Effect of Sb implantation on copper silicides formation and morphology after annealing of Cu/Si structures

In this work, the solid state reaction between a thin film of copper and silicon has been studied using Rutherford backscattering spectroscopy, X-ray diffraction, scanning electron microscopy and microprobe analysis. Cu films of 400 and 900 Å thicknesses are thermally evaporated on Si(1 1 1) substrates, part of them had previously been implanted with antimony ions of 5×10¹⁴ or 5×10¹⁵ at. cm⁻² doses. The samples are heat-treated in vacuum at temperatures in the range 200–700 °C for various times. The results show the growth and formation of Cu₃Si and Cu₄Si silicides under crystallites shape dispatched on the sample surface, independently of the implantation dose. On the other hand, it is established that the copper layer is less and less consumed as the antimony dose increases, resulting in the accumulation of Sb⁺ ions at silicide/Si interface and in the silicide layer close to surface. The exposure of samples to air at room temperature shows the stability of Cu₄Si phase whereas the Cu₃Si silicide disappears to the benefit of the silicon dioxide formation. The observed phenomena are discussed.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

Synthesis of ZSM‐5 Films and Monoliths with Bimodal Micro/Mesoscopic Structures

A route to synthesize ZSM‐5 crystals with a bimodal micro/mesoscopic pore system has been developed in this study; the successful incorporation of the mesopores within the ZSM‐5 structure was performed using tetrapropylammonium hydroxide (TPAOH)‐impregnated mesoporous materials containing carbon nanotubes in the pores, which were encapsulated in the ZSM‐5 crystals during a solid rearrangement process within the framework. Such mesoporous ZSM‐5 zeolites can be readily obtained as powders, thin films, or monoliths.     

Effect of the Distribution of Manganese Ions on the Properties of Mn-Doped (Ba,Y)TiO3 PTCR Ceramics

The electrical properties and microstructure of (Ba,Y)TiO₃ PTCR ceramics were studied. The results indicate that the Mn ions increase the intergranular barrier height and produce a high-resistance layer on the grain surface. The temperature-dependent resistances of the grain bulk, surface layer, and grain boundaries, the temperature coefficient of resistance, and the magnitude of the varistor effect were assessed as a function of Mn content.     

Structural Changes Induced in Nonstoichiometric Titanium Carbide by High-Temperature Deformation

The microstructure evolution in nonstoichiometric titanium carbide is studied during high-temperature deformation at high strain rates and low strains (shock compression) and at slow strain rates and high strains (superplastic regime). The results demonstrate that high-temperature deformation in a broad range of strain rates offers a means of controlling the microstructure of titanium carbide. By varying deformation conditions, one can obtain materials differing in microstructure and chemical composition, in particular, with equilibrium and nonequilibrium microstructures. Accordingly, the physicochemical properties of such materials also differ.     

On the physical and logical topology design of large-scale optical networks

We consider the problem of designing a network of optical cross-connects (OXCs) to provide end-to-end lightpath services to large numbers of label switched routers (LSRs). We present a set of heuristic algorithms to address the combined problem of physical topology design (i.e., determine the number of OXCs required and the fiber links among them) and logical topology design (i.e., determine the routing and wavelength assignment for the lightpaths among the LSRs). Unlike previous studies which were limited to small topologies with a handful of nodes and a few tens of lightpaths, we have applied our algorithms to networks with hundreds or thousands of LSRs and with a number of lightpaths that is an order of magnitude larger than the number of LSRs. In order to characterize the performance of our algorithms, we have developed lower bounds which can be computed efficiently. We present numerical results for up to 1000 LSRs and for a wide range of system parameters such as the number of wavelengths per fiber, the number of transceivers per LSR, and the number of ports per OXC. The results indicate that it is possible to build large-scale optical networks with rich connectivity in a cost-effective manner, using relatively few but properly dimensioned OXCs.     

An improved statistical analysis of the least mean fourth (LMF) adaptive algorithm

The paper presents an improved statistical analysis of the least mean fourth (LMF) adaptive algorithm behavior for a stationary Gaussian input. The analysis improves previous results in that higher order moments of the weight error vector are not neglected and that it is not restricted to a specific noise distribution. The analysis is based on the independence theory and assumes reasonably slow learning and a large number of adaptive filter coefficients. A new analytical model is derived, which is able to predict the algorithm behavior accurately, both during transient and in steady-state, for small step sizes and long impulse responses. The new model is valid for any zero-mean symmetric noise density function and for any signal-to-noise ratio (SNR). Computer simulations illustrate the accuracy of the new model in predicting the algorithm behavior in several different situations.     

2-D symmetry: theory and filter design applications

In this comprehensive review article, we present the theory of symmetry in two-dimensional (2-D) filter functions and in 2-D Fourier transforms. It is shown that when a filter frequency response possesses symmetry, the realization problem becomes relatively simple. Further, when the frequency response has no symmetry, there is a technique to decompose that frequency response into components each of which has the desired symmetry. This again reduces the complexity of two-dimensional filter design. A number of filter design examples are illustrated.     

Effect of anisotropy of tin on thermomechanical behavior of solder joints

Properties of body centered tetragonal tin are highly anisotropic. As a consequence large stresses can develop at the tin grain boundaries due to coefficient of thermal expansion mismatch during temperature excursions. A modeling approach to evaluate the 3D stress states that develop at grain boundaries during thermomechanical fatigue in tin-based solder is presented. Development of significant amounts of stresses in the plane of the grain boundary can cause grain-boundary sliding and surface-relief effects, while those normal to the grain boundary can cause grain-boundary decohesion and cracking.