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Sustainable Process Systems Engineering

 

Research in the Sustainable Process Systems Engineering (SuPSE) group focuses on the development of highly efficient processes for the successful transition into a sustainable future. We include the evaluation of whole process chains in order to identify main bottlenecks and related scientific challenges. The main question seeking for an answer is: How can we utilize available resources in the most sustainable way? The group uses a combination of computational and experimental methods to advance the development of emerging sustainable technologies.

Computational methods include the use of Process Systems Engineering (PSE) tools to synthesize, integrate and analyze processes by taking into account the needs of people (social), planet (environment) and profits (economy), the tri-fold metrics of sustainability. These tools include process synthesis/modeling and integration, techno-economic (TEA) and Life Cycle Assessments (LCA). Particular interest is given in integration of chemical and renewable energy technologies for exploiting synergies leading to optimization of processes in a circular economy concept. Of special focus are Hydrothermal Liquefaction (HTL) technology for the production of renewable bio-crude from a variety of biomass and waste feedstock and Power to X technologies as a solution for large-scale energy storage.

Some example applications of PSE methods & tools currently used in the group include:

  • Process synthesis, modeling and simulations to select unit operations, chemical pathways and integration schemes.
  • Process integration targeting for energy and material synergies between different processes.
  • Process intensification for more resource-efficient processes.
  • Techno-economic assessment (TEA) and scale up of chemical processes.
  • Life Cycle Assessment (LCA) methodology for assessing the environmental impacts of chemical processes and products.

At the same time, SuPSE utilizes a range of experimental facilities (lab to pilot scale) in order (a) to generate the necessary data for input in the models and/or for model validation and (b) to explore new/more efficient chemical pathways. Of special focus is HTL and in particular reaction kinetics for different feedstock and feedstock mixtures as well as HTL by-product utilization (solids, process water and gas) and biocrude upgrading