Development of ductile green flame retardant poly(lactic acid) composites using hydromagnesite&huntite and bio-based plasticizer

Turning brittle poly(lactic acid) (PLA) to ductile form via plasticizer inclusion is an effective option in the case of processing with high amounts of additives. Additionally, the integration of natural flame retardants to PLA involving bio-based plasticizer enables to use of environmentally friendly composites in conditions where fire resistance performance is required. In the current study, ductile green fire retardant PLA composites were manufactured using hydromagnesite&huntite (HH) as a natural fire retardant additive and acetyl tributyl citrate as a bio-based plasticizer. The influences of plasticizer and HH contents on the fire retardant, thermal and mechanical performances of the composites were explored. According to test results, the limiting oxygen index (LOI) value of PLA reduced from 29.2 to 28.0 and the UL-94 V rating changed from V2 to BC with the addition of 20 wt% plasticizer owing to the reduction in melt viscosity. The peak heat release rate (pHRR) and average heat release rate (avHRR) values increased steadily as the concentration of plasticizer increased due to the formation of a more porous residue structure stemming from the increased transportation rate of gases. In order to produce ductile flame retardant material, the plasticizer content was required to 20 wt% of HH. The highest LOI value (36.2) and UL-94 rating of V0 were achieved with the inclusion of 70 wt% HH in the presence of 20 wt% plasticizer. Improvement in impact resistance and reduction in tensile strength were observed as the added amount of plasticizer increased.     

Cellular neural network with trapezoidal activation function

This paper presents a cellular neural network (CNN) scheme employing a new non‐linear activation function, called trapezoidal activation function (TAF). The new CNN structure can classify linearly non‐separable data points and realize Boolean operations (including eXclusive OR) by using only a single‐layer CNN. In order to simplify the stability analysis, a feedback matrix W is defined as a function of the feedback template A and 2D equations are converted to 1D equations. The stability conditions of CNN with TAF are investigated and a sufficient condition for the existence of a unique equilibrium and global asymptotic stability is derived. By processing several examples of synthetic images, the analytically derived stability condition is also confirmed. Copyright © 2005 John Wiley & Sons, Ltd.     

Wear behavior of as-deposited and oxidized ternary (Zr,Hf)N coatings

In the present study, the tribological performance of ternary (Zr,Hf)N coatings, whose Hf content was varied between 0 and 21 wt pct, has been systematically examined in the as-deposited and oxidized conditions. Coatings were applied on AISI D2 tool steel plates by arc physical vapor deposition (PVD). Oxidation was conducted at 400 °C for times up to 12 hours in air. Wear tests revealed pronounced improvement in the wear resistance with increasing Hf content in the as-deposited coatings. Oxidation for 12 hours yielded more than a fourfold increase in wear resistance. The beneficial effect of Hf on wear resistance decreased upon oxidation.     

A comparative study on structural,morphological and photocatalytic properties of anodically grown ZnO nanowires under varying parameters

Journal of Materials Science: Materials in Electronics - In this study, zinc oxide (ZnO) nanowires (NWs) were successfully produced on Zn plates through electrochemical anodization in potassium...     

Science and technology in the region: The output of regional science and technology, its strengths and its leading institutions

Summary We operationalize scientific output in a region by means of the number of articles (as in the SciSearch database) per year and technology output by means of the number of patent applications (as in the database of the European Patent Office) per priority year. All informetric analyses were done using the DIALOG online-system. The main research questions are the following: Which scientific and technological fields or topics are most influent within a region and which institutions or companies are mainly publishing articles or holding patents? Do the distributions of regional science and technology fields and of publishing institutions follow the well-known informetric function? Are there - as it is expected - only few fields and few institutions which dominate the region? Is there a connection between the economic power of a region and the regional publication and patent output? Examples studied in detail are seven German regions: Aachen, Düsseldorf, Hamburg, Köln (Cologne), Leipzig - Halle - Dessau, München (Munich), and Stuttgart. Three different indicators were used, science and technology attraction of a region (number of scientific articles and patents), science and technology intensity (articles and patents per 1,000 inhabitants), and science and technology density (articles and patents per 1 billion EURO gross value added). Top region concerning both attraction and intensity is Munich, concerning density it is Aachen.     

Dynamic modeling and fuzzy logic control of vibrations of a railway vehicle for different track irregularities

Safe and comfortable transportation of passengers and goods on railways can be achieved by solving the vibration problem. In this study, the dynamic modeling of the full railway vehicle is used to perform vibration analysis in order to observe displacements and accelerations. The full railway vehicle model consists of 54 degrees of freedom which are defined by differential equations. Additionally, wheel–rail contact problem (i.e. creepage factors and hertzian spring stiffness of rails) is analyzed by finite element method. Dynamic modeling and vibration analysis are carried out using Matlab–Simulink software. Using the developed model, the car body vibrations, caused by a lateral and two vertical sinusoidal track irregularities, are controlled by fuzzy logic controllers placed between the car body and bogies. The fuzzy logic algorithm herein is used for realizing the active control of car body vibrations. The simulations of vibration analysis are obtained in time and frequency domains and compared with passive controlled status. The robustness of the designed controller is verified by simulations, carried out for the cases of car body mass variations. The results show the effectiveness of the proposed algorithm.     

Effect of cathodic arc plasma treatment on the properties of WC–Co based hard metals

In this study, ion bombardment in a cathodic arc physical vapor deposition system was applied on WC–Co hard metal surfaces aiming to benefit from the diffusion acceleration effect, and to investigate the role of this effect on the surface composition, morphology and corrosion resistance of the materials. Chromium ions obtained via cathodic arc evaporation were accelerated under low (− 150 V) and high (− 1000 V) bias voltages in order to apply coating–bombardment cycles to sample surfaces. Substrate temperatures were measured by an optical pyrometer during the processes. The treated samples were characterized by scanning electron microscopy (SEM) and X-ray diffractometry (XRD). Temperature measurements showed that the sample temperature could be controlled precisely by adjusting the bias voltage. Temperatures in the range of 750–1200 °C were measured during the treatment depending on the duration of the high bias voltage cycles. XRD analysis showed η phase formation in the near surface regions of all treated samples. The amount of the formed η phase was shown to be dependent on the heating–cooling regime that varied with the applied mode of bias. The corrosion behavior of the samples was investigated by immersing treated and untreated samples in a solution of 5% H₃PO₄ containing 1 g/l Zn^{+ 2} for 24 h at 50 °C. The samples were investigated via SEM observations after immersion. Cathodic arc plasma treated samples showed a better resistance to corrosion in this environment.     

Various approaches for constructing an ensemble of metamodels using local measures

Metamodels are approximate mathematical models used as surrogates for computationally expensive simulations. Since metamodels are widely used in design space exploration and optimization, there is growing interest in developing techniques to enhance their accuracy. It has been shown that the accuracy of metamodel predictions can be increased by combining individual metamodels in the form of an ensemble. Several efforts were focused on determining the contribution (or weight factor) of a metamodel in the ensemble using global error measures. In addition, prediction variance is also used as a local error measure to determine the weight factors. This paper investigates the efficiency of using local error measures, and also presents the use of the pointwise cross validation error as a local error measure as an alternative to using prediction variance. The effectiveness of ensemble models are tested on several problems with varying dimensionality: five mathematical benchmark problems, two structural mechanics problems and an automobile crash problem. It is found that the spatial ensemble models show better performances than the global ensemble for the low-dimensional problems, while the global ensemble is a more accurate model than the spatial ensembles for the high-dimensional problems. Ensembles based on pointwise cross validation error and prediction variance provide similar accuracy. The ensemble models based on local measures reduce cross validation errors drastically, but their performances are not that impressive in reducing the error evaluated at random test points, because the pointwise cross validation error is not a good surrogate for the error at a point.