High-throughput experimentation in catalyst testing and in kinetic studies for heterogeneous catalysis

Quantitative data in high-throughput experimentation are extremely important in the secondary development stage, comprising catalyst testing, kinetic studies, diagnostics, catalyst characterization (temperature programmed techniques), and stability tests. Even for systems that require long analysis times parallellization is worth application. The information from catalyst testing should be scalable. The reactor should be designed properly and the relevant criteria should be adhered to. The test reactor is not per se a scaled down version of the associated commercial reactor but in specific cases, e.g. riser technology the so-called Dinky Toy approach is appropriate. For structured reactors the scaled down version really simulates the commercial unit. Here, the Dinky Toy approach could well be the best. This is in particular attractive for the pharmaceutical industry. Parallellization is the logical approach in catalyst testing, but single units will survive, however, where the reactor operation is too complex or when one of the aims is to produce semi-commercial amounts of products. Analysis is crucial in design of parallel testing units. GC is the benchmark in quantitative studies, but other techniques should also be taken into consideration. This holds in particular for optical techniques, that offer the potential of fast and in situ analysis. In catalyst testing in a packed bed it is usually advisable to dilute the catalyst bed. It is crucial to carry out the dilution such that a well-mixed bed is created. Even for a homogeneously mixed bed dilution should not be exaggerated and for gas systems the proposed criterion should be adhered to. This bed dilution case study shows the advantage of parallellization for situations where a highly quantitative comparison between different samples is required.