The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Tuning Catalytic Selectivity at the Mesoscale via Interparticle Interactions
Open accessAbstract
The selectivity of heterogeneously catalyzed chemical reactions is well-known to be dependent on nanoscale determinants, such as surface atomic geometry and composition. However, principles to control the selectivity of nanoparticle (NP) catalysts by means of mesoscopic descriptors, such as the interparticle distance, have remained largely unexplored. We used well-defined copper catalysts to deconvolute the effect of NP size and distance on product selectivity during CO 2 electroreduction. Corroborated by reaction-diffusion modeling, our results reveal that mesoscale phenomena such as interparticle reactant diffusion and readsorption of intermediates play a defining role in product selectivity. More importantly, this study uncovers general principles of tailoring NP activity and selectivity by carefully engineering size and distance. These principles provide guidance for the rational design of mesoscopic catalyst architectures in order to enhance the production of desired reaction products.
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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
Li, C. W., & Kanan, M. W. (2012) · Journal of the American Chemical Society · doi:10.1021/ja3010978 · Cited by 2,000
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
Competition between CO 2 Reduction and H 2 Evolution on Transition-Metal Electrocatalysts
Zhang, Y.-J., Sethuraman, V., Michalsky, R., & Peterson, A. A. (2014) · ACS Catalysis · doi:10.1021/cs5012298 · Cited by 509
Cited by
Progress and perspectives of electrochemical CO2 reduction on copper in aqueous electrolyte
Nitopi, S., Bertheussen, E., Scott, S. B., Liu, X., Engstfeld, A. K., Horch, S., Seger, B., Stephens, I. E. L., Chan, K., Hahn, C., et al. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00705 · Cited by 5,223
Advances and challenges in understanding the electrocatalytic conversion of carbon dioxide to fuels
Birdja, Y. Y., Pérez-Gallent, E., Figueiredo, M. C., Göttle, A. J., Calle-Vallejo, F., & Koper, M. T. M. (2019) · Nature Energy · doi:10.1038/s41560-019-0450-y · Cited by 2,747
Highly selective plasma-activated copper catalysts for carbon dioxide reduction to ethylene
Mistry, H., Varela, A. S., Bonifacio, C. S., Zegkinoglou, I., Sinev, I., Choi, Y.-W., Kisslinger, K., Stach, E. A., Yang, J. C., Strasser, P., et al. (2016) · Nature Communications · doi:10.1038/ncomms12123 · Cited by 1,214
Self-citationJu, W., Bagger, A., Hao, G.-P., Varela, A. S., Sinev, I., Bon, V., Roldan Cuenya, B., Kaskel, S., Rossmeisl, J., & Strasser, P. (2017) · Nature Communications · doi:10.1038/s41467-017-01035-z · Cited by 1,203
Self-citationGarg, S., Li, M., Weber, A. Z., Ge, L., Li, L., Rudolph, V., Wang, G., & Rufford, T. E. (2020) · Journal of Materials Chemistry A · doi:10.1039/c9ta13298h · Cited by 478
Gao, D., Zegkinoglou, I., Divins, N. J., Scholten, F., Sinev, I., Grosse, P., & Roldan Cuenya, B. (2017) · ACS Nano · doi:10.1021/acsnano.7b01257 · Cited by 458
Self-citationGrosse, P., Gao, D., Scholten, F., Sinev, I., Mistry, H., & Roldan Cuenya, B. (2018) · Angewandte Chemie International Edition · doi:10.1002/anie.201802083 · Cited by 425
Self-citationStructure- and Electrolyte-Sensitivity in CO2 Electroreduction
Arán-Ais, R. M., Gao, D., & Roldan Cuenya, B. (2018) · Accounts of Chemical Research · doi:10.1021/acs.accounts.8b00360 · Cited by 341
Self-citationJeon, H. S., Timoshenko, J., Scholten, F., Sinev, I., Herzog, A., Haase, F. T., & Roldan Cuenya, B. (2019) · Journal of the American Chemical Society · doi:10.1021/jacs.9b10709 · Cited by 266
Self-citationTuning of CO2 Reduction Selectivity on Metal Electrocatalysts
Wang, Y., Liu, J., Wang, Y., Al‐Enizi, A. M., & Zheng, G. (2017) · Small · doi:10.1002/smll.201701809 · Cited by 241
Metadata
- Authors
- Mistry, H., Behafarid, F., Reske, R., Varela, A. S., Strasser, P., & Roldan Cuenya, B.
- Venue
- ACS Catalysis
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-01-13
- Volume
- 6
- Issue
- 2
- Pages
- 1075-1080
- ISSN
- 2155-5435 (ISSN-L)
- OpenAlex
- W2234779942
- Cited by
- 161
- References
- 4
- FWCI
- 3.71
- Type
- journal article
- Language
- en
- Open access
- green
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