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  Towards automation of operando experiments: A case study in contactless conductivity measurements

Kraus, P., Wolf, E., Prinz, C., Bellini, G., Trunschke, A., & Schlögl, R. (2022). Towards automation of operando experiments: A case study in contactless conductivity measurements. Digital Discovery, 1(3), 241-254. doi:10.33774/chemrxiv-2021-mh17g.

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towards-automation-of-operando-experiments-a-case-study-in-contactless-conductivity-measurements.pdf (Preprint), 2MB
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 Creators:
Kraus, Peter1, 2, Author              
Wolf, Elisabeth1, 3, Author              
Prinz, Charlotte4, Author              
Bellini, Giulia1, Author              
Trunschke, Annette1, Author              
Schlögl, Robert1, 3, Author              
Affiliations:
1Inorganic Chemistry, Fritz Haber Institute, Max Planck Society, ou_24023              
2School of Molecular and Life Sciences,Curtin University, GPO Box U1987, Perth 6845, WA, Australia, ou_persistent22              
3Research Department Schlögl, Max Planck Institute for Chemical Energy Conversion, Max Planck Society, ou_3023874              
4Molecular Physics, Fritz Haber Institute, Max Planck Society, ou_634545              

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 Abstract: Automation of experiments is a key component on the path of digitalisation in catalysis and relatedsciences. Here we present the lessons learned and caveats avoided during the automation of our con-tactless conductivity measurement set-up, capable of operando measurement of catalytic samples. Webriefly discuss the motivation behind the work, the technical groundwork required, and the philosophyguiding our design. The main body of this work is dedicated to the detailing of the implementationof the automation, data structures, as well as the modular data processing pipeline. The open-sourcetoolset developed as part of this work allows us to carry out unattended and reproducible experiments,as well as post-process data according to current best practice. This process is illustrated by implement-ing two routine sample protocols, one of which was included in theHandbook of Catalysis, providingseveral case studies showing the benefits of such automation, including increased throughput and higherdata quality. The datasets included as part of this work contain catalytic and operando conductivity1 data, and are self-consistent, annotated with metadata, and are available on a public repository in amachine-readable form. We hope the datasets as well as the tools and workflows developed as part ofthis work will be an useful guide on the path towards automation and digital catalysis.

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Language(s): eng - English
 Dates: 2021-10-282021-10-292022-02-252022-06-01
 Publication Status: Published online
 Pages: 14
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 Table of Contents: -
 Rev. Type: Peer
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Title: Digital Discovery
Source Genre: Journal
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Publ. Info: RSC
Pages: 14 Volume / Issue: 1 (3) Sequence Number: - Start / End Page: 241 - 254 Identifier: ISSN: 2635-098X
CoNE: https://pure.mpg.de/cone/journals/resource/2635-098X