Emerging contaminants are defined as synthetic or naturally occurring chemicals or microorganisms that are not currently regulated but have the potential to enter the environment and cause adverse ecological and/or human health effects. With recent development in analytical techniques, emerging contaminants have been detected in wastewater, source water, and finished drinking water. These environmental occurrence data have raised public concern about the fate and ecological impacts of such compounds. Concerns regarding emerging contaminants and the many chemicals that are in use or production necessitate a task to assess their potential health effects and removal efficiency during water treatment. Advanced oxidation processes (AOPs) are attractive and promising technologies for emerging contaminant control due to its capability of mineralizing organic compound via reactions with highly active hydroxyl radicals. However, the nonselective reactivity of hydroxyl radicals and the radical chain reactions make AOPs mechanistically complex processes. In addition, the diversity and complexity of the structure of a large number of emerging contaminants make it difficult and expensive to study the degradation pathways of each contaminant and the fate of the intermediates and byproducts. The intermediates and byproducts that are produced may pose potential effects to human and aquatic ecosystems. Consequently, there is a need to develop first-principle based mechanistic models that can enumerate reaction pathway, calculate concentrations of the byproducts, and estimate their human effects for both water treatment and reuse practices. This dissertation develops methods to predict reaction rate constants for elementary reactions that are identified by a previously developed computer-based reaction pathway generator. Many intermediates and byproducts that are experimentally identified for HO* induced reactions with emerging contaminants include common lower molecular weight organic compounds on the basis of several carbons. These lower carbon intermediates and byproducts also react with HO* at relatively smaller reaction rate constants (i.e., k < 109 M-1s-1) and may significantly affect overall performance of AOPs. In addition, the structures of emerging contaminants with various functional groups are too complicated to model. As a consequence, the rate constant predictors are established based on the conventional organic compounds as an initial approch. A group contribution method (GCM) predicts the aqueous phase hydroxyl radical reaction rate constants for compounds with a wide range of functional groups. The GCM is a first comprehensive tool to predict aqueous phase hydroxyl radical reaction rate constants for reactions that include hydrogen-atom abstraction from a C-H bond and/or a O-H bond by hydroxyl radical, hydroxyl radical addition to a C=C unsaturated bond in alkenes and aromatic compounds, and hydroxyl radical interaction with sulfur-, nitrogen-, or phosphorus-atom-containing compounds. The GCM shows predictability; factor of difference of 2 from literature-reported experimental values. The GCM successfully predicts the hydroxyl radical reaction rate constants for a limited number of emerging contaminants. Linear free energy relationships (LFERs) bridge a kinetic property with a thermochemical property. The LFERs is a new proof-of-concept approach for Ab initio reaction rate constants predictors. The kinetic property represents literature-reported and our experimentally obtained hydroxyl radical reaction rate constants for neutral and ionized compounds. The thermochemical property represents quantum mechanically calculated aqueous phase free energy of activation. Various Ab initio quantum mechanical methods and solvation models are explored to calculate the aqueous phase free energy of activation of reactantas and transition states. The quantum mechanically calculcated aqueous phase free energies of activation are within the acceptable range when compared to those that are obtained from the experiments. These approaches may be applied to other reaction mechanisms to establish a library of rate constant predictions for the mechanistic modeling of AOPs. The predicted kinetic information enables one to identify important pathways of AOP mechanisms that are initiated by hydroxyl radical, and can be used to calculate concentration profiles of parent compounds, intermediates and byproducts. The mechanistic model guides the design of experiments that are used to examine the reaction mechanisms of important intermediates and byproducts and the application of AOPs to real fields.

En Imagerie par Résonance Magnétique (IRM), l’augmentation du champ magnétique statique permet en théorie de fournir un rapport signal sur bruit accru, améliorant la qualité des images. L’objectif de l’IRM à ultra haut champ est d’atteindre une résolution spatiale suffisamment haute pour pouvoir distinguer des structures si fines qu’elles sont actuellement impossibles à visualiser de façon non-invasive. Cependant, à de telles valeurs de champs magnétiques, la longueur d’onde du rayonnement électromagnétique envoyé pour basculer les spins des protons de l’eau est du même ordre de grandeur que l’objet dont on souhaite faire l’image. Des phénomènes d’interférences sont observés, ce qui se traduit par l’inhomogénéité de ce champ radiofréquence (RF) au sein de l’objet. Ces interférences engendrent des artefacts de signal et/ou de contraste dans les images IRM, et rendent ainsi leur exploitation délicate. Il est donc crucial de fournir des solutions pour atténuer la non-uniformité de l’excitation des spins, à défaut de quoi de tels systèmes ne pourront atteindre leurs pleins potentiels. Pour obtenir des diagnostics pertinents à très haut champ, il est donc nécessaire de créer des impulsions RF homogénéisant l'excitation de l'ensemble des spins (ici du cerveau humain), optimisées pour chaque individu. Pour cela, un système de transmission parallèle (pTX) à 8 canaux a été installé au sein de notre imageur à 7 Tesla. Alors que la plupart des systèmes IRM cliniques n’utilisent qu’un seul canal d’émission, l’extension pTX permet de jouer différentes formes d’impulsions RF de concert. La somme résultante de ces interférences doit alors être optimisée pour atténuer la non-uniformité observée classiquement. L’objectif de cette thèse est donc de synthétiser ce type d’impulsions, en utilisant la pTX. Ces impulsions auront pour contrainte supplémentaire le respect des limitations internationales concernant l'exposition à des champs radiofréquence, qui induit une hausse de température dans les tissus. En ce sens, de nombreuses simulations électromagnétiques et de températures ont été réalisées en introduction de cette thèse, afin d’évaluer la relation entre les seuils recommandés d’exposition RF et l’élévation de température prédite dans les tissus. Cette thèse porte plus spécifiquement sur la conception de l’ensemble des impulsions RF refocalisantes utilisées dans des séquences IRM non-sélectives, basées sur l’écho de spin. Dans un premier temps, seule une impulsion RF a été générée, pour une application simple : l’inversion du déphasage des spins dans le plan transverse. Dans un deuxième temps, sont considérées les séquences à long train d’échos de refocalisation appliquées à l’in vivo. Ici, l’opérateur mathématique agissant sur la magnétisation, et non pas son état final comme il est fait classiquement, est optimisé. Le gain en imagerie à très haut champ est clairement visible puisque les opérations mathématiques (la rotation des spins) voulues sont réalisées avec plus de fidélité que dans le cadre des méthodes de l’état de l’art. Pour cela, la génération de ces impulsions RF combine une méthode d’excitation des spins avec navigation dans l’espace de Fourier, les kT-points, et un algorithme d’optimisation, appelé Gradient Ascent Pulse Engineering (GRAPE), utilisant le contrôle optimal. Cette conception est rapide grâce à des calculs analytiques plus directs que des méthodes de différences finies. La prise en compte d’un grand nombre de paramètres nécessite l’usage de GPUs (Graphics Processing Units) pour atteindre des temps de calcul compatibles avec un examen clinique. Cette méthode de conception d’impulsions RF a été validée expérimentalement sur l’imageur 7 Tesla de NeuroSpin, sur une cohorte de volontaires sains. / In Magnetic Resonance Imaging (MRI), the increase of the static magnetic field strength is used to provide in theory a higher signal-to-noise ratio, thereby improving the overall image quality. The purpose of ultra-high-field MRI is to achieve a spatial image resolution sufficiently high to be able to distinguish structures so fine that they are currently impossible to view in a non-invasive manner. However, at such static magnetic fields strengths, the wavelength of the electromagnetic waves sent to flip the water proton spins is of the same order of magnitude than the scanned object. Interference wave phenomena are then observed, which are caused by the radiofrequency (RF) field inhomogeneity within the object. These generate signal and/or contrast artifacts in MR images, making their exploitation difficult, if not impossible, in certain areas of the body. It is therefore crucial to provide solutions to mitigate the non-uniformity of the spins excitation. Failing this, these imaging systems with very high fields will not reach their full potential.For relevant high field clinical diagnosis, it is therefore necessary to create RF pulses homogenizing the excitation of all spins (here of the human brain), and optimized for each individual to be imaged. For this, an 8-channel parallel transmission system (pTX) was installed in our 7 Tesla scanner. While most clinical MRI systems only use a single transmission channel, the pTX extension allows to simultaneously playing various forms of RF pulses on all channels. The resulting sum of the interference must be optimized in order to reduce the non-uniformity typically seen.The objective of this thesis is to synthesize this type of tailored RF pulses, using parallel transmission. These pulses will have as an additional constraint the compliance with the international exposure limits for radiofrequency exposure, which induces a temperature rise in the tissue. In this sense, many electromagnetic and temperature simulations were carried out as an introduction of this thesis, in order to assess the relationship between the recommended RF exposure limits and the temperature rise actually predicted in tissues.This thesis focuses specifically on the design of all RF refocusing pulses used in non-selective MRI sequences based on the spin-echo. Initially, only one RF pulse was generated for a simple application: the reversal of spin dephasing in the transverse plane, as part of a classic spin echo sequence. In a second time, sequences with very long refocusing echo train applied to in vivo imaging are considered. In all cases, the mathematical operator acting on the magnetization, and not its final state as is done conventionally, is optimized. The gain in high field imaging is clearly visible, as the necessary mathematical operations (that is to say, the rotation of the spins) are performed with a much greater fidelity than with the methods of the state of the art. For this, the generation of RF pulses is combining a k-space-based spin excitation method, the kT-points, and an optimization algorithm, called Gradient Ascent Pulse Engineering (GRAPE), using optimal control.This design is relatively fast thanks to analytical calculations rather than finite difference methods. The inclusion of a large number of parameters requires the use of GPUs (Graphics Processing Units) to achieve computation times compatible with clinical examinations. This method of designing RF pulses has been experimentally validated successfully on the NeuroSpin 7 Tesla scanner, with a cohort of healthy volunteers. An imaging protocol was developed to assess the image quality improvement using these RF pulses compared to typically used non-optimized RF pulses. All methodological developments made during this thesis have contributed to improve the performance of ultra-high-field MRI in NeuroSpin, while increasing the number of MRI sequences compatible with parallel transmission.