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Concept and technology for full monolithic MOSFET and JBS vertical integration in multi-terminal 4H-SiC power converters
No full textInternational audienceNew and original medium power multi-terminal SiC monolithic converter architectures are investigated with vertical switching cells based on SiC JBS diodes and VDMOS transistors. 2D TCAD and mixed-mode Sentaurus™ simulations are performed to optimize switching structures as Buck, Boost, H-bridge high-side row chip common drain-type and low-side row chip common source-type. The proper operation in the turn-on and turn-off of each cell is also studied and validated. To fabricate these new monolithic integrated architectures, two main technological bricks have been developed, for vertical insulation and the integration of a top Ni metal via. To achieve the vertical insulation deep trenches are necessary combining dry plasma and wet KOH electrochemical etching through the thick N + substrate
Design and Characterization of an Optical 4H-SiC Bipolar Junction Transistor
No full textInternational audienceIn this paper, a first demonstration of the optical triggering about a 10 kV 4H-SiC Bipolar Junction Transistor is reported. A laser emitting UV (349 nm) has been used for the generation electron-hole pairs within the device. A current density about 20 A.cm-2 has been obtained. This low value in comparison with 100 A.cm-2 for “conventional” BJT is due to the low pulse width (5 ns). The current waveform shows the effect of the carrier lifetime in the base and collector regions. From these measurements, we have extracted the IC (VCE) characteristics for different laser power and the switch-on time which is about 1 µs
Biocompatible fluorescent carbon dots nanoparticles used for anti-counterfeiting of cultural artefacts
No full textInternational audienceDans cette étude, des nanoparticules de carbone fluorescentes et biocompatibles ont été synthétisées à l'aide d'une méthode de synthèse ascendante sous haute pression. L'influence des différents paramètres de synthèse a été étudiée afin d'explorer le mécanisme de formation de cette méthode et leur impact sur les propriétés photophysiques des nanoparticules.Les points de carbone formés par cette méthode ont ensuite été intégrés dans divers milieux pour produire des marques de sécurité anti-contrefaçon utilisées pour protéger des objets culturels découverts sur des sites archéologiques à haut risque de pillage.Pendant de nombreuses années, les biens culturels en général, et surtout les artefacts archéologiques, ont été susceptibles d'être volés pendant et après le processus de fouille afin d'être introduits sur le marché noir. À l'échelle mondiale, on estime couramment que le trafic illicite du patrimoine culturel figure parmi les plus grands trafics illicites au monde, générant plusieurs milliards de dollars.Pour résoudre ce problème, une solution technique sécurisée est nécessaire pour retracer les artefacts archéologiques volés. Des nanoparticules fluorescentes biocompatibles peuvent être utilisées pour produire des marques anti-contrefaçon originales, sûres sans formation particulière et difficiles à reproduire par les pilleurs.En 2004, Xu et al. ont découvert des nanoparticules composées de carbone qui produisaient une photoluminescence bleue. Les points de carbone sont des nanomatériaux 0D constitués d'une structure hybride avec des grappes de carbone sp2 de type graphène liées dans une coque de carbone sp3 amorphe comprenant des groupes fonctionnels organiques à sa surface. Ils présentent des propriétés idéales pour des applications anti-contrefaçon telles que la biocompatibilité, la stabilité et une fluorescence étroite dépendant également de la longueur d'onde d'excitation.Étant principalement composés de carbone, ils constituent une alternative plus sûre aux points quantiques de métaux lourds et nous permettent d'éviter toute contamination avant l'analyse. À ce jour, le noir de carbone est la base des encres noires actuellement utilisées pour le marquage et il est chimiquement identique aux points de carbone.Diverses structures de points de carbone peuvent être synthétisées par une synthèse ascendante sous haute pression à partir de précurseurs organiques. Les conditions de pression et de température ainsi que les précurseurs utilisés dans la synthèse sont choisis en fonction des propriétés d'émission et du rendement quantique des points de carbone. Des caractérisations structurales telles que la spectroscopie FTIR et Raman sont également étudiées afin d'apporter de nouvelles informations sur l'origine de la fluorescence dans leur structure.À titre de preuve de concept, des points de carbone synthétisés à partir de 1,6-dihydroxynaphtalène selon un protocole développé par Yan et al. ont été synthétisés. Après purification par chromatographie sur colonne de silice, nous avons obtenu une solution colloïdale avec une émission fluorescente à 590 nm sous excitation UV ou verte. Cette solution a montré un rendement quantique absolu de 22,6% sous excitation à 530 nm. L'intégration de ces nanoparticules à l'intérieur d'un vernis à ongles transparent commercial utilisé par les archéologues pour la protection des artefacts a été réalisée par séchage et dispersion dans de l'acétate d'éthyle. Les revêtements produits étaient méconnaissables à l'œil nu par rapport aux revêtements de protection habituels mais fluorescents sous l'excitation correcte, permettant l'identification de l'artefact culturel.References(1)Barker, A. W. Looting, the Antiquities Trade, and Competing Valuations of the Past. Annu. Rev. Anthropol. 2018, 47 (1), 455–474. https://doi.org/10.1146/annurev-anthro-102116-041320.(2)Xu, X.; Ray, R.; Gu, Y.; Ploehn, H. J.; Gearheart, L.; Raker, K.; Scrivens, W. A. Electrophoretic Analysis and Purification of Fluorescent Single-Walled Carbon Nanotube Fragments. J. Am. Chem. Soc. 2004, 126 (40), 12736–12737. https://doi.org/10.1021/ja040082h.(3)Emam, A. N.; Loutfy, S. A.; Mostafa, A. A.; Awad, H.; Mohamed, M. B. Cyto-Toxicity, Biocompatibility and Cellular Response of Carbon Dots–Plasmonic Based Nano-Hybrids for Bioimaging. RSC Adv. 2017, 7 (38), 23502–23514. https://doi.org/10.1039/C7RA01423F.(4)Yan, F.; Zhang, H.; Yu, N.; Sun, Z.; Chen, L. Conjugate Area-Controlled Synthesis of Multiple-Color Carbon Dots and Application in Sensors and Optoelectronic Devices. Sens. Actuators B Chem. 2021, 329, 129263. https://doi.org/10.1016/j.snb.2020.129263
Analysis of the effect of surface mechanical attrition treatment on the mechanical properties of 17-4 PH stainless steel obtained by material extrusion
No full textInternational audienceIn this study, the influence of the surface mechanical attrition treatment (SMAT) on a 17-4PH stainless steel made by material extrusion additive manufacturing is investigated under mechanical loading. The evolutions of the deformations at the local scale have been performed during in-situ tensile tests up to failure around 4kN. The strain maps are obtained with an original process based on the use of nanogauges displacement from the recorded of scanning electron microscope images. These maps allow to analyze the deformation mechanisms of as-fabricated and mechanically treated samples. The porosities evolutions at the surface are especially investigated for the two types of samples. The crack propagation in the as-fabricated samples is strongly influenced by porosities/defects related to the additive manufacturing process. Moreover, the SMATed samples present slip bands at the surface during the deformation. This deformation mechanism is similar to the one commonly observed in metallic materials obtained with traditional processes. Even if the application of SMAT does not show huge modifications of tensile properties with similar ultimate tensile strength around 650 MPa, it allows to improve the material surface quality by drastically reducing the surface roughness. SMAT treatment also allows a reduction of porosities in few microns from the sample surface. These improvements present a limited impact on tensile properties, but leads to its possible use for industrial applications when applied as an innovative post-treatment on metal part obtained by additive manufacturing
Time Series Clustering for Enhanced Dynamic Allocation in A/B Testing
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Investigation of Security Threat Datasets for Intra- and Inter-Vehicular Environments
No full textInternational audienceVehicular networks have become a critical component of modern transportation systems by facilitating communication between vehicles and infrastructure. Nonetheless, the security of such networks remains a significant concern, given the potential risks associated with cyberattacks. For this purpose, artificial intelligence approaches have been explored to enhance the security of vehicular networks. Using artificial intelligence algorithms to analyze large datasets can enable the early identification and mitigation of potential threats. However, developing and testing effective artificial-intelligence-based solutions for vehicular networks necessitates access to diverse datasets that accurately capture the various security challenges and attack scenarios in this context. In light of this, the present survey comprehensively examines the vehicular network environment, the associated security issues, and existing datasets. Specifically, we begin with a general overview of the vehicular network environment and its security challenges. Following this, we introduce an innovative taxonomy designed to classify datasets pertinent to vehicular network security and analyze key features of these datasets. The survey concludes with a tailored guide aimed at researchers in the vehicular network domain. This guide offers strategic advice on selecting the most appropriate datasets for specific research scenarios in the field
Blockchain Meets O-RAN: A Decentralized Zero-Trust Framework for Secure and Resilient O-RAN in 6G and Beyond
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A novel and efficient framework for in-vehicle security enforcement
No full textInternational audienceThe Internet of Vehicles (IoV) has garnered significant popularity thanks to rapid technological advancements and the widespread availability of the Internet. IoV encompasses vehicles with multiple electronic control units (ECUs) interconnected via advanced intra-vehicle networks. These networks play a crucial role in managing various vehicle functions, with the Controller Area Network (CAN) being of particular significance. However, the increased adoption of intelligent vehicles has also led to a rise in cyberattacks in the intra-vehicular network. These existing vulnerabilities pose significant security and user safety challenges. Extensive efforts have been dedicated to enhancing intra-vehicular network security. Yet, there are open concerns with limited progress made by academic and industry experts on effectively detecting CAN bus attacks. These concerns are essential to ensure intelligent vehicles’ overall security and safety. It requires collaboration between academia, industry, and the development of innovative solutions to fortify vehicular networks against evolving cyber threats. Current intra-vehicular security systems need more robustness and need to consider intelligent methodologies in their proposed works. To overcome all these limitations, This paper introduces a novel intrusion detection framework for in-vehicle networks based on integrating federated learning with transfer learning, improving the detection capabilities of individual vehicles within the network. Our framework employs a trusted authority for secure communication, a cloud server for model distribution and aggregation, and leverages the CAN bus for data collection and training. It guarantees that vehicles start with standardized baseline models and refine them through transfer learning, resulting in a collective intelligence-based final IDS engine for ongoing improvement. We used the Maximum Mean Discrepancy (MMD) to select data from the source domain similar to the target domain. The selected data is more likely to contain patterns and features useful for detecting intrusions in the target domain, leading to better generalization and detection capabilities
Solving the Two-Stage Robust Elective Patient Surgery Planning Under Uncertainties with Intensive Care Unit Beds Availability
No full textInternational audienceThis paper explores the intricate challenges of the elective surgery scheduling problem, considering uncertainties in both surgery duration and length of stay in the intensive care unit. We present a novel two-stage robust approach employing the column-and-constraint generation algorithm to address the master surgical schedule and surgery case assignment problems under these uncertainties. Our approach differs from traditional methods by incorporating a specific modeling of uncertainty using independent uncertainty sets and accounts for surgical teams and resource availability. Comparative analysis with the cutting-plane method demonstrates the effectiveness of our approach, offering valuable insights for the enhanced management of uncertainties in elective surgery planning
Optimizing quality inspection plans in knitting manufacturing: a simulation-based approach with a real case study
No full textInternational audienceThis paper introduces a simulation-based approach to enhance quality defect detection in a prominent French textile company’s manufacturing process. The production workflow is initially simulated and analyzed to identify key parameters influencing defect creation and detection. After assessing the existing control process using performance metrics, a novel Inspection Quality Plan (IQP) is formulated. To validate the effectiveness of the proposed IQP, a simulation model is developed and calibrated to mirror real-world conditions. This model, initially validated against the current solution, acts as a benchmark for evaluating predefined scenarios and determining optimal configurations. The implemented scenario, tested in the workshop under authentic conditions, results in a remarkable 42% improvement in defect detection within the knitting process. The positive outcomes are meticulously examined and discussed. This study, employing a holistic approach that integrates simulation modeling, performance evaluation, and real-world deployment, establishes an optimized strategy for enhancing defect detection in the textile industry. It underscores the effectiveness of the proposed IQP, showcasing significant improvements observed in practical settings based on a simulation model