Recent advances in electrochemical CO2 reaction to C3 + products
One effective strategy for mitigating carbon emissions is utilizing carbon dioxide as a substrate to synthesize high-value multi-carbon products through the electrochemical CO2 reduction reaction (CO2RR). Despite the widespread application of C3+ oxygenated hydrocarbons, including propanol, acetone,...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | Next Materials |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949822825002904 |
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| Summary: | One effective strategy for mitigating carbon emissions is utilizing carbon dioxide as a substrate to synthesize high-value multi-carbon products through the electrochemical CO2 reduction reaction (CO2RR). Despite the widespread application of C3+ oxygenated hydrocarbons, including propanol, acetone, and butanol, in numerous industrial chemical processes, the literature provides scant reporting on their role in electrochemical CO2 reduction reactions. In this review, the reaction mechanisms specific to predominant C3 products are analyzed in detail. Subsequently, we outline advancements concerning three distinct variants of Cu-based catalysts, namely 1) Cu oxide-derived catalysts, 2) Cu nanoparticle catalysts, and 3) Cu single atoms and molecular Cu catalysts. Meanwhile, the feasibility of designing copper-based tandem catalytic systems to produce C3+ products in CO₂RR is also discussed. Additionally, the review explores the emergence of non-Cu-based catalysts, particularly nickel (Ni)- and molybdenum (Mo)-based transition-metal phosphides and chalcogenides. These systems, with the characterization of high catalytic efficiency, excellent stability and low cost, provide sustainable and economical alternatives. The integration of such catalysis offers promising solutions to overcome existing limitations, paving the way for efficient, scalable, and sustainable CO2RR technologies. Besides artificial intelligence (AI) and machine learning (ML) combined with DFT and high-throughput (HT) experiments, as a new paradigm shift in data-driven catalyst exploration, this review addressed some promising recent work for catalysts to yield C3+ products from CO2RR on that edge. |
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| ISSN: | 2949-8228 |