areas
Zeolcat.pt group is dedicated and experienced in the synthesis and characterization of advanced and multifunctional materials, including hierarchical porous zeolite materials and metal-supported heterogenous catalysts. Our group uses alternative synthesis method,s together with advanced characterization techniques, to develop and design new catalysts with targeted properties for crude oil refinement and petrochemistry, biomass valorization, photocatalysis, etc. Synthesis methods include hydrothermal conditions, microwave-assisted heating and top-down, bottom-up synthesis strategies. Advanced spectroscopic techniques like Infrared and UV-Visible are used to characterize more in depth the different catalytic systems, under (in-situ) controlled conditions or under reaction, in order to give a better understanding of the relationship between the materials structure and their reactivity.
The evaluation of the catalytic performance of the prepared catalysts, such as activity, selectivity and stability, and the understanting of the reaction mechanism play a key role in all catalytic processes. We are able to study several catalytic reactions involved in the production of clean fuels and value-added chemicals and on the prevention and abatement of pollution. These reactions can be run in a wide range of operating conditions at laboratory and pilot scales. For that reactions either model compouds or real feeds can be used.
The most recently acquired reaction setup is a Multi-reactor Hydroprocessing Pilot plant which will allow gathering relevant data regarding the efficient and flexible co-processing of advanced unconventional feedstock such as either bio-oil derived from biomass or non-recyclable plastics in parallel with vegetable oils and animal fats.
The development of sustainable chemical processes requires in-depth knowledge and optimisation at various levels. Multi-scale computational models will therefore be the cornerstone of new process development through their implementation in process simulators. However, the high complexity of the models and the lack of experimental data prevent the use of this approach. Therefore, we develop (1) multi-scale models with tailored complexity at the relevant scales for a given reaction/application and (2) innovative data scrapping and data science-based modelling methodologies that enable the construction of multi-scale models from open data.