Preparation of nanocrystalline nickel oxide from nickel hydroxide using spark plasma sintering and inverse Hall-Petch related densification

Nanocrystalline nickel oxide (NiO) was prepared from nickel hydroxide by Spark plasma sintering (SPS) and the mechanisms involved in the densification of NiO were studied. Reverse precipitated nickel hydroxide powders were SPS processed at 400, 600 and 700?°C with 70?MPa pressure. Pure NiO with 12?nm crystallite size formed after 400?°C sintering process. However NiO grains had grown to 18 and 38?nm after 600 and 700?°C sintering respectively. NiO pellets prepared using 600 and 700?°C SPS sintering schedules had relative densities of 83% and 94% respectively. Two displacement rate regimes were observed during densification of NiO in both 600 and 700?°C sintering processes. Decomposition of nickel hydroxide and particle sliding of NiO led to first displacement rate maximum while inverse Hall-Petch based plastic deformation facilitated densification during the constant second displacement rate regime. No densification occurred during sintering holding times indicating the limited role that diffusion played during densification.     

Finite element analysis of advanced multilayer capacitors

We establish a systematic methodology to design and analyse electromagnetic components such as advanced multilayer ceramic capacitors (MLCCs) using the finite element (FE) method. We employ a coupled formulation to compute the interaction between the electric and magnetic fields. Unlike a linear distribution of current assumed in the circuit model, an accurate electrostatic solution to model the entire advanced MLCCs (4 × 4 × 27 = 432 cells) is presented. The FE solution is used to compute the lumped parameters for a range of frequencies. These lumped parameters are then used to compute the parasitic elements of the MLCCs. We introduce two algorithms to efficiently analyse the behaviour of a capacitor with changing frequency. The lower frequency (much below the self‐resonant frequency of the capacitor) algorithm separates the effect of the electric and magnetic fields and reduces the computational effort required to solve the FE problem, whereas, the high‐frequency algorithm couples the effect between the electric and the magnetic fields. We use these algorithms in conjunction with a new multiple scale technique to effectively determine the small values of R, L and C in MLCCs. The formulation, the implementation, and the numerical results demonstrate the efficacy of the present FE formulation and establish a systematic methodology to design and analyse advanced electromagnetic components. Copyright © 2003 John Wiley & Sons, Ltd.     

Mixed oxide supported hydrodesulfurization catalysts—a review

Support effects form important aspect of hydrodesulfurization (HDS) studies and mixed oxide supports received maximum attention in the last two decades. This review will focus attention on studies on mixed oxide supported Mo and W catalysts. For convenience of discussion, these are divided into Al₂O₃ containing mixed oxide supports, TiO₂ containing mixed oxide supports, ZrO₂ containing mixed oxide supports and other mixed oxide supports containing all the rest. TiO₂ containing mixed oxides received maximum attention, especially TiO₂–Al₂O₃ supported catalysts. A brief discussion about their prospects for application to ultradeep desulfurization is also included. An overview of the available literature with emphasis on research carried out in our laboratory form the contents of this publication.     

Optical switching properties of RCo2-type alloy thin films by electrochemical hydrogenation

The switchable optical properties of Pd-protected RCo₂-type Ho_0.6Mm_0.4Co₂ alloy thin films have been investigated in a KOH electrolyte. The reversible optical switching has been carried out simultaneously by measuring transmitted light through the thin film during electrochemical charging–discharging of hydrogen. The dependence of switching speed and cyclic durability of the film on the charging and discharging current density as well as concentration of KOH electrolyte has been studied. In addition, cyclic voltammetric measurements have been performed to examine the hydride formation and decomposition reactions.     

Predicting Acute Renal Failure after Cardiac Surgery: Validation and Re‐definition of a Risk‐Stratification Algorithm

Background:  Acute renal failure (ARF) after cardiac surgery is associated with significant morbidity and mortality, irrespective of the need for dialysis. Previous studies have attempted to identify predictors of ARF and develop risk stratification algorithms. This study aims to validate the algorithm in an independent cohort of patients that includes a significant proportion of female and black patients and compares two different definitions of renal outcome.
Methods:  A large single center cardiac surgery database was examined (n, 24,660; 1993–2000) which included 29.9% females and 3.7% black patients. Post‐operative ARF was defined as: a) ARF requiring dialysis, b) > 50% reduction in creatinine clearance relative to baseline or requiring dialysis. Clinical variables related to baseline renal function and cardiovascular disease were used in recursive partitioning analysis for both outcome definitions. Chi‐square goodness of fit analysis was performed to validate the algorithm.
Results:  The frequency of post‐operative ARF requiring dialysis ranged between 0.5 and 15.5% based on the risk categories with the area under the receiver operating characteristic (ROC) curve of 0.78. Using the more inclusive definition of ARF, the frequency was significantly higher ranging from 2.6 to 25%(P < 0.001) with an area under ROC curve of 0.65.
Conclusions:  The renal risk stratification algorithm is valid in predicting post‐operative ARF in an independent cohort of patients, well represented by differences in gender and race. Since the need for dialysis remains subjective, a more objective and inclusive definition of ARF may help in identifying a larger number of patients 'at‐risk'.     

DSP-based digital FM demodulation for GMSK signals

Demodulation of Gaussian Minimum Shift Keying (GMSK) using a limiter-discriminator is a low complexity alternative to coherent demodulation. This so-called digital FM demodulation is followed by clock recovery, sampling, and thresholding. Conventionally, clock recovery is done in hardware, and matched filtering is usually not possible when the Gaussian pulse is wider than a bit duration. We propose a clock recovery technique based on discrete-time processing of the demodulated baseband signal. This technique couples very nicely with a new maximum likelihood sequence estimator for the data that uses a whitening filter followed by a Viterbi decoder. The entire detection algorithm can be implemented in an efficient manner on a Digital Signal Processor (DSP). Computer simulation results are presented to show that the new algorithm performs better than the conventional slicer by as much as 5.5 dB.     

THERMAL STABILITY ANALYSIS OF THE LIQUID PHASE METHANOL SYNTHESIS REACTOR

The effect of addition of an inert liquid phase on the rate of heat generation in the catalytic synthesis of methanol from syngas has been studied. Gas compositions typical of product gases from Lurgi and Koppers-Totzek gasifiers, represented by H₂-rich and CO-rich syngas respectively, were used to experimentally verify the “slope” and “dynamic” critria in a three-phase fixed bed recycle reactor. The liquid medium, witco-40 oil, has been effective in controlling the rate of heat generation and in preventing catalyst overheating, signifying that the liquid phase synthesis is thermally far more stable than the vapor phase synthesis. The experimental thermal stability study provides crucial and valuable information in commercializing the liquid phase methanol synthesis process. The current approach of thermal stability analysis does not require any a priori assumption or predetermined reaction kinetics.     

Basic studies leading to the development of an ultrahigh strength,high fracture toughness low-alloy steel

Ultrahigh strength steels have been used increasingly in recent years for critical aircraft and aerospace structural applications. In such applications, though materials performance is of prime consideration, cost and availability makes the low-alloy steels an attractive option. This paper describes the development of an ultrahigh strength NiSiCrCoMo low-alloy steel, supported by significant findings obtained from the basic studies that were aimed at understanding how solute additions influence fracture resistance of iron, with and without the presence of carbon. The results of the basic studies, in combination with the work of Garrison (1986) on a NiSiCr steel, have profitably been employed in the development of a NiSiCrCoMo low-alloy steel possessing a strength-toughness combination quite comparable to the highly alloyed 250-grade maraging steel. Reproducibility of attractive strength and toughness properties has been established in tonnage scale melts. This steel, in the softened condition, has good formability and machinability. Weld parameters have also been established. The NiSiCrCoMo low-alloy steel thus meets the requirements of performance and cost rendering it an attractive option for advanced structural applications.     

Space and time efficient parallel algorithms and software for EST clustering

Expressed sequence tags, abbreviated as ESTs, are DNA molecules experimentally derived from expressed portions of genes. Clustering of ESTs is essential for gene recognition and for understanding important genetic variations such as those resulting in diseases. We present the algorithmic foundations and implementation of PaCE, a parallel software system we developed for large-scale EST clustering. The novel features of our approach include 1) design of space-efficient algorithms to limit the space required to linear in the size of the input data set, 2) a combination of algorithmic techniques to reduce the total work without sacrificing the quality of EST clustering, and 3) use of parallel processing to reduce runtime and facilitate clustering of large data sets. Using a combination of these techniques, we report the clustering of 327,632 rat ESTs in 47 minutes, and 420,694 Triticum aestivum ESTs in 3 hours and 15 minutes, using a 60-processor IBM xSeries cluster. These problems are well beyond the capabilities of state-of-the-art sequential software. We also present thorough experimental evaluation of our software including quality assessment using benchmark Arabidopsis EST data.