Experimental Studies of Surface Tensions for Binary and Ternary Systems of Benzyl Alcohol, N-Hexanol and Water. Modeling with Neural Networks

The design of installations in the chemical industry requires knowledge of the thermodynamic properties of liquid mixtures. In the absence of experimental data, accurate predictive methods are needed. In this work, the refractive index and the surface tension are experimentally determined at different temperatures and atmospheric pressure, for the binary and ternary systems of benzyl alcohol, n-hexanol and water, less studied in the literature. Two models were developed for the correlation of excess surface tension with composition, normalized temperature and refractive index. The statistical processing of the experimental data with the multiple linear regression method allowed the development of a model for which, in the validation stage, the correlation coefficient was 0.9086 and the standard deviation was 4.36. With the best performing neural model, a correlation coefficient of 0.9727 and a standard deviation of 2.14 were obtained in the validation stage.