Characterization method of thermomechanical parameters for microelectronic materials

Reliability of thermomechanical simulations is critically linked to the accuracy of the mechanical properties that govern the behaviour of structure, like Young's modulus (E) and coefficient of thermal expansion (CTE). For many cases, the values found in literatures are dealing with bulk properties without detailed information on temperature effects. To address such issues, it is necessary to measure the materials parameters as a function of temperature. The measurement of CTE is usually accomplished by evaluating the thermal deflections of a subjected material layer deposited on a substrate, providing that E is known at a specific temperature of experiment. A bilayer method, based on theory of elasticity, is proposed to determine both E and CTE for a given temperature with a good resolution. This paper presents the theoretical analysis, the design and process of the microsystem test structures, and the main calculation results.     

3-D boundary element method for cracks in a plate

New fundamental solutions which automatically satisfy boundary conditions at the interfaces of an elastic plate perfectly bonded to two elastic halfspaces are implemented in a 3-D boundary element method (BEM) for crack problems. The BEM features a new integration scheme for highly singular kernels. The capability is achieved through a part analytic and part numerical integration procedure, such that the analytic part of the integration is similar for all slip/opening variations, ‘Part-through’ elliptic cracks in an elastic plate with traction-free surfaces are analysed and the stress intensity factor (SIF) values along the crack front are found to compare favourably with widely accepted numerically obtained SIF results by Raju and Newman.¹     

Formation of C49-TiSi2 in flash memories: a nucleation controlled phenomenon?

The formation of Ti silicides has been examined in flash memories with 0.25 μm linewidth by X-ray diffraction, scanning electron microscopy, and transmission electron microscopy. It has been observed that, after the first rapid thermal process and the selective metal etch, there is no silicide on the source and on a majority of drain contacts while C49-TiSi₂ is found on the gate. A pre-amorphisation implant increases drastically the formation of C49-TiSi₂ in the drain zone while modifications of annealing conditions have little impact. These results indicate that the formation of C49-TiSi₂ is most likely controlled by nucleation and that this nucleation is sensitive to both the width and the length of the reaction zone. The formation of a Ti rich silicide may play an important role in this nucleation by decreasing the driving force for the formation of C49-TiSi₂. Curiously enough, the formation of C49-TiSi₂ appears thus as a major concern for the salicide process in flash memories.     

Automatic Channel Detection Using DNN on 2D Seismic Data

Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon resources. Channels are among the most important geological features interpreters analyze to locate petroleum reservoirs. However, manual channel picking is both time consuming and tedious. Moreover, similar to any other process dependent on human intervention, manual channel picking is error prone and inconsistent. To address these issues, automatic channel detection is both necessary and important for efficient and accurate seismic interpretation. Modern systems make use of real-time image processing techniques for different tasks. Automatic channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil companies. In this paper, we propose an innovative automatic channel detection algorithm based on machine learning techniques. The new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation process. The algorithm uses deep neural network to train the classifier with both the channel and non-channel patches. We provide a field data example to demonstrate the performance of the new algorithm. The training phase gave a maximum accuracy of 84.6% for the classifier and it performed even better in the testing phase, giving a maximum accuracy of 90%.     

Deep neural network architectures for dysarthric speech analysis and recognition

Neural Computing and Applications - This paper investigates the ability of deep neural networks (DNNs) to improve the automatic recognition of dysarthric speech through the use of convolutional...     

Effect of thickness stretching and porosity on mechanical response of a functionally graded beams resting on elastic foundations

The novelty of this paper is the use of an efficient beam theory for bending, free vibration and buckling analysis of functionally graded material (FGM) beams on two-parameter elastic foundation. The present theory accounts for both shear deformation and thickness stretching effects by a parabolic variation of all displacements across the thickness, and satisfies the stress-free boundary conditions on the upper and lower surfaces of the beam without requiring any shear correction factor. Due to porosities, possibly occurring inside FGMs during fabrication, it is therefore necessary to consider the vibration, bending and buckling behaviors of beams having porosities in this work. The equation of motion for FGM beams is obtained through Hamilton’s principle. The closed form solutions are obtained by using Navier technique, and then fundamental frequencies are found by solving the results of eigenvalue problems. The validity of the present theory is investigated by comparing some of the present in literature. It can be concluded that the proposed theory is accurate and simple in solving the bending, free vibration and buckling behaviors of FGM sandwich beams.     

Study of Magnetic Properties of Fe-Doped CuO: Monte Carlo Simulations

Using Monte Carlo simulations, we are studying the magnetic properties of Fe-doped CuO thin films. The total magnetizations and the susceptibilities are studied as a function of the effect doping, external magnetic field, and exchange coupling. The critical temperature is discussed as a function of the effect of iron concentration. On the other hand, we investigate the effect of increasing temperatures on the coercive field for a constant value of exchange coupling and a fixed concentration. The coercive magnetic field is found to decrease with increasing temperature values until reaching its null value. The effect of increasing the exchange coupling amount on the saturation magnetic field H _s is illustrated. A linear growth of the saturation magnetic field is found as a function of the exchange coupling interaction. To complete this study, we presented and discussed the magnetic hysteresis cycle loops.     

Electro-oxidation of two reactive azo dyes on boron-doped diamond electrode

Electrochemical oxidation (decolorization/degradation) of blue and red commercial reactive azo dyes was carried out on boron-doped diamond (BDD) electrode. The effect of various quantities of FeSO(4) was investigated in the electro-Fenton reaction on BDD. Progress of dyes degradation during the electrolysis and electro-Fenton reaction was monitored by UV-visible absorption and by estimation of the chemical oxygen demand (COD). Direct electrolysis showed a limiting capacity for red and blue dye removal even at high current densities, e.g. maximum red color and COD removal were 70 and 20%, respectively at 30 mA cm(-2) after 300 min. Higher red and blue color removal efficiencies were achieved by electro-Fenton oxidation. Current density of 30 mA cm(-2) in the presence of 0.05 mmol/L of FeSO(4) resulted in the red color and COD removal of 98 and 96%, respectively. The optimum FeSO(4) concentration for the electro-Fenton reaction was determined to be 0.05 mmol/L. Instantaneous current efficiency (ICE) in the presence of FeSO(4) was almost three times higher than for experiments carried out without FeSO(4).