This study explores the influence of SiC reinforcement on the microstructure, mechanical properties and ballistic performance of Al2O3-SiC composites fabricated by Spark Plasma Sintering. Composites containing 1 to 30 vol% SiC were processed using optimized SPS cycles to ensure high densification and controlled microstructural development. The addition of SiC led to significant improvements in hardness, fracture toughness and Young's modulus with the best compromise observed at 25 vol% SiC, sintered at 1600 degrees C. At this composition, a 30 % reduction in residual depth of penetration versus 7.62 mm x 51 FMJ/PB/HC AP P80 (0.308 Win) threat was measured compared to pure alumina, confirming the effectiveness of SiC reinforcement in enhancing ballistic resistance. Although higher SiC contents (>= 25 vol%) resulted in the formation of mullite and a slight decrease in fracture toughness, the 25 vol% SiC composite offers an optimal balance between mechanical performance and cost-efficiency. These results position Al2O3-SiC composites as promising materials for lightweight and affordable ballistic protection systems.

Controlling the microstructure of a diffusion welded interface is a critical point to ensure optimum mechanical properties and the homogeneity of the joint. Beyond the intimate contact formation between bonded parts studied in the literature, this article focuses on the grain boundary crossing of the interface during this process and its measurement. Following this perspective, a Level-Set method has been used for full-field microstructure simulations in 2D with various interface parameters. Two crossing measurement models have been formulated, tested and discussed over the simulations.

Titanium/nanodiamond (ND) mixtures were sintered using spark plasma sintering (SPS). Densification was studied for Ti + x wt% ND mixtures (where x = 2, 5, 10 and 15) to determine the optimized cycles. Ti/ND mixtures were then sintered under these optimized conditions achieving relative densities higher than 96 %. The SPS temperatures for the Ti + 2 wt% ND, Ti + 5 wt% ND, Ti + 10 wt% ND and Ti + 15 wt% ND mixtures were 1000 degrees C, 1050 degrees C, 1150 degrees C and 1150 degrees C, respectively. Numerical simulation by finite elements were used to check the thermal homogeneity in the sample and to determine the maximal temperature in the sample to ensure avoiding graphitization. The effects of ND on the Ti/ND mixtures were investigated. Microstructural characterizations reveal the presence of three different phases including a Ti phase, a non-stoichiometric TiCx solid phase and NDs located inside the TiCx grains. Indeed, NDs react with Ti to form the TiCx solid phase. However, a fast sintering with temperature below graphitization of diamond allows to keep nanodiamond structure into the Ti/ND mixtures. Hardness and electrical conductivity of the Ti/ND mixtures were measured. The results show that the higher the ND content, the more the hardness of the composite increases and the more the electrical conductivity decreases. Hardness increased from 340 HV to 1346 HV for Ti and the Ti + 15 wt% ND mixture, respectively. Electrical conductivity is reduced by a factor of three for the Ti + 15 wt% ND mixture relative to Ti which can be explained by the microstructure exhibiting fewer Ti grains in favor of the TiCx solid phase when ND content was increased in the composite.

Over the last two decades, Spark Plasma Sintering (SPS) has become a major technique for manufacturing advanced materials. Nevertheless, the control of SPS process is complex and requires the use of complex multiphysics and multiscale numerical simulations. Nowadays, the emerging data-driven approaches such as Deep Learning (DL) have proven their effectiveness in many fields. Thus, we develop a DL architecture based on Convolutional Neural Network (CNN) and Generative Adversial Neural Network (GAN). The network is trained on high-throughput macroscale FEM simulation maps and associated process parameter tabular data. The power of this approach lies in the ability of the network training process to be incrementally augmented by multivariate data such as real microstructure images and real sintering signals: toward a SPS digital twin.

Spark Plasma Sintering technology is widely used to develop new materials with a fine and controlled microstructure. The key stage in its development (i.e. industrialisation) is the mastering of scale-up. From a SPS perspective, this requires suitable graphite tooling and a sintering cycle that can be applied to large parts. Samples with 60 mm diameter and 10 mm height were sintered from an aluminium alloy powder and characterised to determine the sintering conditions. Then, samples with 170 mm diameter and 15 mm height were sintered. Their metallurgical characterisations, including the numerical simulations of the sintering process, were performed to determine the effects of the scale-up and, at the end, to optimize the sintering conditions to obtain dense and homogeneous samples.

The aim of the paper is to propose the development of a MEX feedstock composed of a bio-sourced binder and a tool steel powder to be printed with a pellet printer.A bio-based feedstock with the highest powder load is made using different powder sizes. It is shaped into test samples with Fused Granulate Fabrication process, from where the polymer binder is then eliminated by thermal degradation. The resulting powder skeleton is densified by conventional sintering, to achieve a maximal density. The densified samples are examined by X-ray tomography for the evaluation of their internal porosity. The developed method permits to get, from optimised stages, final components with a high density of 97%, equivalent to that obtained using conventional PIM processes, with a dimensional shrinkage of 13%. The physicochemical composition of the densified components obtained is in line with the literature.

Titanium (Ti)-nanodiamond (ND) composite discs were sintered using spark plasma sintering (SPS). Several parameters were studied such as the mixing technique, the heating rate and the applied pressure. The effect of these parameters on the densification of Ti + ND composites was shown. The mixing techniques and the applied pressure have a great influence on the densification of Ti + ND composites. The heating rate also has an influence, but less so for the mixing technique and applied pressure parameters. This study determines the optimized sintering parameters for the Ti + ND composites. Density, hardness and electrical conductivity were measured. The higher the ND content in the Ti + ND powder, the more the TiC solid phase forms in the composite which increases the hardness and reduces the electrical conductivity. At a given temperature, the density decreases with increasing ND content.

Energy-efficient materials are key to combating the high energy costs and climate change. The manufacturing temperatures of industrially important Zr-based bulk metallic glasses (BMGs) relative to steels are low, and exist between the liquidus temperature Tl (∼850 °C) and glass transition temperature Tg (∼400 °C). However, these materials show limited plastic deformability (ductility) at room temperature (strains typically less than 3 %); moreover they soften but exhibit limited ductility at high processing temperatures. Their low ductility should be improved because it impedes fatigue resistance and machinability, such as via cold (plastic) forming. In this study, chemical composition changes, which reduced Tg, resulted in remarkably ductile BMGs with extreme deformations of over 70 % under compression, thereby enabling their energy-efficient processing at low temperatures. In contrast to previously reported conclusions on the high GFA and deformation-induced nanocrystallization being the precursors to ductility, formation of a low amount of meso-crystallites within the glassy material during cooling efficiently hindered the propagation of shear bands and microcracks under loading, thus increasing significantly ductility. This characteristic, in addition to optimal chemical composition, played an important role in improving the ability of BMGs to undergo solid-state processing at low temperatures and increased deformation rates.

This study examines the possibility of simulating the rearrangement stage of 316L steel powder using a modified cam-clay model. The oedometric compression tests were carried out at up to 900°C using an SPS device. Unlike clay soils, the virgin consolidation line is non-linear, with a slope dependent on volumetric deformation. The dependency of the slope is characterized at different temperatures and a consolidation law under isostatic pressure is proposed. The initial pressure at which the virgin powder starts to densify plastically was successfully adjusted. This adjustment was made using density measurements obtained after HIP interrupted tests performed on the same powder encapsulated in a spherical container. The complete consolidation law can be implemented in FEM simulations to take into account the rearrangement stage in the densification of industrial parts. The second part aims at determining the optimal simulation parameters for oedometric cold pressing of the powder powder using the discrete element method. The simulation uses the Hertz-Mindlin contact model and the Spherical Johnson-Kendall-Roberts model to account for powder particle adhesion. Simulation parameters have been optimised through iterative refinement. The particle size distribution is measured experimentally by sieving. For this size distribution, the values determined for the simulation parameters were 5 nanoseconds for the minimum time step, 0.002 for the friction coefficient and 0.36 for the adhesion coefficient. These parameters ensure accurate representation of the powder behaviour in monotonic compression but the simulation lacks of efficiency when unloading-reloading stages are applied.

Soft magnetic Fe65Ni28Mn7 (at. %) alloy was successfully synthesized by mechanical alloying and spark plasma sintering (SPS) and, in parallel, the same composition was prepared by arc melting (AM) for comparison. Several SPS conditions were tested. X-ray diffraction and scanning electron microscopy were used to investigate the structure, phase composition, and morphology of the samples. It was found that mechanical alloying produced BCC and FCC supersaturated solid solution after 130 h of milling, with a fine microstructure (i.e., crystallite size of 10 nm). Spark plasma sintering performed at 750 °C and 1000 °C under two pressures of 50 MPa and 75 MPa revealed stable FCC phases. A single FCC phase was observed after the arc melting synthesis. The magnetic properties of milled powders and solids obtained by AM and SPS were investigated. The specimen consolidated by SPS at 1000 °C under the pressure of 50 MPa exhibits soft magnetic behavior (coercivity 0.07 Oe), whereas the mechanically alloyed sample revealed hard magnetic behavior. The specimen consolidated at 750 °C under a pressure of 75 MPa showed a higher compressive strength of 1700 MPa and a Vickers hardness of 425 ± 18 HV. As a result, sintering at 750 °C/75 MPa can be utilized to enhance the mechanical properties, while those sintered at 1000 °C/50 MPa increase magnetic softness.

As a first step to devise a hybrid process for the production of TiC wear coatings on 316L, consisting of magnetron sputtering followed by titanium carburization, interfacial reactivity between stainless steel and titanium has to be finely understood. Systematic comparisons were carried out on diffusion couples of increasing chemical and geometrical complexity (Fe/Ti, 316L/Ti, and 316L/sputtered Ti), highlighting the formation mechanisms of interfacial structures. Transmission and scanning electron microscopy composition profiles revealed that long-range microstructures in titanium are the result of iron diffusion and oxygen impurities interactions. FeTi and Fe2Ti intermetallics formation is first kinetically driven, then favors thermodynamic stability, leading to compositional changes during thermal cycles. Their growth is shown to be non-diffusion controlled. These compounds act as diffusion barriers for chromium, and traps for carbon, indirectly generating a complex layered structure at the interface. Differences between bulk and sputtered titanium are exclusively linked to the latter smaller scale, including destabilized diffusion fronts, and superficial TiO formation by oxygen rejection after iron diffusion.

This study focuses on the atomization of pure zinc rods using a LASER beam as a heating source. A LASER solution makes it possible to reach higher rotational speed, in order to reduce particles size, but also to observe the process in-situ by high-speed imaging. The study also focuses on particle size, shape, and distribution, depending on the process parameters. The higher the rotational speed, the narrower the PSD is and shifts to finer powder size distributions. Prediction models for particle size and atomization regime were compared to experimental results and discussed.While predictions for particle size are in agreement with experiments, prediction for atomization regime, however, shows some mismatches between predicted regime and observations.Finally, atomizations were conducted in ambient atmosphere where the process is strongly affected.

This paper describes the SWCNTs and nano WC when were introduced into TiC(1-x)– ZrCx with (x=2) nano-composite into ceramics to improve the fracture toughness (KIC) and hardeness (Hv). TiC–ZrC, TiC–ZrC–single walled carbon nanotubes (SWCNTs) (3 mass %) and TiC–ZrC–SWCNTs (3 mass %) - tungestun nanocarbide (NWC) (20 mass %) nano-composites were prepared by vacuum sintering FAST-SPS-FCT technology at the temperatures in the range of 1700–1800 °C for 400 s under pressure of 50 Mpa. Microtructural properties were investigated by X-ray diffraction and energy-dispersive spectrometry in addition scanning electron miroscopy. The investigations shows that the phase separation of the as-sintered (Ti, Zr) C into two phases: TiC-rich (Ti, Zr) C (dark) and ZrC-rich (Zr, Ti) C (bright) indicating that the as-sintered (Ti, Zr) C was thoroughly decomposed into two solid phases after sintering. The effect of nanostructures of SWCNTs and NWC is already illustrated. X-ray diffraction and energy-dispersive spectrometry results indicate that bright grains are (Zr, Ti) C solid solution. The relative density increases with the addition of SWCNTs and nano-WC content. Fully dense TiC-ZrC, TiC–ZrC-SWCNTs and TiC–ZrC-CNTs-NWC nanocomposites with a relative density of more than 98 % were obtained. The Vickers hardness (HV) and fracture toughness (KIC), of TiC-based nano-composites with SWCNTs and NWC will be performed in the near future. In addition, ballistic performance (the properties of shock resistance) ; thermo-mechanical modelling in-situ FAST-SPS-FCT cycle, also will be evaluated using the Rosenberg model and compared with the experimental results in order to better understand the shock behavior of nano-composites that to be applied for body armor

The work engaged for many years between the ICB laboratory and the Nexter Munitions company has clearly shown the interest of combining a high-energy mechanical milling of the metallic powders followed by a SPS sintering. Indeed, commercial powders are mechanically activated (i.e. successive actions of fracture | cold welding of the powder particles) by the use of high-energy planetary ball mill, which leads (i) to increase the agglomerate sizes, (ii) to reduce the crystallite sizes and (iii) to induce structural defects. Thus, these so-called mechanically activated agglomerates allow a densification at a lower temperature while avoiding the formation of undesirable phases and limiting the grain growth. The second interest of mechanical milling is to stabilize sometimes out-of-equilibrium phases. Several examples (nickel, maraging steels, ...) will exhibit the existence of a relationship between the powder microstructure and sintered microstructure and consequently on the tensile properties.

Due to lacks of final shape prediction after HIP by the Abouaf-Chenot model used in previous collaborative projects, we implement a new model initially developed for stage III creep (with reversed stress). The so-called LPS model (viscoplastic) meets the Gurson model (plastic) when the Norton exponent tends to infinity and provides the exact solution for a hollow sphere. The complex mathematical definition of the gauge surface was first numerically approached to simplify the numerical implementation of the model. The creep law of the bulk material is determined by Hot Uniaxial Pressing tests using a SPS device. The model is then fitted on the densification curve obtained by a simple diameter measurement of a spherical container after interrupted HIP tests. The model is finally implemented in a finite element simulation and confronted to the 3D reconstruction of the external shape of a large 316L steel part elaborated by HIP.

This paper discusses an innovative additive manufacturing process, using a combination of polymer 3D printing by fused filament fabrication and powder metallurgy to create complex shaped, high density parts from powders without tooling. This process offers interesting prospects for reducing material waste and costs for prototyping or small series, as it does not require specific equipment. In this current work, the selected powder is a steel-tool alloy. The study covers the whole process, from the development of the feedstock material to its shaping including debinding and sintering steps, in order to manage all the steps to achieve a final component without defects and excellent mechanical and physical properties.

Diamond grinding wheels (DGWs) have a central role in cutting-edge industries such as aeronautics or defense and spatial applications. Characterizations of DGWs are essential to optimize the design and machining performance of such cutting tools. Thus, the critical issue of DGW characterization lies in the detection of diamond grits. However, the traditional diamond detection methods rely on manual operations on DGW images. These methods are time-consuming, error-prone and inaccurate. In addition, the manual detection of diamond grits remains challenging even for a subject expert. To overcome these shortcomings, we introduce a deep learning approach for automatic diamond grit segmentation. Due to our small dataset of 153 images, the proposed approach leverages transfer learning techniques with pre-trained ResNet34 as an encoder of U-Net CNN architecture. Moreover, with more than 8600 hyperparameter combinations in our model, manually finding the best configuration is impossible. That is why we use a Bayesian optimization algorithm using Hyperband early stopping mechanisms to automatically explore the search space and find the best hyperparameter values. Moreover, considering our small dataset, we obtain overall satisfactory performance with over 53% IoU and 69% F1-score. Finally, this work provides a first step toward diamond grinding wheel characterization by using a data-driven approach for automatic semantic segmentation of diamond grits.

316L grade stainless steel powders were produced by centrifugal atomization during the melting of a rotating rod heated by a high-power LASER beam. The feasibility has been demonstrated by atomizing a range of stainless steel rods. The atomization process has been observed via high-speed imaging and fragmentation regimes have been identified according to a literature review on the rotating electrode process (REP). Results were compared with literature data and an existing prediction model for such a process. High-speed observation can monitor the present process and it is shown that a solidified layer of metal is formed at the edge of the rod during the process inducing metal flake ejection due to the centrifugal stresses. Effects of incident LASER beam power density, ejection speed and oxygen content of the surrounding atmosphere on the particle size distribution and the sample surface have been studied and compared with literature data on classical REP atomizers. The study focuses on the production of irregular particles during the atomization process and highlights the influence of the oxygen content in the surrounding atmosphere on the fragmentation regime and the resulting particle size distribution.(c) 2022 Published by Elsevier B.V. on behalf of The Society of Powder Technology Japan All rights reserved.