The DOI matches its Crossref record.
Fe‐Doped Ni3C Nanodots in N‐Doped Carbon Nanosheets for Efficient Hydrogen‐Evolution and Oxygen‐Evolution Electrocatalysis
Abstract
Uniform Ni 3 C nanodots dispersed in ultrathin N‐doped carbon nanosheets were successfully prepared by carburization of the two dimensional (2D) nickel cyanide coordination polymer precursors. The Ni 3 C based nanosheets have lateral length of about 200 nm and thickness of 10 nm. When doped with Fe, the Ni 3 C based nanosheets exhibited outstanding electrocatalytic properties for both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). For example, 2 at % Fe (atomic percent) doped Ni 3 C nanosheets depict a low overpotential (292 mV) and a small Tafel slope (41.3 mV dec−1) for HER in KOH solution. An outstanding OER catalytic property is also achieved with a low overpotential of 275 mV and a small Tafel slope of 62 mV dec−1 in KOH solution. Such nanodot‐incorporated 2D hybrid structures can serve as an efficient bifunctional electrocatalyst for overall water splitting.
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
No references could be resolved yet.
Research works printed but not linked: 38
- 10.1002/anie.201502438 · DOI · Paper page
- 10.1002/ange.201502438 · DOI · Paper page
- 10.1039/C6SC02083F · DOI
- 10.1039/C4CC03711A · DOI
- 10.1016/j.ensm.2015.10.004 · doi:10.1016/j.ensm.2015.10.004
- 10.1038/nenergy.2015.27 · DOI · Paper page
- 10.1021/nn505582e · DOI · Paper page
- 10.1016/j.apcata.2015.05.005 · DOI
- 10.1039/C6TA04943E · DOI
- 10.1021/acscatal.6b01951 · DOI
- 10.1016/j.ensm.2016.03.005 · DOI
- 10.1039/C5TA02637G · DOI · Paper page
- 10.1016/j.ensm.2016.10.006 · DOI
- 10.1038/ncomms7430 · DOI · Paper page
- 10.1021/ja405735d · DOI · Paper page
- 10.1021/nn501390j · DOI
- 10.1126/science.1241488 · DOI · Paper page
- 10.1038/ncomms2664 · DOI · Paper page
- 10.1039/c3nr06678a · DOI · Paper page
- 10.1021/ja501520b · DOI · Paper page
- 10.1002/smll.201502106 · DOI · Paper page
- 10.1002/anie.201400294 · DOI · Paper page
- 10.1002/ange.201400294 · DOI
- 10.1016/j.ceramint.2014.11.050 · DOI
- 10.1002/adfm.201505240 · DOI · Paper page
- 10.1039/C1CC15812K · DOI
- 10.1021/acsami.5b06708 · DOI · Paper page
- 10.1002/anie.201602237 · DOI · Paper page
- 10.1002/ange.201602237 · DOI · Paper page
- 10.1021/ja511572q · DOI · Paper page
- 10.1016/j.nanoen.2017.05.044 · DOI · Paper page
- 10.1002/adfm.201600915 · DOI · Paper page
- 10.1039/C6RA02766K · DOI
- 10.1021/acs.chemmater.5b00621 · DOI · Paper page
- 10.1002/anie.201306166 · DOI · Paper page
- 10.1002/ange.201306166 · DOI
- 10.1016/j.ensm.2015.08.001 · DOI
- 10.1021/acsnano.6b06259 · DOI
Cited by
Recent Advances in Electrocatalytic Hydrogen Evolution Using Nanoparticles
Zhu, J., Hu, L., Zhao, P., Lee, L. Y. S., & Wong, K.-Y. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.9b00248 · Cited by 3,133
Anantharaj, S., Kundu, S., & Noda, S. (2021) · Nano Energy · doi:10.1016/j.nanoen.2020.105514 · Cited by 932
Ouyang, T., Ye, Y., Wu, C., Xiao, K., & Liu, Z. (2019) · Angewandte Chemie International Edition · doi:10.1002/anie.201814262 · Cited by 804
Gao, Q., Zhang, W., Shi, Z., Yang, L., & Tang, Y. (2019) · Advanced Materials · doi:10.1002/adma.201802880 · Cited by 734
Zhu, K., Zhu, X., & Yang, W. (2019) · Angewandte Chemie International Edition · doi:10.1002/anie.201802923 · Cited by 721
Metadata
- Authors
- Fan, H., Yu, H., Zhang, Y., Zheng, Y., Luo, Y., Dai, Z., Li, B., Zong, Y., & Yan, Q.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2017-09-05
- Volume
- 56
- Issue
- 41
- Pages
- 12566-12570
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W2746949191
- Cited by
- 387
- References
- 0
- FWCI
- 12.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Funders
- Singapore MOE Tier 1 (2016-T1-002-065, RG113/15)
- Singapore EMA (EIRP 12/NRF2015EWT-EIRP002-008)
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: Fe‐Doped Ni3C Nanodots in N‐Doped Carbon Nanosheets for Efficient Hydrogen‐Evolution and Oxygen‐Evolution Electrocatalysis. https://app.cochat.ai/papers/10.1002/anie.201706610
- The paper
- Fan, H., Yu, H., Zhang, Y., Zheng, Y., Luo, Y., Dai, Z., Li, B., Zong, Y., & Yan, Q. (2017). Fe‐Doped Ni3C Nanodots in N‐Doped Carbon Nanosheets for Efficient Hydrogen‐Evolution and Oxygen‐Evolution Electrocatalysis. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201706610
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.