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    Enabling oxygen-dependent biocatalysis under fine bubble aeration in a rotating bed reactor
    (2025)
    Percin, Zeynep
    ;
    Liese, Andreas
    The scope of the thesis is the detailed investigation and demonstration of different approaches to overcome mass transfer limitations for the oxidative biocatalytic application in a modified reaction vessel of a rotating bed reactor. The benefits of the fine bubble aeration method over macrobubble aeration in application with a rotating packed bed reactor are demonstrated. Improved reaction rate and gas utilization are shown, resulting in increased catalytic productivity. Biocatalyst reuse, leading to efficient utilization of oxidases, was successfully applied. Considering the process limitations, the findings extend the potential use of fine bubble aeration for sustainable biotransformation processes using a rotating packed bed reactor.
    Publicationtype: Doctoral Thesis
      88  67
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      59
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    Structuration of plant-based milk powder for improved reconstitution
    (Cuvillier, 2025)
    Kramm, Kathrin
    ;
    Heinrich, Stefan
    Publicationtype: Doctoral Thesis
      22
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    Einfluss von Hochdruck auf die Synthese von N-Acetylneuraminsäure in einem Festbettreaktor
    (2025)
    Reich, Jannis Alexander
    ;
    Liese, Andreas
    The continuous application of high pressure in biotechnology was shown for the production of Neu5Ac starting from GlcNac and Pyr. Two immobilized enzymes were used. For the investigation of the reaction kinetic a fixed bed reactor and for the position of equilibrium a circular reactor was used. By using up to 1,300 bar the equilibrium was positively influenced by pressure. Pressure caused an increase in affinity for some reactants towards the enzymes. The high-pressure circular reactor in particular showed great potential due to two different pressure regimes (high pressure and ambient pressure) enabling an easy taking of samples while the reaction is at high pressure.
    Publicationtype: Doctoral Thesis
      56  49
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    Co-culture of Acetobacterium woodii and Clostridium drakei using CO₂ and in situ generated H₂ to produce caproic acid via lactic acid
    (2024)
    Herzog, Jan
    ;
    Zeng, An-Ping
    Syngas fermentation processes have been proposed as promising technology for high value chemical production from one carbon compounds including CO2, reducing both direct carbon emissions and replacing fossil fuels as feedstock in the chemical industry. Among the potential microorganisms able to utilize CO2 as main carbon source, Acetobacterium woodii is one of the most extensively studied and is considered a model organism for acetogens. Its main metabolite is the rather low value product acetic acid; however, recent recombinant strains are capable of producing lactate from CO2 and H2. Using the chain-elongating bacteria Clostridium drakei, a synthetic co-culture has the potential to produce higher value products such as caproic acid. In this study, a synthetic co-culture with the acetogens Acetobacterium woodii and Clostridium drakei in a stirred tank bioreactor, using CO2 and H2 as substrates for the production of caproic acid via the intermediate lactate was successfully developed and established. The H2 for the process was generated in situ with an All-in-One electrode, which was designed for effective H2 generation in any standard bioreactor. Caproate concentrations reached a maximum concentration of 0.1 g/L and a yield from lactate of up to 0.2 g/g. The co-cultivation was found to be beneficial for Clostridium drakei as inhibiting effects observed in pure culture were not noticed during co-cultivations. For the development of the co-culture, both strains were characterized separately. The recently developed strain Acetobacterium woodii ΔlctBCD ΔpyrE [p83_PbgaL_NFP] was found to be the most promising in comparison to other Acetobacterium woodii strains, reaching 0.5 g/L of lactate in the bioelectrochemical system with a volumetric productivity of up to 0.2 g/L d. H2 supply limitation was identified as the major bottleneck for the fermentations with the All-in-One electrode, as conventional gas fermentations with the same Acetobacterium woodii strain yielded 8.1 g/L lactate with a volumetric productivity of up to 2.0 g/L d. Nonetheless, cathode surface enlargement and reduction of Faradaic losses or numbering-up of the All-in-One could increase H2 production and thus lactate production. To the author’s best knowledge, this is the first study to show data of Clostridium drakei cultivations in a stirred-tank bioreactor growing on lactate. The maximum caproate concentration added up to 1.5 g/L with a volumetric productivity of 0.7 g/L d. The inhibitory level of caproic acid was identified at 1.5 g/L. Lastly, a lactate dependent process control was developed for the co-cultivation process, which can adjust the H2 production rate dynamically depending on the lactate concentrations measured online during the cultivation.
    Publicationtype: Doctoral Thesis
      154  437
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    Automated kinetic model identification of biocatalysts under process conditions
    (2024)
    Hennecke, Leon
    ;
    Liese, Andreas
    Kinetic model identification is important for the optimization and scale-up of enzymatic processes. The modelling process is strongly influenced by human error, experimental design and model selection, which can be overcome by automation. Therefore, in this work, an automated reactor platform has been developed to perform kinetic model identification for a model enzymatic reaction. This reaction is catalyzed by a formate dehydrogenase from the yeast Candida boidinii. The reduction of NAD+ to NADH with the hydride donor sodium formate is monitored by inline UV/Vis spectroscopy at 340 nm in the design space of 0.35 to 2 mM NAD+ and 50 to 300 mM formate. The enzyme is utilized in a packed bed reactor, where it is immobilized on functionalized porous resin particles. The steady-state concentration of NADH is measured to determine the corresponding reaction rate at various initial substrate concentrations, providing data for identifying a kinetic model from eight candidate models. These kinetic models serve as the basis for a model-based design of experiments using the Akaike weight design criterion. This method uses Akaike weights to measure the relative goodness of fit for candidate models and identify experiments with maximum information content. Once a successful model discrimination is achieved, parameter estimation is improved through additional experiments according to the e-optimal design criterion to reduce the confidence intervals of the model parameters of the discriminated kinetic model. The model identification process is based on six fully factorial designed experiments initially, which is then improved through nine additional experiments. This approach leads to the discovery of a kinetic model within 15 experiments, with standard deviations of less than 10% within the range of measurement error. The double substrate Michaelis-Menten model accurately represented the packed bed reactor data after implementing a multi-start heuristic and extending the design space. The kinetic model identification was optimized and applied to data from an enzyme membrane reactor process with formate dehydrogenase in solution. The resulting model showed non-competitive product inhibition, in contrast to the model for the immobilized enzyme. The reactor configuration and immobilization resulted in a distinct kinetic model and confidence intervals. This emphasizes the impact of experimental design on identifying kinetic models and the advantages of automation in this field.
    Publicationtype: Doctoral Thesis
      54  116
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    Flow characteristics of differently sized Lagrangian Sensor Particles in a 15,000 l bioreactor
    (2024)
    Brouwers, Isabel Sophie
    In the industry, process parameters are monitored using fixed sensors mounted at the reactor wall. However, this Eulerian approach provides barely detailed insights and information about the mixing performance, which is crucial for productivity in bioprocesses. In contrast, the Lagrangian approach focuses on Lagrangian Sensor Particles (LSPs) in the moving fluid exhibiting an appropriate flow-following behavior mimicking a cell. As demonstrated in previous studies, they can be equipped with multiple process parameter sensors such as temperature, pH, dissolved oxygen or pressure. This thesis addresses three key aspects: the hydrodynamic characterization of a single-phase 15,000 L bioreactor with a pitched blade impeller and Rushton Turbine setup by means of LSPs, the comparison of two LSP sizes regarding their flow-following behavior, and the determination of differently mixed regimes within the reactor, known as compartments. LSPs with two different diameters, 40 mm (LSP40) and 60 mm (LSP60), equipped with a pressure sensor, are investigated in this study. The experiments are carried out at five different impeller frequencies. Based on measured pressure data, the axial probability of presence over the reactor height, axial velocities, circulation times, and selected circulation time distributions are analyzed to further ascertain axial compartments and, consequently, conduct a Lagrangian regime analysis. Additionally, the overall circulation times of both LSPs are compared to global mixing times in the same setup. The estimated Stokes number for the LSP40 and LSP60 are 0.21 and 0.32 for the meso-scale and 0.002 and 0.004 for the macro-scale, respectively. Hence, for the macro-scale a flow-following behavior is assumed, as it results in St ≪1. The hypothesis of the LSP60 having a bigger inertia than the LSP40 is experimentally shown in the probability of presence and the Lagrangian velocity analysis. Furthermore, the overall circulation times of LSP60 are up to 1.4 times lower than those of LSP40. As LSP60 exhibit velocities in the same range as the LSP40, this indicates that LSP60 follow shorter circulation loops. Circulation time results reveal three compartments within the reactor, which boundaries are assumed above the pitched blade impeller and below the Rushton Turbine. According to these results, the Lagrangian regime analysis shows that the middle compartment exhibits a broad residence times distribution. In contrast, the top and bottom compartment show less probability for higher residence times. At least three circulation loops within the reactor are estimated, as seen in the CTD displaying a trimodal distribution for the horizontal plane below the PB. Similarly to literature statements and confirming the latter, the ratio of the examined global mixing time to overall circulation time is between 3 and 4. This thesis emphasizes the potential and broad applicability of LSPs to gain insights into mixing processes solely through pressure data. This research underscores that the used LSP40 are more likely to discover a flow-following behavior on the meso-scale, especially for higher impeller frequencies.
    Publicationtype: Master Thesis
      144  204
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    Design, construction and evaluation of lagrangian sensor particles for the flow behavior determination in a 200 l and 15000 l bioreactor
    (2023)
    Gopalsingh, Paramveer Singh
    Stirred Tank Reactors (STRs) are frequently employed in the bioprocessing industry to produce bioproducts employing bacterial, yeast, or mammalian cell lines. The productivity of these reactors may be impacted when they grow in size due to the presence of heterogeneous zones. Using the Lagrangian measurement approach with free-flowing sensors is one way to look at these heterogeneities. In this thesis, two Lagrangian Sensor Particles (LSPs) that can be made using off-the-shelf components and a shell that can be produced by computer numerical control (CNC) machining are designed and built to circumvent this problem and study the heterogeneities in STRs. One type of LSP was built around an Inertial Measurement Unit (IMU), and the second was built around a pressure sensor. They are built to have a density between 1000 and 1005 kg m^-3. These LSPs are then tested in a 200 L and 15000 L reactor. Particle Tracking Velocimetry (PTV) is performed on the LSP in the 200 L reactor. The distribution of acceleration, velocity, and axial position is then determined using the LSPs. The data obtained via Particle Tracking Velocimetry (PTV) is then compared with the data obtained from the LSPs. A steady increase in axial velocity is seen with increasing impeller speeds, according to data from pressure and IMU sensors. Thus, a modular Lagrangian Sensor Particle (LSP) is developed, which can help investigate heterogeneities in STRs by making the LSP platform widely accessible, providing consistent results for all types of sensors. Enhancing the sensor module, the microcontroller, and the data processing method can further expand these findings.
    Publicationtype: Master Thesis
      69  40