No abstract

Physical adsorption of SO 2 on exfoliated graphite is studied using classical adsorption volumetry and Monte Carlo computer simulations. The experimental isotherms have been obtained in a wide temperature range to determine the critical temperature for the completion of several layers. The computer simulations are in good agreement with the experimental data. The adsorption potential is analyzed and the results are employed to interpret the distributions of adsorbed molecules according to the gas-solid energy. The adsorbed phase exhibits a certain degree of order in an incommensurate phase with respect to the graphite surface. From the simulations, the structure of the adsorbed phase is analyzed, and the unit cell edge length is estimated.

In order to analyze the adsorption capacities of different solid substrates, we present a multi-step method to separately study the isotherm at different pressure ranges (steps). The method is based on simple gas isotherm measurements (nitrogen, methane, carbon dioxide, argon, and oxygen) and is tested to describe the adsorption process and characterize a graphitized surface (GCB) and two different granular activated carbons (GAC). The GCB isotherms are described as a sum of Fowler-Guggenheim-Langmuir shifted curves; isotherm behaviors are quite similar at different temperatures, but change below a certain threshold. In GAC the first steps show the same adsorption characteristics at low pressures (Dubinin's description), but this behavior changes at higher pressure regimes, which allows one to elucidate how heterogeneous the surfaces are or how strong the interactions between adsorbed molecules are for this marginal adsorption to occur. We tested different approaches (from BET multilayer to Aranovich) and found quite different features. We finally conclude that if the description of the adsorption on complex substrates, such as those presented here, is carried using only one model, e. g. Dubinin in case of GACs, the resulting characteristics of the adsorbent would be very biased.