Formulation and evaluation of a semi-empirical relation for estimating the thermal expansion coefficient of organic liquids

Résumé

The thermal expansion coefficient (α), or thermal expansivity, is a fundamental thermophysical property that quantifies the volumetric response of a liquid to temperature variations. It plays a crucial role in a range of applications, including thermodynamic property estimation, chemical process design, and fluid system calibration. Moreover, it serves as a key parameter in the theoretical computation of various thermodynamic properties within the framework of statistical mechanical theories.  Due to the challenges associated with its experimental determination and the demand for predictive approaches requiring minimal input data, a new semi-empirical relation has been developed for estimating the thermal expansion coefficient in pure organic liquids. The proposed relation was validated across a broad spectrum of polar and nonpolar organic liquids over a range of temperatures. Its performance was benchmarked against existing methods, with the results demonstrating strong agreement with experimental data.  The analysis reveals that equations based on simplified hard-sphere models show significant deviations from experimental values, particularly at higher temperatures, due to their neglect of intermolecular forces and molecular complexity. The Stakhorsky relation provides better estimates but shows increased deviations as temperature rises. The newly proposed equation demonstrates low and consistent deviations across the studied temperature range. The accuracy, stability, and effectiveness of the model can be attributed to the inclusion of the molar volume term in the equation. This indicates the proposed relation’s reliability and practical utility for estimating the thermal expansion coefficient using minimal input data, particularly in situations where experimental data are unavailable. Empirical and semi-empirical relations for estimating thermodynamic properties, such as the thermal expansion coefficient, using minimal input data are especially valuable when experimental data are limited. Additionally, developing simplified relations based on statistical theories offers the advantage of incorporating interaction parameters, which more accurately represent molecular behavior and thereby enhance the reliability of property predictions.