2023 AIChE Annual Meeting
(615b) Comparison of Surface Tension Predictions from Butler’s Method and Classical Density Functional Theory Based on Statistical Associating Fluid Theory
Author
Wang, L. - Presenter, Rice University
Gas-liquid surface tension modeling is essential to the efficient and reliable design of chemical processes. Accurate predictions of surface properties can be challenging, especially due to the presence of highly nonideal interactions (such as hydrogen bonding interactions) among molecules and nonuniform molecular distribution across the interface. In this work, we compare two of the theoretical methods, namely the Butlerâs method and classical density functional theory. Both models rely on Statistical Associating Fluid Theory in the homogenous bulk liquid and gas regions, allowing unbiased comparisons of prediction quality of surface properties.