Scale-up study of electrochemical carbon dioxide reduction process through data-driven modelling

Zhang, Guyu, Liu, Xiaoteng, Lei, Hanhui, Wang, Yucheng, Bildan, Denise, Zhuge, Xiangqun, Xing, Lei and Luo, Kun 2024. Scale-up study of electrochemical carbon dioxide reduction process through data-driven modelling. Fuel 373 , 132400. 10.1016/j.fuel.2024.132400

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Abstract

Efficient electrochemical carbon dioxide reduction (eCO2RR) depends on addressing mass transfer kinetics hindering CO2 diffusion to the cathode surface. Gas diffusion electrodes (GDE) have enhanced this process, but the shift from lab-scale research to industrial use is to be explored, and we systematically assessed four variable factors: electrode area, gas flow rate, catalytic layer (CL) thickness and gas diffusion layer (GDL) porosity for scaling-up the electrolyser with a comprehensive two-dimensional physical model was developed to investigate the concentration, distribution, and consumption of CO2. Random Forest (RF) coupled with Latin Hypercube Sampling (LHS) data collection method demonstrate a prediction accuracy of 98.67 % and a RMSE of 0.00058 for the average CO2 concentration. A maximum CO2 consumption rate of 98 % was achieved at a CL thickness of 73 μm and a GDL with a porosity of 0.8, for an electrode area of 100 cm2 and a gas flow rate of 91 mL/min. This high level of CO2 consumption was sustained throughout the scaling-up process, consistently at 96.7 %, as the evidence attests to the reliability and feasibility of the scale-up approach.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Chemistry Cardiff Catalysis Institute (CCI)
Publisher:	Elsevier
ISSN:	0016-2361
Funders:	EPSRC
Date of First Compliant Deposit:	6 August 2024
Date of Acceptance:	2 July 2024
Last Modified:	13 Aug 2024 14:00
URI:	https://orca.cardiff.ac.uk/id/eprint/171217

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