Issue 18, 2024

A bridge between trust and control: computational workflows meet automated battery cycling

Abstract

Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We successfully interface off-the-shelf battery cycling hardware with the computational workflow management software AiiDA, allowing us to control experiments, while ensuring trust in the data by tracking its provenance. We design user interfaces compatible with this tooling, which span the inventory, experiment design, and result analysis stages. Other features, including monitoring of workflows and import of externally generated and legacy data are also implemented. Finally, the full software stack required for this work is made available in a set of open-source packages.

Graphical abstract: A bridge between trust and control: computational workflows meet automated battery cycling

Supplementary files

Article information

Article type
Paper
Submitted
09 Nov 2023
Accepted
20 Mar 2024
First published
03 Apr 2024
This article is Open Access
Creative Commons BY license

J. Mater. Chem. A, 2024,12, 10773-10783

A bridge between trust and control: computational workflows meet automated battery cycling

P. Kraus, E. Bainglass, F. F. Ramirez, E. Svaluto-Ferro, L. Ercole, B. Kunz, S. P. Huber, N. Plainpan, N. Marzari, C. Battaglia and G. Pizzi, J. Mater. Chem. A, 2024, 12, 10773 DOI: 10.1039/D3TA06889G

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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