PlasMACatDESIGN

DESIGNING THE PACKING MATERIALS AND CATALYSTS FOR SELECTIVE AND ENERGY EFFICIENT PLASMA-DRIVEN CONVERSIONS

We aim to develop design rules for (catalytically activated) packing materials to enhance plasma-activated gas phase conversion reactions to basic chemicals. By understanding the material properties-activity correlation we target enhanced conversion, selectivity and energy efficiency of plasma driven chemical production for two selected industrially and environmentally relevant model reactions in which plasma catalysis can have specific advantages:

• selective CO₂ conversion towards C1-C3 (oxygenated) hydrocarbons and
• inorganic amine synthesis (hydroxylamine, NO/NO₂).

We tend to progress the field of plasma catalysis in its wide application beyond the reactions and reactors studied here, while at the same time creating breakthroughs in CO₂ utilisation and process intensification for nitrogen fixation. Furthermore, the project assists in introducing renewable energy in chemical industry and/or valorizing waste gases. Moreover, with the developments of structured hierarchical packing materials/catalysts in this project, we will also achieve progress in material development and specific design, through advanced manufacturing, coating and activation of plasma catalytic packing material. Note: in literature, plasma catalysis indicates the implementation of materials into the plasma phase, creating performance enhancement, even though the enhancing effect might be physical rather than what is understood as catalysis thermally. In plasma this is all grouped in one term "plasma catalysis". We will particularly study:

1. underlying mechanisms and structure-activity correlations,
2. demonstrate the advantages and limitations of using alternative reaction pathways in plasma at mild conditions,
3. proof the concept of producing inorganic amines selectively out of nitrogen and water via plasma catalysis,
4. demonstrate techno economics and environmental benefits of plasma catalysis and how it is affected by different types of uncertainty, identifying key R&D targets.

 ​Project partners:

• Universiteit Gent - INCAT, FEA
• Universiteit Antwerpen
• Universiteit Hasselt - imo-imomec
• VITO