Engineering Process Intensification and Catalysis

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Economic growth while accounting for social needs, climate change and environmental protection are key to tackle the United Nations Sustainable Development Goals (UN-SDGs) and accelerate the energy transition towards the electrification of the chemical industry. This CRC in Engineering Process Intensification (PI) and Catalysis (EPIC) has as objectives i) to address the technological gap between PI and catalysis; ii) to quantify the energy density and efficiency of alternative energy vectors to accelerate and decrease the footprint and cost for chemical reactions and iii) to identify life cycles and quantify techno-economics of these innovative, disruptive technologies. To do so, the CRC surveys a series of catalysts and reactive systems in different intensified reactors (ultrasound, microwaves, spinning disc and continuous mechano-chemical reactors) for which time scale analysis will be performed to quantify the individual and overall energy density and efficiency of the transport phenomena involved. In a holistic approach, life cycle and cost analysis (LC-CA), as well techno-economic analysis (TEA) are performed. The synergistic effects of catalysis and energy intensification methods have been little explored so far. Another original character of this CRC lies in applying, for the first time, the time scale analysis to intensified processes to quantify the characteristic time and energy flux (density and efficiency) of each transport phenomenon in relation to the others, thus providing new metrics for PI and develop new PI indicators. For the first time, dynamic LC-CA models are applied to PI technologies and TEA is performed for both full-scale and modular units. This CRC will generate a number of high impact contributions since i) it identifies synergies between catalysts and intensified methods to increase productivity by minimizing energy input and reactor size; ii) it develops high speed particle image velocimetry methods that can be applied to different systems; iii) it proposes a methodology to calculate PI factors for each transport phenomenon and an overall PI factor; iv) it develops realistic LC-CA and TEA models that take into account electricity grid technology immaturity; v) it accelerates the knowledge and thus the adoption of PI technologies to the market. Ultimately vi) PI technologies have the potential to be implemented in developing countries, by local renewable-based modular (small scale) plants.