The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Nitrogen-Doped Graphene and Its Iron-Based Composite As Efficient Electrocatalysts for Oxygen Reduction Reaction
Open accessAbstract
The high cost of platinum-based electrocatalysts for the oxygen reduction reaction (ORR) has hindered the practical application of fuel cells. Thanks to its unique chemical and structural properties, nitrogen-doped graphene (NG) is among the most promising metal-free catalysts for replacing platinum. In this work, we have developed a cost-effective synthesis of NG by using cyanamide as a nitrogen source and graphene oxide as a precursor, which led to high and controllable nitrogen contents (4.0% to 12.0%) after pyrolysis. NG thermally treated at 900 °C shows a stable methanol crossover effect, high current density (6.67 mA cm(-2)), and durability (∼87% after 10,000 cycles) when catalyzing ORR in alkaline solution. Further, iron (Fe) nanoparticles could be incorporated into NG with the aid of Fe(III) chloride in the synthetic process. This allows one to examine the influence of non-noble metals on the electrocatalytic performance. Remarkably, we found that NG supported with 5 wt % Fe nanoparticles displayed an excellent methanol crossover effect and high current density (8.20 mA cm(-2)) in an alkaline solution. Moreover, Fe-incorporated NG showed almost four-electron transfer processes and superior stability in both alkaline (∼94%) and acidic (∼85%) solutions, which outperformed the platinum and NG-based catalysts.
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
Superior Thermal Conductivity of Single-Layer Graphene
Balandin, A. A., Ghosh, S., Bao, W., Calizo, I., Teweldebrhan, D., Miao, F., & Lau, C. N. (2008) · Nano Letters · doi:10.1021/nl0731872 · Cited by 13,823
High-Performance Electrocatalysts for Oxygen Reduction Derived from Polyaniline, Iron, and Cobalt
Wu, G., More, K. L., Johnston, C. M., & Zelenay, P. (2011) · Science · doi:10.1126/science.1200832 · Cited by 3,984
High oxygen-reduction activity and durability of nitrogen-doped graphene
Geng, D., Chen, Y., Chen, Y., Li, Y., Li, R., Sun, X., Ye, S., & Knights, S. (2011) · Energy & Environmental Science · doi:10.1039/c0ee00326c · Cited by 1,219
Yang, S., Feng, X., Wang, X., & Müllen, K. (2011) · Angewandte Chemie International Edition · doi:10.1002/anie.201100170 · Cited by 1,109
Self-citationShao, Y., Sui, J., Yin, G., & Gao, Y. (2008) · Applied Catalysis B: Environmental · doi:10.1016/j.apcatb.2007.09.047 · Cited by 763
Novel catalyst support materials for PEMfuelcells: current status and future prospects
Shao, Y., Liu, J., Wang, Y., & Lin, Y. (2009) · J. Mater. Chem. · doi:10.1039/b808370c · Cited by 660
Cited by
Electrochemistry of Graphene and Related Materials
Ambrosi, A., Chua, C. K., Bonanni, A., & Pumera, M. (2014) · Chemical Reviews · doi:10.1021/cr500023c · Cited by 1,208
Zhong, H., Wang, J., Zhang, Y., Xu, W., Xing, W., Xu, D., Zhang, Y., & Zhang, X. (2014) · Angewandte Chemie International Edition · doi:10.1002/anie.201408990 · Cited by 938
Wu, G., Santandreu, A., Kellogg, W., Gupta, S., Ogoke, O., Zhang, H., Wang, H.-L., & Dai, L. (2016) · Nano Energy · doi:10.1016/j.nanoen.2015.12.032 · Cited by 744
25th Anniversary Article: Hybrid Nanostructures Based on Two‐Dimensional Nanomaterials
Huang, X., Tan, C., Yin, Z., & Zhang, H. (2014) · Advanced Materials · doi:10.1002/adma.201304964 · Cited by 632
Carbon materials for Li–S batteries: Functional evolution and performance improvement
Liang, J., Sun, Z.-H., Li, F., & Cheng, H.-M. (2016) · Energy Storage Materials · doi:10.1016/j.ensm.2015.09.007 · Cited by 593
Metadata
- Authors
- Parvez, K., Yang, S., Hernandez, Y., Winter, A., Turchanin, A., Feng, X., & Müllen, K.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2012-10-16
- Volume
- 6
- Issue
- 11
- Pages
- 9541-9550
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2092235578
- Cited by
- 612
- References
- 6
- FWCI
- 25.63
- Type
- journal article
- Language
- en
- Open access
- green
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: Nitrogen-Doped Graphene and Its Iron-Based Composite As Efficient Electrocatalysts for Oxygen Reduction Reaction. https://app.cochat.ai/papers/10.1021/nn302674k
- The paper
- Parvez, K., Yang, S., Hernandez, Y., Winter, A., Turchanin, A., Feng, X., & Müllen, K. (2012). Nitrogen-Doped Graphene and Its Iron-Based Composite As Efficient Electrocatalysts for Oxygen Reduction Reaction. ACS Nano. https://doi.org/10.1021/nn302674k
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.
