Complex shape metallic glass composites produced in one step by mini-thixoforming

Mini-thixoforming is a technique based on forming in semi-solid state: the material becomes partially melted, retains a fraction of solid phase and is able to fill intricate cavities in a single forming step. In this study, metallic glass composites were produced by a combination of powder metallurgy and processing of material in semi-solid state. The experimental program was composed of processing mechanically compressed powder in semi-solid state. The powder mixture consisting of iron powder + metallic glass powder. Metallic glass was obtained in the form of a rod and prior to semi-solid processing was characterized by scanning electron microscopy (SEM), light microscopy and micro-hardness test. The rod was milled and obtained powder was mixed with Fe powder. In order to achieve a better compaction, the mixture was mechanically compressed before heating to a semi-solid state. After the semi-solid processing was carried out, homogenous composites reinforced with Fe powder were obtained. Characterization of the produced structures and comparison of final structures at different temperatures were carried out again by DTA-TG, XRD, SEM-EDX, light microscopy and micro-hardness test, and the analysis results of composite structures have been compared with the initial ones. It was concluded that one step formation process of compact composite was successfully completed.     

Delayed-feedback control of oscillations in non-linear planar systems

The use of delayed feedback of position for the control of oscillatory behaviour is analysed. It is shown that linear feedback can annihilate limit cycles and stabilize the origin. Furthermore, it is possible to create an asymptotically stable limit cycle with any prescribed amplitude using a simple non-linear feedback. For almost all values of the delay, these feats can be achieved without using derivative information in the feedback. The results indicate a possible mechanism by which biological systems accomplish complex control tasks using delayed and partial state information.     

In doped CdO films: Electrical,optical, structural and surface properties

Recently, there has been a lot of work on the production and investigation of the physical properties of Transparent Conducting Oxide (TCO) materials which have common application area in photovoltaic solar cells and some optoelectronic devices. In this work, CdO film which is a material belongs to TCO family has been produced by Ultrasonic Spray Pyrolysis technique on microscope glass substrates at the substrate temperature of 250 ± 5 °C. Electrical, optical, structural and surface properties of undoped and In doped (at 1.3 and 5%) CdO films and the effect of In doping percentage on the physical properties of CdO films have been investigated. It has been determined that electrical conductivity of CdO film is high and this value has been decreased by In doping. After the optical investigations, it has been observed that the transmittances of the films are about 30% and decreased dramatically by In doping. XRD investigations showed that, films have polycrystalline structure and good crystallinity levels. It has been found that In element hasn't got an important effect on the morphology of the films after the examination of surface micrographs. It has been determined that Cd and O elements are present in the solid film by using EDS. After all investigations, it has been concluded that In doping has an important effect on the electrical, optical, structural and surface properties of CdO films.     

Numerical investigation of heat transfer and pressure drop in enhanced tubes

This study investigates passive heat transfer enhancement techniques to determine the distribution of temperature and static pressure in test tubes, the friction factor, the heat flux, the temperature difference between the inlet and outlet fluid temperatures, the pressure drop penalty and the numerical convective heat transfer coefficient, and then compares the results to the experimental data of Zdaniuk et al. It predicts the single-phase friction factors for the smooth and enhanced tubes by means of the empirical correlations of Blasius and Zdaniuk et al. This study performed calculations on a smooth tube and two helically finned tubes with different geometric parameters also used in the analyses of Zdaniuk et al. It also performed calculations on two corrugated tubes in the simulation study. In Zdaniuk et al.'s experimental setup, the horizontal test section was a 2.74 m long countercurrent flow double tube heat exchanger with the fluid of water flowing in the inner copper tube (15.57–15.64 mm i.d.) and cooling water flowing in the annulus (31.75 mm i.d.). Their test runs were performed at a temperature around 20 °C for cold water flowing in the annulus while Reynolds numbers ranged from 12,000 to 57,000 for the water flowing in the inner tube. A single-phase numerical model having three-dimensional equations is employed with either constant or temperature dependent properties to study the hydrodynamics and thermal behaviors of the flow. The temperature contours are presented for inlet, outlet and fully developed regions of the tube. The variations of the fluid temperature and static pressure along tube length are shown in the paper. The results obtained from a numerical analysis for the helically tubes were validated by various friction factor correlations, such as those found by Blasius and Zdaniuk et al. Then, numerical results were obtained for the two corrugated tubes as a simulation study. The present study found that the average deviation is less than 5% for the friction factors obtained by the Fluent CFD program while Blasius's correlation has the average deviation of less than 10%. The corrugated tubes have a higher heat transfer coefficient than smooth tubes but a lower coefficient than helically finned tubes. The paper also investigates the pressure drop penalty for the heat transfer enhancement.     

Application of artificial neural networks for prediction of natural convection from a heated horizontal cylinder

A generalized neural network analysis for natural convection heat transfer from a horizontal cylinder is developed in this paper. Cylinder diameter, cylinder surface temperature and ambient temperature are selected as the input parameters, while the Nusselt number as the output. A three-layer network is used for predicting the Nusselt number. The number of the neurons in the hidden layer was determined by a trial and error process together with cross-validation of the experimental data evaluating the performance of the network and standard sensitivity analysis. The trained network gives the best values over the correlations with less than 2.5% mean relative error. The experimental data of the average Nusselt number over the horizontal cylinders having different diameters of 4.8 mm–9.45 mm are from Atay?lmaz and Teke [1]. The results from the trained network were compared with the proposed correlation for the average Nusselt number over the cylinder and it is shown that the results are in satisfactory agreement. The Nusselt numbers obtained from the experimental study were seen to be consistent by ± 20% with the well known correlations for natural convection heat transfer from horizontal cylinder developed by Morgan [2], Fand and Brucker [3], and Churchill and Chu [4]. Moreover it is seen that that results from the trained network show absolute agreement with the experimental data in ± 5% deviation band better than the correlations given by Morgan [2], Fand and Brucker [3], and Churchill and Chu [4].     

Large enhancement of fluorescence efficiency from CdSe/ZnS quantum dots induced by resonant coupling to spatially controlled surface plasmons

Nanoengineered fluorescent response is reported from semiconductor core-shell (CdSe/ZnS) quantum dots in proximity to the surface plasmon polariton field of periodic Ag nanoparticle arrays. Tuning the surface plasmon polariton resonance to the quantum dot exciton emission band results in an enhancement of up to approximately 50-fold in the overall fluorescence efficiency, in a design where each Ag nanoparticle is interconnected by a continuous Ag thin film. Propagating modes of surface plasmon resonances have a direct impact on the fluorescence enhancement.     

Efficient schema-based XML-to-Relational data mapping

Storing and querying XML documents using a RDBMS is a challenging problem since one needs to resolve the conflict between the hierarchical, ordered nature of the XML data model and the flat, unordered nature of the relational data model. This conflict can be resolved by the following XML-to-Relational mappings: schema mapping, data mapping and query mapping. In this paper, we propose: (i) a lossless schema mapping algorithm to generate a database schema from a DTD, which makes several improvements over existing algorithms, (ii) two linear data mapping algorithms based on DOM and SAX, respectively, to map ordered XML data to relational data. To our best knowledge, there is no published linear schema-based data mapping algorithm for mapping ordered XML data to relational data. Experimental results are presented to show that our algorithms are efficient and scalable.     

Influence of desensitizing procedures on adhesion of resin cements to dentin

This study evaluated the effect of two desensitizer agents with different contents and Nd:YAG laser irradiation on the shear bond strength (SBS) of adhesive resin cements to dentin. New treatment options of Nd:YAG laser irradiation and tetracalcium phosphate-containing agent applications were compared with routinely used glutaraldehyde-containing agents. One hundred and twenty human, caries-free premolars were embedded in acrylic resin blocks 2 mm below the cementoenamel junction. Buccal surfaces of the teeth were ground to expose dentin. The specimens were randomly assigned into three different surface treatments (desensitizing agents, Nd:YAG laser) and the control, then into three different adhesive resin cement applications (n = 10). Resin cements (Panavia SA cement (PA), Panavia SA cement with Clearfil Universal Bond (PACU), and Multilink N (MN)) were applied to the conditioned teeth surfaces using Teflon tubes. The specimens were thermocycled (5000 cycles, 5–55 ± 1 °C, dwell time 30 s). The SBS test was performed in all groups. The results were submitted to two-way ANOVA and Tukey HSD tests (p < .05). Further, SEM analysis was performed on the dentin surfaces. SBS values were significantly difference among the surface treatment groups and also among adhesive resin cement groups (p < .05). The specimen cemented with PA showed lower SBS values than PACU- and MN-applied specimens. The highest SBS value was obtained in the Nd:YAG laser group which was cemented with PACU cement. The lowest SBS value was obtained in the control group which was cemented with PA cement. In addition, SEM evaluation revealed that desensitizing agents and Nd:YAG laser occluded dentin tubules.     

Micelles and ‘reverse micelles’ with a novel water-soluble diblock copolymer

A series of poly[2-(diisopropylamino)ethyl methacrylate]-block-poly[2-(N-morpholino)ethyl methacrylate], [PDPA-b-PMEMA], have been synthesized by using group transfer polymerization. These novel PDPA-b-PMEMA diblock copolymers dissolved molecularly in aqueous solution at low pH (<6.0) due to the protonation of all tertiary amine residues of both blocks and formed PDPA-core micelles at pH 7.5 by PMEMA block forming the micelle coronas. On the other hand, it was also observed that these diblock copolymers formed near-monodisperse ‘reverse micelles’, PMEMA-core micelles, in n-alkanes with or without requiring cosolvent depending on comonomer ratios. Dynamic light scattering studies indicated monodisperse or near-monodisperse micelles in both cases. The intensity-average radii of the PDPA-core and the PMEMA-core micelles were between 10 nm and 17 nm (polydispersity index, μ₂/Γ² < 0.08) and between 10 nm and 13 nm in n-hexane (μ₂/Γ² < 0.09), respectively.     

Nanomaterial interfaces designed with different biorecognition elements for biosensing of key foodborne pathogens

Foodborne diseases caused by pathogen bacteria are a serious problem toward the safety of human life in a worldwide. Conventional methods for pathogen bacteria detection have several handicaps, including trained personnel requirement, low sensitivity, laborious enrichment steps, low selectivity, and long-term experiments. There is a need for precise and rapid identification and detection of foodborne pathogens. Biosensors are a remarkable alternative for the detection of foodborne bacteria compared to conventional methods. In recent years, there are different strategies for the designing of specific and sensitive biosensors. Researchers activated to develop enhanced biosensors with different transducer and recognition elements. Thus, the aim of this study was to provide a topical and detailed review on aptamer, nanofiber, and metal organic framework–based biosensors for the detection of food pathogens. First, the conventional methods, type of biosensors, common transducer, and recognition element were systematically explained. Then, novel signal amplification materials and nanomaterials were introduced. Last, current shortcomings were emphasized, and future alternatives were discussed.