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Microalgae cultivation offers a sustainable alternative to another production organisms that are used in biotechnological industry – since they are able to remove carbon dioxide from atmosphere and various nutrients from wastewater, converting them into various products. However, due to lack of efficient and cost-effective cultivation methods, the development of this branch of biotechnology is not as rapid as anticipated.
This thesis introduces a novel multiphase slug flow tubular photobioreactor as a potential solution to some of the aforementioned problems. The novel photobioreactor combines the advantages of slug flow regime and tubular photobioreactors: enhanced mass transfer and mixing rates as well as enlarged illumination area. The main goal of this thesis was the construction and implementation of this novel photobioreactor design. In order to achieve this, various experiments have been conducted, including toxicity assessment of organic solvents and hydrodynamics tests of the three-phase slug flow into long microchannels.
The toxicity assessment revealed that n-decane and sunflower oil are the most biocompatible of the tested solvents. It was also found that all the examined alkanes allow fairly stable slug flow generation in a 1mm ID capillary as opposed to sunflower oil, which was found not suitable for that capillary diameter, as it caused its blockage. The results of the final experiment reveal that there is still a lot of room for improvement in the novel photobioreactor concept, as it was found that the biomass concentration decreases over time of cultivation. It was hypothesized that the reason for the cell number decrease is the improved mixing and mass transfer rate that enhanced toxicity of the organic solvent.
The aim of the project was to produce, identify and quantify PHB. The bacterial strain Azohydromonas lata was cultured in multiple batch processes and the accumulation of biopolymer was observed. The following results were obtained after 50 hours of a 3L batch fermentation: a dry cell weight of 3.197 g/L, a PHB concentration of 1.939 g/L and a PHB content of 60.65%. Subsequently, the same set-up was extrapolated to an 8L batch fermentation, which yielded in a dry cell weight, PHB concentration and PHB content of 2.964 g/L, 1.090 g/L and 36.79%, respectively. The synthesized biopolymer was recovered from the bacterial cells in two ways, namely by SDS digestion and by chloroform Soxhlet extraction. Afterwards, three analytical methods were tested for detecting and quantifying the produced PHB. Fermentation samples stained with the Nile Red dye were analysed with both fluorescence microscopy and spectrofluorometry, and the presence of PHB granules could be confirmed. Both methods showed promising results, but further optimization is still necessary. Finally, the chloroform extracted PHB samples were successfully analysed using HPLC. The HPLC method proved to reliably identify and to relatively accurately quantify the recovered PHB.
Diese Bachelorarbeit gibt einen Überblick über die Verbesserungen und Optimierungen am erst 2018 neu aufgesetzten Reklamationsprozess sowie die daraus resultierenden Korrekturmaßnahmen unter Einbezug der DIN ISO 10002 am Beispiel der Garlock GmbH in Neuss. Hierzu wurden zunächst die Anforderungsprofile der beteiligten Parteien, was die Reklamationsbearbeitung betrifft, dargestellt. Ebenso wurde durch mehrfaches Durchlaufen des gesamten Prozesses ein Ist-Soll-Vergleich durchgeführt aus dem Korrekturmaßnahmen abgeleitet wurden. Abschließend zeigt der Autor die abgeleiteten Korrekturen und Verbesserungen am gesamten Reklamationsprozess auf, die neben einer schnelleren Abarbeitung von Reklamationen auch die Implementierung der Software QlikView zur Datenbankanalyse sowie grundsätzliche Anpassungen am ERP-System Oracle beinhaltet.
This review paper focused on the potential uses of nut and fruit shells. Based on the information from several kinds of literature, the composition of nut and fruit shells were studied, and the shells demonstrated the possibility to produce a wide range of materials such as bio-adsorbent like activated carbon; construction materials like concrete block, earth block, bricks, cement, etc.; and bio-composites like WPC, bio-plastic, etc. Besides these antimicrobials, drugs, insecticides, nanoparticles, and impact-resistant materials could be prepared from nut and fruit shells. Moreover, the production process for these materials was explained in the later part of the paper. Also, the yield, cost, and performance of materials prepared from nut and fruit shells were discussed and found that some of the products were as good as commercially available materials. The environmental impact being one of the important parts, materials from nut and fruit shells had a beneficial impact on nature. However, the entire life cycle assessment suggested that better techniques are required to attain a lower negative impact on the ecosystem. Since nut and fruit shells were the easy and low-cost raw material, they had a greater chance of replacing other expensive, non-environment-friendly raw materials and their products. Overall, this research shed light on the material use of nut and fruit shells along with its benefits; production process; material yield, cost, and performance; with possible implications and recommendations that can lead to better utilization of biological resources.
A clean energy future based on a hydrogen economy has been proposed as a feasible alternative to the current combustion of fossil fuels to reduce CO2 and other greenhouse gas (GHG) emissions. However, hydrogen’s “clean” reputation is questionable due to its main production method of steam methane reforming (SMR), which produces large quantities of CO2 emissions. To abide by recent international regulations, the production of hydrogen needs an immediate transition to low-emission production methods. A promising solution is the thermo-catalytic decomposition of methane (TCMD), which thermally decomposes methane into hydrogen gas and solid carbon without any direct GHG emissions. The problem with this process is that the catalyst deactivates quickly and therefore must be replaced periodically for sustained hydrogen yields. This results in high catalyst turnover costs, which is the main bottleneck in the successful commercialisation of this process. By developing a simplified model using the most commercially viable parameters and linking the turnover costs with the deactivation of the catalyst, this study aimed to accelerate the adoption of the TCMD process by better enabling companies to analyse the feasibility of their potential low-emission TCMD solutions.
The most commercially viable solution featured the use of a fluidised bed reactor (FBR) for continuous operation with an iron-based catalyst due to their low-cost. Catalyst regeneration was found to be ineffective and the best method for mitigating catalyst deactivation was the optimisation of the process conditions. A simplified mathematical model was then constructed to enable this adjustment to maximise the production of hydrogen and minimise the turnover costs. This model was based on the ideal continuous stirred tank reactor but incorporated the fluidising behaviour through several variables including the development of the novel “Fluidisation Factor”. An optimisation ratio was also developed to quantify the simulation results and obtain the optimal conditions.
The results showed that the ideal conditions for this process was at the highest temperature before the catalyst starts to sinter (≈950ºC) and at the maximum pressure. The largest catalyst particle size of 150 𝜇m and the maximum amount of catalyst was found to allow for higher fluidisation velocities and to delay the deactivation time respectively. The inlet gas velocity and the catalyst activity limit were found to be highly dependent on the hydrogen production rate and therefore due to the conditions used in this study the optimum inlet gas velocity was 10% of the fluidisation velocity range (and composed of pure methane), whilst the optimum activity limit was at 22% activity. Lastly, a comparison of the heating method found that controlled heating was more suitable than constant heating due to the stable temperatures during deactivation, which prevent catalyst sintering. Comparing the optimised results from this study with the SMR production method found that the estimated catalyst turnover costs were 10¢/kg H2 and 18¢/kg H2 respectively. This demonstrates that the simplified model developed in this work can better enable companies to optimise and assess the feasibility of their proposed TCMD solutions and help transition their hydrogen production processes to cleaner alternatives.
Oloids are said to be very energy efficient stirrers, generating low shear rates while providing good mixing for small-to-medium-sized water bodies, which would make them optimal for decreasing energy cost in large installations as well as protecting shear-sensitive microorganisms. Yet oloids are relatively obscure and there are few works dealing with detailed analysis of their flow profile and comparison against standard stirrers. This work tries to add to this topic. In this thesis the potential of deploying oloid stirrers in bioprocesses and wastewater treatment in general is to be probed by computational fluid simulation and compared against a propeller and a Smith turbine (modification of a Rushton turbine). Parameters of interest are flow and pressure profile as well as shear stress.
The results show that oloids have much lower shear at their surface compared to both propeller and Smith turbine. The flow is pulsating and in three dimensions, and while the results need verification, it seems like the oloid is well usable for agitation in ungassed bioprocesses, because it can mix a small water body at much lower stirrer speeds than rotating impellers. The application in an actively gassed vessel and whether it is usable for active gas dispersion has not been analysed. Based on data generated by others, the oloid can also be used efficiently as surface aerator in natural open water bodies.
Zielstellung: Das Ziel dieser Arbeit war es, eine Methode zur Identifizierung von Mikroorganismen über Mikro-Raman-Spektroskopie zu entwickeln. Dafür musste zunächst eine Methode gefunden werden, um Spektren verschiedener Mikroorganismen mit ausreichender Qualität zu erhalten. Im Anschluss sollte die Datensammlung erfolgen, bei der möglichst viele repräsentative Spektren gesammelt werden. Mit den Daten mussten danach Modelle zur Vorhersage unbekannter Raman-Spektren entwickelt werden, was eine entsprechende Datenvorbehandlung voraussetzte. Um die Praxistauglichkeit der Modelle zu prüfen, sollten diese auf Spektren von Proben angewandt werden, die nicht in den Kalibrationssets enthalten waren. Neben der Entwicklung der Methode und der Vorhersagemodelle, sollten auch verschiedene Einflüsse der Analysebedingungen berücksichtigt werden.
Methoden: Neun verschiedene Mikroorganismen, die aus kryokonservierten Reinkulturen stammten, wurden bei 30 °C für 24 Stunden auf Trypton Soja Agar (TSA) bebrütet. Die Spektrenaufzeichnung erfolgte bei einer Anregung von 633 nm über ein konfokales Raman-Mikroskop der Firma Renishaw. Sowohl die Datenvorbehandlung (Basislinienkorrektur, Glättung, Normalisierung, Hauptkomponentenanalyse (PCA)), als auch die Modellentwicklung, erfolgte über die Software MATLAB. Es wurden verschiedene Klassifikationsverfahren angewandt, um ein Modell mit möglichst guter Leistung zu finden.
Ergebnisse: Für die Entwicklung der Kalibrationsmodelle wurden insgesamt 2953 Raman-Spektren von neun verschiedenen Mikroorganismen gesammelt. Störungen durch Fluoreszenz wurden durch Vorbestrahlung von bis zu 15 Minuten ausgebrannt. Die Modelle basierend auf der Quadratischen Diskriminanzanalyse (QDA), dem k-Nächster-Nachbar-Algorithmus (kNN) und der Support Vector Maschine (SVM), wurden mit verschiedener Anzahl an Hauptkomponenten und einer fünffachen Kreuzvalidierung erstellt. Die theoretischen Vorhersagegüten belaufen sich bei den genauesten Modellen auf 99,0 % (QDA), 99,1 % (kNN) und 99,7 % (SVM). Für die praktische Validierung wurden für jeden Mikroorganismus 100 weitere „unbekannte“ Spektren gesammelt. Die Vorhersagegenauigkeiten in der Praxis belaufen sich auf 98,1 % (QDA), 97,1 % (kNN) und 97,0 % (SVM).
Diskussion: Eine zuverlässige Identifizierung der in dieser Arbeit untersuchten Mikroorganismen konnte über alle verwendeten Klassifikationsverfahren erreicht werden. Auf Stamm-ebene erzielt die SVM in der Praxis die genauesten Ergebnisse, jedoch nicht bei den restlichen Mikroorganismen. Die QDA erzielt in der Praxis etwas genauere Vorhersagen als das kNN-Modell, jedoch basiert das kNN-Modell mit der besten Leistung auf den wenigsten Hauptkomponenten. Dies kann als Vorteil angesehen werden, da weniger Dimensionen zur erfolgreichen Klassifizierung in der Regel robustere Modelle in der Praxis bedeuten.
Bei der industriellen Saftherstellung fallen große Mengen an Orangenschalen als Abfallprodukte an. Hierbei stellt sich die Frage: Wie können diese Stoffe wirtschaftlich und ökologisch zur Ölgewinnung verwertet werden, sodass ein nutzbares Endprodukt entsteht?
Das Ziel ist es, ein Orangenöl herzustellen, mit einem hohen Einzelstoffvorkommen an Limonen, mithilfe der Wasserdampfdestillation und einer speziellen eigenen Trennmethodik zu entwickeln. Die Trennung von fluiden Stoffen wird erläutert und sichtbar dargestellt. Während des Destillationsprozesses entstehen unterschiedliche Heizleistungen, die im Verlauf dieser Arbeit zur Ölausbeute zum Zeitfaktor angepasst werden. Die erstellten Diagramme geben Aufschluss über die Dauer und die unterschiedlichen Heizleistungseinstellungen. Eine Trennung der Phasen während des Destillierprozesses wird detailliert dargestellt.
Das hier verwendete Trennverfahren könnte zu weiteren Forschungsansätzen dienen und weiter ausgebaut werden. Das bedeutet, dass die Destillationszeit anhand des verwendeten Verfahrens eingegrenzt werden kann. Die verminderte Destillationszeit, führt zu Prozessoptimierung, welches durch die Energieeinsparung Produktionskosten senken könnte. Die gewonnene Ölausbeute in finanzieller und ökologischer Sichtweise könnte einen industriellen Nutzen darstellen.
This bachelor thesis deals with contaminants in the food industry and presents them in a hazard analysis and risk assessment according to the specifications of Sauels Frische Wurst GmbH Fleischwaren & Co. KG. Allergenic, microbiological, chemical, bio-chemical and physical contaminants were considered.
The allergenic contaminants include gluten, crustaceans and molluscs, fish, eggs, soy, milk, nuts, peanuts and celery. The microbiological ones are the apathogenic microorganisms yeasts and molds and the pathogenic microorganisms are Bacillus cereus, Clostridium perfingens, Escherichia coli, Yersinia enterocolitica, Campylobacter jejuni, Listeria monocytogenes, Toxoplasma gondii and Staphylococus areus. Hard plastic and metal were evaluated as possible foreign bodies. In the chemistry section, intentional radiation, acrylamide, mercury, bisphenol A, and ethylene oxide were addressed. The bio-chemical contaminant considered was aflatoxin. The following contaminants were evaluated as highly critical. Whilst all allergens pose a risk due to their harmful potential, it is the incorrect labeling which constitutes the risk from the producers perspective. Among microbiological contaminants, Listeria monocytogenes and Escherichia coli are the microorganisms with the highest risk. This is based on the fact that these are typical recontamination bacteria. The physical contaminants described all recieved the same rating in the hazard analysis and risk assessment. The actual nature of a foreign body determines the hazard in each individual case in the assessment. Ethylene oxide has been evaluated as the most critical in the analysis among the chemical contaminants, because of its high probability of occurrence, which is based on the calculated recall rate and its carcinogenicity. The highest risk of the bio-chemical contaminants comes from aflatoxins, as this is the only mycotoxin that is pathogenic.
The application of hazard analysis and risk assessment must take into account company-specific factors. New scientific findings, detection methods and other relevant contaminants must be continuously incorporated into the analysis.
The identification and classification of microorganisms remains a challenge in many areas, especially considering time and cost-efficiency. Fast, reliable and cheap methods are of great interest for research, industry and health care. Raman spectroscopy is a method that fulfills these criteria and, in this work, we aim to show its effectiveness to classify a selection of microorganisms. Using a standardized protocol, eighteen microorganisms were measured using Raman spectroscopy and classified with several types of mathematical classification models, including linear discriminant analysis, support vector machines and convolutional neural networks. To prepare the measured spectral data for classification several steps for the data evaluation and transformation were applied and their effectiveness for removing noise and other interferences evaluated. The resulting predictions outcomes were compared to select the most efficient model, showing that with an overall true positive prediction rate of 86.87 % the convolutional neural network performed the best. Further inspection of the results shows issues with the measurements of selected organisms, indicating that an improved measurement protocol is required to achieve proper predictions. Overall this work shows that Raman spectroscopy in combination with mathematical classification models is a viable and fast method for classification of microorganisms.