A review on catalyst convergence: Unleashing the potential of MXenes for CO2 electrochemical reduction into high-value liquid product

• Published in: Nano materials science 2024-07
• Main Authors: Samia, Jameel, Muhammad Hasnain, Arain, Musfira, Hussain, Iftikhar, Hanif, Muhammad Bilal, Atri, Shalu, Mayzan, Mohd Zul Hilmi, Dai, Haitao
• Format: Article
• Language: English
• Subjects: CO2; Electrochemical reduction; Hydrocarbons fuel; MXene
• ISSN: 2589-9651; 2589-9651
• DOI: 10.1016/j.nanoms.2024.06.006

The electrochemical reduction reaction of carbon dioxide (CO2-ERR) holds tremendous potential as a key approach for achieving carbon neutrality by harnessing renewable resources. However, the current state of CO2-ERR encounters challenges in terms of efficiency and selectivity. Overcoming these obstacles requires the development of a robust electrocatalyst capable of enhancing process efficiency and improving selectivity towards desired products. In recent years, 2D materials have garnered significant attention as efficient catalysts. Among them, MXene stands out of high interest due to unique multilayered structure and presence of surface functional moieties. The MXene material offers high electrical conductivity, versatile surface chemistry, and tunable interface designs. This comprehensive review explores the utilization of MXene-based catalysts for CO2-ERR into valuable products. It covers fundamental aspects of electrochemical conversion, including CO2 adsorption on MXene Ti3C2Tx, the mechanism of CO2-ERR on MXene (Mo2CS2) single-atom catalysts, applications, synthesis methods of MXene production, and future prospects. Additionally, the review highlights the significance of modern artificial intelligence techniques, particularly machine learning, in screening and activating CO2, making it a pioneering scientific endeavor. [Display omitted] •CO2 electro-reduction is a practical solution for greenhouse challenges.•MXene's modifiable features and adaptable gaps make it versatile for electrochemical applications.•MXene nanosheets with modified surfaces enhance electrochemical CO2 reduction efficiency.•The Ti3C2Tx ​adsorbent shows high CO2 selectivity over N2, indicating its potential as a CO2 conversion catalyst.•Machine learning is used in CO2-ERR ​research on MXene electrocatalysts to improve cost and time efficiency.