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Margraf, Johannes T. ; Ulissi, Zachary W. ; Jung, Yousung ; Reuter, Karsten:
Heterogeneous Catalysis in Grammar School.
In: The Journal of Physical Chemistry C.
Bd. 126
(2022)
Heft 6
.
- S. 2931-2936.
ISSN 1932-7455
DOI: https://doi.org/10.1021/acs.jpcc.1c10285
Abstract
The discovery of new catalytically active materials is one of the holy grails of computational chemistry as it has the potential to accelerate the adoption of renewable energy sources and reduce the energy consumption of chemical industry. Indeed, heterogeneous catalysis is essential for the production of synthetic fuels and many commodity chemicals. Consequently, novel solid catalysts with higher activity and selectivity, increased sustainability and longevity, or improved prospects for rejuvenation and cyclability are needed for a diverse range of processes. Unfortunately, computational catalyst discovery is a daunting task, among other reasons because it is often unclear whether a proposed material is stable or synthesizable. This perspective proposes a new approach to this challenge, namely the use of generative grammars. We outline how grammars can guide the search for stable catalysts in a large chemical space and sketch out several research directions that would make this technology applicable to real materials.
Weitere Angaben
| Publikationsform: | Artikel in einer Zeitschrift |
|---|---|
| Begutachteter Beitrag: | Ja |
| Institutionen der Universität: | Fakultäten > Fakultät für Biologie, Chemie und Geowissenschaften > Fachgruppe Chemie > Lehrstuhl Künstliche Intelligenz in der physiko-chemischen Materialanalytik Fakultäten > Fakultät für Biologie, Chemie und Geowissenschaften > Fachgruppe Chemie > Lehrstuhl Künstliche Intelligenz in der physiko-chemischen Materialanalytik > Lehrstuhl Künstliche Intelligenz in der physiko-chemischen Materialanalytik - Univ.-Prof. Dr. Johannes Theo Margraf |
| Titel an der UBT entstanden: | Nein |
| Themengebiete aus DDC: | 500 Naturwissenschaften und Mathematik > 540 Chemie |
| Eingestellt am: | 13 Nov 2023 13:49 |
| Letzte Änderung: | 13 Nov 2023 13:49 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/87656 |