The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
In Situ CO2-Emission Assisted Synthesis of Molybdenum Carbonitride Nanomaterial as Hydrogen Evolution Electrocatalyst
Abstract
We reported a novel protocol to efficiently synthesize molybdenum carbonitride (MoCN) nanomaterials with dense active sites and high surface area. The key step in this protocol is the preparation of the catalyst precursor, which was obtained by polymerizing diaminopyridine in the presence of hydrogen carbonate. The abundant amino groups in the poly diaminopyridine bound numerous Mo species via coordination bonds, resulting in the formation of dense Mo active sites. The addition of hydrogen carbonate to the synthesis mixture resulted in CO2 gas evolution as the local pH decreased during polymerization. The in situ evolved CO2 bubbles mechanically broke down the precursor into MoCN nanomaterials with a high surface area. The synthesized MoCN materials were demonstrated as an electrocatalyst for hydrogen evolution reaction (HER). It exhibited an HER onset potential of -0.05 V (vs RHE) and a high hydrogen production rate (at -0.14 V vs RHE, -10 mA cm(-2)) and is therefore one of the most efficient, low-cost HER catalysts reported to date.
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
Nanostructured Nickel Phosphide as an Electrocatalyst for the Hydrogen Evolution Reaction
Popczun, E. J., McKone, J. R., Read, C. G., Biacchi, A. J., Wiltrout, A. M., Lewis, N. S., & Schaak, R. E. (2013) · Journal of the American Chemical Society · doi:10.1021/ja403440e · Cited by 2,911
Tian, J., Liu, Q., Asiri, A. M., & Sun, X. (2014) · Journal of the American Chemical Society · doi:10.1021/ja503372r · Cited by 2,373
Xie, J., Zhang, J., Li, S., Grote, F., Zhang, X., Zhang, H., Wang, R., Lei, Y., Pan, B., & Xie, Y. (2013) · Journal of the American Chemical Society · doi:10.1021/ja408329q · Cited by 2,350
Cao, B., Veith, G. M., Neuefeind, J. C., Adzic, R. R., & Khalifah, P. G. (2013) · Journal of the American Chemical Society · doi:10.1021/ja4081056 · Cited by 998
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
Liu, Y., Yu, G., Li, G., Sun, Y., Asefa, T., Chen, W., & Zou, X. (2015) · Angewandte Chemie International Edition · doi:10.1002/anie.201504376 · Cited by 734
Gao, Q., Zhang, W., Shi, Z., Yang, L., & Tang, Y. (2019) · Advanced Materials · doi:10.1002/adma.201802880 · Cited by 734
Cobalt‐doping in molybdenum‐carbide nanowires toward efficient electrocatalytic hydrogen evolution
Lin, H., Liu, N., Shi, Z., Guo, Y., Tang, Y., & Gao, Q. (2016) · Advanced Functional Materials · doi:10.1002/adfm.201600915 · Cited by 460
Yu, P., Wang, F., Shifa, T. A., Zhan, X., Lou, X., Xia, F., & He, J. (2019) · Nano Energy · doi:10.1016/j.nanoen.2019.01.017 · Cited by 434
Theerthagiri, J., Lee, S. J., Murthy, A. P., Madhavan, J., & Choi, M. Y. (2020) · Current Opinion in Solid State and Materials Science · doi:10.1016/j.cossms.2020.100805 · Cited by 417
Wang, Z.-L., Hao, X.-F., Jiang, Z., Sun, X.-P., Xu, D., Wang, J., Zhong, H.-X., Meng, F.-L., & Zhang, X.-B. (2015) · Journal of the American Chemical Society · doi:10.1021/jacs.5b09021 · Cited by 414
Lu, J., Zhou, W., Wang, L., Jia, J., Ke, Y., Yang, L., Zhou, K., Liu, X., Tang, Z., Li, L., et al. (2016) · ACS Catalysis · doi:10.1021/acscatal.5b02302 · Cited by 159
Zheng, M., Du, J., Hou, B., & Xu, C.-L. (2017) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.7b07465 · Cited by 136
Inocêncio, C. V. M., Holade, Y., Morais, C., Kokoh, K. B., & Napporn, T. W. (2023) · Electrochemical Science Advances · doi:10.1002/elsa.202100206 · Cited by 57
Nguyen, V.-T., Nguyen, N.-A., Ali, Y., Tran, Q. C., & Choi, H.-S. (2019) · Carbon · doi:10.1016/j.carbon.2019.01.087 · Cited by 55
Yao, X., Zhu, J., Wang, H., Yang, K., Shu, Y., & He, J. (2022) · Applied Surface Science · doi:10.1016/j.apsusc.2022.152842 · Cited by 36
Metadata
- Authors
- Zhao, Y., Kamiya, K., Hashimoto, K., & Nakanishi, S.
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-12-26
- Volume
- 137
- Issue
- 1
- Pages
- 110-113
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W2329474155
- Cited by
- 301
- References
- 4
- FWCI
- 10.37
- 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.
