The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Boron Phosphide Nanoparticles: A Nonmetal Catalyst for High‐Selectivity Electrochemical Reduction of CO2 to CH3OH
Abstract
Electrocatalysis has emerged as an attractive way for artificial CO 2 fixation to CH 3 OH, but the design and development of metal‐free electrocatalyst for highly selective CH 3 OH formation still remains a key challenge. Here, it is demonstrated that boron phosphide nanoparticles perform highly efficiently as a nonmetal electrocatalyst toward electrochemical reduction of CO 2 to CH 3 OH with high selectivity. In 0.1 m KHCO 3, this catalyst achieves a high Faradaic efficiency of 92.0% for CH 3 OH at −0.5 V versus reversible hydrogen electrode. Density functional theory calculations reveal that B and P synergistically promote the binding and activation of CO 2, and the rate‐determining step for the CO 2 reduction reaction is dominated by *CO + *OH to *CO + *H 2 O process with free energy change of 1.36 eV. In addition, CO and CH 2 O products are difficultly generated on BP (111) surface, which is responsible for the high activity and selectivity of the CO 2‐to‐CH 3 OH conversion process.
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Generalized Gradient Approximation Made Simple
Perdew, J. P., Burke, K., & Ernzerhof, M. (1996) · Physical Review Letters · doi:10.1103/physrevlett.77.3865 · Cited by 215,824
Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set
Kresse, G., & Furthmüller, J. (1996) · Physical Review B · doi:10.1103/physrevb.54.11169 · Cited by 123,652
Kresse, G., & Furthmüller, J. (1996) · Computational Materials Science · doi:10.1016/0927-0256(96)00008-0 · Cited by 75,638
Grimme, S., Antony, J., Ehrlich, S., & Krieg, H. (2010) · The Journal of Chemical Physics · doi:10.1063/1.3382344 · Cited by 59,686
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
Enhanced electrocatalytic CO2 reduction via field-induced reagent concentration
Liu, M., Pang, Y., Zhang, B., De Luna, P., Voznyy, O., Xu, J., Zheng, X., Dinh, C. T., Fan, F., Cao, C., et al. (2016) · Nature · doi:10.1038/nature19060 · Cited by 2,000
Partially oxidized atomic cobalt layers for carbon dioxide electroreduction to liquid fuel
Gao, S., Lin, Y., Jiao, X., Sun, Y., Luo, Q., Zhang, W., Li, D., Yang, J., & Xie, Y. (2016) · Nature · doi:10.1038/nature16455 · Cited by 1,865
Kondratenko, E. V., Mul, G., Baltrusaitis, J., Larrazábal, G. O., & Pérez-Ramírez, J. (2013) · Energy & Environmental Science · doi:10.1039/c3ee41272e · Cited by 1,802
Recent Advances in Inorganic Heterogeneous Electrocatalysts for Reduction of Carbon Dioxide
Zhu, D. D., Liu, J. L., & Qiao, S. Z. (2016) · Advanced Materials · doi:10.1002/adma.201504766 · Cited by 1,594
Zhao, C., Dai, X., Yao, T., Chen, W., Wang, X., Wang, J., Yang, J., Wei, S., Wu, Y., & Li, Y. (2017) · Journal of the American Chemical Society · doi:10.1021/jacs.7b02736 · Cited by 1,365
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Electrocatalysis for CO 2 conversion: from fundamentals to value-added products
Wang, G., Chen, J., Ding, Y., Cai, P., Yi, L., Li, Y., Tu, C., Hou, Y., Wen, Z., & Dai, L. (2021) · Chemical Society Reviews · doi:10.1039/d0cs00071j · Cited by 1,295
Pu, Z., Liu, T., Amiinu, I. S., Cheng, R., Wang, P., Zhang, C., Ji, P., Hu, W., Liu, J., & Mu, S. (2020) · Advanced Functional Materials · doi:10.1002/adfm.202004009 · Cited by 604
Metadata
- Authors
- Mou, S., Wu, T., Xie, J., Zhang, Y., Ji, L., Huang, H., Wang, T., Luo, Y., Xiong, X., Tang, B., & Sun, X.
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2019-07-23
- Volume
- 31
- Issue
- 36
- Pages
- e1903499-e1903499
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- OpenAlex
- W2963408627
- Cited by
- 253
- References
- 33
- FWCI
- 6.54
- Type
- journal article
- Language
- en
- Open access
- closed
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- Mou, S., Wu, T., Xie, J., Zhang, Y., Ji, L., Huang, H., Wang, T., Luo, Y., Xiong, X., Tang, B., & Sun, X. (2019). Boron Phosphide Nanoparticles: A Nonmetal Catalyst for High‐Selectivity Electrochemical Reduction of CO2 to CH3OH. Advanced Materials. https://doi.org/10.1002/adma.201903499
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