Concept

Poudre noire

Résumé
La poudre noire, parfois dénommée poudre à canon ou poudre à fusil, est le plus ancien explosif chimique connu. De couleur noire, elle est constituée d'un mélange déflagrant de soufre, de nitrate de potassium (salpêtre) et de charbon de bois. Inventée en Chine probablement vers le , la poudre noire s'est progressivement diffusée en Europe et en Asie jusqu'au . Utilisée pour les canons et les fusils, c'était le seul explosif chimique connu jusqu'au . La poudre noire n'est plus utilisée de nos jours pour les armes modernes et pour les applications industrielles, en raison de sa faible efficacité comparée à celle des explosifs plus récents. Son usage est aujourd'hui limité à des armes anciennes de chasse et de tir sportif (armes authentiques ou répliques), aux pétards et aux feux d'artifice. Historique vignette|upright=1.2|De la poudre noire.|alt=Histoire de la poudre à canon Certaines sources situent l'invention de la poudre noire durant la dynastie Han (206 av. J.-C. à 2
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Publications associées (77)

Additive Fabrication of Silicon Pillars on Monocrystalline Silicon by Direct Laser Melting

Marie Camille Laëtitia Le Dantec

Additive Manufacturing (AM) is an emerging part production technology that offers many ad-vantages such as high degree of customization, material savings and design of 3D highly complex structures. However, AM is a complex multiphysics process. Therefore, only a limited number of materials can already be commercially used to produce parts and a handful of others are being studied or developed for such process. Consequently, limited knowledge on this process is available, especially concerning materials that present thermomechanical challenges such as brittle materials. The present research focuses on additive fabrication of silicon pillars on a monocrystalline silicon wafer by Direct Laser Melting (DLM) with a pulsed 1064 nm laser beam. The simple geometry of pillars allowed for the first determining steps into process understanding. Several results were achieved through this PhD work. First, crack-free silicon pillars were successfully built onto monocrystalline silicon wafers. With the help of in-situ process monitoring and sample characterization, wafer substrate temperature and laser repetition rate were found to be the main influential parameters to obtain crack-free samples, as minimum substrate temperature of 730°C and a minimum repetition rate of 100 Hz were necessary to reach this goal (for a feed rate of 15 g/min and a pulse duration of 1 ms). The influence of secondary process parameters such as feed rate and energy per pulse were also discussed. A simple Finite Element Modeling (FEM) model validated by the experiments was used to explain crack propagation in the samples. Then, process monitoring of the DLM process was realized. High-speed camera image analysis re-vealed that vertical stage speed and powder feed rate should match to obtain a constant pillar building rate. As all pillars presented necking at their base, estimations of the thermal characteristics of the pillar during growth were carried out by FEM simulations. They were additionally used to explain the pillar final shape. Finally, the microstructure of the pillars built was characterized by the Electron Back-Scattering Dif-fraction (EBSD) technique. In the conditions presented in this work, the microstructure of the pillar was found to be in the columnar growth mode. The feed rate was identified as the most influential parameter on the microstructure, followed by the stage speed, the impurity content of the powder and the crystallographic orientation of the substrate. Epitaxial growth was achieved on more than 1 mm with a feed rate of 1.0 g/min, a stage speed of 0.1 mm/s, a powder with purity of 4N and a oriented wafer substrate. This work could be further continued by making improvements to the DLM setup, studying the influence of additional process parameters on the thermomechanical behavior and the microstructure control of the pillars, and/or using these results to realize more complicated shapes, either with this setup or by using a powder bed technique.
EPFL2018

Prédiction et compréhension de la densification des poudres commerciales d'alumine et de fer grâce à une approche par réseau de neurones artificiels

The influence of the properties of commercial powders on the densification during their packing, compaction and sintering process is still not understood in detail. With regard to the sintering process, neither the well-known sintering equation for the first sintering step nor the relation between the density and grain size at the final sintering step can describe the influence of powder characteristics on its densification behaviour. For improving the sintered density of a ceramic powder, it is known to be crucial to start with a highly dense and homogeneous green body. Therefore, the powder has to fulfil different requirements such as being agglomerate free, reasonably spherical and having a narrow size distribution (but not mono-dispersed). The aim of this work is to develop a better understanding of the relation between the powder properties and the densification behaviour during the packing, compaction and sintering process, of commercial, micron sized, metallic and ceramic powders. Another aim of this work is to evaluate if prediction of the packed, green and sintered densities based only on the known powder characteristics is possible via a neural network approach. The presented results show that a well learnt neural network is a useful tool for the prediction of green and sintered densities of granulated alumina powder produced either by milling (Bayer process) or by chemical processes. Moreover, the simulated influences of characteristics, on the green and sintered densifications, fit well literature models behaviours and intrinsic properties of such powders. Concerning the green densification, Bayer powders are denser for coarser particles and/or a broader size distribution. Relating to the chemically produced powders, those tendencies are inversed, due a stronger agglomeration with a broader size distribution and coarser particles. Regarding the sintered density, the neuronal approach highlights a better sinterability for finer powders. Limits of the artificial neural network tool are emphasized with its application to metallic powders: the learning stage seems to be primeval and simulated results are to be analysed and interpreted with care and inside the validity domain of each specific artificial neural network.
EPFL2004

Etude par microscopie électronique de particules nanostructurées d'oxalate de cobalt précipitées en milieu aqueux

The understanding of material self-assembling and self-organization mechanisms, at mesoscale, is crucial for nanotechnologies development. Such structures, hierarchically organized in superlattices or colloïdal crystals, are observed in inorganic or organo-metallic precipitates. The classical characterization, using electron microscopy and X-ray diffraction, of a synthesized powder is inadequate to describe the hierarchically organized polycrystalline structure of the final particles. Here, we have highlighted the successive steps that lead to the spontaneous formation of a cobalt oxalate dihydrate (COD) colloïdal crystals that precipitate in aqueous media. The characterization of the final particles, made by X-ray and electronic diffraction, has allowed us to determine the controversial crystalline phase of the precipitated COD. The β and γ COD phases has been discriminated by comparing experimental results with simulations of X-ray diffractogram and electron diffraction patterns for these both structures. The precipitated COD corresponds to the γ phase indicating that it comes from solid dehydration of cobalt oxalate tetrahydrate. The final powder characterization, performed by X-ray diffraction (XRD), atomic force microscopy (AFM), low voltage high resolution scanning electron microscopy (LVHRSEM) and transmission electron microscopy (TEM), gives some diverging results about monocrystalline or polycrystalline nature of the precipitates. XRD and AFM analysis show a polycrystalline structure of particles whereas LVHRSEM, TEM and electron diffraction observations indicate a monocrystalline structure. This apparent contradiction has led us to elaborate a new characterization method allowing to follow the growth and the structural evolution of the precipitate as a function of time. The cryo- preparation techniques are well adapted as they allow freezing and direct observation of solid state suspension by electron microscopy. The freeze/drying method has been modified and used for both SEM and TEM, and has allowed us to study the morphological and structural evolution of the COD precipitate from nanoscale to mesoscale. In addition, TEM analysis of samples prepared by classical techniques has been performed to complement cryo-electron microscopy observations. The combination of these two methods show that COD precipitation is a complex multi-step process leading to the formation of a core/shell heterostructure. The anisotropic core is porous and partially crystalline. It is formed by agglomeration of isolated primary particles and agregated ones (15-20 nm sized secondary particles). The crystalline shell corresponds to the final particles faces and is made up by the layer by layer self-assembling and alignment of 5-7 nm sized crystalline primary particles. These nanoparticles are aligned and perfectly ordered in strings of nanograins in the layer structure. The self-assembling occurs in the last step of growth where we have a lower ionic strength and supersaturation inducing slower kinetics of growth and aggregation. Moreover, the crystalline order in the primary and secondary particles increase with the time of reaction consistent with a continuous process of primary particle nucleation and growth. Our results show that self-assembling occurs layer by layer with terraces, kinks and steps that are present on the faces. This reminds the layer by layer crystalline growth models but in this case, the buiding blocks are colloïdal instead of atomic or molecular. Based on these different results, we propose an original model describing the COD precipitate growth. In addition, we have studied the poly(methacrylic acid-sodium salt) effect on the COD precipitation. This additive (PMMA) appeared to be a very good growth inhibitor. The PMMA effect on the final particles morphology is dramatic. Its concentration variation in solution slows down the nanoparticles aggregation rates along a [101] preferential direction. The crystal habit can then be controlled and we have synthesized platelets, cubes and rods with tailored length. The use of cryogenic electron microscopy has been shown to be a powerful tool for the understanding of time dependent aspects of particle growth. The use of such techniques for the study of other systems, where the final precipitate appearance may hide particle substructures, will help to elucidate growth mechanisms and allow finer control of nanostructured materials for many applications. The complex self-assembling and self-organization processes could then be highlighted and studied on a nanometer to micrometer scale.
EPFL2004
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Concepts associés (69)
Explosif
Un explosif est défini par un mélange de corps qui, lors de leur transformation, sont susceptibles de dégager en un temps très court un grand volume de gaz porté à haute température, ce qui constitue
Nitrate de potassium
Le nitrate de potassium est un corps chimique, ionique, anhydre, composé d'anions nitrate et de cations potassium, de formule brute . Ce composé minéral salin de densité entre 2,1 et 2,2 suivant sa p
Moyen Âge
vignette|alt=Miniature de laboureurs devant un château.|Le château fort, ici le Louvre, est l'une des constructions caractéristiques de la fin du Moyen Âge, remplaçant la motte castrale (les très rich
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Cours associés (20)
MSE-214: Mise en oeuvre des matériaux I
Introduction aux relations mise en œuvre-structures-propriétés des polymères, céramiques et métaux, fournissant les bases nécessaires à la sélection de matériaux et procédés pour la fabrication de composants en microtechnique.
MSE-422: Advanced metallurgy
This course covers the metallurgy, processing and properties of modern high-performance metals and alloys (e.g. advanced steels, Ni-base, Ti-base, High Entropy Alloys etc.). In addition, the principles of computational alloy design as well as approaches for a sustainable metallurgy will be addressed
ME-413: Introduction to additive manufacturing
The state of the art in the domain of additive production processes (the part is built by material addition without use of a shape tool) will be presented. The main application/benefits/shortcomings of the common additive processes as well as technological and economical issues will be discussed.
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