Study of inductively coupled Cl2/BCl3 plasma process for high etch rate selective etching of via-holes in GaAs

We have investigated the selective etching of 50 μm diameter via-holes for etch depth >200 μm using 30 μm thick photo resist mask in Inductively Coupled Plasma system with Cl₂/BCl₃ chemistry. Resultant etch rate/etch profiles are studied as a function of ICP process parameters and photo resist mask sidewall profile. Etch yield and aspect ratio variation with process pressure and substrate bias is also investigated at constant ICP power. The etch yield of ICP process increased with pressure due to reactant limited etch mechanism and reached a maximum of ∼19 for 200 μm depth at 50 mTorr pressure, 950 W coil power, 80 W substrate bias with an etch rate ∼4.9 μm/min. Final aspect ratio of etched holes is increased with pressure from 1.02 at 20 mTorr to 1.38 at 40 mTorr respectively for fixed etch time and then decreased to 1.24 at 50 mTorr pressure. The resultant final etch profile and undercut is found to have a strong dependence on the initial slope of photo resist mask sidewall angle and its selectivity in the pressure range of 20-50mTorr.     

A novel algorithm for estimation of depth map using image focus for 3D shape recovery in the presence of noise

Three-dimensional shape recovery from one or multiple observations is a challenging problem of computer vision. In this paper, we present a new Focus Measure for the estimation of a depth map using image focus. This depth map can subsequently be used in techniques and algorithms leading to the recovery of a three-dimensional structure of the object, a requirement of a number of high level vision applications. The proposed Focus Measure has shown robustness in the presence of noise as compared to the earlier Focus Measures. This new Focus Measure is based on an optical transfer function implemented in the Fourier domain. The results of the proposed Focus Measure have shown drastic improvements in estimation of a depth map, with respect to the earlier Focus Measures, in the presence of various types of noise including Gaussian, Shot, and Speckle noises. The results of a range of Focus Measures are compared using root mean square error and correlation metric measures.     

Comparison of stochastic filtering methods for 3D tracking

In the recent years, the 3D visual research has gained momentum with publications appearing for all aspects of 3D including visual tracking. This paper presents a review of the literature published for 3D visual tracking over the past five years. The work particularly focuses on stochastic filtering techniques such as particle filter and Kalman filter. These two filters are extensively used for tracking due to their ability to consider uncertainties in the estimation. The improvement in computational power of computers and increasing interest in robust tracking algorithms lead to increase in the use of stochastic filters in visual tracking in general and 3D visual tracking in particular. Stochastic filters are used for numerous applications in the literature such as robot navigation, computer games and behavior analysis. Kalman filter is a linear estimator which approximates system's dynamics with Gaussian model while particle filter approximates system's dynamics using weighted samples. In this paper, we investigate the implementation of Kalman and particle filters in the published work and we provide comparison between these techniques qualitatively as well as quantitatively. The quantitative analysis is in terms of computational time and accuracy. The quantitative analysis has been implemented using four parameters of the tracked object which are object position, velocity, size of bounding ellipse and orientation angle.     

Liquid-Liquid Extraction of Ruthenium from Chloride Media by N,N'-Dimethyl- N,N'-Dicyclohexylmalonamide

Abstract

Research on the solvent extraction of ruthenium from hydrochloric acid media has been carried out using N,N'-dimethyl-N,N'-dicyclohexylmalonamide (DMDCHMA) dissolved in 1,2-dichloroethane. Ruthenium extraction percentages (%E) ranging from 50% to 80% have been achieved for HCl concentrations between 5 M and 7 M. Extraction curves exhibiting the dependence of the %E ruthenium on HCl concentration in the aqueous phases are presented, the latter solutions being obtained by dissolution of either Ru(III) or Ru(IV) salts. The influence of some experimental parameters on the %E Ru, such as the equilibration time, extractant concentrations, and hydrogen-ion activities, has been thoroughly investigated. Additionally, DMDCHMA is also adequate for extracting Pd(II) from 5 M to 7 M HCl solutions and under similar experimental conditions, %E Rh(III) is below 5%, and Pt(IV), Ir(III), and Ir(IV) cause the formation of third phases. Both Ru and Pd(II) can be successfully stripped from the loaded organic phases with water. A partition scheme to isolate Ru from a number of some associated elements has also been attempted.     

Plasma surface modification and characterization of collagen‐based artificial cornea for enhanced epithelialization

Argon plasma treatment enhanced the attachment of epithelial cells to a collagen‐based artificial cornea crosslinked using glutaraldehyde (GA) and glutaraldehyde‐polyethylene oxide dialdehyde (GA‐PEODA) systems. The epithelialization of untreated and treated surfaces was evaluated by the seeding and growth of human corneal epithelial cells. Characterization of polymer surface properties such as surface hydrophilicity and roughness was also made by contact angle measurement and atomic force microscopy, respectively. Contact angle analysis revealed that the surface hydrophilicity significantly increased after the treatment. In addition, AFM characterization showed an increase in surface roughness through argon plasma treatment. Based on the biological and surface analysis, argon plasma treatment displays promising potential for biocompatibility enhancement of collagen‐based artificial corneas. It was also found that the cell attachment to artificial cornea surfaces was influenced by the combined effects of surface chemistry (i.e., surface energy), polymer surface morphology (i.e., surface roughness), and polar interactions between functional groups at the polymer surface and cell membrane proteins. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007     

Design tradeoff analysis of floating-point adders in FPGAs

With gate counts of ten million, field-programmable gate arrays (FPGAs) are becoming suitable for floating-point computations. Addition is the most complex operation in a floating-point unit and can cause major delay while requiring a significant area. Over the years, the VLSI community has developed many floating-point adder algorithms aimed primarily at reducing the overall latency. An efficient design of the floating-point adder offers major area and performance improvements for FPGAs. Given recent advances in FPGA architecture and area density, latency has become the main focus in attempts to improve performance. This paper studies the implementation of standard; leading-one predictor (LOP); and far and close datapath (2-path) floating-point addition algorithms in FPGAs. Each algorithm has complex sub-operations which contribute significantly to the overall latency of the design. Each of the sub-operations is researched for different implementations and is then synthesized onto a Xilinx Virtex-II Pro FPGA device. Standard and LOP algorithms are also pipelined into five stages and compared with the Xilinx IP. According to the results, the standard algorithm is the best implementation with respect to area, but has a large overall latency of 27.059 ns while occupying 541 slices. The LOP algorithm reduces latency by 6.5% at the cost of a 38% increase in area compared to the standard algorithm. The 2-path implementation shows a 19% reduction in latency with an added expense of 88% in area compared to the standard algorithm. The five-stage standard pipeline implementation shows a 6.4% improvement in clock speed compared to the Xilinx IP with a 23% smaller area requirement. The five-stage pipelined LOP implementation shows a 22% improvement in clock speed compared to the Xilinx IP at a cost of 15% more area.     

An adaptive power system stabilizer based on recurrent neuralnetworks

Application of recurrent, neural networks in the design of an adaptive power system stabilizer (PSS) is presented in this paper. The architecture of the proposed adaptive PSS has two recurrent neural networks. One functions as a tracker to learn the dynamic characteristics of the power plant and the second one functions as a controller to damp the oscillations caused by the disturbances. In the proposed approach, the weights of the neural networks are updated on-line. Therefore, any new information available during actual control of the plant is considered. Simulation studies show that the artificial neural network (ANN) based PSS can provide very good damping over a wide range of operating conditions     

An application of frequency and duration approach in generationplanning

The available analytical tools for planning not only inadequately model pumped storage (PS) power plant units but also underestimate their load-levelling benefits. Therefore, if a PS power plant is among the candidate plants, its selection in the final “optimal plan” is highly unlikely. This research deals to assess the complete load-levelling benefits of PS units. The technique used is the frequency and duration approach coupled with the equivalent load duration curve (ELDC) method, used for generation planning. The proposed method is applied to IEEE RTS data and it is shown that almost 50% of PS benefits are not quantified in ELDC method