Thesis (M.Tech.: Chemical Engineering)-Dept. of Chemical Engineering, Durban University of Technology, 2005 1 v. (various pagings) / In bubble-less aeration oxygen diffuses through the membrane in a molecular form and dissolves in the liquid. Oxygen is fed through the lumen side of silicone rubber tube. On the outer surface of the membrane there is a boundary layer that is created by oxygen. This then gets transported to the bulk liquid by convective transport created by water circulation through the pump. The driving force of the convective transport is due to concentration difference between the dissolved oxygen in water and oxygen saturation concentration in water at a particular temperature and pressure. The design of a membrane aerated bioreactor needs an understanding of the factors that govern oxygen mass transfer. It is necessary to know the effects of operating conditions and design configurations. Although various methods of bubble-less aeration have been reported, there still exists a lack of knowledge on the immersed membrane systems. This study is aiming at contributing to the development of an immersed membrane bioreactor using silicone rubber tubular membrane as means of providing oxygen. The secondary objective was to investigate the influence that the operating conditions and module configuration have on the system behaviour. From the experimental study, the characteristic dissolved oxygen -time curve show that there is a saturation limit equivalent to the equilibrium dissolved oxygen concentration, after which there is no increase in dissolved oxygen with time. At ambient conditions the equilibrium dissolved oxygen is approximately 8 mg/L. This is when water is in contact with air at one atmospheric pressure. At the same conditions the equilibrium dissolved oxygen concentration when water is in contact with pure oxygen is approximately 40 mg/L. This is why all the experiments were conducted from 2mg/L dissolved oxygen concentration in water, to enable enough time to reach equilibrium so as to determine mass transfer coefficient. The most important parameters that were investigated to characterise the reactor were, oxygen supply pressure, crossflow velocity, temperature and module orientation. Observations from the experimental study indicated that when the system is controlled by pressure, crossflow does not have a significant effect on mass transfer. When the system is controlled by the convective transport from the membrane surface to the bulk liquid, pressure does not have a significant effect on mass transfer. All four effects that were investigated in the study are discussed.

The word cybernetics has its roots in the Greek word \kybernetes" or \steers-man" and was coined by Norbert Wiener in 1948 to describe \the science of control and communication, in the animal and the machine". The discipline focuses on the way various complex systems (animals/machines) steer towards/maintain their goals utilizing information, models and control actions in the face of various disturbances. For a given animal/machine, cybernetics considers all the possible behaviors that the animal/machine can exhibit and then enquires about the constraints that result in a particular behavior. The thesis focuses on the application of principles of cybernetics to the modeling and optimization of bioreactors and lies at the interface of systems engineering and biology. Specifically, it lies at the interface of control theory and the growth behavior exhibited by microorganisms. The hypothesis of the present work is that the principles and tools of control theory can give novel insights into the growth behavior of microorganisms and that the growth behavior exhibited by microorganisms can in turn provide insights for the development of principles and tools of control theory. Mathematical models for the growth of microorganisms such as stoichiometric, optimal and cybernetic assume that microorganisms have evolved to become optimal with respect to certain cellular goals or objectives. Typical cellular goals used in the literature are the maximization of instantaneous/short term objectives such biomass yield, instantaneous growth rate, instantaneous ATP production rate etc. Since microorganisms live in a dynamic world, it is expected that the microorganisms have evolved towards maximizing long term goals. In the literature, it is often assumed that the maximization of a short term cellular goal results in the maximization of the long term cellular goal. However, in the systems engineering literature, it has long been recognized that the maximization of a short term goal does not necessarily result in the maximization of the long term goal. For example, maximization of product production in a fed-batch bioreactor involves two separate phases: a first phase in which the growth of microorganisms is maximized and a second phase in which the production of product is maximized. An analogous situation arises when the bacterium E. coli passes through the digestive tract of mammals wherein it first encounters the sugar lactose in the proximal portions and the sugar maltose in the distal portions. Mitchell et al. (2009) have experimentally shown that when E. coli encounters the sugar lactose, it expresses the genes of maltose operons anticipatorily which reduces its growth rate on lactose. This regulatory strategy of E. coli has been termed asymmetric anticipatory regulation (AAR) and is shown to be beneficial for long term cellular fitness by Mitchell et al. (2009). The cybernetic modeling framework for the growth of microorganisms, developed by Ramakrishna and co-workers, is extended in the present thesis for modeling the AAR strategy of E. coli. The developed model accurately captures the experimental observations of the AAR phenomenon, reveals the inherent advantages of the cybernetic modeling framework over other frameworks in explaining the AAR phenomenon, while at the same time suggesting a scope for the generalization of the cybernetic framework. As cybernetics is interested in all the possible behaviors that a machine (which is, in the present case, microorganism) can exhibit, a rigorous analysis of the optimal dynamic growth behavior of microorganisms under various constraints is carried out next using the methods of optimal control theory. An optimal control problem is formulated using a generalized version of the unstructured Monod model with the objective of maximization of cellular concentration at a fixed final time. Optimal control analysis of the above problem reveals that the long term objective of maximization of cellular concentration at a final time is equivalent to maximization of instantaneous growth rate for the growth of microorganisms under various constraints in a two substrate batch environment. In addition, reformulation of the above optimal control problem together with its necessary conditions of optimality reveals the existence of generalized governing dynamic equations of the structured cybernetic modeling framework. The dynamic behavior of the generalized equations of the cybernetic modeling framework is analyzed further to gain insights into the growth of microorganisms. For growth of microorganisms on a single growth limiting carbon substrate, the analysis reveals that the cybernetic model exhibits linear growth behavior, similar to that of the unstructured Contois model at high cellular concentrations, under appropriate constraints. During the growth of microorganisms on multiple substitutable substrates, the analysis reveals the existence of simple correlations that quantitatively predict the mixed substrate maximum specific growth rate from single substrate maximum specific growth rates during simultaneous consumption of the substrates in several cases. Further analysis of the cybernetic model of the growth of S. cerevisiae on the mixture of glucose and galactose reveals that S. cerevisiae exhibits sub-optimal dynamic growth with a long diauxic lag phase and suggests the possibility for S. cerevisiae to grow optimally with a significantly reduced diauxic lag period. Since cybernetics is interested in understanding the constraints under which a particular machine (microorganism) exhibits a particular behavior, a methodology is then developed for inferring the internal constraints experienced by the microorganisms from experimental data. The methodology is used for inferring the internal constraints experienced by E. coli during its growth on the mixture of glycerol and lactose. An interesting question in the study of the growth behavior of microorganisms concerns the objective that the microorganisms optimize. Several studies aim to determine these cellular objectives experimentally. A similar question that is relevant to the optimization of fed-batch bioreactors is \what are the objectives that are to be optimized by the feed flow rate in various time intervals for the optimization of a final objective?" It was mentioned previously that the maximization of product production in a fed-batch bioreactor involves maximization of growth of microorganisms first and the maximization of product production later. However, such guidelines can only be stated for relatively simple bioreactor optimization problems and no such guidelines exist for sufficiently complex problems. For complex problems, the answer to the above question requires the formulation and solution of a genetic programming problem which can be quite challenging. An alternative numerical solution methodology is developed in the present thesis to address the above question. The solution methodology involves the specification of bioreactor objectives in terms of the bioreactor trajectory in the state space of substrate concentration-volume. The equivalent control law of the sliding mode control technique is used for finding the inlet feed ow rate that tracks the bioreactor trajectory accurately. The search for the best bioreactor trajectory is carried out using the stochastic search technique genetic algorithm. The effectiveness of the developed solution methodology in determining the optimal bioreactor trajectory is demonstrated using three challenging bioreactor optimization problems.

This thesis examined the use of two-phase partitioning bioreactors (TPPBs) for the biodegradation of poorly water-soluble compounds. TPPBs are stirred tank bioreactors composed of a biocatalyst-containing aqueous phase and an immiscible second phase containing large amounts of poorly water-soluble or toxic substrates. Degradation of the bioavailable substrate in the aqueous phase will result in equilibrium-driven partitioning of additional substrate from the immiscible phase into the aqueous phase, theoretically allowing for complete substrate degradation. Fundamental work was undertaken with the PCB-degrading organisms Burkholderia xenovorans LB400 in liquid-liquid and solid-liquid TPPBs. Initially biphenyl was used as the sole carbon source due to its hydrophobic nature and structural similarity to the environmentally relevant PCBs. The critical LogKO/W (octanol/water partitioning coefficient) of the organism was determined to be 5.5 and its growth kinetics on biphenyl were determined in a liquid-liquid TPPB. A polymer selection strategy for solid-liquid TPPBs was developed in the next chapter, and it was shown in the following chapter that biphenyl degradation in solid-liquid TPPBs was mass transfer limited, as described mathematically utilising the previously estimated microbial kinetics. The fundamental knowledge gained in the early chapters was then applied to the degradation of PCBs by the same organism. It was shown that the aqueous phase availability of PCBs is the rate-limiting step in biphasic bioreactors, and not the mass transfer rate. The low specific microbial degradation rates, resulting from substrate-limited growth were addressed with increased biomass concentrations; however, it was also found that an additional carbon source was required to maintain microbial activity over an extended period of time. Pyruvic acid was selected as a carbon source which, once added to actively PCB-degrading cells, maintained the cells’ activity towards PCBs and up to 85 % of 100 mg l-1 was degraded in 15 h. It was shown as the final contribution in this thesis that TPPBs can be combined with a PCB soil extraction step as a potential remediation scheme for PCB contaminated soil. PCBs were extracted from soil with polymer beads (up to 75 % removal), followed by biodegradation of the PCBs in a solid-liquid TPPB in which PCBs were delivered to the degrading organism from the same polymer. / Thesis (Ph.D, Chemical Engineering) -- Queen's University, 2007-08-07 16:11:00.494

L'épuisement annoncé dans les prochaines décennies des ressources fossiles qui fournissent actuellement plus de 70% du carburant consommé dans les transports terrestres, aériens et maritimes au niveau mondial, incite à l'identification et le développement de nouvelles sources d'énergies renouvelables. La production de biocarburants issue de l'exploitation de la biomasse représente une des voies de recherche les plus prometteuses. Si la première génération des biocarburants (production à partir de plantes sucrières, de céréales ou d'oléagineux) atteint ses limites (concurrence avec les usages alimentaires, en particulier), la deuxième génération, produite à partir de ressources carbonées non alimentaires (lignocellulosique, mélasse, vinasse...), pourrait prendre le relais, une fois que les procédés de conversion seront suffisamment maîtrisés. À plus long terme, une troisième génération pourrait voir le jour, qui reposerait sur l'exploitation de la biomasse marine (microalgues, en particulier) mais où de nombreux verrous restent toutefois à lever : optimisation des procédés de culture et de récolte, extraction à coût réduit, optimisation des voies métaboliques etc. Il est à retenir que la stratégie nationale de recherche et d'innovation (SNRI) a retenu quatre « domaines clés » pour l'énergie : le nucléaire, le solaire photovoltaïque, les biocarburants de deuxième génération et les énergies marines. Ceux-ci sont complétés, au nom de leur contribution potentielle à la lutte contre le changement climatique, par le stockage du CO2, la conversion de l'énergie (dont les piles à combustible) et l'hydrogène. Le présent projet de recherche s'intéresse à explorer des voies d'amélioration de l'efficacité de la biotransformation de matière organique non alimentaire de nature industrielle en biocarburants de deuxième génération. En particulier, on s'intéressera à deux aspects complémentaires : l'optimisation des organismes microbiens et des voies métaboliques pour l'amélioration du rendement biologique de fabrication de biocarburants ; l'optimisation des procédés de mise en culture des microorganismes et d'extraction des biocarburant. Le projet de thèse consiste à mettre en œuvre les biotechnologies blanches, la biologie de synthèse et le génie des procédés pour la caractérisation de souches bactériennes, de leurs voies métaboliques et de prototypes expérimentaux pour la fabrication de biocarburants, de méthane et d'hydrogène à partir de rejets provenant de l'industrie sucrière de La Réunion, à savoir la mélasse ou la vinasse. Ce projet permettrait d'envisager de nouvelles perspectives de valorisation pour ces déchets industriels et de participer à la construction, à terme, d'une industrie réunionnaise durable des biocarburants et de l'hydrogène. / Hydrogen is a candidate for the next generation fuel with a high energy density and an environment friendly behavior in the energy production phase. Micro-organism based biological production of hydrogen currently suffers low hydrogen production yields because the living cells must sustain different cellular activities other than the hydrogen production to survive. To circumvent this, a team have designed a synthetic cell-free system by combining 13 different enzymes to synthesize hydrogen from cellobiose. This assembly has better yield than microorganism-based systems. We used methods based on differential equations calculations to investigate how the initial conditions and the kinetic parameters of the enzymes influenced the productivity of a such system and, through simulations, to identify those conditions that would optimize hydrogen production starting with cellobiose as substrate. Further, if the kinetic parameters of the component enzymes of such a system are not known, we showed how, using artificial neural network, it is possible to identify alternative models that allow to have an idea of the kinetics of hydrogen production. During our study on the system using cellobiose, other cell-free assemblies were engineered to produce hydrogen from different raw materials. Interested in the reconstruction of synthetic systems, we decided to conceive various tools to help the automation of the assembly and the modelling of these new synthetic networks. This work demonstrates how modeling can help in designing and characterizing cell-free systems in synthetic biology.