TEXTURAL CHARACTERIZATION OF ORDERED MESOPOROUS SILICA MATERIALS WITH CYLINDRICAL PORES FROM N2, Ar AND Kr ADSORPTION ISOTHERMS AT 77 K USING GRAND CANONICAL MONTE CARLO SIMULATION

JHONNY VILLARROEL-ROCHA; RAÚL LÓPEZ; KARIM SAPAG

Baltimore

Congreso; FOA 11, 11th International Conference on the Fundamentals of Adsorption; 2013

International Adsorption Society

Ordered mesoporous materials (OMMs) have played a major role in modern technology because of their chemical, biochemical and environmental applications such as catalyst supports and adsorbents, particularly in reactions involving large molecules [1,2]. In particular, mesoporous silica materials have attracted attention in materials science due to their morphological and textural properties, such as high specific surface area, large pore volumes, narrow pore-size distribution and regular pore structure [3]. In all the applications of these kinds of materials, one of the most important properties to be analyzed is the Pore Size Distribution (PSD), which limits the size of the molecules that can act inside them. To obtain the PSD of different materials two microscopic methods have been recognized, one of them use the Density Functional Theory (DFT method) and the other one is based on the Grand Canonical Monte Carlo ensemble (GCMC). Advances in molecular modeling of adsorption phenomena by means of GCMC simulations have been applied to study several porous carbonaceous materials [4,5,6], but the study for porous silica materials is scarce and null for some gases like Kr. In this work, by experimental adsorption of different gases at 77 K and GCMC simulation it was studied the characterization of OMMs with cylindrical pore geometries like the SBA-15 and MCM-41 [7]. Adsorption-desorption isotherms of nitrogen, argon and krypton at 77 K were measured at sub-atmospheric pressures. In Figure 1 are shown the N2 and Ar adsorption isotherms at 77 K for the SBA-15 sample. A GCMC simulation for the adsorption of different gases on cylindrical pores of silica was used to obtain the kernel (Figure 2) of local isotherms for different pore sizes. The simulated data were adjusted to experimental data to optimize the model. Different textural properties such as specific surface area, micropore volume, total pore volume and pore size distribution were obtained by GCMC and compared with classical models. Finally, the PSDs obtained by GCMC were compared with those obtained by using the DFT method for this kind of materials.