Influence of the Polyvinyl Pyrrolidone Concentration on Particle Size and Dispersion of ZnS Nanoparticles Synthesized by Microwave Irradiation

Zinc sulfide semiconductor nanoparticles were synthesized in an aqueous solution of polyvinyl pyrrolidone via a simple microwave irradiation method. The effect of the polymer concentration and the type of sulfur source on the particle size and dispersion of the final ZnS nanoparticle product was carefully examined. Microwave heating generally occurs by two main mechanisms: dipolar polarization of water and ionic conduction of precursors. The introduction of the polymer affects the heating rate by restriction of the rotational motion of dipole molecules and immobilization of ions. Consequently, our results show that the presence of the polymer strongly affects the nucleation and growth rates of the ZnS nanoparticles and therefore determines the average particle size and the dispersion. Moreover, we found that PVP adsorbed on the surface of the ZnS nanoparticles by interaction of the C–N and C=O with the nanoparticle’s surface, thereby affording protection from agglomeration by steric hindrance. Generally, with increasing PVP concentration, mono-dispersed colloidal solutions were obtained and at the optimal PVP concentration (5%), sufficiently small size and narrow size distributions were obtained from both sodium sulfide and thioacetamide sulfur sources. Finally, the sulfur source directly influences the reaction mechanism and the final particle morphology, as well as the average size.     

Effects of Welding and rotational speeds on the Microstructure and Hardness of Friction Stir Welded Single-Phase Brass

This study focuses on the effects of rotational and welding speeds on the microstructure and hardness of joints in friction stir welded single-phase brass. Welds were achieved under low heat input conditions at rotational and welding speeds of 400-800 r/min and 100-300 mm/min, respectively. In order to characterize the obtained welds, optical microscopy and Vickers hardness measurements were taken on the weld cross sections. According to the obtained results, increasing the welding speed and/or decreasing the rotational speed caused the grain size of the stir zone to decrease and, hence, improved the average hardness of this region. These results are discussed with respect to the interplay between the welding parameters and the peak temperature in the weld thermal cycle.     

Synthesis,characterization and TL properties of SrSO_4:Dy,Tb nanocrystalline phosphor

SrSO4:Dy,Tb nanocrystalline with crystalline size in the range of 44–54 nm was prepared by co-precipitation method followed by thermal treatment and characterized by X-ray diffraction(XRD), scanning electron microscopy(SEM), energy dispersive X-ray spectroscopy(EDX) and UV-visible spectrometry. Our results provided direct evidence of incorporation of impurities into nanocrystalline SrSO4. The thermoluminescence(TL) properties of SrSO4:Dy,Tb nanocrystalline pellets irradiated with gamma rays at different doses were studied. The TL glow curve of SrSO4:Dy,Tb nanocrystalline pellets had a prominent peak at around 490 K and a small peak at around 430 K. The major peak in the TL glow curve was almost resolved from other peaks, which was analyzed using Chen's peak shape method to determine the TL kinetic parameters such as activation energy, E and kinetic order, b. The intensity of main dosimetric peak of SrSO4:Dy,Tb nanocrystalline pellets at around 490 K increased linearly with the increase in gamma dose. The TL response was linear in the range of 0.1–7 kGy. These properties made it a candidate as a dosimeter to be used for estimating the high dose of gamma rays.     

An artificial neural-network model for impact properties in X70 pipeline steels

An artificial neural-network (ANN) model has been developed for the analysis and simulation of the correlation between the mechanical properties and composition and thermomechanical treatment parameters of high strength, low alloy steels. The input parameters of the model consist of alloy compositions (C, Si, Mn, P, S, Cu, Ni, Cr, Mo, Ti, V, Nb, Ca, Al, B) and tensile test results (yield strength, ultimate tensile strength, percentage elongation). The outputs of the ANN model include impact energy (?10 °C). The model can be used to calculate the properties of low alloy steels as a function of alloy composition and thermomechanical treatment variables. The current study achieved a good performance of the ANN model, and the results are in agreement with experimental knowledge.     

Comparability Analyses of the <Emphasis Type="Italic">SPI</Emphasis> and <Emphasis Type="Italic">RDI</Emphasis> Meteorological Drought Indices in Different Climatic Zones

Comparability analyses are performed to investigate similarities/differences of the standard precipitation index (SPI) and the reconnaissance drought index (RDI), respectively, utilizing precipitation and ratio of precipitation over potential evapotranspiration (ET ₀). Data are from stations with different climatic conditions in Iran. Drought characteristics of the 3-month, 6-month and annual SPI and RDI time series are developed and Markov chain order dependencies are investigated by the Log-likelihood, AIC and BIC tests. Steady state probabilities and Markov chain characteristics, i.e., expected residence time in different drought classes and time to reach “Near Normal” class are investigated. According to results, both indices exhibit an overall similar behaviour; particularly, they follow the first order Markov chain dependency. However, climatic variability may produce some differences. In several cases, the “Extremely Dry” class has received a more critical value by RDI. Furthermore, the expected residence time of “Near Normal” class and expected time to reach “Near Normal” class are quite different in a number of cases. The results show that the RDI by utilizing the ET ₀ can be very sensitive to climatic variability. This is rather important, since if the drought analyses are for agricultural applications, utilization of the RDI would seem to serve a better purpose.     

New analytical method for solving Burgers' and nonlinear heat transfer equations and comparison with HAM

In this study, we present a numerical comparison between the differential transform method (DTM) and the homotopy analysis method (HAM) for solving Burgers' and nonlinear heat transfer problems. The first differential equation is the Burgers' equation serves as a useful model for many interesting problems in applied mathematics. The second one is the modeling equation of a straight fin with a temperature dependent thermal conductivity. In order to show the effectiveness of the DTM, the results obtained from the DTM is compared with available solutions obtained using the HAM [M.M. Rashidi, G. Domairry, S. Dinarvand, Commun. Nonlinear Sci. Numer. Simul. 14 (2009) 708-717; G. Domairry, M. Fazeli, Commun. Nonlinear Sci. Numer. Simul. 14 (2009) 489-499] and whit exact solutions. The method can easily be applied to many linear and nonlinear problems. It illustrates the validity and the great potential of the differential transform method in solving nonlinear partial differential equations. The obtained results reveal that the technique introduced here is very effective and convenient for solving nonlinear partial differential equations and nonlinear ordinary differential equations that we are found to be in good agreement with the exact solutions.     

Effect of in-service strengthening on the axial load carrying capacity of steel box columns

To avoid any interruption of service and considering economic issues, strengthening of existing columns usually occurs while the member is under service loads. One of the important issues being neglected in the redesign process of retrofitted columns is the effects of significant axial load existing in the columns. This paper presents a numerical study to investigate the behavior and the ultimate bearing capacity of box shaped steel columns reinforced with continuous welded plates while under load. In the first phase of the study, it is intended to evaluate the variation of results with respect to the existing design relations. For this purpose, the ultimate bearing capacity of un-preloaded models is assumed to be in accordance with the selected design code and the corresponding geometric imperfection for each model is defined using several analyses to reach the values obtained with the design code, for further studies. In the second phase, the magnitude of initial imperfection is set to 1/500 of the studied columns. In both phases, the effect of magnitude of existing preload on ultimate bearing capacity is investigated considering two influential parameters, namely the slenderness ratio of the column and the ratio between cross sectional area of the column and reinforcing plates. Results show that by increasing the preload magnitude, the ultimate bearing capacity of reinforced columns with identical reinforcing plates, decreases. This reduction is more notable for the columns with median slenderness ratios. However, as the magnitude of preload increases, the effect of slenderness ratio on the reduction of ultimate bearing capacity becomes more evident. Also, it is found that by using a fixed imperfection ratio of L/500, even for un-preloaded models the ultimate bearing capacity of the strengthened column will be less than the values calculated as per the selected design code. Finally, an empirical relation is proposed to calculate reduction of ultimate bearing capacity for columns affected from various preload level considering different slenderness ratios.     

Distributed multi-target tracking using joint probabilistic data association and average consensus filter

In this paper, a distributed multi-target tracking (MTT) algorithm suitable for implementation in wireless sensor networks is proposed. For this purpose, the Monte Carlo (MC) implementation of joint probabilistic data-association filter (JPDAF) is applied to the well-known problem of multi-target tracking in a cluttered area. Also, to make the tracking algorithm scalable and usable for sensor networks of many nodes, the distributed expectation maximization algorithm is exploited via the average consensus filter, in order to diffuse the nodes’ information over the whole network. The proposed tracking system is robust and capable of modeling any state space with nonlinear and non-Gaussian models for target dynamics and measurement likelihood, since it uses the particle-filtering methods to extract samples from the desired distributions. To encounter the data-association problem that arises due to the unlabeled measurements in the presence of clutter, the well-known JPDAF algorithm is used. Furthermore, some simplifications and modifications are made to MC–JPDAF algorithm in order to reduce the computation complexity of the tracking system and make it suitable for low-energy sensor networks. Finally, the simulations of tracking tasks for a sample network are given.     

Encapsulation and delivery of protein from within poly(sulfobetaine) hydrogel beads

Advancement of therapeutic protein therapies can be hindered by their poor stability and short in vivo half-life. There is emerging evidence that biocompatible zwitterionic materials can prevent nonspecific interactions within proteins systems that contribute to protein instability. Here, zwitterionic hydrogel beads are synthesized from poly(sulfobetaine methyl methacrylate), pSB, using an inverse emulsion, free radical polymerization reaction technique. The transport properties within the zwitterionic hydrogels were characterized using ¹H NMR diffusometry. Equilibrium water content as high as 0.90 was measured for the synthesized hydrogels. Our study revealed that the pSB hydrogels are nontoxic, ion responsive, and their swelling is temperature dependent. The zwitterionic hydrogel beads were capable of undergoing lyophilization without aggregation. Hydrogel beads were loaded with a model protein, bovine serum albumin (BSA), using a postfabrication loading technique. The protein loading was studied using confocal laser microscopy, indicating homogenous protein dispersion of up to 40 μg BSA/mg hydrogel within the beads. Furthermore, the release rate of the protein from the synthesized hydrogel was studied at different crosslinker to monomer ratios. The protein encapsulated within the zwitterionic hydrogel had slower rates of thermal aggregation compared to nonencapsulated protein in solution. Furthermore, the protein-loaded inside the zwitterionic hydrogel better maintained its bioactivity.