Using High Throughput Experimentation Approach for the Evaluation of Dehydrogenation Catalysts: Potential Interests and Drawbacks

Linear monoolefins with 10 to 14 carbon atoms are intermediates in the manufacture of biodegradable detergent products. These olefins can be obtained industrially by dehydrogenation of long chain paraffins on specific dehydrogenation catalysts under suitable operating conditions. The active phase of these catalysts is generally multimetallic, platinum-based modified by one or more promoters. Use of a high throughput experimentation approach may be interesting to optimise multimetallic formulations due firstly to the increasing number of possible formulations with the number of elements considered and secondly to the possible existence of nonlinear interactions between the elements. This article is therefore dedicated to a description of the high throughput experimentation tools used for preparation and catalytic evaluation during dehydrogenation of n-decane of alumina-supported “Pt-Sn-X” model catalysts, alongside the strategy used to optimise the formulation and the experimental results obtained in the predefined study domain. An approach based on the use of design of experiments to build a mathematical prediction model has been implemented to attempt to optimise the formulation of trimetallic “Pt-Sn-X” catalysts within a defined study domain. This approach could not be completed since the variation of the catalytic properties depending on the catalytic formulations of the design of experiments is not large enough with respect to the experimental variance. The results obtained nevertheless demonstrated a key concept to maximise the selectivity of a long chain paraffin dehydrogenation catalyst. At the same residual acidity and assuming that the formation of coproducts mainly involves bifunctional mechanisms for which the limiting step occurs on the acid phase, maximising the selectivity goes hand in hand with maximising the activity of the catalytic dehydrogenating function