Preparation and characterization of palladium-plated porous glass for hydrogen enrichment

In this study, cylindrical porous glass tablets were plated by palladium using electroless plating technique. Hypophosphite and Co(II) complexes were used as reducing agents in the prepared plating baths. Experiments were carried out in an especially designed glass vessel in which helium gas was continuously bubbled through the solution to create uniform concentration and to remove hydrogen gas from the surface for the case of hypophosphite-based procedure. XRF analysis of the upper layer of the composite membrane prepared by the hypophosphite-based bath showed a Pd/Si ratio of 4.6. SEM photographs indicated impregnation of Pd into the substrate upto 200 μm. However, the thickness of the dense Pd layer was only about 15 μm. SEM photographs and XRF results showed that hypophosphite-based bath was much more successful than the Co(II) complex-bath in Pd plating. Permeation experiments carried out at different temperatures showed that the contribution of surface diffusion to the permeation was significant at low temperatures and solution–diffusion mechanism was not important in the 40–200 °C temperature range for these membranes. The selectivity ratio for H₂/N₂ was found to be about 7 at 200 °C.     

Improved discrimination of soft and hard white wheat using SKCS and imaging parameters

Natural variation of hardness of wheat kernels often results in overlapping hardness indices (HI) distributions between hard and soft classes as measured with the single kernel characterization system (SKCS). This is particularly true for the case of the hard white (HW) and soft white (SW) wheat classes. To address this problem, a color camera was incorporated into the SKCS system so that color and kernel size data could be combined with SKCS measurements for classification purposes. Samples of hard red (HR), soft red (SR), HW, and SW wheat were classified using the SKCS system with and without the camera and results compared. Using the camera system, errors for separating HW from SW classes were reduced to less than 5%, as compared to 17.1% using SKCS alone. Furthermore, improved data processing applied to the low-level data currently produced by the SKCS system led to greater than 50% reduction in classification errors between SW and HR as compared to using HI data alone. Similar improvements in classification accuracies for 300-kernel sample containing mixtures of SW and HW were also achieved. The 300 kernel sample classification is usually what inspectors and grain traders use to determine sample purity rather than individual kernel results. The techniques developed should aid grain inspectors in properly identifying mixtures of these two classes. Unfortunately, for the SR and HR classes, incorporating the camera data decreased classification accuracy while increasing the complexity of the system. However, SR and HR classes can be adequately distinguished with the SKCS in its current form. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.     

Trace metal content in nine species of fish from the Black and Aegean Seas,Turkey

Trace metal content of nine fish species harvested from the Black and Aegean Seas were determined by microwave digestion and atomic absorption spectroscopy (MD–AAS). Verification of the MD–AAS method was demonstrated by analysis of standard reference material (NRCC-DORM-2 dogfish muscle). Trace metal content in fish samples were 0.73–1.83 μg/g for copper, 0.45–0.90 μg/g for cadmium, 0.33–0.93 μg/g for lead, 35.4–106 μg/g for zinc, 1.28–7.40 μg/g for manganese, 68.6–163 μg/g for iron, 0.95–1.98 μg/g for chromium, and 1.92–5.68 μg/g for nickel. The levels of lead and cadmium in fish samples were higher than the recommended legal limits for human consumption.     

The effects of maleic anhydride terpolymer and its ester derivatives on tensile bond strength between the acrylic resin and resilient lining material

The present study investigated the effects on the bonding between the denture base acrylic resin and the soft silicon based lining material of maleic anhydride‐styrene‐vinyl acetate (MA‐St‐VA) terpolymer and some of its ester derivatives. These ester derivatives were n‐propylmaleate‐styrene‐vinyl acetate (n‐PrMA‐St‐VA), n‐buthylmaleate‐styrene‐vinyl acetate (n‐BuMA‐St‐VA) and n‐benzylmaleate‐styrene‐vinyl acetate (n‐BzMA‐St‐VA). Fourier Transform infrared spectroscopy method was used to determine interactions between terpolymers with the acrylic resin and soft lining material. The tensile bond strength of all the groups was compared and the obtained differences were statistically significant (P < 0.05). The highest value was found for the samples lined with n‐BuMA‐St‐VA (2.11 ± 0.21 MPa) and the samples lined with n‐BzMA‐St‐VA had the lowest bond strength (0.3 ± 0.12 MPa). © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 1338–1341, 2007     

Characterization of Dielectric Particles by Impedance Spectroscopy (Part I)

Impedance spectroscopy is an effective method to investigate physical properties of multicomponent systems so that contributions of individual components can be extracted from different sections of the spectra, which is frequency dependent. Slurries can be considered as 0–3 mixed systems containing a host liquid and dispersed particles. It was shown that low-frequency part of impedance spectra is sensitive to dielectric properties of dispersed particles. Applicability of this technique was extended using various dielectric powders dispersed in appropriate liquids. Characterization of slurries by impedance spectroscopy through applying of equivalent circuit models allows a reliable measurement of dielectric constant of particulate materials and liquids.     

An efficient joint channel estimation and decoding algorithm for turbo-coded space?time orthogonal frequency division multiplexing receivers

The challenging problem in the design of digital receivers of today's and future high-speed, high data-rate wireless communication systems is to implement the optimal decoding and channel estimation processes jointly in a computationally feasible way. Without realising such a critical function perfectly at receiver, the whole system will not work properly within the desired performance limits. Unfortunately, direct implementation of such optimal algorithms is not possible mainly due to their mathematically intractable and computationally prohibitive nature. A novel algorithm that reaches the performance of the optimal maximum a posteriori (MAP) algorithm with a feasible computational complexity is proposed. The algorithm makes use of a powerful statistical signal processing tool called the expectation maximisation (EM) technique. It iteratively executes the MAP joint channel estimation and decoding for space'time block-coded orthogonal frequency division multiplexing systems with turbo channel coding in the presence of unknown wireless dispersive channels. The main novelty of the work comes from the facts that the proposed algorithm estimates the channel in a non-data-aided fashion and therefore except a small number of pilot symbols required for initialisation, no training sequence is necessary. Also the approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen'Loeve (KL) orthogonal expansion and finds MAP estimates of the uncorrelated KL series expansion coefficients. Based on such an expansion, no matrix inversion is required in the proposed MAP estimator. Moreover, optimal rank reduction is achieved by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the iterative estimation approach.