Shahid, MM, Abbas, SZ orcid.org/0000-0003-1502-020X, Maqbool, F et al. (3 more authors) (2021) Modeling of sorption enhanced steam methane reforming in an adiabatic packed bed reactor using various CO₂ sorbents. Journal of Environmental Chemical Engineering, 9 (5). 105863. ISSN 2213-3437
Abstract
A 1-D heterogeneous model of sorption-enhanced steam methane reforming (SE-SMR) process in a packed bed reactor consisting of nickel catalyst well mixed with CO₂ sorbent particles is investigated for three types of common sorbents. The performance of SE-SMR process is studied under low medium pressure conditions (3 – 11 bar) to find the optimum operating conditions. Optimal CaO sorption corresponding to 82% CH₄ conversion and 85% H₂ purity is found at 900 K, 3 bar, 3.5 kgm⁻²s⁻¹ and S/C of 3.0. In contrast, lithium zirconate (LZC) and hydrotalcite (HTC) sorbents exhibited best sorptions under the operating conditions of 773 K, 5 bar and S/C of 3 with CH₄ conversion of 91.3% and 55.2%, and H₂ purity of 94.1% and 77.8% respectively. In these conditions, the CH₄ conversion increased by 114%, 111% and 67% compared to the conventional SMR for the processes enhanced by HTC, LZC and CaO sorption respectively.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Sorption-enhanced steam methane reforming; Sorbent; CO₂ capture; Modeling; CH₄ conversion enhancement |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/K000446/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Jun 2021 15:44 |
Last Modified: | 08 Jan 2025 16:00 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.jece.2021.105863 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:175127 |