Lactic acid production in a membrane bioreactor system with thermophilicBacillus coagulans: fouling analysis of the used ceramic membranes

Kenics Static Mixer Combined with Gas Sparging for the Improvement of Cross-Flow Microfiltration: Modeling and Optimization

The use of membrane filtration as a downstream process for microbial biomass harvesting is hampered due to the low permeate flux values achieved during the microfiltration of fermentation broths. Several hydrodynamic methods for increasing permeate flux by creating turbulent flow patterns inside the membrane module are used to overcome this problem. The main goal of this study was to investigate the combined use of a Kenics static mixer and gas sparging during cross-flow microfiltration of Bacillus velezensis IP22 cultivation broth. Optimization of the microfiltration process was performed by using the response surface methodology. It was found that the combined use of a static mixer and gas sparging leads to a considerable increase in the permeate flux, up to the optimum steady-state permeate flux value of 183.42 L·m−2·h−1 and specific energy consumption of 0.844 kW·h·m−3. The optimum steady-state permeate flux is almost four times higher, whilst, at the same time, the specific energy consumption is almost three times lower compared to the optimum results achieved using gas sparging alone. The combination of Kenics static mixer and gas sparging during cross-flow microfiltration is a promising technique for the enhancement of steady-state permeate flux with simultaneously decreasing specific energy consumption.

Modeling and Optimization of Gas Sparging-Assisted Bacterial Cultivation Broth Microfiltration by Response Surface Methodology and Genetic Algorithm

Production of highly efficient biomass-based microbial biopesticides significantly depends on downstream processing in terms of obtaining as high concentration of viable cells as possible. Microfiltration is one of the recommended operations for microbial biomass separation, but its main limitation is permeate flux decrease due to the membrane fouling. The effect of air sparging as a hydrodynamic technique for improvement of permeate flux during microfiltration of Bacillus velezensis cultivation broth was investigated. Modeling of the microfiltration was performed using the response surface methodology, while desirability function approach and genetic algorithm were applied for optimization, i.e., maximization of permeate flux and minimization of specific energy consumption. The results have revealed antagonistic relationship between the investigated dependent variables. The optimized values of superficial feed velocity and transmembrane pressure were close to the mean values of the investigated value ranges (0.68 bar and 0.96 m/s, respectively), while the optimized value of superficial air velocity had a more narrow distribution around 0.25 m/s. The results of this study have revealed a significant improvement of microfiltration performance by applying air sparging, thus this flux improvement method should be further investigated in downstream processing of different bacterial cultivation broths.

Influence of Ceramic Membrane Surface Characteristics on the Flux Behavior of a Complex Fermentation Broth

The valorization of agro-industrial residues using yeasts as biocatalysts requires efficient methods for biomass separation. Filtration with ceramic membranes is suitable for this task, however, the challenge of flux decline and the unavoidable cleaning must be taken into account. We investigated the filtration of fermentation broth and its components using tubular microfiltration and ultrafiltration membranes, and hollow-fiber ultrafiltration membranes, with cut-offs of 30 and 200 nm. The steady-state flux was limited by fouling under comparable wall shear stress conditions but increased when the wall shear stress was higher. Single-component filtration with two 30 nm tubular ultrafiltration membranes, whose average surface roughness ranged from 1.0 to 3.9 µm, showed that smoother surfaces experience less biomass fouling under more intense hydrodynamic conditions. Furthermore, we showed experimentally and by scanning electron microscopy in filtration with 30 nm tubular membranes that the thickness of the first separation layer is responsible for the degree of irreversible resistance caused by the deposition of organic material in the membrane pores. The thickness of this layer should therefore be minimized without compromising mechanical stability.

Recovery and Purification of Protein Aggregates From Cell Lysates Using Ceramic Membranes: Fouling Analysis and Modeling of Ultrafiltration

The characterization of membrane fouling provides valuable information about the performance and operational range of filtration processes. The range of operational parameters for the purification and concentration of protein aggregates from cell lysates by ultrafiltration is determined by evaluating the filtration resistances. We therefore investigated the cross-flow ultrafiltration of ovalbumin (OVA) aggregates with a mean size of 304 nm using a 50 nm cut-off ceramic membrane. We observed a 90% decline in flux within the first 10 min of filtration, demanding an in-depth analysis of membrane fouling. Resistance-in-series analysis revealed that the main filtration resistance originated from the cell lysate in the feed solution. Flux decline was monitored at different transmembrane pressures (TMPs) and concentrations for the most significant fouling phenomenon, indicating that the intermediate pore blocking model correlated best with the observed filtration data. The TMP for purification and concentration was set at 1.5 bar based on the prediction of a limited, mostly pressure-independent flux of 12 L·m−2·h−1 for solutions with an OVA aggregate concentration of 0.5 g·L−1. Higher pressure increased the filtration performance only slightly, but led to a linear increase in filtration resistance. A 10-fold variation in protein aggregate concentration strongly influenced filtration performance, with higher protein concentrations increasing the filtration resistance by 413% and causing an 85% decline in flux.

Dynamic Modeling Using Artificial Neural Network of Bacillus Velezensis Broth Cross-Flow Microfiltration Enhanced by Air-Sparging and Turbulence Promoter

Cross-flow microfiltration is a broadly accepted technique for separation of microbial biomass after the cultivation process. However, membrane fouling emerges as the main problem affecting permeate flux decline and separation process efficiency. Hydrodynamic methods, such as turbulence promoters and air sparging, were tested to improve permeate flux during microfiltration. In this study, a non-recurrent feed-forward artificial neural network (ANN) with one hidden layer was examined as a tool for microfiltration modeling using Bacillus velezensis cultivation broth as the feed mixture, while the Kenics static mixer and two-phase flow, as well as their combination, were used to improve permeate flux in microfiltration experiments. The results of this study have confirmed successful application of the ANN model for prediction of permeate flux during microfiltration of Bacillus velezensis cultivation broth with a coefficient of determination of 99.23% and absolute relative error less than 20% for over 95% of the predicted data. The optimal ANN topology was 5-13-1, trained by the Levenberg-Marquardt training algorithm and with hyperbolic sigmoid transfer function between the input and the hidden layer.