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Item Open Access Calculation of pure substance and mixture viscosities using PCP-SAFT and entropy scaling(Stuttgart : Universität Stuttgart, Institut für Technische Thermodynamik und Thermische Verfahrenstechnik, 2020) Lötgering-Lin, Oliver; Gross, Joachim (Prof. Dr.-Ing.)Item Open Access Predicting by-product gradients of baker’s yeast production at industrial scale : a practical simulation approach(2020) Sarkizi Shams Hajian, Christopher; Haringa, Cees; Noorman, Henk; Takors, RalfScaling up bioprocesses is one of the most crucial steps in the commercialization of bioproducts. While it is known that concentration and shear rate gradients occur at larger scales, it is often too risky, if feasible at all, to conduct validation experiments at such scales. Using computational fluid dynamics equipped with mechanistic biochemical engineering knowledge of the process, it is possible to simulate such gradients. In this work, concentration profiles for the by-products of baker’s yeast production are investigated. By applying a mechanistic black-box model, concentration heterogeneities for oxygen, glucose, ethanol, and carbon dioxide are evaluated. The results suggest that, although at low concentrations, ethanol is consumed in more than 90% of the tank volume, which prevents cell starvation, even when glucose is virtually depleted. Moreover, long exposure to high dissolved carbon dioxide levels is predicted. Two biomass concentrations, i.e., 10 and 25 g/L, are considered where, in the former, ethanol production is solely because of overflow metabolism while, in the latter, 10% of the ethanol formation is due to dissolved oxygen limitation. This method facilitates the prediction of the living conditions of the microorganism and its utilization to address the limitations via change of strain or bioreactor design or operation conditions. The outcome can also be of value to design a representative scale-down reactor to facilitate strain studies.Item Open Access Highly porous free-standing rGO/SnO2 pseudocapacitive cathodes for high-rate and long-cycling Al-ion batteries(2020) Jahnke, Timotheus; Raafat, Leila; Hotz, Daniel; Knöller, Andrea; Diem, Achim Max; Bill, Joachim; Burghard, ZaklinaEstablishing energy storage systems beyond conventional lithium ion batteries requires the development of novel types of electrode materials. Such materials should be capable of accommodating ion species other than Li+, and ideally, these ion species should be of multivalent nature, such as Al3+. Along this line, we introduce a highly porous aerogel cathode composed of reduced graphene oxide, which is loaded with nanostructured SnO2. This binder-free hybrid not only exhibits an outstanding mechanical performance, but also unites the pseudocapacity of the reduced graphene oxide and the electrochemical storage capacity of the SnO2 nanoplatelets. Moreover, the combination of both materials gives rise to additional intercalation sites at their interface, further contributing to the total capacity of up to 16 mAh cm-3 at a charging rate of 2 C. The high porosity (99.9%) of the hybrid and the synergy of its components yield a cathode material for high-rate (up to 20 C) aluminum ion batteries, which exhibit an excellent cycling stability over 10,000 tested cycles. The electrode design proposed here has a great potential to meet future energy and power density demands for advanced energy storage devices.Item Open Access Streamlining the analysis of dynamic 13C-labeling patterns for the metabolic engineering of corynebacterium glutamicum as L-histidine production host(2020) Feith, André; Schwentner, Andreas; Teleki, Attila; Favilli, Lorenzo; Blombach, Bastian; Takors, RalfToday’s possibilities of genome editing easily create plentitudes of strain mutants that need to be experimentally qualified for configuring the next steps of strain engineering. The application of design-build-test-learn cycles requires the identification of distinct metabolic engineering targets as design inputs for subsequent optimization rounds. Here, we present the pool influx kinetics (PIK) approach that identifies promising metabolic engineering targets by pairwise comparison of up- and downstream 13C labeling dynamics with respect to a metabolite of interest. Showcasing the complex l-histidine production with engineered Corynebacterium glutamicum l-histidine-on-glucose yields could be improved to 8.6 ± 0.1 mol% by PIK analysis, starting from a base strain. Amplification of purA, purB, purH, and formyl recycling was identified as key targets only analyzing the signal transduction kinetics mirrored in the PIK values.Item Open Access Scale-up of gas fermentations : modelling tools for risk minimisation(2020) Siebler, FloraThe reduction of greenhouse gas emissions is a global endeavour supported by society, politics and industry. In recent years, circular economy, reducing the exploitation of fossil energy sources, have increased the demand for new solutions when producing commodities and fine chemicals. Caboxydotrophic fermentations with acetogenic bacteria are potential processes in order to reach these goals. They convert gaseous substrates such as CO, and CO2/H2 mixtures. However, gases as sole substrate are rather challenging, not only in small lab-scales but especially in large-scale. Transferring an efficient fermentation process from experimental to industrial scales often results in unpredictable performance losses. This study presents an in silico concept minimising possible risks in gas fermentations up-scaling. First, the economical feasibility of various fermentation methods is investigated. Then, two computational tools are presented using Clostridium ljungdahlii as model organism and synthesis gas as substrate in a 125 m3 bubble column reactor. The combination of economical investigation with modelling tools show high potential for successful scale-up of gas fermentations. With this concept feasibility, reactor design, operation mode and general risk minimisation can be analysed and specified.