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Reactions at Surfaces: From Atoms to Complexity (Nobel Lecture)
Abstract
The spatio–temporal formation of patterns on the surface during a chemical reaction is one phenomenon that can now be understood and modeled thanks to the Nobel Prize winning research on the course of heterogeneous catalysis. The picture shows a pattern formed by a feedback mechanism during the oxidation of CO. Reactions that have been illuminated by this work include the synthesis of ammonia and the purification of waste gases.
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Cited by
Towards the computational design of solid catalysts
Nørskov, J. K., Bligaard, T., Rossmeisl, J., & Christensen, C. H. (2009) · Nature Chemistry · doi:10.1038/nchem.121 · Cited by 4,161
Theory-guided design of catalytic materials using scaling relationships and reactivity descriptors
Zhao, Z.-J., Liu, S., Zha, S., Cheng, D., Studt, F., Henkelman, G., & Gong, J. (2019) · Nature Reviews Materials · doi:10.1038/s41578-019-0152-x · Cited by 657
Electron Transfer at Oxide Surfaces. The MgO Paradigm: from Defects to Ultrathin Films
Pacchioni, G., & Freund, H. (2013) · Chemical Reviews · doi:10.1021/cr3002017 · Cited by 320
Ternary intermetallic LaCoSi as a catalyst for N2 activation
Gong, Y., Wu, J., Kitano, M., Wang, J., Ye, T.-N., Li, J., Kobayashi, Y., Kishida, K., Abe, H., Niwa, Y., et al. (2018) · Nature Catalysis · doi:10.1038/s41929-017-0022-0 · Cited by 319
MoO3 nanosheets for efficient electrocatalytic N2 fixation to NH3
Han, J., Ji, X., Ren, X., Cui, G., Li, L., Xie, F., Wang, H., Li, B., & Sun, X. (2018) · Journal of Materials Chemistry A · doi:10.1039/c8ta03974g · Cited by 319
Metadata
- Authors
- Ertl, G.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2008-04-21
- Volume
- 47
- Issue
- 19
- Pages
- 3524-3535
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W2124126215
- Cited by
- 1,356
- References
- 0
- FWCI
- 92.18
- Type
- journal article
- Language
- en
- Open access
- closed
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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.