Capability of thermodesorption/pyrolysis DART FT-ICR MS to distinguish fluoropolymers and identify blend composition

International audienceDirect analysis in real time (DART) was coupled with a thermal desorption/pyrolysis (TDPy) device for the analysis of fluoropolymers. The product ions were analyzed using a Fourier transform cyclotron resonance mass spectrometer (FT-ICR MS). Two different polyvinylidene fluoride (PVDF) samples were studied individually and in a 50/50 mixture. This study demonstrates the capability of TDPy DART FT-ICR MS to provide information on PVDF polymers, including the determination of end-groups and the detection of comonomers.The temperature program used enabled the desorption of the smallest oligomers (Mn ≈ 600 Da) below 400 °C, allowing for the identification of the end-groups, which ensured the differentiation of the PVDF. At temperatures above 400 °C, Cw Hx Fy- ions were predominantly formed as a result of the thermal cleavage of the PVDF backbone.Specific pyrolysis products observed for one PVDF sample suggested the presence of 4.6 mol% hexafluoropropylene (HFP), as determined by NMR measurements. The molar percentage of HFP was also determined by a new approach using TDPy DART MS. The analysis of a 50/50 PVDF blend revealed species from both polymers during the thermo-desorption and pyrolysis events, confirming the ability of the proposed methodology to determine the mol% of the HFP comonomer. This represents the first TDPy DART FT-ICR MS study of fluoropolymers. Applicable to non-soluble or poorly soluble polymers, the proposed methodology enables the identification of end-groups, suggests the possibility of distinguishing fluoropolymers, and identifies blend composition. Additionally, the molar percentage of comonomers can be defined for poly(VDF-co-HFP) copolymers.</div

AI-enabled spectral classification of plastic resins from E-waste via laser-induced breakdown spectroscopy for advanced sorting applications

International audienceIn the framework of the circular economy (CE), efficient waste segregation is essential for sustainable recycling. Plastic waste from waste electrical and electronic equipment (WEEE) poses challenges due to complex resin structures and the presence of brominated flame retardants (BFRs). This study investigates the use of laserinduced breakdown spectroscopy (LIBS) combined with supervised machine learning (ML) for the classification of various e-waste plastics, including mixed resins and those containing BFRs. Although the primary analysis was conducted using static LIBS data, dynamic tests were also performed to simulate real-world sorting conditions. Among the classifiers, Support Vector Machine (SVM) and Neural Network Multilayer Perceptron (NNMLP) delivered the best results, reaching 92-94 % accuracy on test data and up to 96 % on unseen datasets. Furthermore, dynamic trials showed over 98 % accuracy, confirming the robustness of the approach. These findings highlight the potential of LIBS-ML systems for scalable, high-precision sorting, advancing industrial recycling strategies

Using thin AZO layers coupled with SiNx:H as a way to decrease Indium consumption in SHJ cells and modules

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Digital electronics upgrade of the INDRA <math altimg="si2.svg" display="inline" id="d1e354"><mrow><mn>4</mn><mi>π</mi></mrow></math> charged particle detection array and resulting performance improvements

International audienceINDRA is a 4π charged particle detection array in use since 1993 for the study of nuclear collisions at bombarding energies from a few 10s to a few 100s of MeV/nucleon. Originally equipped with custom electronics using the VXI standard, the entire acquisition system was recently upgraded to a fully digital system using commercially-available modules supplied by mesytec GmbH &amp; Co. KG. At the same time, both low and high voltage supplies and all cabling and signal routing outside of the reaction chamber have also been replaced. The new electronics were used for the first time in 2022 in an experiment at GANIL coupling INDRA with 12 blocks of FAZIA telescopes placed at forward angles. The full details of the upgraded system, and the resulting improvements in performance, stability, dead time and identification capabilities are presented in this article

Statistical modeling and generation of inertial ductile fracture surfaces

International audienceSpallation in ductile metals involves complex void nucleation and growth mechanisms, but the interactions between voids and the resulting statistical structure of fracture surfaces remain a persistent challenge for both experimental and theoretical modeling. This study develops a generative model to capture the statistical features of spall-induced fracture surfaces in highpurity aluminum. Aluminum samples were subjected to nanosecond laser-induced spallation, and the resulting fracture surfaces were imaged via scanning electron microscopy (SEM) and reconstructed in 3D. Individual dimples were segmented and analyzed to extract void size distributions and the spatial arrangement of nucleation sites. Boolean models and Gaussian random fields were then used to generate synthetic surfaces and compared against the experimental data using one-and two-point statistics. The analysis revealed a Poisson distribution of nucleation centers within the spall plane but significant out-of-plane spatial correlations in nucleation depth. The extended generative model successfully reproduces both the surface height distribution and the spatial covariance observed experimentally. These results emphasize the need to incorporate large-scale spatial correlations in predictive models of dynamic ductile damage. The proposed framework provides a basis for future studies of collective void growth and spall surface formation in dynamic ductile fracture.</div

Search for Magnetic Monopoles with the Complete ANTARES Dataset

International audienceThis study presents a novel search for magnetic monopoles using data collected over a 14 year period (2008-2022) by the ANTARES neutrino telescope. The interaction of magnetic monopoles with matter was modeled according to Kazama, Yang, and Goldhaber cross-section. Upper limits on the flux of magnetic monopoles are obtained for velocities both above and below the Cherenkov threshold. No events consistent with the passage of magnetic monopoles were detected, enabling the setting of an upper flux limit for relativistic magnetic monopoles of the order of $10^{-18} \mathrm{cm}^{-2} \mathrm{s}^{-1} \mathrm{sr}^{-1}$

Comparative assessment of feature extraction for fast neutron spectra prediction with machine learning algorithms using a CVD diamond detector

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Technological trajectories in iron smelting: slag signatures, recipes, and traditions from Phnom Dek (Cambodia, 7th–20th c. CE)

International audienceThis study investigates the long-term dynamics of bloomery iron smelting practices across the Phnom Dek region of Cambodia, a major metallurgical landscape active from at least the 7th to 20th centuries CE. Based on pXRF analysis of more than 1,700 slag samples, it develops an interpretive framework that integrates multiple scales of evidence, combining chemical composition, spatial distribution, technical features, and chronological context. At the core of this approach is the identification of coherent chemical signatures in slag, which, by using multivariate analyses, function as proxies for metallurgical recipes, and, at a broader level, enduring technological traditions shaped by the social organization of production. These signatures serve as comparative units for tracing production behaviors across sites and time periods. Through the categories of practice and recipe, the analysis aims to identify patterns of continuity, adaptation, and transformation in iron-making processes or smelting behavior over time. Results point to significant changes in ore procurement and recipe during the 11th–12th centuries, likely linked to wider transformations within Angkorian state dynamics. The persistence of specific chemical profiles and regionally shared smelting practices beyond this period suggests a bloomery tradition sustained across the landscape. Ultimately, the study argues that the chemistry of slag, as a material trace of smelting activities derived from technical, spatial, and chronological contexts, has unique capabilities to acquire interpretive significance when analyzed across these dimensions. This approach enables the discussion of technological trajectories in iron production and the socio-technical logics that shaped the evolution of the Phnom Dek metallurgical landscape

VENDETA: VErsatile Neutron DETector Array, a new high-resolution neutron time-of-flight measurement array

International audienceThe VErsatile Neutron DETector Array (VENDETA) is a high-resolution time-of-flight array for neutron detection. VENDETA’s liquid scintillator detectors offer a high intrinsic efficiency for neutron detection from 100keV to 20MeV, as well as neutron-γ discrimination capabilities down to 10keVee. VENDETA was specifically designed for versatility and is relevant for a wide range of physics measurements, from prompt fission neutron spectra measurements to neutron spectroscopy studies, such as elastic and inelastic neutron scattering measurements. VENDETA was first deployed at the Los Alamos Neutron Science Center. This article will provide a detailed overview of its characteristics

Validation of a lipopetide approach to a Safe-and-Sustainable-by-Design strategy on nano-TiO2 UV filters

International audienceTitanium dioxide (TiO2) nanoparticles are well suited for cosmetics and polymer films because they efficiently absorb UV light while remaining transparent to visible light. Their widespread use requires strategies for managing potential human and environmental risks. Implementing the Safe and Sustainable by Design (SSbD) methodology to advanced chemicals and materials is a major global challenge and a concept that is included in several EU research projects. This study employed a SSbD strategy by functionalizing the surface of TiO2 nanoparticles with a lipopeptide-based biosurfactant (Sodium Surfactin, SS). A colloidal heterocoagulation approach was used to produce SS-modified TiO2 nanoparticles. Different design options (TiO2 source, order of addition, TiO2/SS weight ratio) were investigated, and the properties were compared by measuring the UV filtering capability, photoreactivity, dustiness index, biological and ecotoxicological endpoints. This allowed us to estimate the safety and sustainability profile in agreement with the steps suggested by the JRC SSbD framework. The lipopeptide-based coating was essential for managing UV light-induced photoactivity and significantly lowering both in vitro cytotoxicity and ecotoxicity while simultaneously enhancing photostability when applied in cosmetic formulations. These results demonstrate that a colloidal process, which can be easily scaled up for industrial purposes, is a promising and exploitable SSbD strategy for the design and implementation of nano-TiO2 based UV filters