The DOI matches its Crossref record.
Carbon Nitride as a Nonprecious Catalyst for Electrochemical Oxygen Reduction
Abstract
Nitrogen-doped carbon-based catalysts are increasingly being studied as Pt-free electrodes for oxygen reduction in polymer electrolyte membrane fuel cells. Here, we study the oxygen reduction activity of stoichiometric carbon nitride, which has much higher nitrogen content and is synthesized at lower temperatures, without using ionic or metallic iron. Carbon nitride was studied and characterized via X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, BET specific surface area analysis, and thermogravimetric analysis. Rotating electrode voltammetry in oxygen-saturated sulfuric acid was used to determine the catalytic activity. The onset potential for oxygen reduction by carbon nitride electrodes was 0.69 V (vs NHE) compared to 0.45 V for a carbon black reference electrode. However, the current density was low, possibly due to the low surface area of the material. Blending the carbon nitride with a high surface area carbon black support resulted in a significant improvement in current density and in an increase in onset potential to 0.76 V. The role of surface area was elucidated via cyclic voltammetry. This work confirms that stoichiometric carbon nitride has improved inherent oxygen reduction activity compared to pure carbon, and suggests that Fe coordination sites are not essential for electrochemical oxygen reduction in nitrogen-containing carbon materials.
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
Cited by
Design of electrocatalysts for oxygen- and hydrogen-involving energy conversion reactions
Jiao, Y., Zheng, Y., Jaroniec, M., & Qiao, S. Z. (2015) · Chemical Society Reviews · doi:10.1039/c4cs00470a · Cited by 5,388
Metal-Free Catalysts for Oxygen Reduction Reaction
Dai, L., Xue, Y., Qu, L., Choi, H.-J., & Baek, J.-B. (2015) · Chemical Reviews · doi:10.1021/cr5003563 · Cited by 2,380
Chatenet, M., Pollet, B. G., Dekel, D. R., Dionigi, F., Deseure, J., Millet, P., Braatz, R. D., Bazant, M. Z., Eikerling, M., Staffell, I., et al. (2022) · Chemical Society Reviews · doi:10.1039/d0cs01079k · Cited by 2,025
Yang, S., Feng, X., Wang, X., & Müllen, K. (2011) · Angewandte Chemie International Edition · doi:10.1002/anie.201100170 · Cited by 1,109
Carbon-based electrocatalysts for advanced energy conversion and storage
Zhang, J., Xia, Z., & Dai, L. (2015) · Science Advances · doi:10.1126/sciadv.1500564 · Cited by 735
Zhang, J., & Dai, L. (2015) · ACS Catalysis · doi:10.1021/acscatal.5b01563 · Cited by 590
Efficient Metal‐Free Electrocatalysts from N‐Doped Carbon Nanomaterials: Mono‐Doping and Co‐Doping
Gao, K., Wang, B., Tao, L., Cunning, B. V., Zhang, Z., Wang, S., Ruoff, R. S., & Qu, L. (2019) · Advanced Materials · doi:10.1002/adma.201805121 · Cited by 486
2D Graphitic Carbon Nitride for Energy Conversion and Storage
Wang, Y., Liu, L., Ma, T., Zhang, Y., & Huang, H. (2021) · Advanced Functional Materials · doi:10.1002/adfm.202102540 · Cited by 448
Khan, A. H., Ghosh, S., Pradhan, B., Dalui, A., Shrestha, L. K., Acharya, S., & Ariga, K. (2017) · Bulletin of the Chemical Society of Japan · doi:10.1246/bcsj.20170043 · Cited by 432
Sun, Y., Li, C., Xu, Y., Bai, H., Yao, Z., & Shi, G. (2010) · Chemical Communications · doi:10.1039/c001635g · Cited by 301
Emerging new generation electrocatalysts for the oxygen reduction reaction
Raj, C. R., Samanta, A., Noh, S. H., Mondal, S., Okajima, T., & Ohsaka, T. (2016) · Journal of Materials Chemistry A · doi:10.1039/c6ta03300h · Cited by 201
Zhang, K., Yue, Q., Chen, G., Zhai, Y., Wang, L., Wang, H., Zhao, J., Liu, J., Jia, J., & Li, H. (2011) · The Journal of Physical Chemistry C · doi:10.1021/jp108305v · Cited by 147
Jhong, H. M., Tornow, C. E., Smid, B., Gewirth, A. A., Lyth, S. M., & Kenis, P. J. A. (2017) · ChemSusChem · doi:10.1002/cssc.201600843 · Cited by 125
Self-citationN-doped graphene catalysts with high nitrogen concentration for the oxygen reduction reaction
Lemes, G., Sebastián, D., Pastor, E., & Lázaro, M. J. (2019) · Journal of Power Sources · doi:10.1016/j.jpowsour.2019.227036 · Cited by 112
Metadata
- Authors
- Lyth, S. M., Nabae, Y., Moriya, S., Kuroki, S., Kakimoto, M.-A., Ozaki, J.-I., & Miyata, S.
- Venue
- The Journal of Physical Chemistry C
- Publisher
- American Chemical Society (ACS)
- Published
- 2009-10-28
- Volume
- 113
- Issue
- 47
- Pages
- 20148-20151
- ISSN
- 1932-7447 (ISSN-L)
- 1932-7455
- OpenAlex
- W2072223080
- Cited by
- 369
- References
- 0
- FWCI
- 7.95
- 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
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.
