Skip to main navigation Skip to search Skip to main content

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

Guyu Zhang, Xiaoteng Liu, Hanhui Lei, Yucheng Wang, Denise Bildan, Xiangqun Zhuge, Lei Xing, Kun Luo*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    10 Citations (Scopus)
    24 Downloads (Pure)

    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.
    Original languageEnglish
    Article number132400
    Pages (from-to)1-9
    Number of pages9
    JournalFuel
    Volume373
    Early online date3 Jul 2024
    DOIs
    Publication statusPublished - 1 Oct 2024

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 9 - Industry, Innovation, and Infrastructure
      SDG 9 Industry, Innovation, and Infrastructure
    2. SDG 13 - Climate Action
      SDG 13 Climate Action

    Keywords

    • CO reduction
    • Electrochemical
    • Machine learning
    • Mass transfer
    • Scale-up

    Fingerprint

    Dive into the research topics of 'Scale-up study of electrochemical carbon dioxide reduction process through data-driven modelling'. Together they form a unique fingerprint.

    Cite this