Mechanical fragmentation,Voronoi polyhedra and the theory of information

Objects which can undergo mechanical fragmentation are composed of all kinds of materials and comprise the entire span of sizes from celestial bodies to particles with initial sizes of a few mm. The problem has been treated theoretically by Mott, by a Monte Carlo simulation of the Voronoi diagram by Kiang, and also experimentally. Taking an essential element from the Mott formalism, we use the theory of information to derive an equation for the distribution of fragment masses. The result is equivalent to a distribution which follows from Mott's work. In contrast to earlier work, the relation is general since no specific assumptions have been made as to the nature of the fragmented material or with respect to its ductility (or lack of it). Reasons why the Monte Carlo results differ from the present ones are explained.     

Canonical structures of DC-AC thyristor converters

Realizability conditions of periodic waveforms in passive switched circuits are presented. Formulae for an identification of state matrices in switched circuits are derived. As input data, time functions of excitation and response are chosen. Six general transformer structures of 1-port thyristor converters have been obtained as a result of the synthesis method. The synthesis methods presented can be applied to create new thyristor and transistor arrangements, particularly thyristor compensators.     

Pressure leaching of a sulphide copper concentrate with simultaneous regeneration of the leaching agent

An experimental study is presented of leaching of a sulphide copper concentrate with aqueous ferric sulphate under oxygen pressure. The effects of oxygen pressure, sulphuric acid concentration and ferrous iron additions on the copper leaching rate have been determined. Partial pressure of oxygen has been found to govern the rate of copper leaching while the concentration of sulphuric acid only slightly influences this rate. Oxygen enhances the leaching rate mainly by oxidizing ferrous iron to ferric iron — the major leaching agent — and not by direct action on the minerals.Leaching of a sulphide copper concentrate under oxygen pressure with aqueous ferric sulphate leads to a three-fold reduction of both the necessary leaching time and ferric sulphate concentration in the leaching solution over those for conventional leaching with concentrated aqueous ferric sulphate.     

Fuzzy polynomial neurons as neurofuzzy processing units

In this study, we introduce and study fuzzy polynomial neurons (FPNs) being regarded as generic processing units in neurofuzzy computing. The underlying topology of FPNs is formed through fuzzy rules, fuzzy inference and polynomials. Each polynomial offers a nonlinear mapping and is centred around a modal value of the corresponding membership functions defined in the input space of the neuron. The adjustable order of the polynomial is essential when addressing the level of nonlinearity to be handled in the approximation problem. We demonstrate that fuzzy polynomial neurons form a certain class of functional neurons and afterwards discuss their properties and an overall design process. Furthermore, these neurons are discussed in the context of universal approximation and universal approximators     

A model of flocculation

The phenomenon of flocculation in liquid suspensions has a variety of applications, including mineral processing, treatment of industrial effluents, and municipal sewage sludge purification. Obtaining metals from ores would not be possible without the slurry processing route. Flocculants play here a double role: limiting environmental contamination and also slowing down depletion of raw materials — including potable, industrial and agricultural water. Development of better flocculants requires improved understanding of the mechanism of their action. We propose a model of flocculation based on the assumption that effective flocculants pervade large volumes of liquids in the suspensions. Since many flocculants are polymers, good flocculants according to the model should have large radii of gyration R_G. We therefore assume a connection between R_G and settling velocities y of particles out of suspension. Four different types of aqueous suspensions are studied, containing in turn silica, coal, Mn ore and Fe ore. A unique relationship is demonstrated between R_G and y for several polymeric flocculants in each type of slurry. For each suspension type the corresponding equation has the form y = aR_G^b, where the two parameters characterize the suspended particles and the liquid medium. While polysaccharides from natural sources are used as flocculants, we show how their cationization enhances the flocculation efficiency in all media we have studied. Large effects are achieved for the flocculating agent concentrations in the range of 6-9 ppm.     

Imaging domains of hard magnetic materials by SEM and MFM

The paper deals with observation of the magnetic domain structure of hard magnetic materials by the colloid-scanning electron microscopy (colloid-SEM) technique and the magnetic force microscopy (MFM) method. The specimens studied were anisotropic sintered Nd-Fe-B-based and SmCo₅ magnets, produced by powder metallurgy route. Observations of the magnetic microstructure were carried out in the thermally demagnetized state of the magnets at the surface perpendicular to the alignment axis. The domain structure is of complicated character. The coarse domain pattern consists of the main domains (forming a maze pattern near the specimen surface) and surface reverse spikes. Besides the coarse domain structure, the presence of fine scale surface domains is revealed by MFM.     

Evolutionary design of hybrid self-organizing fuzzy polynomial neural networks with the aid of information granulation

We introduce a new architecture of information granulation-based and genetically optimized Hybrid Self-Organizing Fuzzy Polynomial Neural Networks (HSOFPNN). Such networks are based on genetically optimized multi-layer perceptrons. We develop their comprehensive design methodology involving mechanisms of genetic optimization and information granulation. The architecture of the resulting HSOFPNN combines fuzzy polynomial neurons (FPNs) that are located at the first layer of the network with polynomial neurons (PNs) forming the remaining layers of the network. The augmented version of the HSOFPNN, “IG_gHSOFPNN”, for brief, embraces the concept of information granulation and subsequently exhibits higher level of flexibility and leads to simpler architectures and rapid convergence speed to optimal structure in comparison with the HSOFPNNs and SOFPNNs.

The GA-based design procedure being applied at each layer of HSOFPNN leads to the selection of preferred nodes of the network (FPNs or PNs) whose local characteristics (such as the number of input variables, the order of the polynomial, a collection of the specific subset of input variables, the number of membership functions for each input variable, and the type of membership function) can be easily adjusted. In the sequel, two general optimization mechanisms are explored. The structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is afterwards carried out in the setting of a standard least square method-based learning. The obtained results demonstrate a superiority of the proposed networks over the existing fuzzy and neural models.     

Effect of As Passivation on Vapor-Phase Epitaxial Growth of Ge on (211)Si as a Buffer Layer for CdTe Epitaxy

We report an investigation of epitaxial germanium grown by chemical vapor deposition (CVD) on arsenic-terminated (211)Si, which is the preferred substrate in the USA for fabrication of night-vision devices based on mercury cadmium telluride (MCT) grown by molecular-beam epitaxy (MBE). The films were characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), cross-sectional transmission electron microscopy (XTEM), and x-ray diffraction (XRD). Arsenic passivation was found to be effective in preventing cross-contamination of unwanted residual species present inside the reactor chamber and also in prolonging the evolution of layer-by-layer growth of Ge for significantly more monolayers than on nonpassivated Si. The two-dimensional (2D) to three-dimensional (3D) transition resulted in Ge islands, the density and morphology of which showed a clear distinction between passivated and nonpassivated (211)Si. Finally, thick Ge layers (∼250 nm) were grown at 525°C and 675°C with and without As passivation, where the layers grown with As passivation resulted in higher crystal quality and smooth surface morphology.     

Natural-Synthetic Hybrid Polymers Developed via Electrospinning: The Effect of PET in Chitosan/Starch System

Chitosan is an amino polysaccharide found in nature, which is biodegradable, nontoxic and biocompatible. It has versatile features and can be used in a variety of applications including films, packaging, and also in medical surgery. Recently a possibility to diversify chitosan properties has emerged by combining it with synthetic materials to produce novel natural-synthetic hybrid polymers. We have studied structural and thermophysical properties of chitosan + starch + poly(ethylene terephthalate) (Ch + S + PET) fibers developed via electrospinning. Properties of these hybrids polymers are compared with extant chitosan containing hybrids synthesized by electrospinning. Molecular interactions and orientation in the fibers are analyzed by infrared and Raman spectroscopies respectively, morphology by scanning electron microscopy and thermophysical properties by thermogravimetric analysis and differential scanning calorimetry. Addition of PET to Ch + S systems results in improved thermal stability at elevated temperatures.