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Grain boundary segregation spectrum in basal-textured Mg alloys: From solute decoration to structural transition
No full textInternational audienceMg alloys are promising lightweight structural materials due to their low density and excellent mechanical properties. However, their limited formability and ductility necessitate improvements in these properties, specifically through texture modification via grain boundary segregation. While significant efforts have been made, the segregation behavior in Mg polycrystals, particularly with basal texture, remains largely unexplored. In this study, we performed atomistic simulations to investigate grain boundary segregation in dilute and concentrated solid solution Mg-Al alloys. We computed the segregation energy spectrum of basal-textured Mg polycrystals, highlighting the contribution from specific grain boundary sites, such as junctions, and identified a newly discovered bimodal distribution which is distinct compared to the conventional skewnormal distribution found in randomly-oriented polycrystals. Using a hybrid molecular dynamics/Monte Carlo approach, we simulated segregation behavior at finite temperatures, identifying grain boundary structural transitions, particularly the varied fraction and morphology of topologically close-packed grain boundary phases when changing thermodynamic variables. The outcomes of this study offer crucial insights into basaltextured grain boundary segregation and phase formation, which can be extended to other relevant Mg alloys containing topologically close-packed intermetallics
High‐Entropy Alloy Design Toward Cobalt Substitution for High Hardness and Low Wear Rate Using X–Cr–Fe–Mn–Ni System
No full textInternational audienceIn the aerospace, nuclear, and machining industries, alloys require high hardness and excellent wear rate. Most high‐performance alloys rely on cobalt for high‐temperature properties, despite its political, ethical, and health concerns. High‐entropy alloys (HEAs), enabled by structural hardening, lattice distortion, and sluggish diffusion, offer pathways to eliminate this critical element. This study examines cobalt substitution in HEAs to optimize hardness and wear rate. New alloys based on the Cantor system (CoCrFeMnNi) are produced by individually replacing cobalt with copper, aluminum, vanadium, or molybdenum. Four equiatomic HEAs (AlCrFeMnNi, CrFeMnNiV, CrCuFeMnNi, and CrFeMnMoNi) are compared with two literature alloys (Al 0.2 Co 1.5 CrFeNi 1.5 Ti and CoCrFeMnNi) and with the pure substituent elements, all evaluated in the same metallurgical state. All synthesized HEAs except CoCrFeMnNi are multiphased and do not mimic the structure of their corresponding pure element; CrCuFeMnNi also departs from valence electron concentration predictions. Pure cobalt shows the lowest wear rate, while the Cantor alloy exhibits a higher one. Aluminum, vanadium, and molybdenum strengthen HEAs despite limited performance in their pure state. Ultimately, pure cobalt, CrFeMnMoNi, and AlCrFeMnNi display similar and superior wear rate compared with the optimized reference alloy Al 0.2 Co 1.5 CrFeNi 1.5 Ti
Gas analysis system for studying sand mold’s atmosphere during steel casting
No full textInternational audienceThe composition of the mold atmosphere plays a critical role in mold-metal interactions during steel casting and is a root cause of certain casting defects. However, studying this atmosphere is challenging due to technical difficulties in extracting gases from sand molds and the harsh condi- tions of the metal casting process. Most of the studies realized in the field uses gas chromatography and mass spectrometry technics to investigate atmosphere in a foundry mold. Single-gas sensors, being readily available nowadays, present a cost-effective alternative to aforementioned technics. In this paper, we present an innovative gas analysis system designed for real-time, in-situ moni- toring of the mold atmosphere. This system has been developed in collaboration between ENSAM Cluny (LaBoMaP) and the industrial partner Safe Metal
Verification of flow curve determination from plane strain compression tests
No full textInternational audienceThe work-hardening curve of sheet metals under large plastic strains can be extracted from the Plane Strain Compression Test (PSCT) using an analytical method that relies on several simplifying assumptions and correction factors (friction, boundary conditions, lateral spreading, tool geometry, yield criterion, anisotropy). This study rigorously assesses each of these correction factors using finite element simulations. Synthetic materials with predefined hardening laws are used to enable direct comparison between the reference curves and those extracted from simulated PSCTs. Dedicated simulation setups were developed to isolate the effect of each factor through progressive 2D and 3D configurations. The results show that the analytical method is generally valid when appropriate corrections are applied, with improved accuracy observed when using rounded tools with small radii under low-friction conditions. Recommendations for the selection of correction factors are provided to enhance the reliability of flow curves obtained through this method
Grain size impact on sheet metal behavior via CPFEM
No full textInternational audienceA novel multiscale computational framework based on Crystal Plasticity Finite Element (CPFE) modeling is proposed to investigate the effect of grain size on the mechanical behavior and ductility limits of thin metal sheets, featuring both uniform and gradient grain structures. This approach relies on designing unitcell models that reflect the microstructural characteristics of thin metal sheets. The overall response of the unit cell is obtained from that of its single crystal constituents using the periodic homogenization scheme. At the single crystal level, the mechanical behavior is modeled within a finite strain, rate-independent plasticity framework, where the plastic flow is governed by the classical Schmid law. The effect of individual grain size is incorporated at the single crystal scale by adjusting the critical resolved shear stress (CRSS) evolution, using a combination of the microscopic Hall–Petch relationship and a dislocation density-based hardening model. To efficiently solve the single crystal constitutive equations, a return-mapping algorithm coupled with the Fischer–Burmeister complementarity function is developed and implemented into ABAQUS/Standard through a user-defined material subroutine (UMAT). At the macroscopic level, the ductility limits are predicted by the Rice bifurcation theory. The performance of the proposed strategy is validated through a series of polycrystalline aggregate simulations. The numerical results demonstrate a significant influence of grain size on both the macroscopic strength and ductility limits of polycrystalline aggregates. Additionally, the introduction of gradient grain structures is shown to substantially enhance both strength and ductility. These findings provide valuable insights for optimizing material performance in engineering applications
A review on the multiscale strategies of dissipative materials under fully coupled thermomechanical conditions
No full textInternational audienceIn this short review, the multiscale modeling of dissipative composites undergoing fully coupled thermomechanical processes is outlined through the models presented in a collection of recent works. The aim is to demonstrate the challenges and limitations of: (1) the multiscale approaches (full-field or meanfield techniques), (2) the computational approaches dealing with complex material systems, (3) the alternative methodologies dedicated to the analysis of composite structures, such as those founded on the data-driven modeling and the model order reduction techniques
A robust determination of the effective thermal conductivity of a multilayer Si3N4/SiO2 stack using multiple heater geometries in the 3-omega method
No full textInternational audienceMultilayer dielectric thin films are fundamental components in modern microelectronic and photonic devices where thermal management is critical. This work presents a robust methodological framework for accurately determining the cross-plane effective thermal conductivity (κeff,⊥) of such complex systems using the 3-omega method. We use a five-layer Si3N4/SiO2 stack fabricated by plasma-enhanced chemical vapor deposition as a case study. The analysis combines experimental data from multiple heater geometries with a 3D finite element method based inverse analysis. We first demonstrate, through a frequency-dependent sensitivity analysis, that a direct multi-parameter fit for intrinsic layer properties is an ill-posed problem. This analysis provides a clear, quantitative justification for adopting a simpler and more robust effective medium model (EMA). The validity and application boundaries of the EMA are then rigorously established through a numerical study on a series of “virtual samples.” Finally, applying this validated framework to our experimental data, the thermal conductivity of a fused silica substrate was determined to be 1.287 ± 0.030 W/(m K), and the effective thermal conductivity of the 1288 nm thick stack was reliably determined to be 0.621 ± 0.008 W/(m K). This work provides not only a key thermophysical property for Si3N4/SiO2 multilayers but also a comprehensive and validated workflow for reliably characterizing complex thin film systems where standard analytical solutions fail
Mechanical behavior study at the macroscopic and microscopic scales of carburized austenitic stainless steels using combined in-situ tensile test and high-energy X-ray diffraction
No full textInternational audienceThe macroscopic and microscopic mechanical behaviors of two austenitic stainless steels, 316L and Ti-stabilized alloy (Ti-ASS) proposed as absorbent cladding candidates in Sodium Fast Reactor, were studied using high-energy X-ray diffraction (HEXRD) combined with in-situ tensile testing after exposure to carburizing sodium at 500 °C for 1000 h. Carburization of 316L resulted on the formation of iron-chromium rich M23C6 carbides with adjacent metallic depleted austenite and carbon supersaturated austenite. At the macroscopic scale, this microstructure induced an increase of Yield Strength (YS), a decrease of Ultimate Tensile Strength (UTS) and a loss of ductility. For Ti-ASS, only expanded austenite was formed after carburization. For this sample, no YS increase, no ductility loss but an increase of the UTS was observed at macroscopic scale. The HEXRD with in-situ tensile tests revealed a gradient of mechanical properties across the thickness of the carburized samples. For 316L, brittle behavior in the region where carbides were formed and ductile behavior where no carbides precipitated were detected. For Ti-ASS, it was clearly evidenced that the YS and the UTS of the carburized zones increased with the increase of carbon concentration. The results clearly demonstrate the benefit of characterizing the mechanical behavior at microscopic scale to emphasize the mechanical properties as a function of microstructure and carbon content and monitor the damage as function of the microstructure within the sample
MiSuRe is all you need to explain your image segmentation
No full textThe last decade of computer vision has been dominated by Deep Learning architectures, thanks to their unparalleled success. Their performance, however, often comes at the cost of explainability owing to their highly non-linear nature. Consequently, a parallel field of eXplainable Artificial Intelligence (XAI) has developed with the aim of generating insights regarding the decision making process of deep learning models. An important problem in XAI is that of the generation of saliency maps. These are regions in an input image which contributed most towards the model's final decision. Most work in this regard, however, has been focused on image classification, and image segmentation - despite being a ubiquitous task - has not received the same attention. In the present work, we propose MiSuRe (Minimally Sufficient Region) as an algorithm to generate saliency maps for image segmentation. The goal of the saliency maps generated by MiSuRe is to get rid of irrelevant regions, and only highlight those regions in the input image which are crucial to the image segmentation decision. We perform our analysis on 3 datasets: Triangle (artificially constructed), COCO-2017 (natural images), and the Synapse multi-organ (medical images). Additionally, we identify a potential usecase of these post-hoc saliency maps in order to perform post-hoc reliability of the segmentation model