Stefan Junne is currently group leader of the working groups “Smart Bioproduction Grids” and “Process Analytical Technologies” at the lab of bioprocess engineering, institute of biotechnology at TU Berlin (Germany). As chemical engineer by training, he started to work in the area of bioprocess engineering, in particular biofuels production, about 15 years ago. After Dr. Junne obtained his Ph.D. in 2010 in the area of systems biology and modeling, he meanwhile focuses on the development, experimental optimization and scale up of various microbial bioprocesses in the area of mono, co- and anaerobic mixed cultivation for the production of bulk and fine chemicals, food and feed components. Beside a development of tailored bioreactors, in particular rocking single-use reactors, the understanding of cell physiology and morphology and the interaction of cells to different environmental conditions is in the focus of research. Therefore, single-cell based methods for in line applications are applied to understand the impact of stress conditions, as they occur during scale up and which are mimicked in scale down bioreactors, on population heterogeneity and to control of co-cultures. Such concepts are applied within a wide range of microorganisms, like microalgae, yeast and bacteria as well as filamentous fungi. Finally, by combining bioreactor design and suitable process analytical technology, morphologic control is conducted and coupled to population balances, e.g. under varying shear force cultivation conditions and gradient formation like it appears in the liquid phase of large scale production.
Besides, another major aim of Dr. Junne's work within bioprocess optimization is also to broaden the range of applicable feedstock by suitable pre-treatment methods, analytical tools, reactor and process design in order to achieve regional closed material cycles. Economic and life cycles aspects are considered for the energetic and material use of biogenic raw and residual material to obtain a high degree of sustainability and applicability up to the large scale.