Contact

Jennifer Uebbing, M.Sc.
Jennifer Uebbing, M.Sc.
External Affairs Chair
Phone:+49 39 1611-0252

MPI - Process Systems Engineering

Scientific Clusters

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Topics

I) Biotechnological Production Processes

This cluster focuses on contributions related to improving biologicals, (bio) chemical and biopolymers production processes. Those may include:

  • Computation strain design & new design principles, e.g. microbial metabolism engineering
  • Dynamic modelling & process control under uncertainty for tailor-made biopolymers
  • Cell culture-based production of viral vaccines and recombinant proteins

II) Process Systems for Renewable Energy Conversion
In this cluster, contributions related to efficient energy conversion processes based on renewable processes are considered. Among them:

  • Modelling, simulation and optimization of complex chemical energy conversion networks
  • Analysis of reaction and transport phenomena in water electrolysis processes
  • Multiscale analysis of catalytic conversion processes
  • Dynamic storage and utilization of the heat of system (exothermic chemical conversion)

III) Production and Separation Methods for Active Pharmaceutical Ingredients
This cluster deals with methods and processes to produce active pharmaceutical ingredients efficiently in energetical, financial and sustainable ways. This includes:

  • Recovery of natural products from their sources, e.g. by solid-liquid extraction
  • Green chemical synthesis of APIs, e.g. by waste reduction- and utilisation or photocatalysis
  • Selective separation processes for purification of APIs from crude solutions, e.g. by crystallization and chromatography
  • Coupling of several process steps and optimization of process chains for API production

IV) Process Engineering Theoretical Tools and Concepts
In this cluster, discussions revolve around process engineering theoretical concepts and tools such as:

  • Algorithms for decision-making under uncertainty
  • Optimal and feedback controllers for chemical & biological processes under uncertainty
  • Statistical inversion of nonlinear problems
  • Partial differential equations and model-based co-simulations
 
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