English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

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

Foppa, L., Sutton, C. A., Ghiringhelli, L. M., De, S., Löser, P., Schunk, S. A., et al. (2022). Learning Design Rules for Selective Oxidation Catalysts from High-Throughput Experimentation and Artificial Intelligence. ACS Catalysis, 12(4), 2233-2232. doi:10.1021/acscatal.1c04793.

Item is

Files

show Files
hide Files
:
acscatal.1c04793.pdf (Publisher version), 3MB
Name:
acscatal.1c04793.pdf
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
2022
Copyright Info:
The Author(s)

Locators

show

Creators

show
hide
 Creators:
Foppa, Lucas1, 2, Author           
Sutton, Christopher A.1, Author           
Ghiringhelli, Luca M.1, 3, Author           
De, Sandip4, Author
Löser, Patricia5, Author
Schunk, Stephan A.4, 5, Author
Schäfer, Ansgar4, Author
Scheffler, Matthias1, 2, Author           
Affiliations:
1NOMAD, Fritz Haber Institute, Max Planck Society, ou_3253022              
2The NOMAD Laboratory, Humboldt-Universität zu Berlin, Zum Großen Windkanal 6, D-12489 Berlin, Germany, ou_persistent22              
3FAIRmat, Humboldt-Universität zu Berlin, Zum Großen Windkanal 6, D-12489 Berlin, Germany, ou_persistent22              
4BASF SE, Carl-Bosch-Straße 38, D-67065 Ludwigshafen, Germany, ou_persistent22              
5hte GmbH, Kurpfalzring 104, D-69123, Heidelberg, Germany, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: The design of heterogeneous catalysts is challenged by the complexity of materials and processes that govern reactivity and by the fact that the number of good catalysts is very small in comparison to the number of possible materials. Here, we show how the subgroup-discovery (SGD) artificial-intelligence approach can be applied to an experimental plus theoretical data set to identify constraints on key physicochemical parameters, the so-called SG rules, which exclusively describe materials and reaction conditions with outstanding catalytic performance. By using high-throughput experimentation, 120 SiO2-supported catalysts containing ruthenium, tungsten, and phosphorus were synthesized and tested in the catalytic oxidation of propylene. As candidate descriptive parameters, the temperature and 10 parameters related to the composition and chemical nature of the catalyst materials, derived from calculated free-atom properties, were offered. The temperature, the phosphorus content, and the composition-weighted electronegativity are identified as key parameters describing high yields toward the value-added oxygenate products acrolein and acrylic acid. The SG rules not only reflect the underlying processes particularly associated with high performance but also guide the design of more complex catalysts containing up to five elements in their composition.

Details

show
hide
Language(s): eng - English
 Dates: 2022-01-072021-10-182022-01-312022-02-18
 Publication Status: Published in print
 Pages: 10
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1021/acscatal.1c04793
 Degree: -

Event

show

Legal Case

show

Project information

show hide
Project name : NOMAD CoE - Novel materials for urgent energy, environmental and societal challenges
Grant ID : 951786
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

Source 1

show
hide
Title: ACS Catalysis
  Abbreviation : ACS Catal.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Washington, DC : ACS
Pages: 10 Volume / Issue: 12 (4) Sequence Number: - Start / End Page: 2233 - 2232 Identifier: ISSN: 2155-5435
CoNE: https://pure.mpg.de/cone/journals/resource/2155-5435