Characterization of FeS2-pyrite thin films synthesized by sulphuration of amorphous iron oxide films pre-deposited by spray pyrolysis

FeS₂-thin films with good crystallinity were synthesized by a simple method which consists of sulphuration, under vacuum, of amorphous iron oxide thin films pre-deposited by spray pyrolysis of FeCl₃·6H₂O (0.03 M)-based aqueous solution onto glass substrates heated at 350 °C. At optimum sulphuration temperature (450 °C) and duration (6 h), black green layers having granular structure and high absorption coefficient (5.10⁴ cm⁻¹) were obtained. The study of the electrical properties of the as-prepared films vs. the temperature variations showed three temperature domain dependence of the conductivity behaviour. The first one corresponds to the high temperature range (330 K–550 K) for which an Arrhenius plot type was obtained. The activation energy value was estimated at about 61.47 meV. The second domain corresponding to the intermediate temperature range (80 K–330 K) showed a variable activation energy between the grain boundaries. The barrier height, q¯, was estimated to 27±0.5 meV, and the standard deviation, qσ, was evaluated at about 14±0.5 meV. We found that at lower temperatures (20 K–80 K), the conductivity is governed by two conduction types. The density of localised states, was about 2.45×10²⁰ eV⁻¹ cm⁻³.     

Patterned armor performance evaluation

Patterned armor is characterized by an array of repeating cells, such as tiled ceramic armor or reactive armor boxes. Performance characteristics of an ideal patterned armor with respect to multiple hits are discussed, and the types of single-shot ballistic data needed to quantify that performance are presented. An approach to use these data is developed to provide a quantitative measure (probability of nonperforation after a given number of impacts) of the patterned armor performance against multiple impacts. This performance measure can then be compared to a well-posed multiple-hit criterion to assess whether the patterned armor meets the criterion.     

Self-assembly routes towards creating superconducting and magnetic arrays

Using self-assembly from colloidal suspensions of polystyrene latex spheres we prepared well-ordered templates. By electrochemical deposition of magnetic and superconducting metals in the pores of such templates highly ordered magnetic and superconducting anti-dot nano-structures with 3D architectures were created. Further developments of this template preparation method allow us to obtain dot arrays and even more complicated structures. In magnetic anti-dot arrays we observe a large increase in coercive field produced by nanoscale (50–1000nm) holes. We also find the coercive field to demonstrate an oscillatory dependence on film thickness. In magnetic dot arrays we have explored the genesis of 3D magnetic vortices and determined the critical dot size. Superconducting Pb anti-dot arrays show pronounced Little-Parks oscillations in T_c and matching effects in magnetization and magnetic susceptibility. The spherical shape of the holes results in significantly reduced pinning strength as compared to standard lithographic samples. Our results demonstrate that self-assembly template methods are emerging as a viable, low cost route to prepare sub-micron structures.     

An algorithm for accurately estimating the harmonic magnitudes and phase shifts of periodic signals with asynchronous sampling

A digital sampling algorithm that uses two high-resolution integrating voltmeters in a master-slave configuration for accurately measuring the harmonic magnitudes and phase angles of two low-noise, low-frequency, arbitrary voltage signals is presented. It is shown that it is possible to measure up to 64 harmonic magnitudes of 60-Hz signals with an uncertainty of less than 13 /spl mu/V/V relative to the fundamental using commercial stable signal generators and high-resolution digital voltmeters. It is also possible to measure the phase shift between the fundamental components of two equally-synthesized 60-Hz signals with about 3.8% total harmonic distortion with an uncertainty of less than 2.5 /spl mu/rad. Even lower uncertainties can be obtained for low-distortion signals. The algorithm was applied to the measurement of the harmonics of periodic arbitrary signals generated by a commercial source. The differences between computed and measured values of harmonic magnitude suggest that stable digitally-synthesized signal generators can be used as calculable standards of harmonic distortion with an accuracy of less than 6 parts in 10/sup 5/ relative to the fundamental.     

Isothermal and Dynamic Microcalorimetry for Quantifying the Crystallization of an Amorphous Drug during Interactive Powder Mixing

This study reports the crystallization of amorphous nifedipine during an interactive mixing process quantified by using isothermal and dynamic microcalorimetry. Interactive mixtures of amorphous nifedipine and uniform glass beads were prepared by mixing in a Turbula® mixer. The difference in the extent of crystallization of amorphous nifedipine during mixing was characterized by the time it took for the crystallization of a known amount of amorphous nifedipine in isothermal calorimetry and the change in the height of the crystallization peak at 65°C in dynamic calorimetry. It was found that both isothermal and dynamic microcalorimetry are useful techniques for quantifying the physical transition of amorphous nifedipine during interactive mixing. The rate and extent of crystallization of amorphous nifedipine depended on both mixing time and speed, but mixing time played a more dominant role because the transformation of amorphous to crystalline nifedipine was greater after 3180 revolutions (9.7%) than after 405 revolutions (0.9%) at 27 rpm. The same trend was observed at 109 rpm, but the percentage of crystalline nifedipine after 3180 revolutions was only 5.2%. This meant that an increase in mixing time rather than speed increased the rate of amorphous to crystalline transformation. The greatest cause for crystal transformation during interactive mixing was the presence of crystal seeds of the thermodynamically stable nifedipine Modification I because the amount of amorphous to crystalline transformation increased from 2.6% for a completely amorphous mixture to 6.6% for a 92:8 mixture of amorphous and crystalline nifedipine when mixed for 30 minutes at 106 rpm.     

Local structural characterization of Zn:Cd:Se ternary semiconductors

We have studied the local atomic structure around Zn and Cd, in CdSe, ZnSe, and ordered and disordered Zn_0.5Cd_0.5Se thin films, grown by molecular beam epitaxy (MBE) and atomic layer epitaxy (ALE) using X-ray absorption spectroscopy (XAS). Zn K-shell X-ray absorption fine structure (XAFS) shows that the Zn–Se pair nearest neighbor distance is the same in both ordered and disordered ternary samples. This result shows that the ordered (or disordered growth) does not have a significant effect in the nearest neighbor Zn environment. However, results from K-shell Cd XAFS show that the Cd–Se pair nearest neighbor distance in the Zn_0.5Cd_0.5Se ordered film exhibits a contraction compared to the same pair distance in the disordered Zn_0.5Cd_0.5Se sample and the binary CdSe compound. This suggests that the shortest Zn–Se nearest neighbor distance regulates the Cd–Se nearest neighbor distance in the ternary compounds, when these are grown in an ordered, layer by layer, fashion.     

NAROAS: a neural network-based advanced operator support system for the assessment of systems reliability

We have developed and implemented a computerized reliability monitoring system for nuclear power plant applications, based on a neural network. The developed computer program is a new tool related to operator decision support systems, in case of component failures, for the determination of test and maintenance policies during normal operation or to follow an incident sequence in a nuclear power plant. The NAROAS (Neural Network Advanced Reliability Advisory System) computer system has been developed as a modularized integrated system in a C++ Builder environment, using a Hopfield neural network instead of fault trees, to follow and control the different system configurations, for interventions as quickly as possible at the plant. The observed results are comparable and similar to those of other computer system results. As shown, the application of this neural network contributes to the state of the art of risk monitoring systems by turning it easier to perform online reliability calculations in the context of probabilistic safety assessments of nuclear power plants.     

Low-frequency magnetic interference in a SQUID gradiometer caused by a Cryotiger gas-mixture cooler

A Cryotiger^® gas-mixture cooler was applied for cooling of three high-T_c SQUID magnetometers. These SQUID magnetometers were mounted on an alumina holder in an axial gradiometer configuration. From 20 Hz upward, the system noise was about 0.1 pT/√Hz. Below this frequency, the noise gradually increased to a level of 10 pT/√Hz at 1 Hz. This low-frequency excess noise appeared to be due to remnant magnetization of the Cryotiger cold head. Movement of magnetic cold-head parts with respect to the SQUIDs are induced by pressure fluctuations in the heat exchanger lines. By using one SQUID as a reference for the cooler noise, a first-order gradiometer can be formed in which the cooler noise is eliminated. To establish a proper second-order gradiometer either a fourth SQUID has to be added, or the spatial separation between cold head and SQUIDs has to be increased significantly.     

Neural networks based subgrid scale modeling in large eddy simulations

In this paper a multilayer feed-forward neural network (NN) is used as subgrid scale (SGS) model in a large eddy simulation (LES). The NN was previously off-line trained using numerical data generated by a LES of a channel flow at Re_τ=180 with Bardina's scale similar (BFR) SGS model. Results show the ability of NNs to identify and reproduce the highly nonlinear behavior of the turbulent flows, and therefore the possibility of using NN techniques in numerical simulations of turbulent flows.     

Adaptive lifting for shape-based image retrieval

We propose to use adaptive wavelet lifting for image retrieval systems that are based on shape detection and multiresolution structures of objects in a database against a background of texture. To measure the performance of our approach, feature vectors are computed based on moment invariants of detail coefficients produced by the adaptive lifting scheme and retrieval rates are obtained by measuring distances between these vectors. Retrieval rates are compared with the rates obtained when using non-adaptive wavelet filtering as a preprocessing step. A synthetic database is created for this simulation.