103 resultados para Powder mixtures
Resumo:
Some 1R,4R-2-(4-phenylbenzylidene)-p-menthane-3-one derivatives containing the ether or ester linking group between benzene rings of the arylidene fragment have been studied as chiral dopants in ferroelectric liquid crystal systems based on the eutectic mixture (1:1) of two phenylbenzoate derivatives CmH2m+1OC6H4COOC6 H4OCnH2n+1 (n = 6; m = 8, 10). The ferroelectric properties of these compositions (spontaneous polarization, rotation viscosity, smectic tilt angle as well as quantitative characteristics of their concentration dependences) were compared with those for systems including chiral dopants containing no linking group. Ferroelectric parameters of the induced ferroelectric compositions studied have been shown to depend essentially on the presence of the linking group between benzene rings and its nature as well as on the number of the benzene rings in the rigid molecular core of the chiral dopants used. For all ferroelectric liquid crystal systems studied, the influence of the chiral dopants on the thermal stability of N*, SmA and SmC* mesophases has been quantified. The influence of the linking group nature in the dopant molecules on the characteristics of the systems studied is discussed taking into account results of the conformational analysis carried out by the semi-empirical AM1 and PM3 methods.
Resumo:
The mixtures of factor analyzers (MFA) model allows data to be modeled as a mixture of Gaussians with a reduced parametrization. We present the formulation of a nonparametric form of the MFA model, the Dirichlet process MFA (DPMFA). The proposed model can be used for density estimation or clustering of high dimensiona data. We utilize the DPMFA for clustering the action potentials of different neurons from extracellular recordings, a problem known as spike sorting. DPMFA model is compared to Dirichlet process mixtures of Gaussians model (DPGMM) which has a higher computational complexity. We show that DPMFA has similar modeling performance in lower dimensions when compared to DPGMM, and is able to work in higher dimensions. ©2009 IEEE.
Resumo:
We present a study on a series of dye guest-host mixtures using fluorescent perylene-based molecules as the guest dye in an organosiloxane host. These hosts have temperature-independent switching, at room temperature, through 90° for fields of the order of 10 Vrms/μm. Perylene molecules have been grafted onto the organosiloxane moiety via an alkyl spacer producing novel and rugged fluorescent dyes that are readily miscible in the host. Micro-separation of the low molar mass siloxane groups in the mesophases tend to form smectic phases. These planes produce an effective two-dimensional polymer backbonethat engenders the rugged mechanical properties of polymeric liquid crystals onto these low molar mass ferroelectric liquid crystals. In this study we show how the introduction of the dye molecules affects the electro-optic properties of the organosiloxane host. © 2001 OPA (Overseas Publishers Association) N.V. Published by license under the Gordon and Breach Science Publishers imprint, a member of the Taylor & Francis Group,.
Resumo:
The microstructure and mechanical properties of sintered stainless steel powder, of composition AISI 420, have been measured. Ball-milled powder comprising nanoscale grains was sintered to bulk specimens by two alternative routes: hot-pressing and microlaser sintering. The laser-sintered alloy has a porosity of 6% and comprises a mixture of delta ferrite and tempered martensite, and the relative volume fraction varies along the axis of the specimen due to a thermal cycle that evolves with progressive deposition. In contrast, the hot-pressed alloy has a porosity of 0.7% and exhibits a martensitic lath structure with carbide particles at the boundaries of the prior austenite grains. These differences in microstructure lead to significant differences in mechanical properties. For example, the uniaxial tensile strength of the hot-pressed material is one-half of its compressive strength, due to void initiation at the carbide particles at the prior austenite grain boundaries. Nanoindentation measurements reveal a size effect in hardness and also reveal the sensitivity of hardness to the presence of mechanical polishing and electropolishing. © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Resumo:
A one-dimensional analytical model is developed for the steady state, axisymmetric, slender flow of saturated powder in a rotating perforated cone. Both the powder and the fluid spin with the cone with negligible slip in the hoop direction. They migrate up the wall of the cone along a generator under centrifugal force, which also forces the fluid out of the cone through the powder layer and the porous wall. The flow thus evolves from an over-saturated paste at inlet into a nearly dry powder at outlet. The powder is treated as a Mohr-Coulomb granular solid of constant void fraction and permeability. The shear traction at the wall is assumed to be velocity and pressure dependent. The fluid is treated as Newtonian viscous. The model provides the position of the colour line (the transition from over- to under-saturation) and the flow velocity and thickness profiles over the cone. Surface tension effects are assumed negligible compared to the centrifugal acceleration. Two alternative conditions are considered for the flow structure at inlet: fully settled powder at inlet, and progressive settling of an initially homogeneous slurry. The position of the colour line is found to be similar for these two cases over a wide range of operating conditions. Dominant dimensionless groups are identified which control the position of the colour line in a continuous conical centrifuge. Experimental observations of centrifuges used in the sugar industry provide preliminary validation of the model. © 2011 Elsevier Ltd.
Resumo:
The exponential increase of industrial demand in the past two decades has led scientists to the development of alternative technologies for the fast manufacturing of engineering components, aside from standard and time consuming techniques such as casting or forging.Cold Spray (CS) is a newly developed manufacturing technique, based upon the deposition of metal powder on a substrate due to high energy particle impacts. In this process, the powder is accelerated up to considerable speed in a converging-diverging nozzle, typically using air, nitrogen or helium as a carrier gas. Recent developments have demonstrated significant process capabilities, from the building of mold-free 3D shapes made of various metals, to low porosity and corrosion resistant titanium coatings.In CS, the particle stream characteristics during the acceleration process are important in relation to the final geometry of the coating. Experimental studies have shown the tendency of particles to spread over the nozzle acceleration channel, resulting in a wide exit stream and in the difficulty of producing narrow tracks.This paper presents an investigation on the powder stream characteristics in CS supersonic nozzles. The powder insertion location was varied within the carrier gas flow, along with the geometry of the powder injector, in order to identify their relation with particle trajectories. Computational Fluid Dynamics (CFD) results by Fluent v6.3.26 are presented, along with experimental observations. Different configurations were tested and modeled, giving deposited track geometries of copper and tin ranging from 1. mm to 8. mm in width on metal and polymer substrates. © 2011 Elsevier B.V.
Resumo:
A mixture of Gaussians fit to a single curved or heavy-tailed cluster will report that the data contains many clusters. To produce more appropriate clusterings, we introduce a model which warps a latent mixture of Gaussians to produce nonparametric cluster shapes. The possibly low-dimensional latent mixture model allows us to summarize the properties of the high-dimensional clusters (or density manifolds) describing the data. The number of manifolds, as well as the shape and dimension of each manifold is automatically inferred. We derive a simple inference scheme for this model which analytically integrates out both the mixture parameters and the warping function. We show that our model is effective for density estimation, performs better than infinite Gaussian mixture models at recovering the true number of clusters, and produces interpretable summaries of high-dimensional datasets.