The stability of our planet is threatened by climate change, necessitating a shift towards a circular economy in the (bio-)chemical industry to sustainably meet our increasing product demand. Syngas fermentation by acetogenic bacteria, such as Clostridium autoethanogenum, has been identified as a sustainable alternative for the production of biofuels and other chemicals. These bacteria harbour the Wood-Ljungdahl pathway (WLP), enabling them to convert carbon monoxide (CO), carbon dioxide (CO₂) and hydrogen (H₂) into acetate and ethanol. Several process parameters influence the outcome of syngas fermentation and their effects on the metabolic behaviour of syngas fermenting bacteria can be quantified through kinetic modelling.

This study aimed to build a simple quantitative model for steady-state CO fermentation by C. autoethanogenum using unstructured microbial kinetics and the current insights into the ATP production of the CO pathways to acetate and ethanol. To this aim, a dataset compromising 37 steady-state lab-scale syngas fermentations was compiled. Incomplete data was reconciled and recovery gaps were addressed through data reconciliation applied to the dataset. Furthermore, the growth kinetics of C. autoethanogenum was described by coupling ATP production in the catabolism to energy requirements for growth and maintenance through a modified Herbert-Pirt equation. Finally, a preliminary model for CO fermentation by C. autoethanogenum was presented, which given the gas inflow rate, gas inflow composition and liquid dilution rate should predict the consumption and production rates. Moreover, this study emphasizes the necessity for methodologies to measure dissolved gas concentrations and highlights the research gap concerning gas uptake kinetics in syngas fermentation.

The oxygen mass transfer coefficient, kLa, is a critical parameter in bioprocess performance, influencing the design of stirred tank reactors. During a fermentation process, the behavior of bubbles and the kLa can be effected by various components present in the broth. This study investigates the effect of organic compounds (ethanol, glycerol and acetic acid), which are produced during a yeast fermentation process (S. cerevisiae). It is concluded that acetic acid appears to decrease the geometric mean bubble diameter, in aqueous solutions. As a surfactant, the acetic acid molecules accumulate in the gas-liquid interface, thereby inhibiting bubble coalescence. This leads to an increase in interfacial area and a 34% rise in kLa has been measured. Glycerol, however, showed no significant impact in water. Ethanol should exhibit a similar trend to acetic acid, as reported in previous literature (Puiman, Elisiário, et al., 2022). Remarkably, when these organic compounds were added to growth medium for a yeast fermentation - which consist of synthetic medium, glucose and vitamins - the effects were negligible. This likely due to the coalescence-enhancing properties of antifoam, which is present in synthetic media. On the other hand, the concentrations of the organic compounds tested were relatively low. In addition, during the fermentation process, the production of organic compounds did not significantly affect the bubble size. A slight increase in kLa was observed, arguably due to a reduction in working volume. Whilst performing the tests, the kLa was measuring with three different experimental determination methods: the dynamic pressure method, the dynamic gassing-out method, and the gaseous oxygen balance method. The dynamic gassing-out method appeared a bit more consistent than the dynamic pressure method, possibly due to pressure stabilization issues. The gaseous oxygen balance method did not provide consistent results throughout the entire fermentation, as the method is sensitive and relies on very accurate gas measurements, especially when the oxygen consumption is low. The dynamic gassing-out method proved to be stable and provided the most results used for comparisons of experiment. However, considering its limitations, it requires validation with a ground truth, such as a validated reliable chemical method. The experimental kLa data was compared with predicted values, using empirical correlations. All predicted values remained within 50% margin to the experimental values (determined with dynamic gassing-out method). To be able to use these prediction models in bioprocess design, further investigation is essential.

An optical fibre probe was tested in liquids with biotechnologically relevant compounds, to determine if any limits arise in bubble property determination due to these compounds. The data from this fibre probe was compared to the data from a camera for which an image processing algorithm was developed. This algorithm was able to successfully filter objects using configurable parameters. Objects had to be in focus, within a certain size range and elliptical in shape. The filtering was able to work with partially out of focus bubbles, and bubbles at the edges of the image within tolerances specified by the parameters. To provide insight into the relation between the fibre probe data and camera data a control measurement was performed in pure water, after which measurements were performed in a mixture containing 100g/L ethanol and a mixture containing 0.4M NaCl. The data sets from both measurement methods were compared for bubble velocity and bubble size. The velocity would be directly comparable,
the size was however the local height at the point where the fibre probe pierced the bubbles. As such the height directly below the fibre probe of the bubbles was determined from the images to serve as comparable data. The comparison between the probe data and camera data was inconclusive due to a dissimilarity between the distributions. Mainly the overestimation of the comparable size from the camera data was a problem. Which was likely due to the camera showing only a 2D projection of the bubble and as such the entire height would be used for this comparison. For the velocity the camera data had a narrower distribution as compared to the fibre probe data. This could be caused by the camera averaging the speed of bubbles between two or even three frames if a bubble was not detected in the middle frame, the probe might be more sensitive to these variations and as such yield a wider distribution. The image processing algorithm showed a correct processing of the images to yield usable data, the exact comparable data however still needs to be improved for this specific application.