurate results.