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Institute of Catalysis Research and Technology (IKFT)

Karlsruher Institute of Technology (KIT)
Hermann-von-Helmholtz-Platz 1
76344 Eggenstein-Leopoldshafen

Contakt / Office

Fon: +49 721 608-22401
Fax: +49 721 608-22244
officeLgw7∂ikft kit edu

Head of Institute - Speaker
Jörg Sauer

Prof. Dr-Ing. Jörg Sauer

Fon: +49 721 608-22401

Head of Institute
Felix Studt

Prof. Dr. Felix Studt

Fon: +49 721 608-28663

Institute of Catalysis Research and Technology (IKFT)

The Institute of Catalysis Research and Technology was founded 2011. Its mission is to bridge the gap between fundamental and applied research and the development of new technologies and products in the field of catalysis and process technology of catalyzed processes. The focus of our work is the sustainable utilization of alternative feedstocks and their conversion into energy carriers intermediates. This includes the development of new catalytic systems based on a fundamental understanding of processes on a molecular level.



Carrying out multi-phase reactions in continuously flowing microchannels offers numerous advantages. By varying the hydrodynamic parameters of the segmented gas-liquid two-phase flow (Taylor flow), mass transfer resistances can be specifically influenced and optimized with regard to kinetic requirements. Based on theoretical, experimental and numerical work from the literature, a correlation was developed that allows, with a good degree of accuracy, to estimate numerous previously unknown hydrodynamic parameters of the Taylor flow based on parameters known a priori such as pipe diameter, fluid properties and volume flows of gas and liquid, such as Bubble velocity, average fluid velocity, gas volume fraction, thickness of the fluid film, bubble diameter and streamline characteristics in the fluid plug (circulation or bypass flow). M. Wörner: A Correlation for the Characteristic Velocity Ratio to Predict Hydrodynamics of Capillary Gas–Liquid Taylor Flow, Theoretical Foundations of Chemical Engineering 54 (2020) 3-16.
Density functional theory (DFT) is increasingly used for computational screening procedures with the aim of finding new catalysts. To achieve this, it is critical that relative differences between materials are predicted with high accuracy. How DFT at the generalized gradient approximation (GGA) level performs in this respect is investigated in this work for catalytic reactions employing acidic zeotypes using highly accurate DLPNO-CCSD(T) calculations as the reference. This is studied for 65 reaction energies and 130 reaction barriers related to zeolite catalysis. The results obtained for the PBE-D3 and BEEF-vdW functionals show that while these functionals are prone to large errors, they predict trends occurring from one catalyst to another with an accuracy of about 5 kJ/mol, strongly supporting the widespread use of DFT calculations for the computational screening and design of new catalytic materials. [Plessow, P. N.; Studt, F., J. Phys. Chem. Lett. 2020, 4305-4310.]