Learning Design Rules for Selective Oxidation Catalysts from High-Throughput Experimentation and Artificial Intelligence-Reference-Cited by-同舟云学术

Learning Design Rules for Selective Oxidation Catalysts from High-Throughput Experimentation and Artificial Intelligence

Published:2022-01-31 Issue:4 Volume:12 Page:2223-2232
ISSN:2155-5435
Container-title:ACS Catalysis
language:en
Short-container-title:ACS Catal.

Author:

Foppa Lucas¹²^ORCID,Sutton Christopher¹^ORCID,Ghiringhelli Luca M.¹³,De Sandip⁴,Löser Patricia⁵,Schunk Stephan A.⁴⁵,Schäfer Ansgar⁴,Scheffler Matthias¹²

Affiliation:

1. The NOMAD Laboratory, Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany

2. The NOMAD Laboratory, Humboldt-Universität zu Berlin, Zum Großen Windkanal 6, D-12489 Berlin, Germany

3. FAIRmat, Humboldt-Universität zu Berlin, Zum Großen Windkanal 6, D-12489 Berlin, Germany

4. BASF SE, Carl-Bosch-Straße 38, D-67065 Ludwigshafen, Germany

5. hte GmbH, Kurpfalzring 104, D-69123, Heidelberg, Germany

Funder

BASF

H2020 Research Infrastructures

Publisher

American Chemical Society (ACS)

Subject

Catalysis,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acscatal.1c04793

Reference41 articles.

1. CO Oxidation as a Prototypical Reaction for Heterogeneous Processes

2. Heterogeneous Catalysis

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5. The Materials Super Highway: Integrating High-Throughput Experimentation into Mapping the Catalysis Materials Genome

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