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Tuning of CO2 Reduction Selectivity on Metal Electrocatalysts
Abstract
Climate change, caused by heavy CO 2 emissions, is driving new demands to alleviate the rising concentration of atmospheric CO 2 levels. Enlightened by the photosynthesis of green plants, photo(electro)chemical catalysis of CO 2 reduction, also known as artificial photosynthesis, is emerged as a promising candidate to address these demands and is widely investigated during the past decade. Among various artificial photosynthetic systems, solar‐driven electrochemical CO 2 reduction is widely recognized to possess high efficiencies and potentials for practical application. The efficient and selective electroreduction of CO 2 is the key to the overall solar‐to‐chemical efficiency of artificial photosynthesis. Recent studies show that various metallic materials possess the capability to play as electrocatalysts for CO 2 reduction. In order to achieve high selectivity for CO 2 reduction products, various efforts are made including studies on electrolytes, crystal facets, oxide‐derived catalysts, electronic and geometric structures, nanostructures, and mesoscale phenomena. In this Review, these methods for tuning the selectivity of CO 2 electrochemical reduction of metallic catalysts are summarized. The challenges and perspectives in this field are also discussed.
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“The larger, less hydrated, cations adsorb easier on the catalyst surface making the potential at the outer Helmholtz plane more positive and thereby reducing the concentration of H + ions and impeding the formation of H2 and CH4.[205,209,211,212,214]”
From Electrochemical CO 2 Reduction into Chemical Feedstocks: From Mechanistic Electrocatalysis Models to System Design (2019) · cites this paper as [211]
In the citing paper
“Moreover, larger cation concentrations can greatly reduce charge transfer resistances by helping to stabilize the *CO2 -anion radical and leading to higher current densities at the same applied potentials.[190,210,211]”
From Electrochemical CO 2 Reduction into Chemical Feedstocks: From Mechanistic Electrocatalysis Models to System Design (2019) · cites this paper as [211]
In the citing paper
“suppress the HER, [205,211]”
From Electrochemical CO 2 Reduction into Chemical Feedstocks: From Mechanistic Electrocatalysis Models to System Design (2019) · cites this paper as [211]
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Metadata
- Authors
- Wang, Y., Liu, J., Wang, Y., Al‐Enizi, A. M., & Zheng, G.
- Affiliations
- Fudan University (CN)
- King Saud University (SA)
- Corresponding author
- Zheng, Gengfeng
- Venue
- Small
- Publisher
- Wiley
- Published
- 2017-09-14
- Volume
- 13
- Issue
- 43
- ISSN
- 1613-6810 (ISSN-L)
- 1613-6829
- OpenAlex
- W2756379113
- Cited by
- 241
- References
- 124
- Citations by year
- 2026: 6 · 2025: 26 · 2024: 19 · 2023: 23 · 2022: 34 · 2021: 42 · 2020: 38 · 2019: 32 · 2018: 20
- FWCI
- 0.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Small (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (21473038, 21773036)
- Science and Technology Commission of Shanghai Municipality (17JC1402000)
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › CO2 Reduction Techniques and Catalysts
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Advanced Photocatalysis Techniques
- Physical Sciences › Chemical Engineering › Catalysis › Catalysts for Methane Reforming
- Keywords
- electrochemical CO2 reduction, product selectivity, artificial photosynthesis, solar-to-chemical energy conversion, crystal facets, electronic structure, geometric structure, nanostructures, electrolyte effects, mesoscale phenomena
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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