Automation of Interdisciplinary Research Data Management for Catalysis

Background: Research data management (RDM) in scientific research is crucial for ensuring the accessibility, reproducibility and reusability of scientific data. Effective RDM involves the systematic collection, organization and storage of data generated from experiments and simulations. This includes efficient storage of raw data, processed data, and metadata detailing the operating conditions, materials used, software and analytical methods used for generating the data. Automated data acquisition along with automated workflows accelerate research and enable researchers to focus more on analysis and interpretation.

Principal Investigators: Olaf Deutschmann, Shirin Hanf, Felix Studt

Contact: Rinu Chacko, Hendrik Gossler, Olaf Deutschmann

Funding: CRC-1441 TrackAct / Project INF

Selected publications:

1. R. Chacko, H. Gossler, S. Angeli, O. Deutschmann, ChemCatChem 2024, 16, e202301355. DOI: 10.1002/cctc.202301355.
2. R. Chacko, K. Keller, S. Tischer, A. B. Shirsath, P. Lott, S. Angeli, O. Deutschmann, J. Phys. Chem. C 2023, 127, 7628–7639. DOI: 10.1021/acs.jpcc.2c08179
3. H. Gossler, J. Riedel, E. Daymo, R. Chacko, S. Angeli, O. Deutschmann, Chem. Ing. Tech. 2022, 94, 1798–1807. DOI: 10.1002/cite.202200064
4. C. Wulf, M. Beller, T. Boenisch, O. Deutschmann, S. Hanf, N. Kockmann, R. Kraehnert, M. Oezaslan, S. Palkovits, S. Schimmler, S. A. Schunk, K. Wagemann, D. Linke, ChemCatChem 2021, 13, 3223–3236. DOI: 10.1002/cctc.202001974
5. H. Gossler, L. Maier, S. Angeli, S. Tischer, O. Deutschmann, Catalysts 2019, 9, 227. DOI: 10.3390/catal9030227
6. H. Gossler, L. Maier, S. Angeli, S. Tischer, O. Deutschmann, Phys. Chem. Chem. Phys. 2018, 20, 10857–10876. DOI: 10.1039/C7CP07777G