(309g) Monte Carlo and Molecular Dynamics Study of Zeolite-Templated Carbon-Based Membranes for Hydrogen Purification from Steam Methane Reforming

The production and use of hydrogen (H₂) as a means to transport energy, has become increasingly widespread in recent years [1]. The most common industrial method to produce such compound is by steam methane reforming (SMR), where the hydrogen is obtained together with a large amount of CO₂ (which needs to be captured to avoid the large carbon footprint), as well as impurities including mainly carbon monoxide, water vapor, methane, and nitrogen [1].

Separating and reducing the content of impurities is essential for further applications. Such hydrogen purification is usually performed on an industrial scale by a Pressure Swing Adsorption process, typically including the use of several beds operating simultaneously. Nevertheless, membrane-based gas separation technology offers a great advantage because of the differences in the kinetic diameters of the molecules. The purpose is to facilitate the H₂ movement through the membrane while retaining CO₂ and other compounds. Moreover, it has several advantages such as low energy consumption, facile and adaptable operation, and cost-effectiveness [2]. However, there are challenges in tuning the pore structure of the membrane. Among the solid structures, zeolite-templated carbons (ZTCs) are a distinct class of porous framework materials in which a three-dimensional network of pores is contained between atomically thin, polycyclic hydrocarbon walls, synthesized by carbonization within a zeolite template. Such materials are attractive and very versatile, mainly due to their high stability and the possibility of synthesis from widely available and low-cost materials [3].

Knowledge of the molecular behavior is required to design such energy-efficient separation processes in particular the transport properties and the separation selectivity. To make further progress and produce molecular sieve membranes, understanding several issues such as the effect of carbon structure topology and composition, and contaminants effects are needed. In this regard, computational methods have become a standard complementary tool to experiments that can be used to allow an understanding of the microscopic mechanism behind the process [4]. Molecular simulations allow the systematic and controlled study of various relevant variables of the studied system, isolating and quantifying the effect of each of them.

Therefore, this contribution is devoted to molecular simulations on ZTC materials as potential membranes for hydrogen purification. The study has been performed with realistic models, being sufficiently flexible to tune additional parameters such as functionalization in order to reflect specific properties of the material of interest. The link between the texture of carbonaceous materials and the separation properties of the specific material, such as adsorption and diffusion, is far from being straightforward. Therefore, the transport of H_2, CH₄, H₂O, CO₂, and their binary, ternary and quaternary mixtures through carbon-based membranes, is evaluated under different thicknesses, pressure and temperature conditions. Both Grand Canonical Monte Carlo, equilibrium and non-equilibrium Molecular Dynamics techniques were combined to predict diffusion coefficients, density profiles, gas permeabilities and permeation selectivity values, for both single-component and mixtures.

Simulation results demonstrated that the permeation selectivity increases with reducing the pore size distribution of the material (i.e., promising materials found to be AFX-ZTC and BOG-ZTC structures). Furthermore, the selectivities of CH₄-over-H₂ and CO₄-over-H₂ decreased as the temperature was increased, meaning that lower temperature conditions are favorable for hydrogen escape or heavy compound (i.e. carbon dioxide and/or methane) retainment.

We acknowledge support of this work from Khalifa University of Science and Technology through the Research and Innovation Center on CO₂ and Hydrogen, RICH Center (project RCII-2019-007).

References

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[5]. D. Bahamon, L.F. Vega, Langmuir 33 (2017) 11146-11155.