L'eau à des interfaces

Water is the most abundant molecule on earth, indispensable for a plethora of chemical reactions and vital to the functioning of most living organisms. Interfacial water is particularly interesting to study as its physicochemical properties deviate significantly from the bulk whilst being of crucial importance to both fundamental research and industrial process design. In this thesis we study the interfacial water dynamics of three highly relevant phenomena by primarily recurring on microfluidics and ultrarapid imaging approaches. The first part focusses on proton diffusion in complex aqueous environments such as the the cytoplasm which remains a central issue in the biowater controversy. We evaluate and discuss the relevance of different proton diffusion mechanisms in cellular mimic solutions. The second part of this thesis is centred around droplet formation dynamics which are not only omnipresent in nature and technology, but also constitute a very rich phenomenon involving finite time singularities. We evaluate the outstanding pinch-off behaviour of water and aqueous solutions at the water/air interface that significantly deviates from other comparable non-viscous liquids on the millisecond time scale. In the last part we study a three phase system consisting of water and oil embedded in different ‘rough’ microstructures. Surface topology is identified as important determinant for the relative wettability behaviour of oil and water which constitutes a key finding for the development of efficient and environmentally compatible enhanced oil recovery strategies.Cette thèse porte sur l’étude de trois phénomènes interfaciaux reliés à l’eau : (i) la diffusion de protons dans un environnement complexe, (ii) la formation de gouttes et (iii) le déplacement d’huile sous l’effet du déplacement d’une phase aqueuse dans un circuit microfluidique poreux. Dans un premier temps, nous étudions une « quasi-interface », constituée de deux solutions complexes aqueuses de différents pH, telles qu’on les trouve dans les milieux cellulaires. La diffusion des protons ainsi que les dynamiques de réorientation des molécules d’eau sont examinés et nos résultats suggèrent que le transport des protons serait médié par des molécules tampons. La deuxième partie de cette thèse porte sur la rupture de gouttes à l’interface liquide/air. La rupture de gouttes de fluides non-visqueux est un phénomène extrêmement riche et sa description théorique constitue un des cas les plus simples des singularités à temps fini. Dans le chapitre 4 on met en évidence par l’imagerie ultrarapide que l’eau possède une tension de surface dynamique à l’échelle de la milliseconde. Dans le chapitre 5, on s’intéresse à la dynamique de rupture de métaux en évaluant si des mesures électriques permettent de se rapprocher temporellement (et spatialement) au plus près de la rupture (ns). Dans la dernière partie (chapitre 6), on revisite le problème classique du déplacement d’huile avec de l’eau, rencontré dans les techniques de récupération assistée du pétrole (RAP). On s’intéresse au rôle de la topologie de surface de la roche poreuse sur le piégeage de gouttes d’huile et dégage une loi d’échelle générale liant les effets de la rugosité au déplacement du fluide au sein du canal

Gate-to-Gate Energy Consumption in Chemical Batch Plants: Statistical Models Based on Reaction Synthesis Type

Energy consumption in the chemical industry is an important operating cost and environmental impact factor and reducing it is also explicitly mentioned as one of the key principles of green chemistry. Energy consumption has thus been included in diverse process design and evaluation tools as a key metric. However, measurements of energy consumption at the process equipment level are scarce, especially in fine chemical production typically performed in multiproduct and multipurpose batch plants. In this work, we present a shortcut approach based on statistical models, such as probability density functions (PDF) and classification trees, for estimating steam consumption which typically represents the highest energy utility consumption in batch plants. The output of these models is in the form of intervals derived from PDF interquartile ranges and as classes derived from the classification trees, respectively. The validation results (i.e., goodness of fit, cross validation, and case studies) show that the models provide satisfactory interval estimations of steam consumption for benchmarking chemical reaction types and performing uncertainty analysis. The models can be primarily used at early design stages for screening purposes, the reaction type being the minimum needed input information, allowing in the case of classification trees also an analysis of the most influencing predictor variables (i.e., reaction type and operating parameters) upon the steam consumption. This study also demonstrates the use of the PDF statistical models to a previously published case study for the production of the intermediate substance 4-(2-methoxyethyl)-phenol, which can be produced from seven different synthesis routes. The ranking of the synthesis routes according to the PDF models shows similar trends to that of an Energy Loss Index proxy indicator which however requires more detailed chemical and process information

The Dynamic Surface Tension of Water

International audienceThe surface tension of water is an important parameter for many biological or industrial processes, and roughly a factor of 3 higher than that of nonpolar liquids such as oils, which is usually attributed to hydrogen bonding and dipolar interactions. Here we show by studying the formation of water drops that the surface tension of a freshly created water surface is even higher (∼90 mN m &sup−1;) than under equilibrium conditions (~72 mN m ~&sup−1;) with a relaxation process occurring on a long time scale (~1 ms). Dynamic adsorption effects of protons or hydroxides may be at the origin of this dynamic surface tension. However, changing the pH does not significantly change the dynamic surface tension. It also seems unlikely that hydrogen bonding or dipole orientation effects play any role at the relatively long time scale probed in the experiments

Gate-to-Gate Energy Consumption in Chemical Batch Plants: Statistical Models Based on Reaction Synthesis Type

Energy consumption in the chemical industry is an important operating cost and environmental impact factor and reducing it is also explicitly mentioned as one of the key principles of green chemistry. Energy consumption has thus been included in diverse process design and evaluation tools as a key metric. However, measurements of energy consumption at the process equipment level are scarce, especially in fine chemical production typically performed in multiproduct and multipurpose batch plants. In this work, we present a shortcut approach based on statistical models, such as probability density functions (PDF) and classification trees, for estimating steam consumption which typically represents the highest energy utility consumption in batch plants. The output of these models is in the form of intervals derived from PDF interquartile ranges and as classes derived from the classification trees, respectively. The validation results (i.e., goodness of fit, cross validation, and case studies) show that the models provide satisfactory interval estimations of steam consumption for benchmarking chemical reaction types and performing uncertainty analysis. The models can be primarily used at early design stages for screening purposes, the reaction type being the minimum needed input information, allowing in the case of classification trees also an analysis of the most influencing predictor variables (i.e., reaction type and operating parameters) upon the steam consumption. This study also demonstrates the use of the PDF statistical models to a previously published case study for the production of the intermediate substance 4-(2-methoxyethyl)-phenol, which can be produced from seven different synthesis routes. The ranking of the synthesis routes according to the PDF models shows similar trends to that of an Energy Loss Index proxy indicator which however requires more detailed chemical and process information