INF - Automation of interdisciplinary research data management for catalysis

INF
INF

Objective

This project deals with data handling strategies including standard tools like open access publishing, data storage of all meta-data and reduced data sets, linkage of all data used for publications to the corresponding doi, but also the development and use of tools to compare catalytic data, characterization data as well as simulations. The software tool CaRMeN will serve as a starting point for the development of efficient software for an interdisciplinary research data management flow, with a focus on data from theory, the massive amount of data from characterization, and experimental data from engine test benches and the physical and chemical models and numerical simulation codes.

Project-related publications by participating researchers

Project- and subject-related list of publications

R. Chacko, K. Keller, S. Tischer, A. B. Shirsath, P. Lott, S. Angeli, O. Deutschmann, Automating the Optimization of Catalytic Reaction Mechanism Parameters Using Basin-Hopping: A Proof of Concept. J. Phys. Chem. C 2023, 127 (16), 76287639.

DOI: 10.1021/acs.jpcc.2c08179

R. Chacko, H. Gossler, S. Angeli, O. Deutschmann. Interconnected Digital Solutions to Accelerate Modelling of the Reaction Kinetics in Catalysis. ChemCatChem 2024,

DOI: 10.1002/cctc.202301355

H. Gossler, J. Riedel, E. Daymo, R. Chacko, S. Angeli, O. Deutschmann, A New Approach to Research Data Management with a Focus on Traceability: Adacta. Chem. Ing. Tech. 2022, 94 (11), 17981807.

DOI: 10.1002/cite.202200064

S. Hanf, S. Angeli, D. Dussol, C. Fritsch, L. Maier, M. Müller, O. Deutschmann, S. A. Schunk, Methane Dry Reforming. In Chemical Valorisation of Carbon Dioxide (Eds: G. Stefanidis, A. Stankiewicz), The Royal Society of Chemistry, 2022, 187207.

DOI: 10.1039/9781839167645-00187

B. Kreitz, P. Lott, J. Bae, K. Blöndal, S. Angeli, Z. W. Ulissi, F. Studt, C. F. Goldsmith, O. Deutschmann, Detailed Microkinetics for the Oxidation of Exhaust Gas Emissions through Automated Mechanism Generation. ACS Catal. 2022, 12 (18), 1113711151.

DOI: 10.1021/acscatal.2c03378

B. Kreitz, P. Lott, F. Studt, A. J. Medford, O. Deutschmann, C. F. Goldsmith, Automated Generation of Microkinetics for Heterogeneously Catalyzed Reactions Considering Correlated Uncertainties. Angew. Chem. Int. Ed. 2023, 62 (39), e202306514.

DOI: 10.1002/anie.202306514

P. Lott, O. Deutschmann, Heterogeneous Chemical Reactions-A Cornerstone in Emission Reduction of Local Pollutants and Greenhouse Gases. Proc. Combust. Inst. 2022, 000, 133.

DOI: 10.1016/j.proci.2022.06.001

A. Salazar, B. Wentzel, S. Schimmler, R. Gläser, S. Hanf, S. A. Schunk, How Research Data Management Plans Can Help in Harmonizing Open Science and Approaches in the Digital Economy. Chem. Eur. J. 2023, 29 (9), e2022027720.

DOI: 10.1002/chem.202202720

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, A Unified Research Data Infrastructure for Catalysis Research Challenges and Concepts. ChemCatChem 2021, 13 (14), 32233236.

DOI: 10.1002/cctc.202001974