Sour Gas Sweetening and Ethane/Ethylene Separation

Abstract

Chemical separations are responsible for nearly half of the US industrial energy consumption. The next generation of separation processes will rely on smart materials to greatly relieve this energy expense. This thesis research focuses on two very energy-intensive and large-scale industrial separations: sour gas sweetening and ethane/ethylene separation. Traditionally, gas sweetening has been achieved through amine-based absorption processes to selectively remove H2S and CO2 from CH4. Ethane/ethylene is an even harder mixture since the two molecules have very similar sizes, shapes, and self-interaction strengths. Despite their low relative volatility (1.2-3.0), cryogenic distillation is the most commonly used technique for this separation. Compared to absorption and cryogenic distillation, adsorption allows for better performance control by choosing the right adsorbent. Crystalline materials such as zeolites, that have precisely defined pore structure, exhibit excellent molecular sieving properties. Performance is closely linked to structure; identifying top zeolites from a large pool of available structures (~300) is thus crucial for improving the separation. In this thesis research, molecular modeling is used to identify optimal materials for these two separations. Since the accuracy of predictive molecular simulations is governed by the underlying molecular models, the first objective of this thesis research was to develop improved molecular models for H2S, ethane, and ethylene. A wide variety of properties such as vapor-liquid and solid-vapor equilibria, critical and triple points, vapor pressures, mixture properties, relative permittivities, liquid structure, and diffusion coefficients were studied using molecular simulations to parameterize transferable molecular models for these molecules. These models are designed to strike a very good balance between accuracy of predictions and efficiency of simulations. For some of the zeolites for which experimental data existed in the literature, purely predictive adsorption isotherms agreed quantitatively with the available experiments. A computational screening was then performed for over 300 zeolite structures using tailored molecular simulation protocols and high-performance supercomputers. Optimal zeolites for each of the two applications were identified for a wide range of temperatures, pressures, and mixture compositions. Finally, a brief literature survey of the zeolites that have been synthesized in their all-silica form is presented and syntheses for two of the important target framework types is discussed.