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Porous NaTi<sub>2</sub>(PO<sub>4</sub>)<sub>3</sub>-PVDF Composite Granules as Negolyte Boosters for Sodium-Based Redox-Targeting Flow Batteries
No full textInternational audienceRedox-Targeting Flow Batteries (RTFBs) are promising alternatives to classical vanadium-based batteries for large-scale and stationary energy storage. Typically, RTFBs are marked by higher energy densities thanks to the addition of solid boosters within aqueous systems, taking care to limit the use of critical raw materials. This work subsequently investigates the case of sodium titanium phosphate (NTP, NaTi2(PO4)3, 132.8 mAh/g) as a potential booster material for the negolyte side of aqueous RTFBs. Pure NTP and carbon-coated NTP (C-NTP) particles were synthesized and characterized by various techniques (X-ray, TEM, TGA, Raman). So-obtained NTP and C-NTP particles were found to be suitable for creating innovative porous composite boosters formed as centimeter-sized granules by dry processing. Porous composite granules with an open porosity of 65% and 50 wt % of immobilized NTP or C-NTP were successfully produced by an extrusion–dissolution process using a regular PVDF binder and PEO as a porogen agent. Subsequently, intensive electrochemical tests were performed using an innovative dual-mediator reaction system (Fe-Tiron and 2,7-AQDS). High NTP reactivity, with booster utilization rates of up to 84% of its theoretical capacity, can be achieved under flow conditions, with an increase in volumetric capacity by a factor of 1.5, from 4 Ah L–1 to 6 Ah L–1. The mediator concentration (10 – 100 mM) and the mediator/booster ratio (0.5 – 1) play key roles in NTP reactivity. The fundamental work also highlights the benefit of C-NTP, allowing higher reactivity at low mediator concentrations. The study consequently validates the potential of NTP as an interesting booster material in future RTFB applications, with its scalable extrusion–dissolution technique to create innovative porous booster granules
Christian Grataloup Vincent Lemire, 2025, Atlas historique du Moyen-Orient, Paris, L’histoire - Éditions les Arènes, 189 p.
No full textInternational audienceCompte-rendu de l'atlas historique du Moyen-Orient de Christian Grataloup et Vincent Lemire, mis en perspective avec l'atlas éponyme paru en 2020 par Florian Louis
Modèle précurseur et compréhension du phénomène de formation des ombres en maternelle
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Self-written high-efficiency single-mode optical link using a single near-infrared photopolymerization step
No full textAccepté pour publication dans J. Lightwave Tech.International audienceWe present a method for fabricating a self-written waveguide (SWW) between two optical fibers that are single-mode (SM) at 850 nm (780HP/ core diameter: 4.4 µm). The basic principle consists in exposing an acrylic photopolymer formulation sensitive in the near-infrared range (NIR) to a laser beam transmitted simultaneously from both fibers placed face to face, to build a continuous, flexible and self-aligned optical link. The specificity of the presented process (NIR-SM-SWW) lies in the use of a writing wavelength identical to that intended for singlemode propagation in the fibers. This enables the creation in a single step of a SWW directly adapted to the fundamental mode to be transmitted. A precise pre-positioning stage is used to optimize the process. For best photochemical conditions, a coupling efficiency as high as 82 % (-0.86 dB loss) is demonstrated for a 300 µm-long link. The effect of fiber-to-fiber axial and lateral distances is also investigated to estimate the propagation loss and misalignment tolerance, respectively. In addition, measurements performed by quantitative phase optical microscopy indicate a homogeneous index profile in the guide. Using these data, optical modeling is performed and compared to experiments, confirming that a high efficiency SM link is actually fabricated, without the need for further fabrication of an external cladding. This method could therefore be easily applied to the SM connection of a SM VCSEL (vertical-cavity surface-emitting laser) to a SM fiber, which is of major interest for the development of compact optical communications and instrumentation systems
Tensor Decompositions for Signal Processing: Theory, Advances, and Applications
No full textInternational audienceIn the era of big data, rapid advancements in technology and data collection methods have led to the generation and accessibility of vast amounts of multi-modal, high-dimensional data across a diverse range of disciplines. Tensor methods have emerged as essential tools in signal processing, providing powerful frameworks to model and analyze such complex data effectively. This survey offers a comprehensive overview of tensor factorization techniques and their applications in key areas. We explore their role in remote sensing, focusing on tensor-based methods for analyzing hyperspectral and multispectral images, tackling challenges such as recovering super-resolution images and addressing spectral unmixing. In wireless communication, we examine tensor methods used for signal modulation in unsourced massive random access communication, which achieve strong performance in multi-antenna channel and signal modeling. We also discuss tensor applications in network compression, where they reduce the computational demands of deep neural networks, making them more feasible for edge devices. Additionally, we highlight the use of tensor methods in high-dimensional missing data completion problems, showcasing their versatility across various domains. Furthermore, we explore applications in image analysis and computer vision, where tensors are effectively utilized for motion and object tracking, 3D modeling, analysis of satellite imaging, and medical imaging. By bridging theoretical advancements with practical applications, this survey aims to guide researchers in leveraging tensor methods to tackle emerging challenges in signal processing
ROOFS: RObust biOmarker Feature Selection
No full textFeature selection (FS) is essential for biomarker discovery and in the analysis of biomedical datasets. However, challenges such as high-dimensional feature space, low sample size, multicollinearity, and missing values make FS non-trivial. Moreover, FS performances vary across datasets and predictive tasks. We propose roofs, a Python package available at https://gitlab.inria.fr/compo/roofs, designed to help researchers in the choice of FS method adapted to their problem. Roofs benchmarks multiple FS methods on the user's data and generates reports that summarize a comprehensive set of evaluation metrics, including downstream predictive performance estimated using optimism correction, stability, reliability of individual features, and true positive and false positive rates assessed on semi-synthetic data with a simulated outcome. We demonstrate the utility of roofs on data from the PIONeeR clinical trial, aimed at identifying predictors of resistance to anti-PD-(L)1 immunotherapy in lung cancer. The PIONeeR dataset contained 374 multi-source blood and tumor biomarkers from 435 patients. A reduced subset of 214 features was obtained through iterative variance inflation factor pre-filtering. Of the 34 FS methods gathered in roofs, we evaluated 23 in combination with 11 classifiers (253 models in total) and identified a filter based on the union of Benjamini-Hochberg false discovery rate-adjusted p-values from t-test and logistic regression as the optimal approach, outperforming other methods including the widely used LASSO. We conclude that comprehensive benchmarking with roofs has the potential to improve the robustness and reproducibility of FS discoveries and increase the translational value of clinical models
Molecular dynamics study on the coupled effects of size and pre-existing oxide layer on the compressive mechanical properties of copper nanowires
No full textInternational audienceCopper nanowires generally exhibit a native oxide shell layer, which can significantly impact their performance and reliability, especially in nanoelectronics applications. Using molecular dynamics simulations with the variable charge ReaxFF potential, we systematically examine the effects of preexisting oxide layers on the mechanical properties and deformation mechanisms of [001]-oriented Cu nanowires with varying diameters at room temperature. Our findings reveal a size-dependent influence of the native oxide layer on the mechanical behavior. Specifically, the formation of an oxide shell (CuxOy) around the Cu core reduces the activation barrier for defect nucleation, reducing yield properties and, thereby, weakening the nanowires. This effect is more pronounced in smaller samples due to the intensified interaction between the metallic core and the oxide shell. Additionally, while the strength, elastic modulus, and yield stress increase with the diameter of pristine and oxidized specimens, pristine nanowires consistently exhibit superior mechanical properties when compared to their oxidized counterparts. The degradation in mechanical performance primarily stems from the early onset of plasticity initiated at the oxidized surface. These findings emphasize the detrimental impact of native oxide layers on the mechanical behavior of Cu nanowires and highlight the critical role played by size upon the mechanical properties of nano-oxidized metal samples. This work provides valuable insights into tailoring the mechanical properties of Cu nanowires, contributing to the optimization of their performance in both nanoelectronics and mechanical applications.</div
A propos du volume 3 de Serge Schweitzer (Le libéralisme : jalons pour une reconstruction, PUAM 2025, Recension in Journal des libertés 2026 : https://journaldeslibertes.fr/article/le-liberalisme-jalons-pour-une-reconstruction/
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Refining near-infrared spectroscopy for collagen quantification: A new predictive model for archaeological bone
No full textInternational audienceCollagen is a vital archaeological material, preserving biochemical signatures that provide insights into past environments, diets, and human-animal interactions. However, diagenesis can lead to rapid and inconspicuous collagen degradation. Given the variability in collagen preservation and its significance for analyses such as radiocarbon dating, stable isotope analysis, and ZooMS, researchers have developed prescreening techniques to assess collagen preservation before destructive sampling. Current prescreening approaches, including %N and C:N ratios, typically require sample destruction and access to equipped laboratories. Spectroscopic techniques such as Raman spectroscopy and Fourier Transform Infrared spectroscopy have been explored as alternatives, but they are limited in penetration depth, generalizability (at present at least), and are often still destructive, if minimally.Here, we further develop single-point near-infrared (NIR) spectroscopy as a fully non-destructive, rapid, and field-portable method for prescreening bone for collagen preservation. Unlike FTIR and Raman spectroscopic techniques, NIR light penetrates below the surface of bone, enabling assessment of internal collagen preservation without destructive sample preparation. Using Partial Least Squares Regression (PLSR) and Random Forest (RF) modeling, we trained predictive models on whole bones with known collagen yields and validated the models on an independent archaeological collection. Both PLSR and RF models, when restricted to the 2030–2060 nm range, demonstrate strong and comparable performance while avoiding wavelengths associated with consolidants in our reference library. The models outperform traditional % N-based methods in identifying suitable samples for radiocarbon dating. These models enable the high-throughput screening of large collections of bone, improving sample selection and minimizing unnecessary destructive analysis
Search for ttbar resonances in final states with exactly one or two leptons using 140 fb of pp collision data at TeV with the ATLAS experiment
No full textInternational audienceA search for heavy spin-1 and spin-2 resonances decaying into a top-antitop-quark pair has been performed with 140 fb of proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider at a centre-of-mass energy of TeV. Final states with either exactly one electron or muon, or exactly two leptons (, or ), large missing transverse momentum, and two jets, at least one of which must be identified as likely containing a b-hadron decay, are considered. The search targets resonances with both narrow and broad widths relative to the detector resolution, and with masses in the range of 0.4-5.0 TeV. No significant deviation from the Standard Model prediction is observed. Exclusion limits are set on the production cross-section times branching ratio for hypothetical bosons, Kaluza-Klein gravitons, and Kaluza-Klein gluons that decay into top-quark pairs