The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Enhanced Electrocatalytic Reduction of CO2 via Chemical Coupling between Indium Oxide and Reduced Graphene Oxide
Abstract
The chemical coupling interaction has been explored extensively to boost heterogeneous catalysis, but the insight into how chemical coupling interaction works on CO 2 electroreduction remains unclear. Herein we demonstrate how the chemical coupling interaction between porous In 2 O 3 nanobelts and reduced graphene oxide (rGO) could substantially improve the electrocatalytic activity toward CO 2 electroreduction. Such an In 2 O 3 –rGO hybrid catalyst showed 1.4-fold and 3.6-fold enhancements in Faradaic efficiency and specific current density for the formation of formate at −1.2 V versus reversible hydrogen electrode relative to the catalyst prepared by physically loading of In 2 O 3 nanobelts onto rGO, respectively. The density functional theory calculations and electrochemical analysis together revealed that the chemical coupling interaction boosted CO 2 electroreduction activity by improving electrical conductivity and stabilizing key intermediate HCOO –* . The present work not only deepens an understanding of chemical coupling effect but also provides an effective lever to optimize the catalytic performance toward CO 2 electroreduction.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Enhanced electrocatalytic CO2 reduction via field-induced reagent concentration
Liu, M., Pang, Y., Zhang, B., De Luna, P., Voznyy, O., Xu, J., Zheng, X., Dinh, C. T., Fan, F., Cao, C., et al. (2016) · Nature · doi:10.1038/nature19060 · Cited by 2,000
Ionic Liquid–Mediated Selective Conversion of CO 2 to CO at Low Overpotentials
Rosen, B. A., Salehi-Khojin, A., Thorson, M. R., Zhu, W., Whipple, D. T., Kenis, P. J. A., & Masel, R. I. (2011) · Science · doi:10.1126/science.1209786 · Cited by 1,558
Highly selective plasma-activated copper catalysts for carbon dioxide reduction to ethylene
Mistry, H., Varela, A. S., Bonifacio, C. S., Zegkinoglou, I., Sinev, I., Choi, Y.-W., Kisslinger, K., Stach, E. A., Yang, J. C., Strasser, P., et al. (2016) · Nature Communications · doi:10.1038/ncomms12123 · Cited by 1,214
Huang, H., Li, K., Chen, Z., Luo, L., Gu, Y., Zhang, D., Ma, C., Si, R., Yang, J., Peng, Z., et al. (2017) · Journal of the American Chemical Society · doi:10.1021/jacs.7b01036 · Cited by 312
Self-citation
Cited by
Industrial carbon dioxide capture and utilization: state of the art and future challenges
Gao, W., Liang, S., Wang, R., Jiang, Q., Zhang, Y., Zheng, Q., Xie, B., Toe, C. Y., Zhu, X., Wang, J., et al. (2020) · Chemical Society Reviews · doi:10.1039/d0cs00025f · Cited by 1,388
Electrocatalysis for CO 2 conversion: from fundamentals to value-added products
Wang, G., Chen, J., Ding, Y., Cai, P., Yi, L., Li, Y., Tu, C., Hou, Y., Wen, Z., & Dai, L. (2021) · Chemical Society Reviews · doi:10.1039/d0cs00071j · Cited by 1,295
In Situ/Operando Electrocatalyst Characterization by X-ray Absorption Spectroscopy
Timoshenko, J., & Roldan Cuenya, B. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.0c00396 · Cited by 931
Lai, W., Qiao, Y., Zhang, J., Lin, Z., & Huang, H. (2022) · Energy & Environmental Science · doi:10.1039/d2ee00472k · Cited by 373
Self-citationJiang, M., Wang, H., Zhu, M., Luo, X., He, Y., Wang, M., Wu, C., Zhang, L., Li, X., Liao, X., et al. (2024) · Chemical Society Reviews · doi:10.1039/d3cs00857f · Cited by 299
Metadata
- Authors
- Zhang, Z., Ahmad, F., Zhao, W., Yan, W., Zhang, W., Huang, H., Ma, C., & Zeng, J.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-05-28
- Volume
- 19
- Issue
- 6
- Pages
- 4029-4034
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2947463343
- Cited by
- 177
- References
- 4
- FWCI
- 6.13
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Enhanced Electrocatalytic Reduction of CO2 via Chemical Coupling between Indium Oxide and Reduced Graphene Oxide. https://app.cochat.ai/papers/10.1021/acs.nanolett.9b01393
- The paper
- Zhang, Z., Ahmad, F., Zhao, W., Yan, W., Zhang, W., Huang, H., Ma, C., & Zeng, J. (2019). Enhanced Electrocatalytic Reduction of CO2 via Chemical Coupling between Indium Oxide and Reduced Graphene Oxide. Nano Letters. https://doi.org/10.1021/acs.nanolett.9b01393
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.