Unified thermodynamic modeling of adsorption and London dispersive surface energy on Rh-modified H-β zeolite: Coupled effects of temperature, metal loading, and specific surface area

A comprehensive thermomechanical and electronic characterization of solvent adsorption on Rh-modified H-β zeolite was performed using inverse gas chromatography. The adsorbed molecular surface area and the London dispersive surface energy were quantified as functions of temperature, Rh loading ( ), and specific surface area ( ). A unified second-order bivariate model was developed, enabling direct extraction of the temperature derivatives, cross-coupling terms, and structural sensitivity coefficients for every system. The results show that Rh loading enhances the electronic polarizability density of the zeolite surface, leading to increased and amplified temperature sensitivity through negative dispersive surface entropy . Moderate Rh content (0.5–1 wt%) maximizes the adsorbed molecular footprint due to cooperative strengthening of dispersion interactions without excessive pore blocking. In contrast, variations in act primarily through geometric effects: high decreases due to polarizability dilution but significantly increases the adsorbed footprint by reducing confinement and allowing greater molecular deformation with temperature. Comparison of Rh and models demonstrates that adsorption on Rh/H-β-zeolites is governed by two independent mechanisms: electronic enrichment ( -dependent) and geometric deconfinement ( -dependent). Their interplay determines both interaction strength and conformational freedom of adsorbed molecules. This unified framework provides fundamental insight into adsorption thermodynamics on metal-modified zeolites and offers predictive design rules for optimizing catalysts, sorbents, and surface-engineered porous materials. • Unified model links and separation distance to T , Rh loading, and surface area. • Two Rh regimes identified from thermomechanical adsorption behavior. • Anharmonicity drives thermal expansion despite negative linear terms. • shows coupled dependence on temperature, Rh content, and texture. • Framework enables predictive modeling of adsorption on metal-zeolites.