The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
High-Entropy Alloy with Mo-Coordination as Efficient Electrocatalyst for Oxygen Evolution Reaction
Abstract
Electrochemical hydrolytic hydrogen production is the most promising method for renewable energy storage and conversion. However, the kinetic slow oxygen evolution reaction (OER) limits the development of water electrolysis at the anode. The state-of-the-art OER catalysts face a dilemma of high content of noble metals and low OER activities. Herein, a strategy for achieving efficient and stable high-entropy alloy (HEA) catalysts by Mo-coordination is reported. The earth-abundant FeCoNiMo HEA catalyst provides an overpotential as low as 250 mV at the current density of 10 mA cm –2 in alkaline medium, which is 89 mV lower than that of state-of-the-art IrO 2 . The turnover frequency of 0.051 s –1 at the overpotential of 300 mV of FeCoNiMo HEA is 3 times higher than that of commercial IrO 2 catalyst and even 11 times higher than that of the FeCoNi alloy without Mo-coordination. Importantly, the FeCoNiMo HEA exhibits high OER stability at a high current density of 100 mA cm –2 . Methanol molecular probe experiment and X-ray photoelectron spectroscopy analyses suggest that the electrons of Mo transfer to Fe, Co, and Ni in the FeCoNiMo HEA catalyst, which leads to a weakened OH* bonding and, as a result, enhanced OER performance of the FeCoNiMo HEA catalyst. Consistent with the methanol molecular probe analysis, the real-time OER kinetic simulation reveals that the coordination of Mo within FeCoNi can speed up the rate-determining OH* deprotonation step of OER. Our finding opens up a routine for designing efficient cost-effective electrocatalysts for OER, which could facilitate discoveries in OER 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
Burke, M. S., Kast, M. G., Trotochaud, L., Smith, A. M., & Boettcher, S. W. (2015) · Journal of the American Chemical Society · doi:10.1021/jacs.5b00281 · Cited by 1,972
PdMo bimetallene for oxygen reduction catalysis
Luo, M., Zhao, Z., Zhang, Y., Sun, Y., Xing, Y., Lv, F., Yang, Y., Zhang, X., Hwang, S., Qin, Y., et al. (2019) · Nature · doi:10.1038/s41586-019-1603-7 · Cited by 1,461
Self-citationShort-range order and its impact on the CrCoNi medium-entropy alloy
Zhang, R., Zhao, S., Ding, J., Chong, Y., Jia, T., Ophus, C., Asta, M., Ritchie, R. O., & Minor, A. M. (2020) · Nature · doi:10.1038/s41586-020-2275-z · Cited by 1,279
High-Entropy Alloys as a Platform for Catalysis: Progress, Challenges, and Opportunities
Xin, Y., Li, S., Qian, Y., Zhu, W., Yuan, H., Jiang, P., Guo, R., & Wang, L. (2020) · ACS Catalysis · doi:10.1021/acscatal.0c03617 · Cited by 840
Gas hydrates in sustainable chemistry
Hassanpouryouzband, A., Joonaki, E., Vasheghani Farahani, M., Takeya, S., Ruppel, C., Yang, J., English, N. J., Schicks, J. M., Edlmann, K., Mehrabian, H., et al. (2020) · Chemical Society Reviews · doi:10.1039/c8cs00989a · Cited by 809
(2020) · doi:10.1038/s41467-020-19277-9 · Cited by 690
Zagalskaya, A., & Alexandrov, V. (2020) · ACS Catalysis · doi:10.1021/acscatal.9b05544 · Cited by 677
Advanced High Entropy Perovskite Oxide Electrocatalyst for Oxygen Evolution Reaction
Nguyen, T. X., Liao, Y., Lin, C., Su, Y., & Ting, J. (2021) · Advanced Functional Materials · doi:10.1002/adfm.202101632 · Cited by 602
A General Method to Probe Oxygen Evolution Intermediates at Operating Conditions
Tao, H. B., Xu, Y., Huang, X., Chen, J., Pei, L., Zhang, J., Chen, J. G., & Liu, B. (2019) · Joule · doi:10.1016/j.joule.2019.03.012 · Cited by 587
Chen, S., Huang, H., Jiang, P., Yang, K., Diao, J., Gong, S., Liu, S., Huang, M., Wang, H., & Chen, Q. (2020) · ACS Catalysis · doi:10.1021/acscatal.9b04922 · Cited by 574
Cited by
High-entropy alloys in electrocatalysis: from fundamentals to applications
Ren, J.-T., Chen, L., Wang, H.-Y., & Yuan, Z.-Y. (2023) · Chemical Society Reviews · doi:10.1039/d3cs00557g · Cited by 551
Xin, S., Tang, Y., Jia, B., Zhang, Z., Li, C., Bao, R., Li, C., Yi, J., Wang, J., & Ma, T. (2023) · Advanced Functional Materials · doi:10.1002/adfm.202305243 · Cited by 266
High‐Entropy Nanomaterials for Advanced Electrocatalysis
Lee, S. A., Bu, J., Lee, J., & Jang, H. W. (2023) · Small Science · doi:10.1002/smsc.202200109 · Cited by 95
The hybrid Pt nanoclusters/Ru nanowires catalysts accelerating alkaline hydrogen evolution reaction
Yan, J., Wu, R., Jin, G., Jia, L., Feng, G., & Tong, X. (2024) · Advanced Powder Materials · doi:10.1016/j.apmate.2024.100214 · Cited by 68
Metadata
- Authors
- Mei, Y., Feng, Y., Zhang, C., Zhang, Y., Qi, Q., & Hu, J.
- Venue
- ACS Catalysis
- Publisher
- American Chemical Society (ACS)
- Published
- 2022-08-19
- Volume
- 12
- Issue
- 17
- Pages
- 10808-10817
- ISSN
- 2155-5435 (ISSN-L)
- OpenAlex
- W4292296496
- Cited by
- 355
- References
- 42
- FWCI
- 12.05
- 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.
