A bridge between trust and control: computational workflows meet automated battery cycling
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.
WOS:001199481300001
2024-04-03
REVIEWED
Funder | Grant Number |
European Union | 957189 |
NCCR MARVEL (a National Centre of Competence in Research - Swiss National Science Foundation) | 205602 |
Open Research Data Program of the ETH Board (project "PREMISE": Open and Reproducible Materials Science Research) | |
DFG | 490703766 |