LabIMotion: Enhancing Research Data Management in Catalysis with a Customizable Electronic Lab Notebook
Heterogeneous catalysis serves as a "melting pot" for various scientific disciplines, bringing together chemistry, physics, materials science, and engineering. This interdisciplinary nature necessitates robust and adaptable tools to manage the complex data generated throughout the research process from general workflows to unique measurements. Given the intricate workflows involved in catalyst development (ranging from synthesis and preparation to material characterization and activity measurements) there is a pressing need for easy-to-use and adaptable Electronic Lab Notebooks (ELNs). These tools must efficiently capture the rich data structures inherent in such multifaceted research environments. These include in situ characterization at large-scale facilities like synchrotrons and neutron sources as well as activity measurements (also potentially at large-scale facilities with data recorded under operando conditions), adaptation of experimental reactor configurations. Existing solutions are not well-suited to represent such a multifaceted system while still providing a highlevel of customizability, and no clear-cut solution is available. LabIMotion, an extension of the open-source ELN Chemotion used in the NFDI4Chem community, addresses these specific needs. LabIMotion addresses the specific needs of the catalysis development environment by allowing the creation of detailed research plans and structuring into defined functional areas, covering catalyst synthesis, characterization, and activity testing. For advanced characterizations performed at synchrotron and neutron facilities, a link to the metadata catalogue SciCat, widely used in the DAPHNE4NFDI consortium, is currently established as well as to device management tools like Adacta, supported by the NFDI4Cat project. By these connections, the traceability of generated data and metadata related to kinetic performance studies, including device-related resources, will be enhanced. Two examples from catalysis research are presented, covering the fields synthesis, activity measurements and characterization: Cu-based catalysts for methanol synthesis and noble metal-based emission control catalysts. Different scenarios are depicted to highlight the customizability of the application as well as the web-interface for improved user- interaction. The organization of research data (analogously to Chemotion) enables facile sharing of (meta-)data with co-workers and collaborators.
Institutions
- University of Padua (IT)
- Kentucky imaging Technologies (United States) (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-04
- DOI
- https://doi.org/10.5281/zenodo.16736376
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00