Advancing catalysis research through FAIR data principles implemented in a local data infrastructure – a case study of an automated test reactor-Reference-Cited by-同舟云学术

Advancing catalysis research through FAIR data principles implemented in a local data infrastructure – a case study of an automated test reactor

Published:2024 Issue: Volume: Page:
ISSN:2044-4753
Container-title:Catalysis Science & Technology
language:en
Short-container-title:Catal. Sci. Technol.

Author:

Moshantaf Abdulrhman¹,Wesemann Michael¹,Beinlich Simeon¹,Junkes Heinz¹^ORCID,Schumann Julia¹²^ORCID,Alkan Baris¹³,Kube Pierre¹,Marshall Clara Patricia¹,Pfister Nils¹,Trunschke Annette¹^ORCID

Affiliation:

1. Fritz-Haber-Institut der Max-Planck-Gesellschaft, Department of Inorganic Chemistry, Faradayweg 4-6, D-14195 Berlin, Germany

2. Consortium FAIRmat, c/o Physics Department and CSMB, Humboldt-Universität zu Berlin, Zum Großen Windkanal 2, 12489 Berlin, Germany

3. Max-Planck-Institut für Chemische Energiekonversion, Stiftstrasse 34 - 36, 45470 Mülheim an der Ruhr, Germany

Abstract

Digitalisation in experimental catalysis research: we are introducing machine-readable standard operating procedures combined with automated data acquisition, storage and sharing to improve research efficiency and reproducibility.

Funder

Bundesministerium für Bildung und Forschung

Deutsche Forschungsgemeinschaft

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/CY/D4CY00693C

Reference49 articles.

1. Extracting Knowledge from Data through Catalysis Informatics

2. The Rise of Catalyst Informatics: Towards Catalyst Genomics

3. Machine Learning for Catalysis Informatics: Recent Applications and Prospects

4. Open Data in Catalysis: From Today's Big Picture to the Future of Small Data

5. A Unified Research Data Infrastructure for Catalysis Research – Challenges and Concepts