About the Project
Selective hydrogenations of alkynes represent key reactions for several industrial processes that lie at the heart of pharmaceutical and fine chemical industry. These reactions are usually carried out in batch processes in the presence of supported Pd-based catalysts modified with the addition of lead. The presence of this toxic element strongly limits the sustainability of these processes. Furthermore, the need of energy savings led, in the past decade, to a growing interest in new technologies for Process Intensification. For the aforementioned reasons, new reactor solutions and new catalysts need to be further investigated in order to reduce the energy consumption and to establish safe and environment-friendly process solutions.
The goal of this project is to investigate rationally catalysts for the selective hydrogenation of alkynes and to understand their catalytic performance across time and length scale in order to develop detailed first principle microkinetic models. Typical industrial catalysts are based on Pd with their activity and selectivity dramatically affected by the presence of promoters or supporting oxides. Generally, the nature of the active sites in such catalytic systems is not known, owing to their structural complexity (multiple components, formation of alloys). The development of microkinetic models, consisting of a detailed reaction networks and a comprehensive set of theoretically calculated kinetic parameters, can facilitate and accelerate catalyst design efforts via reaction mechanism elucidation and catalyst performance assessment. The developed models will be experimentally validated for a wide range of reactants, operating conditions, active site structures and reactor configurations. Further extensions will be the application of the models for the optimal design of structured reactors for continuous hydrogenations in prospect of Process Intensification.
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If English is not your first language, then you must have International English Language Testing Service (IELTS) average of 6.5 or above with at least 6.0 in each component.
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