EMIBEX Project

EMIBEX Project

In the collaboration project EMIBEX, the Max Planck Institute for Dynamics of Complex Technical Systems collaborates with the Hochschule Anhalt,  University of Applied Sciences (Köthen, Saxony-Anhalt) and the Fraunhofer Center for Chemical-Biotechnological Processes CBP (Leuna, Saxony-Anhalt). The project is funded by the European Fond of Regional Development (EFRE), and managed by the Land Saxony-Anhalt.

Time schedule: The project will be closed in June 2020.

The main goal of the project is to develop and progress industrial mixotrophic cultivation and downstreaming for microalgae, where the production of valuable ingredients (e.g. biocolorants and proteins) are maximised. Special focus will be given for the valorisation of carbon containing residues as nutrient and for a gentle product extraction with hydrocarbons, e.g. propane or other novel type solvent solutions.

The activities in Max Planck Institute concentrate on the adaption and transfer of the dynamic cultivation model originally developed for Dunaliella salina to adiatom Phaeodactylum tricornutum or other micro algal species investigated by the collaboration partners in the EMIBEX project. The model [1] will be extended in terms of temperature dependence to enable more sophisticated process optimisation strategies.

A further project activity for the Max Planck Institute is to develop a superstructure for the overall biorefinery process based on algal cultivation, processing and product valorisation. Here, alternative unit operations in the downstreaming field are mathematically modelled and linked sequentially with other units. This approach offers numerous various process routes which can be analysed and optimised. An extended superstructure contains hundreds or thousands of alternatives which enables a process analysis and a multiobjective optimisation of the overall biorefinery.

[1] M. Fachet, R. Flassig, L. Rihko-Struckmann, K. Sundmacher. (2014). A dynamic growth model of Dunaliella salina: Parameter identification and profile likelihood analysis. Bioresource technology. 173C. 21-31. 10.1016/j.biortech.2014.08.124.

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