The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
High-Entropy Alloys as Catalysts for the CO2 and CO Reduction Reactions: Experimental Realization
Open accessAbstract
Conversion of carbon dioxide into selective hydrocarbon using a stable catalyst remains a holy grail in the catalysis community. The high overpotential, stability, and selectivity in the use of a single-metal-based catalyst still remain a challenge. In current work, instead of using pure noble metals (Ag, Au, and Pt) as the catalyst, a nanocrystalline high-entropy alloy (HEA: AuAgPtPdCu) has been used for the conversion of CO 2 into gaseous hydrocarbons. Utilizing an approach of multimetallic HEA, a faradic efficiency of about 100% toward gaseous products is obtained at a low applied potential (−0.3 V vs reversible hydrogen electrode). The reason behind the catalytic activity and selectivity of the high-entropy alloy (HEA) toward CO 2 electroreduction was established through first-principles-based density functional theory (DFT) by comparing it with the pristine Cu(111) surface. This is attributed to the reversal in adsorption trends for two out of the total eight intermediates—*OCH 3 and *O on Cu(111) and HEA surfaces.
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Cites
How copper catalyzes the electroreduction of carbon dioxide into hydrocarbon fuels
Peterson, A. A., Abild-Pedersen, F., Studt, F., Rossmeisl, J., & Nørskov, J. K. (2010) · Energy & Environmental Science · doi:10.1039/c0ee00071j · Cited by 3,784
A review of catalysts for the electroreduction of carbon dioxide to produce low-carbon fuels
Qiao, J., Liu, Y., Hong, F., & Zhang, J. (2014) · Chem. Soc. Rev. · doi:10.1039/c3cs60323g · Cited by 2,990
Electroreduction of carbon monoxide to liquid fuel on oxide-derived nanocrystalline copper
Li, C. W., Ciston, J., & Kanan, M. W. (2014) · Nature · doi:10.1038/nature13249 · Cited by 1,728
Activity Descriptors for CO 2 Electroreduction to Methane on Transition-Metal Catalysts
Peterson, A. A., & Nørskov, J. K. (2012) · The Journal of Physical Chemistry Letters · doi:10.1021/jz201461p · Cited by 1,667
Electrocatalytic Conversion of Carbon Dioxide to Methane and Methanol on Transition Metal Surfaces
Kuhl, K. P., Hatsukade, T., Cave, E. R., Abram, D. N., Kibsgaard, J., & Jaramillo, T. F. (2014) · Journal of the American Chemical Society · doi:10.1021/ja505791r · Cited by 1,649
Kim, D., Resasco, J., Yu, Y., Asiri, A. M., & Yang, P. (2014) · Nature Communications · doi:10.1038/ncomms5948 · Cited by 1,374
Enhanced Electrochemical Methanation of Carbon Dioxide with a Dispersible Nanoscale Copper Catalyst
Manthiram, K., Beberwyck, B. J., & Alivisatos, A. P. (2014) · Journal of the American Chemical Society · doi:10.1021/ja5065284 · Cited by 546
Back, S., Lim, J., Kim, N.-Y., Kim, Y.-H., & Jung, Y. (2017) · Chemical Science · doi:10.1039/c6sc03911a · Cited by 542
Ma, M., Trześniewski, B. J., Xie, J., & Smith, W. A. (2016) · Angewandte Chemie International Edition · doi:10.1002/anie.201604654 · Cited by 530
Highly Dense Cu Nanowires for Low-Overpotential CO 2 Reduction
Raciti, D., Livi, K. J., & Wang, C. (2015) · Nano Letters · doi:10.1021/acs.nanolett.5b03298 · Cited by 395
Cited by
High-entropy nanoparticles: Synthesis-structure-property relationships and data-driven discovery
Yao, Y., Dong, Q., Brozena, A., Luo, J., Miao, J., Chi, M., Wang, C., Kevrekidis, I. G., Ren, Z. J., Greeley, J., et al. (2022) · Science · doi:10.1126/science.abn3103 · Cited by 1,081
High-entropy energy materials: challenges and new opportunities
Ma, Y., Ma, Y., Wang, Q., Schweidler, S., Botros, M., Fu, T., Hahn, H., Brezesinski, T., & Breitung, B. (2021) · Energy & Environmental Science · doi:10.1039/d1ee00505g · Cited by 963
High-entropy materials for catalysis: A new frontier
Sun, Y., & Dai, S. (2021) · Science Advances · doi:10.1126/sciadv.abg1600 · Cited by 942
(2020) · doi:10.1038/s41467-020-19277-9 · Cited by 690
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
Metadata
- Authors
- Nellaiappan, S., Katiyar, N. K., Kumar, R., Parui, A., Malviya, K. D., Pradeep, K. G., Singh, A. K., Sharma, S., Tiwary, C. S., & Biswas, K.
- Venue
- ACS Catalysis
- Publisher
- American Chemical Society (ACS)
- Published
- 2020-02-19
- Volume
- 10
- Issue
- 6
- Pages
- 3658-3663
- ISSN
- 2155-5435 (ISSN-L)
- OpenAlex
- W3008031353
- Cited by
- 447
- References
- 10
- FWCI
- 11.03
- Type
- journal article
- Language
- en
- Open access
- green
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