L’incorporation de silice, obtenue par un procédé de précipitation en milieu aqueux, à la bande de roulement des pneumatiques a permis d’en réduire significativement la résistance au roulement et par conséquent, l’impact environnemental. L’efficacité de la silice précipitée en tant que charge de renfort est liée à la présence d’agrégats nanométriques au sein de ce matériau et à son interaction avec l’élastomère du pneumatique. La maîtrise de la morphologie des agrégats est donc un levier pour le développement de silices plus performantes. Dans ce contexte, la présente étude porte sur le développement d’un modèle prédictif de la formation de l’agrégat de silice au cours de la précipitation. Un suivi par turbidimétrie en ligne et par DLS a permis d’illustrer l’influence critique des paramètres de synthèse sur la cinétique d’agrégation. Un modèle optique basé sur les propriétés diffusantes des objets fractals a été développé pour extraire des informations morphologiques sur l’agrégat au cours de sa construction à partir des spectres de turbidité expérimentaux. Les résultats semblent indiquer une densification de la structure au fur et à mesure que se déroule l’agrégation. Les analyses de porosimétrie azote et mercure menées sur les produits finaux, obtenus après séchage, ont quant à elles mis en évidence des différences texturales qui ont pu être mises en lien avec la cinétique d’agrégation. L’ensemble de ces informations a été repris dans un bilan de population permettant de traiter à la fois la croissance et l’agrégation des particules de silice ainsi que de simuler les propriétés optiques de la suspension. / Tires manufactured with precipitated silica instead of carbon black present a significantly lower rolling resistance and are therefore more environmentally friendly. Existence of nanometric aggregates inside the precipitated silica is responsible for its efficiency as a reinforcing filler. This level of structure deeply affects the quality of the interactions between silica and the rubber of the tire tread. Gaining control over the morphology of the aggregates could thus be a way to produce silica even more suited to this application.The aim of the present study is to develop a theoretical model able to predict the formation of silica aggregates during the precipitation process. Critical influence of the synthesis parameters on the aggregation kinetics were evidenced by DLS and online turbidimetry measurements. Morphological parameters of the expanding aggregates could be extracted from the experimental turbidity spectra thanks to a fractal scattering optical model. The observed trend suggested a densification of the aggregates over time. Nitrogen and mercury porosimetry analyses were carried out on the dried powders obtained at the end of the precipitation. Differences between the characterized samples could be related to the variations in their aggregation kinetics. Finally, a population balance model was developed. A specific feature of our model is that it is able to take into account both growth and aggregation of silica particles as well as to simulate their optical properties.

Plant derived natural products represent some of the most effective anti-cancer and anti-infectious disease pharmaceuticals available today. However, uncertainty regarding the feasibility of commercial supply due to the limited availability of many plants in nature has resulted in a dramatic reduction in the use of natural products as leads in modern drug discovery. Plant cell suspension culture, consisting of dedifferentiated plant cells grown in vitro and amenable to large scale industrial biotechnology processes, is a production alternative which promises renewable and economical supply of these important drugs. The widespread application of this technology is limited by low product yields, slow growth rates, challenges in scale-up, and above all, variability in these properties, which is poorly understood. Plant cells grow as aggregates in suspension cultures ranging from two to thousands of cells (less than 100 micron to well over 2 mm). Aggregates have long been identified as an important feature of plant cell culture systems, as they create microenvironments for individual cells with respect to nutrient limitations, cell-cell signaling, and applied shear in the in vitro environment. Despite its purported significance, a rigorous engineering analysis of aggregation has remained elusive. In this thesis, aggregation was characterized, analyzed, and modeled in Taxus suspension cultures, which produce the anti-cancer drug paclitaxel. A technique was developed to reliably and routinely measure aggregate size using a Coulter counter. The analysis of aggregate size as a process variable was then used to evaluate the effect of aggregation on process performance, and the analysis of single cells isolated from different sized aggregates was used to understand the effect of aggregation on cellular metabolism and heterogeneity. Process characterization studies indicated that aggregate size changed over a batch cycle as well as from batch to batch, so a population balance equation model was developed to describe and predict these changes in the aggregate size distribution. This multi-scale engineering approach towards understanding plant cell aggregation serves as an important step in the development of rational strategies aimed at controlling the process variability which has heretofore limited the application of plant cell culture technology.

Controlling the size and size distribution of colloidal nanoparticles have gained extraordinary attention as their physical and chemical properties are strongly affected by size. Ligands are widely used to control the size and size distribution of nanoparticles; however, their exact roles in controlling the nanoparticle size distribution and the way they affect the nucleation and growth kinetics are poorly understood. Therefore, understanding the nucleation and growth mechanisms and developing theoretical/modeling framework will pave the way towards controlled synthesis of colloidal nanoparticles with desired sizes and polydispersity. This dissertation focuses on identifying the possible roles of ligands and size on the kinetics of nanoparticle formation and growth using in-situ characterization tools such as small-angle X-ray scattering (SAXS) and kinetic modeling. The presented work further focuses on developing kinetic models to capture the main nucleation and growth reactions and examines how ligand-metal interactions could potentially alter the rate of nucleation and growth rates, and consequently the nanoparticle size distribution. Additionally, this work highlights the importance of using multi-observables including the concentration of nanoparticles, size and/or precursor consumption, and polydispersity to differentiate between different nucleation and growth models and extract accurate information on the rates of nanoparticle nucleation and growth. Specifically, during the formation and growth of colloidal nanoparticles, complex reactions are occurring and as such nucleation and growth can take place through various reaction pathways. Therefore, sensitivity analysis was applied to effectively compare different nucleation and growth models and identify the most important reactions and obtain a reduced model (e.g. a minimalistic model) required for efficient data analysis. In the following chapters, a more sophisticated modeling approach is presented (population balance model) capable of capturing the average-properties of nanoparticle size distribution. PBM allows us to predict the growth rate of nanoparticles of different sizes, the ligand surface coverage for each individual size, and the parameters involved in altering the size distribution. Additionally, thermodynamic calculations of nanoparticle growth and ligand-metal binding as a function of size and ligand surface coverage were conducted to further shed light on the kinetics of nanoparticle formation and growth. The combination of kinetic modeling, in-situ SAXS and thermodynamic calculations can significantly advance the understanding of nucleation and growth mechanisms and guide toward controlling size and polydispersity. / Doctor of Philosophy / The synthesis of colloidal metal nanoparticles with superior control over size and size distribution, and has attracted much attention given the wide applications of these nanomaterials in the fields of catalysis, photonics, and electronics. Obtaining nanoparticles with desired sizes and polydispersity is vital for enhancing the consistency and performance for specific applications (e.g., catalytic converters for automotive emission). Ligands are often employed to prevent agglomeration and also control the nanoparticle size and size distribution. Ligands can affect the precursor reactivity and therefore the reduction/nucleation by binding with the metal precursor. Nucleation refers to the assimilation of few atoms to form initial nuclei acting as templates for nanoparticle growth. Additionally, ligands can bind with the nanoparticle surface sites and change the rate of surface growth and therefore the final nanoparticle size. Despite strong effects of ligands in the colloidal nanoparticle synthesis, their exact role in the nucleation and growth kinetics is yet to be identified. Additionally, nucleation and growth models capable of unraveling the underlying mechanisms of nucleation and growth in the presence of ligands are still lacking in the literature. Therefore, obtaining nanoparticles with desired sizes and polydispersity mostly relies on trial-and-error approach making the synthesis costly and inefficient. As such, developing models capable of predicting suitable synthesis conditions is contingent upon understanding the chemistry and mechanism involved during nanoparticles formation. Therefore, in this study, novel kinetic models were developed to capture the nucleation and growth kinetics of colloidal metal nanoparticles under different synthetic conditions (different types of solvents, different concentrations of ligand and metal). In-situ SAXS was further employed to measure the average diameter, concentration of nanoparticles, and polydispersity during the synthesis and extract the nucleation and growth rates (evolution of concentration of nanoparticles and size). First, an average-property model was developed to account for ligand-metal bindings and capture the size and concentration of nanoparticles during the synthesis. Then, a more complex modeling approach; PBM, accompanied by the thermodynamic calculations of surface growth and ligand-nanoparticle binding enthalpies was implemented to capture the size distribution. As it will be shown later, the determination of the underlying mechanisms resulted in a highly predictive kinetic model capable of predicting the synthetic conditions to obtain nanoparticles with desired sizes. The proposed methodology can serve as a powerful tool to synthesize nanoparticles with specific sizes and polydispersity.

Yes / Twin-screw granulation has emerged as a key process in powder processing industries and in the pharmaceutical sector to produce granules with controlled properties. This comprehensive review provides an overview of the simulation techniques and approaches that have been employed in the study of twin-screw granulation processes. This review discusses the major aspects of the twin-screw granulation process which include the fundamental principles of twin-screw granulation, equipment design, process parameters, and simulation methodologies. It highlights the importance of operating conditions and formulation designs in powder flow dynamics, mixing behaviour, and particle interactions within the twin-screw granulator for enhancing product quality and process efficiency. Simulation techniques such as the population balance model (PBM), computational fluid dynamics (CFD), the discrete element method (DEM), process modelling software (PMS), and other coupled techniques are critically discussed with a focus on simulating twin-screw granulation processes. This paper examines the challenges and limitations associated with each simulation approach and provides insights into future research directions. Overall, this article serves as a valuable resource for researchers who intend to develop their understanding of twin-screw granulation and provides insights into the various techniques and approaches available for simulating the twin-screw granulation process.

La simulation de réacteurs à bulles en régime industriel est un grand défi. L'objectif principal de ce travail est la prédiction de la taille des bulles à l’aide d’un modèle numérique de bilan de population, basé sur la modélisation des phénomènes de brisure et de coalescence, et pouvant être couplé aux conditions hydrodynamiques présentes dans les réacteurs. Différentes données expérimentales sont obtenues pour valider le modèle. La taille des bulles est mesurée à l'aide d'une technique innovante de corrélation croisée. Les essais, réalisés en eau du réseau (partiellement contaminée) et en eau déminéralisée avec ajout éventuel d'éthanol, montrent que les additifs réduisent la coalescence et diminuent la taille moyenne des bulles. Deux distributeurs du gaz différents sont utilisés pour découpler l'étude de la brisure et de la coalescence. Les données expérimentales sont utilisées initialement pour valider des simulations CFD 3D transitoires Eulériennes-Eulériennes. La loi de traînée est corrigée par un facteur de swarm pour intégrer l’effet d’une fraction de gaz élevée. Différents modèles de turbulence sont testés. La contribution de la turbulence induite par les sillages de bulles au mélange de scalaires est évaluée. Enfin, pour prédire la taille des bulles, un bilan de population est couplé au modèle hydrodynamique préalablement validé et est résolu par la méthode de quadrature des moments (QMOM). Un set original de kernels de brisure et coalescence est proposé, capable de prédire la taille des bulles pour différentes conditions opératoires. Le comportement du modèle lors de l’extrapolation des réacteurs est également examiné / The simulation of bubble column reactors under industrial operating conditions is an exciting challenge. The main objective of this work is to predict the bubble size, in turn interconnected to the reactor hydrodynamic conditions, with computational models, by modelling bubble breakage and coalescence. Experimental data is collected for model validation, including bubble size measurements with an innovative cross-correlation technique. Experiments are carried out with tap water and demineralized water, with or without the addition of ethanol, and gathered results show that additives reduce coalescence and lower the mean bubble size. Two different spargers are used, in order to decouple the investigation of breakage and coalescence. The experimental data set is used to validate out unsteady three-dimensional Eulerian-Eulerian CFD simulations. A drag law for oblate bubbles is considered, together with a swarm factor, that accounts for the swarm effect. Several turbulence models are tested. The contribution of bubble induced turbulence (BIT) to scalar mixing is assessed. To predict bubble size, a population balance model is coupled to the hydrodynamic model and is solved with the quadrature method of moments. A set of breakage and coalescence kernels is proposed, capable of predicting the bubble size for different operating conditions. Scale-up effects are also investigated

The early steps of activation are crucial in deciding the fate of T-cells leading to the proliferation. These steps strongly depend on the initial conditions, especially the avidity of the T-cell receptor for the specific ligand and the concentration of this ligand. The recognition induces a rapid decrease of membrane TCR-CD3 complexes inside the T-cell, then the up-regulation of CD25 and then CD25-IL2 binding which down-regulates into the T-cell. This process can be monitored by flow cytometry technique. We propose several models based on the level of complexity by using population balance modeling technique to study the dynamics of T-cells population density during the activation process. These models provide us a relation between the population of T-cells with their intracellular and extracellular components. Moreover, the hypotheses are proposed for the activation process of daughter T-cells after proliferation. The corresponding population balance equations (PBEs) include reaction term (i.e. assimilated as growth term) and activation term (i.e. assimilated as nucleation term). Further the PBEs are solved by newly developed method that is validated against analytical method wherever possible and various approximate techniques available in the literature.

L'objectif de la thèse est d'étudier l'évolution de la morphologie de flocs soumis à des conditions hydrodynamiques turbulentes. A cet effet, des expériences de floculation par neutralisation de charge en présence de sels sont mises en œuvre, dans deux géométries de réacteurs, sous différentes conditions hydrodynamiques. Dans un premier temps, des expériences de floculation sont réalisées sous conditions hydrodynamiques fixées. D'une part, un suivi en ligne de la floculation de microsphères de latex en jar test est effectué par granulométrie à diffraction laser. Plus le taux de cisaillement moyen G caractéristique de l'hydrodynamique globale du réacteur est élevé, plus la cinétique de floculation est rapide ; la distribution de diamètres équivalents demeure alors monomodale et présente une autosimilarité. L'évolution de la dimension fractale Df représentative de l'ensemble de la population montre une compaction des agrégats au cours du temps, d'autant plus marquée que G est élevé. D'autre part, la caractérisation de nombreuses propriétés morphologiques de flocs de bentonite formés dans un réacteur de Taylor-Couette est effectuée par analyse d'images (méthode in situ non intrusive). Un grand nombre d'images sont acquises, permettant de déterminer avec précision l'évolution temporelle des distributions des propriétés morphologiques ainsi que de leurs moments. Bien que les caractéristiques de taille et de forme soient liées, leur dépendance à l'hydrodynamique n'est pas la même. Des flocs produits dans des conditions hydrodynamiques différentes, et dont les distributions de tailles sont similaires, présentent des formes différentes. Le rayon de giration des flocs est corrélé à la micro-échelle de Kolmogorov tandis que leur circularité semble corrélée à la vitesse de rotation du cylindre interne. Dans un second temps, un séquençage des conditions hydrodynamiques consistant en deux cycles de rupture-refloculation est effectué après une première étape de floculation dans le réacteur de Taylor-Couette. L'irréversibilité après rupture est montrée. La refloculation produit des flocs de tailles plus réduites et de formes plus régulières et l'état stationnaire est atteint plus rapidement, sans phase de restructuration significative, contrairement à ce qui est observé après la première étape de croissance. Si la contrainte appliquée lors de la rupture est suffisamment élevée, le second cycle a peu d'influence sur la population de flocs. En revanche si la contrainte de rupture est moins importante, chacun des deux cycles forme des flocs plus compacts et plus lisses, mais aussi plus petits. L'étape de rupture produit des floculi qui deviennent alors les briques élémentaires pour l'étape de refloculation suivante. La taille des flocs obtenus lors de ces étapes de refloculation est limitée par l'hydrodynamique, mais leur structure est déterminée par la taille et la structure des floculi. Enfin, la problématique de la modélisation de la floculation par Bilan de Population (BP) est abordée. Une équation de BP tenant compte de la dimension fractale est formulée pour modéliser les expériences de floculation de latex en jar test. Les seuls paramètres variables du modèle sont les valeurs expérimentales de G et Df. Basée sur la méthode de la quadrature des moments (QMOM), la résolution du BP permet de décrire convenablement l'évolution des six premiers moments de la distribution de tailles expérimentale et de certains diamètres caractéristiques, aux différentes conditions hydrodynamiques mises en œuvre. / The objective of this work is to study the time evolution of floc morphology under turbulent hydrodynamic conditions. For this purpose, flocculation by charge neutralization in the presence of salts is realized within two reactor geometries under various hydrodynamic conditions. As a first step, flocculation experiments under constant hydrodynamic conditions were realized. On the one hand, a laser light scattering technique is used for an on-line monitoring of latex microsphere flocculation conducted in a jar. The higher the global shear gradient G, the faster the flocculation kinetics, and thus the equivalent diameter distribution tends to keep monomodal and autosimilar. The time evolution of the fractal dimension Df, representative for the whole population, shows that aggregates get more compact with time, and this trend is more pronounced when G is higher. . On the other hand, bentonite flocculation is realized in a Taylor-Couette reactor. Various morphological properties are measured by an in situ non-intrusive method of image acquisition and analysis. Each measurement consists of a large number of images, allowing the precise calculation of property distributions and their moments over time. Although size and shape are obviously correlated, their dependency to hydrodynamics is different. Flocs of similar sizes produced under different hydrodynamic conditions exhibit different shapes. The sizes are calibrated by the turbulence as the double radius of gyration is close to Kolmogorov microscale, whereas the circularity seems correlated to the rotation speed. As a second step, a hydrodynamic sequencing is imposed in the Taylor-Couette reactor, in order to realize two breakup and reflocculation cycles after a first flocculation phase. The irreversibility is shown. Reflocculation after breakup produces smaller sizes, more regular shapes, and the steady state is reached faster since there is no restructuration phase such as the one observed after the initial growth step. When the breakup shear is high enough, the second cycle has very little impact. However, if the breakup shear is lower, each of the two cycles produces more compact and smoother, but also smaller flocs. The breakup step produces flocculi that are the building blocks for the next re-flocculation step. The, floc size is conditioned by hydrodynamics, whereas floc structure is determined by flocculi size and structure. Finally, the issue of modelling is addressed. A population balance (PB) equation accounting for the fractal dimension is formulated, in order to model the latex flocculation experiments. The only varying model parameters are the experimental values of G and Df. The PB, solved using the quadrature method of moments, allows to adequately describe the temporal evolution of the first six moments of the experimental distribution obtained under three hydrodynamic conditions.

Master of Science / Department of Mechanical and Nuclear Engineering / Xiao J. Xin / Energy consumption due to dairy production constitutes 10% of all energy usage in the U.S. Food Industry. Improving energy efficiency in food refrigeration and freezing plays an important role in meeting the energy challenges of today. Freezing and hardening are important but energy-intensive steps in ice cream manufacturing. This thesis presents a series of models to address these issues. The first step taken to model energy consumption was to create a temperature-dependent ice cream material using empirical properties available in the literature. The homogeneous ice cream material is validated using finite element analysis (FEA) and previously published experimental findings. The validated model is then used to study the efficiency of various package configurations in the ice cream hardening process. The next step taken is to consider product quality by modeling the ice crystal size distribution (CSD) throughout the hardening process. This is achieved through the use of population balance equations (PBE). Crystal size and corresponding hardened ice cream coarseness can be predicted through the PBE model presented in this thesis. The crystallization results are validated through previous experimental study. After the hardening studies are presented, the topic of continuous freezing is discussed. The actual ice cream continuous freezing process is inherently complex, and therefore simplifying assumptions are utilized in this work. Simulation is achieved through combined computational fluid dynamics (CFD) and PBE modeling of a sucrose solution. By assuming constant fluid viscosity, a two-dimensional cross section is able to be employed by the model. The results from this thesis provide a practical advancement of previous ice cream simulations and lay the groundwork for future studies.

Fossil fuel is an important energy source, but is unavoidabiy running out. Since the cellulosic material is the most abundant source of organic matter, the ethanol, which is produced from cellulosic waste materials, is gaining more and more attention. These materials are cheap, renewable and their availability makes them superior compared to other raw materials. The cellulose must be hydrolyzed to glucose before it can be fermented to ethanol. The enzymatic hydrolysis of cellulose using cellulase enzymes is the most widely used method. The production cost of cellulase enzymes is the major cost in ethanol manufacture. To optimize the cost of ethanol production, enzyme stability needs to be improved through maintaining the activity of the enzymes and by optimizing the production of the cellulase. The aim of researchers, engineers and industrials is to get more biomass for the same cost. The filamentous fungus Trichoderma reesei has a long history in the production of the cellulase enzymes. This production can be influenced strongly by varying the growth media and culture conditions (pH, temperature, DO, agitation,... ). At present, it is my opinion that no modelling study has included both the hydrodynamic and kinetic aspects to investigate the effect of shear and mass transfer on the morphology of microorganisms that influence the rheology of the broth and production of cellulase. This thesis presents the development of a mathematical model for cellulase production and the growth of biomass in an airlift bioreactor. The kinetic model is coupled with the methodology of two-phase flow using mathematical models based on the bubble break-up and coalescence to predict mass transfer rate, which is one of the critical factor in the fermentation. A comparison between the results obtained by the developed model and the experimental data is given and discussed. The design proposed for the airlift geometry by Ahamed and Vermette enables us to get a high mass transfer and production rate. The results are very promising with respect to the potential of such a model for industrial use as a prediction tool, and even for design.

Les premières étapes d’activation des lymphocytes T sont cruciales pour déterminer leur comportement, ainsi que leur prolifération. Ces étapes dépendent fortement des conditions initiales, particulièrement de l’avidité du récepteur du lymphocyte (TCR) pour le ligand spécifique provenant de l’antigène. La reconnaissance du virus entraine une séquence des réactions biochimiques mettant en œuvre de protéines membranaires et cellulaires. Le processus peut être mesuré par cytométrie en flux. On propose ici plusieurs modèles de différents niveaux de complexité. Ces modèles décrivent une relation entre la population de lymphocytes T et leurs composants intracellulaires et extracellulaires. Ils conduisent à des systèmes d’EDO et d’EDP dont la résolution permet d’étudier la dynamique de la densité de population des lymphocytes au cours du processus d'activation. En outre, différentes hypothèses sont proposées pour le processus d'activation des cellules filles après prolifération. Les équations de bilan de population (EBPs) sont résolues par une nouvelle méthode validée par une solution analytique quand elle existe, ou par comparaison à différentes méthodes numériques disponibles dans la littérature. L’avantage de cette nouvelle méthode est d’être utilisable dans certains cas où les méthodes classiques ne le sont pas. / The early steps of activation are crucial in deciding the fate of T-cells leading to the proliferation. These steps strongly depend on the initial conditions, especially the avidity of the T-cell receptor for the specific ligand and the concentration of this ligand. The recognition induces a rapid decrease of membrane TCR-CD3 complexes inside the T-cell, then the up-regulation of CD25 and then CD25–IL2 binding which down-regulates into the T-cell. This process can be monitored by flow cytometry technique. We propose several models based on the level of complexity by using population balance modeling technique to study the dynamics of T-cells population density during the activation process. These models provide us a relation between the population of T-cells with their intracellular and extracellular components. Moreover, the hypotheses are proposed for the activation process of daughter T-cells after proliferation. The corresponding population balance equations (PBEs) include reaction term (i.e. assimilated as growth term) and activation term (i.e. assimilated as nucleation term). Further the PBEs are solved by newly developed method that is validated against analytical method wherever possible and various approximate techniques available in the literature.