Multiscale Modeling of the Oxidative Removal of Pollutants

Background: Heterogeneous catalysts based on supported noble metal clusters and particles are essential components that play a key role in numerous industrial applications such as emission control, electrochemical hydrogen production or hydrogenation in fine chemical synthesis. State-of-the-art catalytic systems are typically hierarchically-structured across different length scales, while their catalytic properties are strongly dependent both on the atomic scale structure, and on cooperative and spatio-temporal effects within the reactor. This introduces a hierarchical complexity and causes structural changes under reaction conditions that together with the pronounced heterogeneity of industrial catalysts pose a great challenge for their knowledge-based design and improvement.

Project: This project aims on the oxidative removal of pollutants such as methane and CO over noble metal-based catalysts. Objective of the project is to develop microkinetic models based on first principles that can predict the catalytic performance in the atomic and reactor scale. Via multiscale approach and employing DFT calculations of elementary reactions and transition states, the detailed microkinetic models are developed and implemented in 1D (fixed bed) and 2D (channel) reactor model coupled with internal and external diffusion models. Mechanistic implications, reaction pathways under varying conditions and description of dynamic phenomena are in focus.

Contact: Sofia Angeli, Olaf Deutschmann

Collaboration: Felix Studt (Institute of Catalysis Research and Technology / IKFT)

Funding: CRC-1441, Project B4

Selected publications:

1. 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), 11137–11151.
   DOI: 10.1021/acscatal.2c03378

2. 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 2022, 127 (16), 7628–7639.
   DOI: 10.1021/acs.jpcc.2c08179

3. 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. Chemie Int. Ed. 2023, 62 (39). DOI: 10.1002/anie.202306514.