Marianna Yiannourakou, Philippe Ungerer, Benoît Leblanc, Xavier Rozanska, Paul Saxe, S Vidal-Gilbert, F Gouth, F Montel. (2013). Molecular Simulation of Adsorption in Microporous Materials. Oil & Gas Science and Technology – Revue d’IFP Energies Nouvelles, 68(6), 977–994.
This recent paper illustrates the unique capabilities of molecular simulations to treat realistic systems, either with zeolites, carbon nanotubes or naturally occurring materials like coal or kerogen.
The development of industrial software, the decreasing cost of computing time, and the availability of well-tested forcefields make molecular simulation increasingly attractive for chemical engineers. We present here several applications of Monte-Carlo simulation techniques, applied to the adsorption of fluids in microporous solids such as zeolites and model carbons (pores < 2 nm).
Adsorption was computed in the Grand Canonical ensemble with the MedeA-GIBBS software, using energy grids to decrease computing time. MedeA-GIBBS has been used for simulations in the NVT or NPT ensembles to obtain the density and fugacities of fluid phases. Simulation results are compared with experimental pure component isotherms in zeolites (hydrocarbon gases, water, alkanes, aromatics, ethanethiol, etc.), and mixtures (methane-ethane, n-hexane-benzene), over a large range of temperatures. Hexane/benzene selectivity inversions between silicalite and Na-faujasites are well predicted with published forcefields, providing an insight on the underlying mechanisms.
Also, the adsorption isotherms in Na-faujasites for light gases or ethane-thiol are well described. Regarding organic adsorbents, models of mature kerogen or coal were built in agreement with known chemistry of these systems. Obtaining realistic kerogen densities with the simple relaxation approach considered here is encouraging for the investigation of other organic systems. Computing excess sorption curves in qualitative agreement with those recently measured on dry samples of gas shale is also favorable. Although still preliminary, such applications illustrate the strength of molecular modeling in understanding complex systems in conditions where experiments are difficult.