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Modeling photocatalytic conversion of carbon dioxide in bubbling twin reactor

Chu, Fengming; Li, Shang; Chen, Huiyao; Yang, Lijun; Ola, Oluwafunmilola; Maroto-Valer, Mercedes; Du, Xiaoze; Yang, Yongping

Authors

Fengming Chu

Shang Li

Huiyao Chen

Lijun Yang

OLUWAFUNMILOLA OLA Oluwafunmilola.Ola@nottingham.ac.uk
Assistant Professor in Materials Engineering

Mercedes Maroto-Valer

Xiaoze Du

Yongping Yang



Abstract

The production of valued added fuels and chemicals via photocatalytic carbon dioxide reduction has attracted increasing attentions in recent years. Based on the traditional twin reactor configuration, a novel bubbling twin reactor is proposed to improve the conversion of carbon dioxide to methanol in this work. The multiphysical model for the bubbling twin reactor is developed and numerically simulated. The variations of the methanol production with the gas inlet flow velocity and gas inlet number are obtained. The results show that the bubbling twin reactor has a higher carbon dioxide conversion efficiency than the traditional one. Moreover, the methanol production subsequently increases as the gas inlet velocity increases. With the constant inlet gas volumetric flow rate, the production of methanol can be improved by increasing the gas inlet number.

Journal Article Type Article
Acceptance Date Jul 23, 2017
Online Publication Date Jul 29, 2017
Publication Date 2017-10
Deposit Date May 4, 2020
Journal Energy Conversion and Management
Print ISSN 0196-8904
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 149
Pages 514-525
DOI https://doi.org/10.1016/j.enconman.2017.07.049
Public URL https://nottingham-repository.worktribe.com/output/4380972
Publisher URL https://www.sciencedirect.com/science/article/pii/S0196890417306854
Additional Information This article is maintained by: Elsevier; Article Title: Modeling photocatalytic conversion of carbon dioxide in bubbling twin reactor; Journal Title: Energy Conversion and Management; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.enconman.2017.07.049; Content Type: article; Copyright: © 2017 Elsevier Ltd. All rights reserved.