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De la solution au réseau poreux : contrôler la morphologie et les propriétés des aérogels de cellulose
No full textAerogel materials exhibit unique characteristics such as low density, open porosity, and a high internal specific surface area. These features make them highly desirable for diverse applications such as thermal insulation, environmental remediation, filtration, catalysis, energy storage, sensing technologies, and space exploration. Traditionally, aerogels are synthesized from silica, metal oxides, or synthetic polymers, relying either on costly raw materials such as silica or petroleum-based chemicals, along with expensive and energy-intensive manufacturing processes.In the early 21st century, a new class of aerogels emerged: they are based on polysaccharides, possessing reduce environmental footprint and unlocking aerogels' use in life sciences (biomedical, pharmaceutical, food, and cosmetics). Among various polysaccharides, cellulose stands out as one of the very promising raw materials for aerogel production due to its abundance, renewability, non-competition with food sources and biodegradability. Despite these advantages, cellulose-based aerogels, as well as other bio-aerogels, have struggled to find widespread applications. This is attributed to several drawbacks, such as long production process relying on diffusion-driven phase separation and use of low- or high-pressure technology needed for drying. Cellulose aerogels also present some structural limitations: for example, the presence of large macropores and aggregated structures compromise thermal insulation performance.This thesis explores the correlations between processing conditions and properties of porous cellulose-based materials made via dissolution-coagulation and drying pathway. The process involves microcrystalline cellulose dissolution, aqueous NaOH is used as an easy to recycle non-toxic cellulose solvent. Dissolution is followed by an optional gelation step, after which solvent exchange occurs via diffusion. This process induces phase separation and cellulose self-aggregation into a three-dimensional network with non-solvent in the pores. After an optional further exchange with other non-solvents, the coagulated gel is dried, usually with supercritical CO2, to obtain the aerogel.Currently, aerogel production largely relies on trial-and-error approaches, limiting advancing cellulose aerogels towards practical applications. The goal of this thesis is thus a systematic examination and understanding of the impact of various non-solvents and of drying conditions on the morphology and properties of cellulose, targeting aerogel-like materials.Several critical issues will be addressed in this thesis. The influence of coagulation non-solvent on the morphology of the porous network will be investigated. Special attention will be given to evaporative drying and the relationship between the properties of the precursor before drying and those of the final dried material. Evaporative drying presents a simple and scalable alternative to supercritical drying; however, capillary pressure must be managed to prevent structural collapse. Achieving aerogel-like properties through evaporative drying requires control of the coagulated gel morphology and drying conditions. Additionally, efforts will be made to chemically modify cellulose to impart hydrophobicity to the aerogels. Finally, the impact of porous material morphology on the diffusion-driven release kinetics for drug-delivery applications will be evaluated.We aim to control the final properties of cellulose aerogels and aerogel-like materials by deepening our understanding of the processing steps involved. This study prioritizes the use of simple techniques, environmentally friendly and low-toxicity compounds, and scalable production methods to reduce manufacturing costs and environmental impact.Les aérogels possèdent des caractéristiques singulière, une faible densité, une porosité ouverte et une grande surface spécifique. Ces propriétés les rendent attractifs pour diverses applications, notamment l'isolation thermique, la dépollution, la filtration, la catalyse, le stockage d'énergie, les capteurs et l'exploration spatiale. Traditionnellement, les aérogels sont synthétisés à partir de silice, d'oxydes métalliques ou de polymères synthétiques, impliquant l'utilisation de matières premières coûteuses (comme la silice ou des produits pétrochimiques) et des procédés de fabrication énergivores et onéreux.Au début du XXIe siècle, un nouveau type d'aérogels à base de polysaccharides a émergé, possédant une empreinte environnementale réduite et ouvrant des perspectives dans le biomédical, la pharmaceutique, l'alimentation et le cosmétique. Parmi les différents polysaccharides, la cellulose est une matière première prometteuse en raison de son abondance, sa renouvelabilité, sa non-compétition avec les ressources alimentaires et sa biodégradabilité. Malgré ces avantages, les aérogels de cellulose peinent à trouver des applications à grande échelle. Cela s'explique par plusieurs contraintes, notamment un processus de production long reposant sur la diffusion et l'utilisation de technologies de séchage sous basse ou haute pression. De plus, les aérogels de cellulose présentent des limitations structurelles, comme la présence de macropores de grande taille et d'agrégats important, ce qui affecte leurs performances en isolation thermique.Cette thèse explore les corrélations entre les conditions de préparation et les propriétés des matériaux poreux à base de cellulose obtenus par dissolution-coagulation et séchage. Le procédé implique la dissolution de cellulose microcristalline dans une solution aqueuse de soude, un solvant non toxique et recyclable. Après dissolution, une étape de gélification peut être réalisée, suivie d'un échange de solvant par diffusion avec un non-solvent. Ce processus entraîne une séparation de phase et une agrégation de la cellulose en un réseau tridimensionnel. Après un éventuel échange supplémentaire avec d'autres non-solvants, le gel coagulé est généralement séché en utilisant du CO₂ supercritique pour obtenir l'aérogel.À l'heure actuelle, la production d'aérogels repose sur une approche empirique, freinant leur développement pour des applications concrètes. L'objectif de cette thèse est donc d'étudier de manière systématique l'impact des différents non-solvants et des conditions de séchage sur la morphologie et les propriétés de la cellulose en vue de produire des matériaux de type aérogel.Plusieurs aspects critiques seront abordés. L'influence du non-solvant de coagulation sur la morphologie du réseau poreux sera analysée, en mettant un accent particulier sur le séchage par évaporation et la relation entre les propriétés du précurseur avant séchage et celles du matériau final. Le séchage évaporatif constitue une alternative simple et évolutive au séchage supercritique, mais il nécessite de maîtriser la pression capillaire pour éviter l'effondrement structurel. Obtenir des propriétés comparables à celles des aérogels par séchage évaporatif exige donc un contrôle précis de la morphologie du gel coagulé et des conditions de séchage. De plus, des modifications chimiques seront envisagées pour rendre les aérogels hydrophobes. Enfin, l'impact de la morphologie poreuse sur les cinétiques de libération contrôlée de médicaments sera évalué.L'objectif est de mieux contrôler les propriétés finales des aérogels de cellulose et des matériaux apparentés en approfondissant la compréhension des étapes de traitement. Cette étude privilégie des techniques simples, des composés à faible toxicité, ainsi que des méthodes de production industrialisable afin de réduire les coûts de fabrication et l'impact environnemental des aérogels de cellulose
A Molecular Representation to Identify Isofunctional Molecules
No full textInternational audienceAbstract The challenges of drug discovery from hit identification to clinical development sometimes involves addressing scaffold hopping issues, in order to optimise molecular biological activity or ADME properties, or mitigate toxicology concerns of a drug candidate. Docking is usually viewed as the method of choice for identification of isofunctional molecules, i. e. highly dissimilar molecules that share common binding modes with a protein target. However, the structure of the protein may not be suitable for docking because of a low resolution, or may even be unknown. This problem is frequently encountered in the case of membrane proteins, although they constitute an important category of the druggable proteome. In such cases, ligand‐based approaches offer promise but are often inadequate to handle large‐step scaffold hopping, because they usually rely on molecular structure. Therefore, we propose the Interaction Fingerprints Profile (IFPP), a molecular representation that captures molecules binding modes based on docking experiments against a panel of diverse high‐quality proteins structures. Evaluation on the LH benchmark demonstrates the interest of IFPP for identification of isofunctional molecules. Nevertheless, computation of IFPPs is expensive, which limits its scalability for screening very large molecular libraries. We propose to overcome this limitation by leveraging Metric Learning approaches, allowing fast estimation of molecules IFPP similarities, thus providing an efficient pre‐screening strategy that in applicable to very large molecular libraries. Overall, our results suggest that IFPP provides an interesting and complementary tool alongside existing methods, in order to address challenging scaffold hopping problems effectively in drug discovery
Développement de la thermodynamique expérimentale et computationnelle pour décrire les équilibres de phases des mélanges cryogéniques dans le contexte la transition énergétique.
No full textIn the context of the energy transition, the solid-fluid equilibrium behavior of low-temperature mixtures of industrial relevance (e.g., H2, CO2, CH4) primarily involves molecular solids. This thesis investigates the phase equilibrium behavior of these cryogenic systems through both experimental and computational approaches. Experimentally, a range of methane-rich systems representative of Liquefied Natural Gas (LNG)-like mixtures were studied using a static-analytic method, conducted as part of a Joint Industry Project. From a modeling standpoint, the influence of both the fluid-phase model, crucial for accurate mixture density predictions, and the solid-phase model, critical for capturing the thermodynamic properties of the solid phase, on the reliability of solubility predictions was investigated. This effort led to the development of a new Gibbs energy equation of state for representing the phase I of solid carbon dioxide. Furthermore, a unified framework for solving phase equilibrium problems involving multiple types of solid phases was proposed, based on a Gibbs energy minimization algorithm. The algorithm accounts for various solid types, including pure solids, fully and partially miscible solids, hydrates, and co-crystals. It has been successfully applied to a range of binary systems encountered in cryogenic applications such as air separation, carbon capture and transport and natural gas liquefactionDans le contexte de la transition énergétique, les solides intervenant dans les équilibres solide-fluide des mélanges cryogéniques ayant un intérêt industriel (par exemple H2, CO2, CH4) sont principalement des solides moléculaires. Ainsi, cette thèse vise à explorer le comportement des équilibres de phases de ces systèmes à basse température à travers une approche expérimentale et computationnelle. Sur le plan expérimental, plusieurs systèmes riches en méthane, représentatifs des mélanges de type Gaz Naturel Liquéfié (GNL), ont été étudiés à l’aide d’une méthode statique-analytique, dans le cadre d’un projet industriel réunissant plusieurs partenaires industriels. Sur le plan de modélisation, l’influence du modèle de phase fluide, essentiel pour prédire correctement la densité des mélanges, ainsi que celle du modèle de phase solide, capable de représenter correctement les propriétés thermodynamiques de la phase solide, sur la fiabilité des prédictions de solubilité a été explorée. Ce travail a conduit au développement d’une nouvelle équation d’état sous forme d’énergie de Gibbs pour représenter la phase I du CO2 solide. En parallèle, une approche unifiée pour résoudre les conditions d’équilibre entre phases impliquant plusieurs types de phases solides a été proposée, reposant sur un algorithme de minimisation de l’énergie de Gibbs. Cet algorithme prend en compte différents types de solides, comme les solides purs, les solides partiellement ou totalement miscibles, les hydrates et les co-cristaux. Il a été appliqué avec succès à divers systèmes binaires rencontrés dans des applications cryogéniques telles que la séparation cryogénique de l’air, le captage et le transport du CO2, ou encore la liquéfaction du gaz naturel
Solving Inverse chemical problems via the Adjoint method: A case study on Uranium In-Situ Recovery
No full textInternational audienceInverse modeling provides a powerful tool for addressing uncertainties inherent in complex physical systems.In the context of chemical processes, this often involves solving large systems of nonlinear equations with poorly constrained parameters.This work demonstrates the application of the adjoint state method for inverse modeling of complex chemical problems. While the direct chemical problem can be approached using various numerical methods, depending on species appearance/disappearance and the degree of implicitness, the adjoint problem remains independent of the chosen direct solver. This is a key advantage of the adjoint approach.Moreover, the adjoint problem is numerically simpler than the direct problem, enabling efficient optimization within a reasonable computational timeframe. The effectiveness of this method is illustrated through case studies involving simplified carbonate systems and a redox-sensitive uranium–iron system
INVESTIGATION OF THE LASER-ALUMINUM MOMENTUM COUPLING COEFFICIENT IN THE KHZ-REGIME FOR LASER ABLATION PROPULSION WITH DONUT-SHAPED BEAM
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Self-Supervised Metric Learning for Gaussian Anomaly Detection in Fundus Images
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Deep Learning Prediction of Dry Friction in DLC Coatings Using Literature-Derived Data
No full textInternational audiencePredicting the friction behavior of diamond-like carbon (DLC) coatings remains a key challenge in tribology due to the complex interplay of test conditions, material properties, and experimental variability. Although literature data are abundant, they are often non-standardized and are reported under highly variable conditions, which hinders their systematic reuse for predictive modeling. This study introduces a machine learning (ML) framework that exploits heterogeneous data with a focus on physical relevance and robustness. A dataset of approximately 4100 points (including 410 friction coefficient points) was compiled from an extensive literature review. Two modeling scenarios are defined: the first uses mechanical, structural, and tribological descriptors; the second adds chemical composition features, offering more detail but reducing dataset size. Six machine learning models are evaluated under standardized training conditions to predict friction. Model performance is evaluated using standard metrics. Extra Trees (ET) and Artificial Neural Networks (ANNs) achieve the highest performance. SHAP (SHapley Additive exPlanations) analysis identifies temperature and hertz pressure as dominant predictors, consistent with the tribological observations. Incorporating chemical composition improved prediction accuracy but reduced dataset size, highlighting a key trade-off between data completeness and feature richness. SHAP analysis shows that while temperature and hertz pressure remain key predictors, the importance of humidity increases, reflecting that chemical inputs enhance not only accuracy but also the physical interpretability of the models. The results demonstrate that literature-based data can support robust and physically meaningful friction modeling when feature richness is balanced with careful control of data quality
Synergistic anti-wear performance of TiO2 nanoparticles and ZDDP: Influence of dispersion methods
No full textInternational audienceZinc dialkyldithiophosphate (ZDDP) remains a cornerstone anti-wear additive in lubricants, particularly in applications demanding extreme boundary lubrication performance. However, emerging challenges in electric vehicle (EV) transmissions, such as higher available torque at standstill and lower lubricant viscosity, necessitate advanced formulations. Metal oxide nanoparticles, particularly anatase TiO2, have demonstrated potential to enhance wear protection through the formation of protective tribofilms. This study investigates the benefits of combining TiO2 nanoparticles with ZDDP in mitigating wear under boundary conditions. We evaluate the impact of dispersion methods, including oleic acid-based physical dispersion and chemical functionalization, on the tribological performance of these hybrid formulations. Using a combination of ball-on-disc tribological testing, profilometry, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), and X-ray photoelectron spectroscopy (XPS) analyses, we demonstrate a synergistic effect between ZDDP and TiO2 nanoparticles, delivering superior wear protection and friction reduction compared to individual components, regardless of dispersion method. However, chemically functionalized TiO2 outperforms physically dispersed nanoparticles by forming a thicker and more uniform anti-wear tribofilm. These findings highlight the potential for hybrid lubricant formulations to meet the demands of advanced automotive applications
