4.7 Article

Numerical modeling of methane pyrolysis in a bubble column of molten catalysts for clean hydrogen production

Journal

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
Volume 48, Issue 20, Pages 7385-7399

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhydene.2022.11.068

Keywords

Methane pyrolysis; Hydrogen; Molten catalyst; Bubble column reactor; Numerical modeling

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A numerical model of a bubble column reactor (BCR) for methane pyrolysis using molten catalysts was developed and validated. The model accurately predicted methane conversion at different temperatures and column heights and provided detailed information on key phenomena. The proposed model is valuable for reactor optimization and scale-up.
Methane pyrolysis using molten catalysts in a bubble column reactor (BCR) has recently been proposed to produce hydrogen with separable carbon particles as byproducts. In this study, a numerical model of the BCR of molten catalysts for methane pyrolysis was developed and validated using experimental data. Based on a non-isothermal 1-D simplification, continuous liquid and discrete bubble phases were considered by incorporating submodels for bubble behaviors, catalytic and homogeneous reactions, heat/mass transfer, and a submerged orifice for methane supply. The initial bubble diameter was predicted using the correlation derived from measurements. When applied to experiments with Ni(27)Bi(73) and mixtures of KCl-MnCl2, the model accurately reproduced the methane conversion at different temperatures and column heights. Furthermore, detailed information on the key phenomena was acquired, including the profiles of the bubble diameter, rise velocity, reaction rates, temperature, and gas composition. A sensitivity analysis confirmed that the uncertainties regarding the physical properties of molten catalysts had a negligible impact. A comparison of the performances of Ni(27)Bi(73) and KCl(50)MnCl2(50) under the same reaction conditions revealed a favorable influence of the catalyst density on methane conversion because of the increased pressure. The proposed model would be useful in reactor optimization and scale-up with high hydrogen productivity.(c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

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