En plein essor, le marché des vernis à ongles représente plusieurs milliards de flacons vendus chaque année à travers le monde. Malgré un durcissement de la réglementation au cours des vingt dernières années, la composition des vernis reste problématique d’un point de vue environnemental. L’agent filmogène secondaire, ou résine, qui permet d’apporter le supplément d’adhésion, de brillance et de stabilité faisant défaut à la nitrocellulose, est le principal obstacle à l’obtention d’un vernis 100 % biosourcé. Dans ce contexte, nous nous sommes attachés à comprendre la physicochimie de ces systèmes complexes, en vue d'orienter la conception de nouvelles résines biosourcées compatibles par l'établissement de relations structures-propriétés. En premier lieu, des caractérisations physicochimiques complètes (état de surface, composition, perméabilité) ont été menées sur l’ongle et deux modèles semi-synthétiques. Un test d’adhésion a été mis au point afin d’évaluer l’adhérence de formulations sur ces substrats. La corrélation des résultats a permis d’identifier le meilleur modèle de l’ongle natif et mis en évidence les mécanismes d’adhésion vernis-ongle. Parallèlement, les résines benchmarks ont été caractérisées afin de définir un cahier des charges précis. L’adaptation d’outils de prédiction aux polymères a permis de relier des modifications structurales à la solubilité et a été validée à l’aide d’oligoesters modèles synthétisés. L’impact de certains motifs structuraux sur la brillance ou la dureté des résines a été mis en évidence et les relations structures-propriétés identifiées ont été confirmées via l'évaluation des performances de nouvelles résines polyesters biosourcées. / Several billion nail polishes are sold every year throughout the world, and the market is still fast-growing. Despite a tightening of regulations over the past twenty years, the composition of varnishes remains problematic from an environmental point of view. The main obstacle to reach a 100% bio-based varnish is the secondary film-forming agent, or resin, which provides the additional adhesion, the gloss and the stability that nitrocellulose lacks. In this context, we have focused on understanding the physicochemistry of these complex systems in order to assist the design of new compatible biosourced resins through the establishment of structures-properties relationships. First, complete physicochemical characterizations (surface aspect and surface energy, composition, permeability) were carried out on native nails and two semi-synthetic models. An adhesion test was developed to evaluate the adhesion of formulations onto substrates. Correlated to physicochemical characterizations, these results allowed to identify the best model of the native nail and highlighted the adhesion mechanisms at the varnish-nail interface. In parallel, the "benchmarks" resins were characterized in order to define precise specifications according to their application performances. Thanks to the adaptation of prediction tools to polymers, we managed to link structural modifications to solubility and was validated using synthesized model oligoesters. The impact of some structural features on the gloss or the hardness of resins has been highlighted and the identified structures-properties relationships were confirmed through the evaluation of the performances of new bio-based polyester resins.

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.

L‟acétonitrile (ACN) peut être considéré comme le solvant de référence utilisé dans les électrolytes pour supercondensateurs car, industriellement, il est le plus utilisé. Il présente en effet de nombreux avantages tels qu‟une viscosité faible et une permittivité élevée, conduisant à une excellente conductivité en présence d‟un sel. Il est cependant hautement volatile, très inflammable et toxique quand il brûle (dégagement de HCN). Ainsi, dans le but de réduire sa pression de vapeur, et donc le risque d‟inflammabilité, il peut être mélangé à un liquide ionique (LI) qui lui est non volatile. Le but de ce travail est de remplacer l‟électrolyte classique des supercondensateurs à base de ACN et de sel de tétraethylammonium tétrafluoroborate (ACN + 1M Et4N+BF4-) par un mélange LI/ACN. Pour ce faire, l‟étude physico-chimique, électrochimique et thermodynamique des mélanges LI/ACN est entreprise. Dans un premier temps, les liquides ioniques ont été synthétisés et caractérisés par différentes techniques d‟analyses physico-chimiques. Ensuite des mélanges LI/ACN ont été formulés. Ces mélanges ont subi des tests de sécurité (tests préliminaires d‟inflammabilité, mesures de point flash) afin de trouver le mélange optimal. Les phénomènes de transport dans ces mélanges ont été aussi étudiés afin de comprendre leur comportement en température. Par ailleurs, l‟étude électrochimique menée sur ces mélanges a montré qu‟il n‟y avait pas de dégradation des performances électrochimiques par comparaison à l‟électrolyte classique. Enfin l‟étude de l‟équilibre liquide vapeur à partir de modèles thermodynamiques semi-prédictifs comme UNIQUAC ou prédictifs comme Cosmo-RS a permis de déterminer les grandeurs d‟excès. / Acetonitrile (ACN) is the most popular solvent in electrolytes designed for use in supercapacitors. It presents many advantages such as a low viscosity and a high permittivity, leading to excellent conductivities in the presence of salts. However it is highly flammable and very toxic when burning (release of HCN ). Thus, in order to reduce its vapor pressure and hence its flammability we propose to mix it with an ionic liquid (IL). As ILs are non volatile compounds, the vapor pressure of the mixture will be reduced (Raoult‟s law). In addition many other benefits may be expected from these mixtures. The aim of this work is to replace the conventional ACN and Et4NBF4 based electrolyte for supercapacitors by a IL/ACN mixture. Thus, the physico-chemical, electrochemical and thermodynamical studies of IL/ACN mixtures have been undertaken. Synthesized and commercial ILs are characterized by mean of different physico-chemical analysis. Then IL/ACN mixtures were formulated. These mixtures were tested for safety (preliminary flammability tests, flash point measurements) and the optimal mixture determined. Transport phenomena in these mixtures were also studied to understand their behavior in response to temperature. Furthermore, the electrochemical study conducted on these mixtures showed that there was no degradation of the electrochemical performances as compared to the conventional electrolyte. Finally the study of vapor liquid equilibrium from semi-predictive thermodynamic models like UNIQUAC or predictive models like Cosmo-RS allowed us to determine the excess properties.

This thesis explores mathematical optimization techniques to address the computeraided molecular and mixture design problems (CAMD/CAMxD). In particular, we leverage the power of mixed-integer linear programs (MILPs) to quickly and efficiently design over the massive chemical search space. These MILPs, when coupled with state-ofthe- art derivative-free optimization (DFO) methods, make for an efficient optimization strategy when designing mixtures of molecules or when considering a single molecule design problem that involves difficult thermodynamics or process models. In the first chapter, we provide a very general overview of the field of CAMD as addressed from the perspective of mathematical optimization. We discuss many relevant quantitative structure-property relationships (QSPRs) and provide constraints typically used in CAMD/CAMxD optimization problems. The second chapter introduces our DFO-based molecular/mixture design algorithm and describes how this approach enables a much greater molecular diversity to be considered in the search space as compared to traditional methods. Additionally, this chapter looks at a few case studies relevant to crystallization solvents and provides a detailed comparison of 27 different DFO algorithms for solving these problems. The third chapter introduces COSMO-RS/-SAC as alternatives to UNIFAC as the method used to capture mixture thermodynamics for a variety of CAMD/CAMxD problems. To fully incorporate COSMO-RS/-SAC into CAMD, we introduce group contribution (GC) methods for estimating a few necessary parameters for COSMO-based methods. We demonstrate the utility of COSMO-RS/-SAC in a few case studies for which UNIFAC-like methods are insufficient. In the fourth chapter, we investigate reaction solvent design using COSMO-based methods. COSMO-RS is particularly suitable for these problems as they allow for modeling of many relevant species in chemical reactions (transition states, charges, etc.) directly at the quantum level. This information can be immediately passed to the CAMD problem. We investigate a number of solvent design problems for a few difficult reactions. We summarize the work and provide a few future directions in the final chapter. Overall, this thesis serves to push the field of CAMD forward by introducing new methods to more efficiently explore the massive chemical search space and to enable a few new classes of problems which were previously untenable.

Metal ions are a tempting tool for organisms thanks to the diversity of func- tions they have to offer, if they can be distinguished properly. Examining metal-ion selectivity computationally is challenging mainly due to complex- ity of electronic structure and solvation effects. A DFT-based protocol for predicting metal-ion selectivity of metal-binding systems was developed. The most essential part of the thesis is discussion of the magnitudes and sources of inherent errors, both for metal-ion complexes and small peptides. The thesis connects the work of four original papers. It includes computational and ex- perimental benchmarks, a case-study validating the computational protocol for obtaining energetic and structural insights, and attempts applying the protocol to peptidic systems. ii

No description available.

Solvation-thermodynamics models based on computational quantum mechanics, such as the conductor-like screening model (COSMO), provide a good alternative to traditional group-contribution methods for predicting thermodynamic phase behavior. Two COSMO-based thermodynamic models are COSMO-RS (real solvents) and COSMO-SAC (segment activity coefficient). The main molecule-specific input for these models is the sigma profile, or the probability distribution of a molecular surface segment having a specific charge density. Generating the sigma profiles represents the most time-consuming and computationally expensive aspect of using COSMO-based methods. A growing number of scientists and engineers are interested in the COSMO-based thermodynamic models, but are intimidated by the complexity of generating the sigma profiles. This thesis presents the first free, open-literature database of 1,513 self-consistent sigma profiles, together with two validation examples. The offer of these profiles will enable interested scientists and engineers to use the quantum-mechanics-based, COSMO methods without having to do quantum mechanics. This thesis summarizes the application experiences reported up to October 2004 to guide the use of the COSMO-based methods. Finally, this thesis also provides a FORTRAN program and a procedure to generate additional sigma profiles consistent with those presented here, as well as a FORTRAN program to generate binary phase-equilibrium predictions using the COSMO-SAC model. / Master of Science

<div>Conventional soybean oil and high-oleic soybean oil offer opportunities as bio-solvents for sweetening sour natural gas, adding value to the soybean oil industry and the natural gas industry. The rise of fracking in the United States and changing economics in the energy industry have increased use of natural gas, which is often rendered sour by high concentrations of hydrogen sulfide (H2S), a toxic and corrosive impurity. The present work evaluates the viability of both conventional and high-oleic soybean oil to act as bio-solvents for removing gaseous H2S. Predictive in silico methods, experimental validation, and economic feasibility analysis are included to draw conclusions regarding the overall capability and feasibility of using soybean oils as bio-solvents for gas sweetening.</div><div><br></div><div>In silico predictive methods for sweetening were implemented to assess the relationship between fatty acid composition in the soybean oils and the ability to effectively partition H2S from methane or nitrogen gases. The Conductor-like Screening Model for Real Solvents (COSMO-RS) was used to predict the partition coefficient (K) of H2S in a bi-phasic liquid-vapor system made up of fatty acids in the liquid phase and methane or nitrogen gas in the vapor phase. The fatty acid mass fractions represented those found in soybean or high-oleic soybean oil. Methane represented gas and nitrogen was considered in order to compare to experimental conditions. This proof of concept work predicted K values for H2S below 0.0005 at temperatures from 10 to 100 °C at atmospheric pressure; K values near zero indicate near-complete removal of H2S from the gas phase.</div><div><br></div><div>Experimental validation included equilibrium extraction experiments as well as data collection for isotherm model development. Experimental equilibrium studies were carried out at residence times ranging from 0 – 60 minutes with mixing at ambient conditions. Experiments resulted in K values below 0.1 for H2S in soybean oil and high-oleic soybean oil at 25 °C with residence times less than 15 minutes and a 2:1 gas to oil ratio. More than 90% of the H2S was removed from the gas phase within 15 minutes. Isotherm models demonstrated the saturation limits of the soybean oils and compared them to saturation limits in water and heptane. </div><div><br></div><div>Economic feasibility experiments used graphical and algebraic methods to determine the number of equilibrium stages needed to remove 99.9% of H2S from feed gas with H2S concentrations ranging from 40 – 400 ppm. A gas flow rate equivalent to industrial levels was used to design an extraction column. Capital costs and operating costs were estimated, along with the revenues to be gained from selling methane and selling recovered elemental sulfur as a secondary product. Solvent regeneration would need to exceed 98% in order to keep the cost of treating a unit of natural gas equal to or less than existing industrial methods. Suggestions for cutting costs and improving process viability are made.</div><div><br></div>