Portail HAL UHA (Université de Haute-Alsace)
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Coordination of aluminum in saponite-like material as a function of synthesis pH
No full textInternational audienceAbstract Saponite-like materials have a wide range of potential applications, especially in heterogeneous catalysis. Despite the simplicity of the synthesis, the mechanisms of the formation of saponite are not well understood yet. The aim of the present study was to investigate a possible correlation between the coordination of Al in the solid phase and in the solution. For this, samples were prepared by varying the initial OH:Si molar ratio from 0.18 to 2.14, leading to a pH in the supernatant after the hydrothermal treatment of 6.7 to 12.7, respectively. The characterization of the material was performed by combining nuclear magnetic resonance (NMR) and X-ray absorption near edge structure (XANES) spectroscopies, and good agreement was obtained between the two techniques. Between pH7 and pH10, 60–65% of aluminum was found to be in tetrahedral coordination, while this percentage increased above pH10 (up to 81%). These results correlated with the speciation of the aluminum in aqueous solution. Indeed, above pH10, all available aluminum was in the soluble form Al(OH) 4 –
UV photocatalysis of ZnO nanowires: the issues of polarity and doping
No full textInternational audienceAs a sustainable wide bandgap compound semiconductor absorbing UV light while exhibiting high photocatalytic activity, ZnO in the form of nanowires has been considered as a promising candidate. Here, its polarity and its intentional doping with Al, Ga, Cu, Sb, Cl, Al-Ga, and Al-Cl are investigated to thoroughly assess their effects on the photocatalytic activity and processes. The photocatalytic processes in ZnO nanowires are found to be governed by the action of •OH hydroxyl radicals, as the main reactive species degrading methyl orange, and hence by free hVB+ acting as the primary active charge carriers on the surfaces of ZnO nanowires, regardless of the nature and concentration of dopants. The photocatalytic activity is further shown to be higher for acceptors than for shallow donors, and to preferentially act on the polar +c-plane top of ZnO nanowires. Eventually, a photo-corrosion phenomenon is concomitant with the photocatalytic processes, raising concerns about the chemical stability of ZnO nanowires. These findings revisit the effects of polarity and intentional doping of ZnO nanowires for photocatalysis and open perspectives to address chemical and technological challenges
Faut-il considérer les exploitations agricoles des piémonts comme des exploitations de moyenne montagne ?
No full textInternational audienceDefining medium altitude mountain is a difficult task. This article suggests to contribute to the thoughts on the subject, especially starting from the criterion of the constraints on farming activity. To this end, it bases on two inquiries conducted in 2019 and 2021 on farming practices in and around two plains: the Lembron plain, located in the heart of the Massif central; and the Rhine valley, surrounded by Vosges and the Black Forest. Whatever the criteria used, it proves difficult to delimit the plain, the edge and the mountain, for these three ensembles certainly have differences, but also common features. We thus conclude that the plain and the mountain are spaces related by transition zones with blurred boundaries, where exchanges and tensions manifest.Définir la moyenne montagne est une tâche ardue. Cet article propose de contribuer aux réflexions sur le sujet en partant notamment du critère des contraintes pesant sur l’activité agricole. Il s’appuie pour cela sur deux enquêtes menées en 2019 et 2021 sur les pratiques agricoles dans et autour de deux plaines : la plaine du Lembron, située au cœur du Massif central ; et le Fossé rhénan, encadré par les Vosges et la Forêt Noire. Quels que soient les critères utilisés, il s’avère difficile de délimiter plaine, bordure et montagne, car ces trois ensembles présentent certes des différences, mais aussi des caractéristiques communes. Nous concluons donc que plaine et montagne sont des espaces reliés par des zones de transition aux limites floues, où se manifestent des échanges et tensions
Correlation between domain size and charge transport properties in benzothiadiazole–thiophene molecules: insights from nano-focus X-ray scattering and fast scanning chip calorimetry
No full textInternational audienceConjugated compounds including thiophene and benzothiadiazole units are promising candidates for next-generation semiconductor materials. Precise control over morphology and crystal orientation is critical for optimizing device performance. By employing a combination of synchrotron nano-focus X-ray scattering and fast chip calorimetry, a correlation was established between the size of ordered domains formed during isothermal crystallization and charge carrier mobility. These findings highlight the potential of advanced in situ techniques for fine-tuning the electronic properties of organic semiconductors
Development of Sustainable Rubber Composites Reinforced with Silk Fabric for High-Performance Bicycle Tires: Material Characterization and Prototype Testing
No full textInternational audienceNatural rubber (NR) composites reinforced with fabrics were prepared through compression molding by sandwiching a layer of fabric between two layers of NR. A range of composite properties were assessed, including adhesion and mechanical-thermal behavior. Cross-linked NR reinforced with silk fabric had better mechanical properties compared to the same NR reinforced with nylon fabric. Furthermore, silk fabric reinforced NR had a lower dissipation energy. This study combined material characterization with pilot-scale manufacturing of racing bicycle tires. It compared commercial nylon-reinforced tires with tires reinforced using silk fabric. The silk-reinforced tire performed better than the conventional nylon-reinforced tire in durability (129%), puncture resistance (157%), and cord tensile strength (243%). In addition, life cycle assessment (LCA) revealed significant environmental advantages of silk-reinforced tires, with reductions of over 80% in global warming potential (GWP), abiotic depletion of fossil resources, ozone depletion potential (ODP), and photochemical oxidation potential (POP) compared to nylon-reinforced tires. These results highlight silk fabric as a sustainable, high-performance alternative for commercial-scale, energy-saving racing bicycle tire applications
High coercivity in A0.54Ca0.46Fe6.5Al5.5O19 (A = Ba and Sr) M-type hexaferrite prepared by sol-gel auto-combustion method
No full textInternational audienc
Transformer-Based Lung Infection Severity Prediction with Cross Attention and Conditional TransMix Augmentation
No full textInternational audienceLung infections, particularly pneumonia, pose significant health risks and can rapidly worsen, especially during pandemics. Developing advanced AI-driven tools for severity prediction based on medical imaging is essential for timely decision-making and treatment, ultimately saving lives. In this study, we introduce a novel approach applicable to multiple medical imaging modalities, including CT scans and chest X-rays, for predicting lung infection severity. Our method consists of two key components: a Transformerbased severity prediction model and an augmentation strategy called Conditional Online TransMix, designed to address data imbalance. The proposed model employs parallel encoders, integrating Pyramid Vision Transformers (PVTs) with a cross-gated attention mechanism and a feature aggregation module to generate a scalar severity score. To enhance model generalization across datasets, we introduce a tailored augmentation technique that synthesizes new mixed severity scores linked to image patches. We validate our approach using the RALO CXR and Per-COVID-19 CT datasets, demonstrating superior performance on multiimage modalities compared to several state-of-the-art deep learning models. By incorporating a customized weighted loss function, our method enhances the precision of automated lung disease severity assessment, providing a reliable and adaptable AI tool for clinical diagnosis and treatment planning
Modeling the Interaction Between Silver(I) Ion and Proteins with 12-6 Lennard-Jones Potential: A Bottom-Up Parameterization Approach
No full textInternational audienceSilver(I) ions and organometallic complexes thereof are well-established antimicrobial agents. They have been employed in medical applications for centuries. It is also known that some bacteria can resist silver(I) treatments through an efflux mechanism. However, the exact mechanism of action remains unclear. All-atom force-field simulations can provide valuable structural and thermodynamic insights into the molecular processes of the underlying mechanism. Lennard-Jones parameters of silver(I) have been available for quite some time; their applicability to properly describing the binding properties (affinity, binding distance) between silver(I) and peptide-based binding motifs is, however, still an open question. Here, we demonstrate that the standard 12-6 Lennard-Jones parameters (previously developed to describe the hydration free energy with the TIP3P water model) significantly underestimate the interaction strength between silver(I) and both methionine and histidine. These are two key amino-acid residues in silver(I)-binding motifs of proteins involved in the efflux process. Using free-energy calculations, we calibrated non-bonded fix (NBFIX) parameters for the CHARMM36m force field to reproduce the experimental binding constant between amino acid sidechain fragments and silver(I) ions. We then successfully validated the new parameters on a set of small silver-binding peptides with experimentally known binding constants. In addition, we monitored how silver(I) ions increased the α-helical content of the LP1 oligopeptide, in agreement with previously reported Circular Dichroism (CD) experiments. Future improvements are outlined. The implementation of these new parameters is straightforward in all simulation packages that can use the CHARMM36m force field. It sets the stage for the modeling community to study more complex silver(I)-binding processes such as the interaction with silver(I)-binding-transporter proteins
A Comparative Study of CNNs and Vision-Language Models for Chart Image Classification
No full textInternational audienceChart image classification is a critical task in automating data extraction and interpretation from visualizations, which are widely used in domains such as business, research, and education. In this paper, we evaluate the performance of Convolutional Neural Networks (CNNs) and Vision-Language Models (VLMs) for this task, given their increasing use in various image classification and comprehension tasks. We constructed a diverse dataset of 25 chart types, each containing 1,000 images, and trained multiple CNN architectures while also assessing the zero-shot generalization capabilities of pre-trained VLMs. Our results demonstrate that CNNs, when trained specifically for chart classification, outperform VLMs, which nonetheless show promising potential without the need for task-specific training. These findings underscore the importance of CNNs in chart classification while highlighting the unexplored potential of VLMs with further fine-tuning, making this task crucial for advancing automated data visualization analysis
