The favorable interaction between proteins and nanoparticles has sparked potential applications of nanotechnology in medicine, and the unique electronic and chemical properties of nanoparticles also provide novel strategies for protein-related therapeutics. The formation of the biocorona has attracted substantial interest over the past decades. For instance, as a potential drug delivery mechanism, protein-coated nanoparticles can improve biocompatibility and increase targeting ability. However, the mechanistic details of protein-nanoparticle interactions remain poorly understood. For example, it is currently impossible to predict the orientation and structure of proteins on the nanoparticle surface, as well as the fate of the biocorona in vivo. Since the composition of the biocorona determines the biological response, identifying and stabilizing the biocorona seems critical for the further development of applications in biological system. In this study, we investigated the physicochemical properties of protein interactions with gold nanoparticles (AuNPs). Firstly, we developed an NMR-based approach for measuring the stoichiometry of protein adsorption to AuNPs, which can be generally applied to globular proteins of different size. Quantitative analysis enabled us to create a protein binding model that involves an initial association, structure reorientation and irreversible adsorption. Secondly, we measured the protein hydrogen-deuterium exchange rates and found that they were unperturbed in the presence of AuNPs, suggesting that proteins retain their globular structure upon adsorption. Finally, we investigated the electrostatic contribution to binding, and we identified a dynamically changing surface in which the factors of net charge, binding affinity and protein size play distinct roles at different phases.

Eicosapentaenoic acid (EPA, C20:5, n-3) is a long chain crucial unsaturated fatty acid, essential for the regulation of critical biological functions in humans. Its benefits include the therapeutic treatment of cardiovascular disease, schizophrenia and Alzheimer's disease. The fungus Pythium irregulare (ATCC 10951) has great potential as a natural EPA producer. In this study, the electroporation conditions for P. irregulare were determined. The auxotrophic selectable genes ura, trp and his were respectively cloned into the plasmid pESC to construct shuttle vectors. Electroporation with 2.0kV and a 0.2cm cuvette was applied as the most effective condition for heterogeneous genes transformation. The yield and content of EPA and other components of total fatty acids (TFA) were further determined by the FAME approach with GC, as well as the analysis of biomass. The EPA content in P. irregulare with heterologous pESC-TRP vector reached 16.68 mg/g if cultured in auxotrophic medium, which showed a 52.33% increase compared to the wild-type P. irregulare. The maximum of EPA yield was 98.52 mg/L from P. irregulare containing the pESC-URA plasmid, a 32.28% increase over the wild-type. However, the maximum cell dried weight of these two organisms were respectively 6.13g/L and 5.3g/L, significantly less than the 6.80g/L of the wild-type. Not only was a feasible approach detected to electro-transform and increase the EPA yield of P. irregulare, this study also inferred that Ï -6 route was mainly involved in the EPA biosynthesis in this organism. An antisense RNA (asRNA) thermodynamic model was developed to design new asRNA constructs capable of fine-tuning gene expression knockdown. The asRNA technology is now identified as an effective and specific method for regulating microbial gene expression at the posttranscriptional level. This is done by targeting mRNA molecules. Although the study of regulation by small RNAs is advanced in eukaryotes, the regulation of expression through artificially introducing antisense oligodeoxynucleotides into host is still being developed in prokaryotes. To study the thermodynamics of asRNA and mRNA binding, (i) the fluorescence protein genes GFP and mCherry were separately cloned into the common pUC19 vector and (ii) antisense GFP and antisense mCherry DNA fragments were randomly amplified and inserted into the constructed plasmid under the control of an additional plac promoter and terminator. The expression level of fluorescence reporter proteins was determined by plate reader in this combinatorial study. A thermodynamic model to describe the relationship between asRNA binding and observed expression level was created. The study indicates two factors that minimum binding energy of the asRNA-mRNA complex and the percentage of asRNA binding mRNA were crucial for regulating the expression level. The correlation relationship between gene expression level and binding percentage multiplied by the minimum binding energy was found to show a good correlation between the thermodynamic parameters and the observed level of gene expression. The model has the potential to predict the sequence of asRNA and the approach will ultimately be applied to cyanobacteria to increase lipids production. Here, the long-term approach is to build metabolic switches from asRNA that can turn "on/off" various cellular programs and metabolic pathways at will in a fine-tuned manner. This will allow engineers to control metabolic activity in response to reactor conditions. / Master of Science

Poor aqueous solubilities of drug candidates limit the biopharmaceutical usefulness in either oral or parenteral dosage forms. Lipid assemblies, such as micelles, may provide a means of enhancing solubility. Despite their usefulness, little is known about the means by which micelles accomplish this result. The goal of the current dissertation is to provide the molecular level understanding of the mechanism by which simple micelle systems solubilize drugs. Specifically, the location, orientation and amount of the drug molecules in micelle systems are the focuses of the work. Three series of model drugs, steroids, benzodiazepines and parabens, in three surfactant systems with anionic, cationic and neutral hydrophilic headgroups were studied. Solubilization power of each micelle system for each model drug was determined by equilibrium solubility. The observed strong surface activities of model drug at hydrocarbon/water interface and the ability of the drugs to compete with surfactants for the model oil/water interface lend support to the hypothesis that drug molecules are mainly solubilized in the interfacial region of the micelles. A surface-localized thermodynamic model that considered the surfactant-drug competition at micelle surface was successfully applied to predict the micelle/water partitioning coefficients. The predictions were made without the use of adjustable parameters in the case of both dilute and concentrated solutions. The orientation of drug at micelle surface was determined by matching calculated occupied areas by solutes at oil/water interface using molecular modeling method to the experimental values. To look into the micro-structure of micelles, twodimensional and diffusion (or PGSE) NMR techniques were employed to detect the specific drug-surfactant interactions and the micelle sizes influenced by model drugs and electrolytes.

Les milieux biologiques et alimentaires sont généralement des mélanges contenant un nombre élevé de constituants (eau, solvants organiques, solides dissous, gaz dissous, espèces ioniques, macromolécules). La prédiction des propriétés d’équilibre de tels milieux requiert l’utilisation d’un modèle thermodynamique entièrement prédictif. Ce modèle doit également permettre d’assurer la cohérence entre des données expérimentales et garantir la robustesse de la représentation simultanée des équilibres physiques (liquide-vapeur, solubilité, etc.) et chimiques (dissociation, oxydo-réduction, complexation, etc.). Le potentiel chimique est une donnée indispensable pour modéliser ces équilibres. Sa connaissance dépend de la prédiction de deux variables : l’enthalpie libre de formation dans un état de référence choisi, et le coefficient d’activité qui dépend aussi de l’état de référence choisi. Le modèle COSMO-RS est un excellent modèle de prédiction des coefficients d’activité très largement utilisé dans le domaine du génie chimique où on s’intéresse essentiellement à des molécules neutres. Ce travail de thèse a permis d’étendre les performances du modèle COSMO-RS au traitement des milieux biologiques et alimentaires dans lesquels on trouve systématiquement des électrolytes en solution (en plus des molécules neutres). Un nouvel outil utilisant les récentes avancées de la mécanique quantique a été développé pour prédire les propriétés de formation à l’état gaz. En combinant des concepts de la thermodynamique, de la mécanique quantique, de l’électrostatique, et de la physique statistique, il a été démontré qu’il est possible d’utiliser le modèle COSMO-RS pour faire la transition entre l’état gaz et la phase condensée. Partant de là, ce travail démontre qu’il est maintenant possible de traiter simultanément les équilibres physiques et chimiques et donc de prédire les propriétés physico-chimiques (aW, pH, Eh) dans les milieux biologiques et alimentaires par le modèle COSMO-RS. / Food and biological systems are generally multicomponent mixtures (including water, organic solvents, dissolved solids, dissolved gases, ionic species, macromolecules). The prediction of the equilibrium properties of such environments requires the use of a fully predictive thermodynamic model. This model must be able to ensure the consistency between experimental data and to ensure the robustness of the simultaneous representation of physical equilibria (liquid-vapour, solubility, etc.) and chemical equilibria (dissociation, redox, complexation, etc.). The chemical potential is an essential property for modelling such equilibria. Its determination depends on two variables: the Gibbs free energy of formation in a chosen reference state, and the prediction of the activity coefficient which also depends on the chosen reference state. The COSMO-RS model is an excellent model for predicting activity coefficients that is widely used in chemical engineering where the studied molecules are generally neutral. This PhD study enabled to extend the performance of the COSMO-RS model toward the treatment of food and biological systems where there are systematically electrolytes in solution (in addition to neutral molecules). A new tool based on the recent advances of quantum mechanics has been developed in order to predict gas phase formation properties. By combining concepts of thermodynamics, quantum physics, electrostatics and statistical physics, it has been demonstrated that it is possible to use the COSMO-RS model to ensure the transition between the gas phase and the condensed phase. In this context, this work demonstrates that it is possible to treat simultaneously physical and chemical equilibria and thus to predict physico-chemical properties (aW, pH, Eh) in food and biological systems using the COSMO-RS model.

This work investigates the volatilities of amine solvents used in post-combustion CO₂ capture from coal-fired power plants. Amine volatility is one of the key criteria used in screening an amine solvent for CO₂ capture: (1) amine losses up the stack can react in the atmosphere to form ozone and other toxic compounds; (2) volatility losses can result in greater solvent make-up costs; (3) high losses will require the use of bigger water wash units, and more water, to capture fugitive amines prior to venting - these translate to higher capital and operating costs; (4) volatilities need to be measured and modeled in order to develop more accurate and robust thermodynamic models. In this work, volatility is measured using a hot gas FTIR which can determine amine, water, and CO₂ in the vapor headspace above a solution. The liquid solution is speciated by NMR (Nuclear Magnetic Resonance). There are two key contributions made by this research work: (1) it serves as one of the largest sources of experimental data available for amine-water volatility; (2) it provides amine volatility for loaded systems (where CO₂ is present) which is a unique measurement not previously reported in the literature. This work studied the volatility of 20 alkanolamines in water at 0.5 - 1.1 molal (m) in water (< 1.5 mol% amine) at zero loading (no CO₂) from 40 ° - 70 °C. An empirical group contribution model was developed to correlate H[subscript 'amine'] to molecular structures of both alkylamines and alkanolamines. The model incorporated additional functional groups to account for cyclic structures and to distinguish between different types of alkyl groups based on the attached neighboring groups. This model represented the experimental H[subscript 'amine'], which spanned five orders in magnitude, to well within an order of magnitude of the measured values. The second component of this research involves upgrading the AspenPlus® v.7.3 model of MDEA-PZ-CO₂-H₂O system primarily by improving MDEA thermodynamics for MDEA-H₂O, MDEA-CO₂-H₂O, and MDEA-PZ-CO₂-H₂O. A key modification was made to include the carbonate (CO₃²⁻) species into the model chemistry set which greatly improved the fit of CO₂ solubility for MDEA-CO₂-H₂O at ultra lean loading ([alpha]) for 0.001 < [alpha] < 0.01. With MDEA-PZ-H₂O, no MDEA-PZ cross interaction parameters were needed to match the blend volatility. Ultimately, both the blend volatility, at unloaded and loaded conditions, along with speciation were adequately represented by the upgraded model. The final component of this research involves screening the volatilities of novel amines at unloaded and nominal lean loading condition from 40 ° - 70 °C (absorber operating conditions). The volatility of tertiary and hindered amines, such as MDEA and AMP, respectively, is not a strong function of loading because these amines are unable to form stable carbamates. Conversely, the volatility of mono-amines and of diamines decreases by ~3 and 5-20 times, respectively, due to a much greater extent of carbamate-forming speciation. PZ or a blend having a diamine promoted by PZ would be favorable for CO₂ capture due to the low volatility of the diamines in loaded solution. . Finally, in order of increasing degree of salting out as reflected by the increasing magnitude of the system asymmetric amine activity coefficient, 7 m MDEA < 4.8 m AMP ~ 7 m MDEA/2 m PZ < 8 m PZ < 7 m MEA. / text

Abstract : This research project has as main objective to study in detail the internal flow features of single-phase supersonic ejectors for refrigeration applications, and the potential effects of injecting droplets on the performance of the device. To this end, a numerical approach is proposed which has been separated into two parts: First, a RANS modelling strategy for supersonic ejectors has been outlined combining the NIST real gas equations database [NIST, 2010] and the k − ω SST turbulence model in its low-Reynolds number formulation. The proposed approach agrees within 5% (resp. 2%) to the experimental entrainment ratio (resp. compression ratio) data of García del Valle et al. [2014], properly captures the main internal flow features and has a reasonable computational cost. This RANS model has been applied in the analysis of a supersonic R134a ejector for refrigeration purposes, showing in particular that the secondary flow is entrained by momentum transfer through the mixing shear layer, that the distance between the primary nozzle exit and the shock-waves in the constant area section varies between 9 and 16 times the primary nozzle exit diameter and that the important axial character of the flow limits mixing of both inlet flows until after the shock train. Furthermore, an exergy analysis through the device shows that the mixing and the oblique shock waves are responsible for between 50% and 70% of the generated losses, the latter might be attenuated through droplet injection in the constant area section. Moreover, it has been shown that drop-in replacement of the working fluid with HFOs R1234yf and R1234ze(E) leads to mild changes in the ejector performance but reduces the HDRC system COP (resp. cooling capacity) in average by 7.1% (resp. 23.3%). Lastly, a comparison of the model predictions with the thermodynamic model of Galanis and Sorin [2016] for an air ejector, shows that as the working fluid approaches the ideal gas behaviour, the flow can be adimensionalized in terms of the secondary inlet temperature and pressure, the motive nozzle throat and the entrainment and compression ratios. In the second part, the influence of droplets has been studied from a local perspective by extending the RANS model to include a discrete phase, which affects the main flow through exchanges of momentum and thermal energy, and from a global perspective by building a thermodynamic model, which predicts the entrainment and limiting compression ratio given a fixed geometry and operating conditions. Both approaches present very good agreement in terms of p, T and M a internal profiles. Results for a supersonic ejector with R134a as baseline working fluid and droplets injected at the constant area section show that the flow structure has perceptible changes only at the highest injection fraction considered 10%, which induces boundary layer detachment, reduces the shock intensity by 8% and diminishes the superheat at the ejector outlet by 15 ◦C. Nonetheless, ejector performance metrics are severely affected as the limiting compression ratio, Elbel efficiency and exergy performance reduce respectively by 5%, 11% and 15%, due mainly to the additional entropy generated through droplet injection and mixing with the main flow. / Ce projet de recherche a pour objectif principal d’étudier en détail les caractéristiques de l’écoulement interne dans des éjecteurs supersoniques monophasiques pour des applications en réfrigération, et les effets potentiels de l’injection de gouttelettes sur les performances de l’appareil. A cette fin, une approche numérique est proposée et a été séparée en deux parties. Tout d’abord, une stratégie de modélisation RANS pour les éjecteurs supersoniques a été décrite en combinant la base de données pour les gaz réels NIST [NIST, 2010] et le modèle de turbulence k − ω SST dans sa formulation à bas nombre de Reynolds. L’approche proposée prédit avec un accord d’environ 5% (resp. 2%) le rapport d’entraînement (resp. rapport de compression) avec les données expérimentales de García del Valle et al. [2014]. Il capte également correctement les principales caractéristiques de l’écoulement interne et a un coût de calcul raisonnable. Ce modèle RANS a été appliqué à l’analyse d’un éjecteur supersonique au R134a utilisé à des fins de réfrigération, montrant en particulier que le flux secondaire est entraîné par un transfert d’impulsion à travers la couche de cisaillement, que la position de départ des ondes de choc dans la section constante se situe dans une plage de 9 à 16 fois le diamètre de sortie de la buse primaire et que l’important caractère axial du flux limite le mélange des deux écoulements d’entrée au-delà du train d’ondes de choc. De plus, une analyse exergétique à travers le dispositif montre que le mélange et les ondes de choc obliques sont responsables de 50% et 70% des pertes générées, ces dernières pouvant être atténuées par injection de gouttelettes dans la section à zone constante. De plus, il a été démontré que le remplacement direct du fluide de travail par les HFO R1234yf et R1234ze(E) entraîne de légers changements dans la performance de l’éjecteur mais réduit en moyenne le COP du système HDRC (resp. la capacité de refroidissement) de 7.1% (resp. 23.3%). Enfin, une comparaison des prédictions du modèle avec le modèle thermodynamique de Galanis and Sorin [2016] pour un éjecteur à air montre que lorsque le fluide de travail se rapproche du comportement de gaz idéal, l’écoulement peut être normalisé en fonction de la température et de la pression à l’entrée secondaire, la gorge de la tuyère principale et les rapports d’entraînement et de compression. Dans la seconde partie, l’influence des gouttelettes a été étudiée d’un point de vue local en étendant le modèle RANS à une phase discrète qui affecte le flux principal par des échanges de quantité de mouvement et d’énergie thermique, et d’un point de vue global en construisant un modèle thermodynamique qui prédit l’entraînement et le rapport de compression limitant étant donné une géométrie fixe et les conditions de fonctionnement. Les deux approches présentent un très bon accord en termes de profils internes de p, T et Ma. Les résultats pour un éjecteur supersonique au R134a comme fluide de base, avec des gouttelettes injectées à mi-chemin dans la section de la zone constante, montrent que la structure d’écoulement dans cette région présente des changements perceptibles seulement à la fraction d’injection la plus élevée, 10%, en diminuant l’intensité du choc de 8% et la surchauffe à la sortie de l’éjecteur de 15 ◦C. Néanmoins, la performance de l’éjecteur est sévèrement affectée vu que le rapport de compression, l’efficacité d’Elbel et le performance exergétique sont réduites respectivement de 5%, 11% et 15%, principalement en raison de l’entropie supplémentaire générée par l’injection de gouttelettes et le mélange avec le flux principal.

The thesis deals with the design of a small-volume four-stroke internal combustion engine with a maximum displacement of 10 cc and a power of 1 kW for autonomous devices of smaller dimensions. In addition to the analysis of individual propulsions for small aircraft, there is also a chapter with the comparison of an internal combustion engine and an electric motor with similar power. Another part of the work is the creation of a thermodynamic model in the GT Power program and its subsequent optimization to increase the overall efficiency of the engine.

This dissertation focuses on copper release in drinking water. Qualitative and quantitative assessment of Cu and Fe corrosion by process water quality was assessed over one year in a field study using finished waters produced from seven different treatment process and eighteen pilot distribution systems (PDSs) that were made from unlined cast iron and galvanized steel pipes, and lined cement and PVC pipes taken from actual distribution systems. Totally seven different waters were studied, which consisted of three source waters: groundwater, surface, and simulated brackish water designated as G1, S1, and RO. With certain pre-established blending ratios, these three waters were blended to form another three waters designated as G2, G3, and G4. Enhanced surface water treatment was CFS, ozonation and GAC filtration, which was designated as S1. The CFS surface water was nanofiltered, which is S2. All seven finished waters were stabilized and chloraminated before entering the PDSs. Corrosion potential was compared qualitatively and quantitatively for all seven waters by monitoring copper and iron release from the PDSs. This dissertation consists of four major parts. (1) Copper corrosion surface characterization in which the solid corrosion products formed in certain period of exposure to drinking water were tried to be identified with kinds of surface techniques. Surface characterization indicated that major corrosion products consists of cuprite (Cu2O) as major underneath corrosion layer and tenorite (CuO), cupric hydroxide (Cu(OH)2) on the top surface. In terms of dissolution/precipitation mechanism controlling the copper concentration in bulk solution, cupric hydroxide thermodynamic model was developed. (2) Theoretical thermodynamic models were developed to predict the copper release level quantitatively based on controlling solid phases identified in part (1). These models are compared to actual data and relative assessment is made of controlling solid phases. (3) Non-linear and linear regression models were developed that accommodated the release to total copper for varying water quality. These models were verified using independent data and provide proactive means of assessing and controlling copper release in a varying water quality environment. (4) Simulation of total copper release was conducted using all possible combinations of water quality produced by blending finished waters from ground, surface and saline sources, which involves the comparison of copper corrosion potentials among reverse osmosis, nanofiltration, enhanced coagulation, lime softening, and conventional drinking water treatment.

Yes / The removal of the ubiquitous phenol and phenolic compounds in industrial wastes is a critical environmental issue due to their harmful threats to wildlife and potential adverse human health effects. The removal of such compounds is therefore of significant importance in water treatment and reuse. In recent years, reverse osmosis (RO) has been successfully utilised in several industrial processes and wastewater treatment including phenol removal. In this paper, a new model based on a spiral-wound RO process is developed for the removal of phenol from wastewater. A simplified mathematical algorithm using an irreversible thermodynamic approach is developed. This results in a set of non-linear Differential and Algebraic Equations (DAEs), which are solved based on a number of optimised model parameters using a combined methodology of parameter estimation and experimental phenol-water data derived from the literature. The effects of several operational parameters on the performance (in terms of removal of phenol) of the process are explored using the model.

No description available.