Related Experiment Video
Updated: Jul 7, 2026

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
Published on: October 17, 2025
Optimization of catalysts using specific, description-based genetic algorithms
Martin Holena1, Tatjana Cukic, Uwe Rodemerck
1Leibniz Institute for Catalysis, Branch Berlin, Richard-Willstätter-Strasse 12, 12489 Berlin, Germany. martin@cs.cas.cz
Abstract:
This paper deals with the key optimization task that has to be solved when improving the performance of many chemical processes--optimization of the catalysts used in the reaction via the optimization of its composition and preparation. A novel approach is presented that allows for the preservation of the advantages of genetic algorithms developed specifically for the optimization of catalytic materials but avoids the disadvantageous necessity to reimplement the algorithm when the scope of the optimized materials changes. Its main idea is to automatically generate problem-tailored implementations from requirements concerning the materials with a program generator. For the specification of such requirements, a formal description language, called catalyst description language, has been developed.
More Related Videos
Related Concept Videos
Heterogeneous Catalysis
Catalytically Perfect Enzymes
Methods of Medium Optimization
Catalysis
Catalysis
Reduction of Alkenes: Asymmetric Catalytic Hydrogenation
The metal catalyst used can be either heterogeneous or homogeneous. When hydrogenation of an alkene generates a chiral center, a pair of enantiomeric products is expected to form. However, an enantiomeric excess of one of the products can be facilitated using an enantioselective reaction or an...

