Determination of favorable inter-particle interactions for formation of substitutionally ordered solid phases from a binary mixture of oppositely charged colloidal suspensions

The solid phase formed by a binary mixture of oppositely charged colloidal particles can be either substitutionally ordered or substitutionally disordered depending on the nature and strength of interactions among the particles. In this work, we use Monte Carlo molecular simulations along with the Gibbs-Duhem integration technique to map out the favorable inter-particle interactions for the formation of substitutionally ordered crystalline phases from a fluid phase. The inter-particle interactions are modeled using the hard core Yukawa potential but the method can be easily extended to other systems of interest. The study obtains a map of interactions depicting regions indicating the type of the crystalline aggregate that forms upon phase transition.

A peer-peer particle swarm optimizer

Particle Swarm Optimization is a parallel algorithm that spawns particles across a search space searching for an optimized solution. Though inherently parallel, they have distinct synchronizations points which stumbles attempts to create completely distributed versions of it. In this paper, we attempt to create a completely distributed peer-peer particle swarm optimization in a cluster of heterogeneous nodes. Since, the original algorithm requires explicit synchronization points we modified the algorithm in multiple ways to support a peer-peer system of nodes. We also modify certain aspect of the basic PSO algorithm and show how certain numerical problems can take advantage of the same thereby yielding fast convergence.

Feature weighting for clustering by particle swarm optimization

Clustering has been the most popular method for data exploration. Clustering is partitioning the data set into sub-partitions based on some measures say the distance measure, each partition has its own significant information. There are a number of algorithms explored for this purpose, one such algorithm is the Particle Swarm Optimization(PSO) which is a population based heuristic search technique derived from swarm intelligence. In this paper we present an improved version of the Particle Swarm Optimization where, each feature of the data set is given significance accordingly by adding some random weights, which also minimizes the distortions in the dataset if any. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The experimental results shows that our proposed methodology performs significantly better than the previously performed experiments.

Multiobjective discrete particle swarm optimization for multisensor image alignment

A new technique is proposed for multisensor image registration by matching the features using discrete particle swarm optimization (DPSO). The feature points are first extracted from the reference and sensed image using improved Harris corner detector available in the literature. From the extracted corner points, DPSO finds the three corresponding points in the sensed and reference images using multiobjective optimization of distance and angle conditions through objective switching technique. By this, the global best matched points are obtained which are used to evaluate the affine transformation for the sensed image. The performance of the image registration is evaluated and concluded that the proposed approach is efficient.

Modified particle swarm optimization for pattern clustering

Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning and data mining. Clustering is grouping of a data set or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait according to some defined distance measure. In this paper we present the genetically improved version of particle swarm optimization algorithm which is a population based heuristic search technique derived from the analysis of the particle swarm intelligence and the concepts of genetic algorithms (GA). The algorithm combines the concepts of PSO such as velocity and position update rules together with the concepts of GA such as selection, crossover and mutation. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The performance of our method is better than k-means and PSO algorithm.

Simultaneous feature selection and clustering using particle swarm optimization

Data clustering groups data so that data which are similar to each other are in the same group and data which are dissimilar to each other are in different groups. Since generally clustering is a subjective activity, it is possible to get different clusterings of the same data depending on the need. This paper attempts to find the best clustering of the data by first carrying out feature selection and using only the selected features, for clustering. A PSO (Particle Swarm Optimization)has been used for clustering but feature selection has also been carried out simultaneously. The performance of the above proposed algorithm is evaluated on some benchmark data sets. The experimental results shows the proposed methodology outperforms the previous approaches such as basic PSO and Kmeans for the clustering problem.

Cooperative Particle Swarm Optimization Based Receiver for Large-Dimension MIMO-ZPSC Systems

In this paper, we propose a cooperative particle swarm optimization (CPSO) based channel estimation/equalization scheme for multiple-input multiple-output zero-padded single-carrier (MIMO-ZPSC) systems with large dimensions in frequency selective channels. We estimate the channel state information at the receiver in time domain using a PSO based algorithm during training phase. Using the estimated channel, we perform information symbol detection in the frequency domain using FFT based processing. For this detection, we use a low complexity OLA (OverLap Add) likelihood ascent search equalizer which uses minimum mean square (MMSE) equalizer solution as the initial solution. Multiple iterations between channel estimation and data detection are carried out which significantly improves the mean square error and bit error rate performance of the receiver.

Particle size, morphology and color tunable ZnO:Eu3+ nanophosphors via plant latex mediated green combustion synthesis

Efficient ZnO:Eu3+ (1-11 mol%) nanophosphors were prepared for the first time by green synthesis route using Euphorbia tirucalli plant latex. The final products were well characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), etc. The average particle size of ZnO:Eu3+ (7 mol%) was found to be in the range 27-47 nm. With increase of plant latex, the particle size was reduced and porous structure was converted to spherical shaped particles. Photoluminescence (PL) spectra indicated that the peaks situated at similar to 590, 615, 648 and 702 nm were attributed to the D-5(0) -> F-7(j(j=1,2,3,4)) transitions of Eu3+ ions. The highest PL intensity was recorded for 7 mol% with Eu3+ ions and 26 ml plant latex concentration. The PL intensity increases with increase of plant latex concentration up to 30 ml and there after it decreases. The phosphor prepared by this method show spherical shaped particles, excellent chromaticity co-ordinates in the white light region which was highly useful for WLED's. Further, present method was reliable, environmentally friendly and alternative to economical routes. (c) 2013 Elsevier B.V. All rights reserved.

Recrystallization and Ag3Sn Particle Redistribution During Thermomechanical Treatment of Bulk Sn-Ag-Cu Solder Alloys

Sn-Ag-Cu (SAC) solders are susceptible to appreciable microstructural coarsening during storage or service. This results in evolution of joint properties over time and thereby influences the long-term reliability of microelectronic packages. Accurate reliability prediction of SAC solders requires prediction of microstructural evolution during service. Microstructure evolution in two SAC solder alloys, such as, Sn-3.0Ag-0.5Cu (SAC 305) and Sn-1.0Ag-0.5 Cu (SAC 105), under different thermomechanical excursions, including isothermal aging at 150 degrees C and thermomechanical cycling (TMC) was studied. In general, between 200 and 600 cycles during TMC, recrystallization of the Sn matrix was observed, along with redistribution of Ag3Sn particles because of dissolution and reprecipitation. These latter effects have not been reported before. It was also observed that the Sn grains recrystallized near precipitate clusters in eutectic channels during extended isothermal aging. The relative orientation of Sn grains in proeutectic colonies did not change during isothermal aging.

Large deviation function and fluctuation theorem for classical particle transport

We analytically evaluate the large deviation function in a simple model of classical particle transfer between two reservoirs. We illustrate how the asymptotic long-time regime is reached starting from a special propagating initial condition. We show that the steady-state fluctuation theorem holds provided that the distribution of the particle number decays faster than an exponential, implying analyticity of the generating function and a discrete spectrum for its evolution operator.

Effect of nanoscale boron carbide particle addition on the microstructural evolution and mechanical response of pure magnesium

In this study, the effect of nano-B4C addition on the microstructural and the mechanical behavior of pure Mg are investigated. Pure Mg-metal reinforced with different amounts of nano-size B4C particulates were synthesized using the disintegrated melt deposition technique followed by hot extrusion. Microstructural characterization of the developed Mg/x-B4C composites revealed uniform distribution of nano-B4C particulates and significant grain refinement. Electron back scattered diffraction (EBSD) analyses showed presence of relatively more recrystallized grains and absence of fiber texture in Mg/B4C nanocomposites when compared to pure Mg. The evaluation of mechanical properties indicated a significant improvement in tensile properties of the composites. The significant improvement in tensile ductility (similar to 180% increase with respect to pure Mg) is among the highest observed when compared to the pure Mg based nanocomposites existing in the current literature. The superior mechanical properties of the Mg/B4C nanocomposites are attributed to the uniform distribution of the nanoparticles and the tendency for texture randomization (absence of fiber texture) achieved due to the nano-B4C addition. (C) 2013 Elsevier Ltd. All rights reserved.

Adsorption study of silica gel particle for improvement in design of adsorption beds used in solar driven cooling units

Simulations using Ansys Fluent 6.3.26 have been performed to look into the adsorption characteristics of a single silica gel particle exposed to saturated humid air streams at Re=108 & 216 and temperature of 300K. The adsorption of the particle has been modeled as a source term in the species and the energy equations using a Linear Driving Force (LDF) equation. The interdependence of the thermal and the water vapor concentration field has been analysed. This work is intended to aid in understanding the adsorption effects in silica gel beds and in their efficient design. (C) 2013 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Photoluminescence, thermoluminescence and EPR studies of solvothermally derived Ni2+ doped Y(OH)(3) and Y2O3 multi-particle-chain microrods

Rod like structures of hexagonal Y(OH)(3):Ni2+ and cubic Y2O3:Ni2+ phosphors have been successfully synthesized by solvothermal method. X-ray diffraction studies of as-formed product shows hexagonal phase, whereas the product heat treated at 700 degrees C shows pure cubic phase. Scanning electron micrographs (SEM) of Y(OH)(3):Ni2+ show hexagonal rods while Y2O3:Ni2+ rods were found to consist of many nanoparticles stacked together forming multi-particle-chains. EPR studies suggest that the site symmetry around Ni2+ ions is predominantly octahedral. PL spectra show emission in blue, green and red regions due to the T-3(1)(P-3)->(3)A(2)(F-3), T-1(2)(D-1)->(3)A(2)(F-3) and T-1(2)(D-1)-> T-3(2)(F-3) transitions of Ni2+ ions, respectively. TL studies were carried out for Y(OH)(3):Ni2+ and Y2O3:Ni2+ phosphor upon gamma-dose for 1-6 kGy. A single well resolved glow peaks at 195 and 230 degrees C were recorded for Y(OH)(3):Ni2+ and Y2O3:Ni2+, respectively. The glow peak intensity increases linearly up to 4 kGy and 5 kGy for Y(OH)(3):Ni2+ and Y2O3:Ni2+, respectively. The kinetic parameters such as activation energy (E), frequency factor (s) and order of kinetics (b) were estimated by different methods. The phosphor follows simple glow peak structure, linear response with gamma dose, low fading and simple trap distribution, suggesting that it is quite suitable for radiation dosimetry. (C) 2014 Elsevier B.V. All rights reserved.

Nano-ZnO particle addition to monolithic magnesium for enhanced tensile and compressive response

In this study, the effects of nanoscale ZnO reinforcement on the room temperature tensile and compressive response of monolithic Mg were studied. Experimental observations indicated strength properties improvement due to nanoscale ZnO addition. A maximum increment in tensile yield strength by similar to 55% and compressive yield strength by 90% (with reduced tension-compression asymmetry) was achieved when 0.8 vol.% ZnO nanoparticles were added to Mg. While the fracture strain values under tensile loads were found to increase significantly (by similar to 95%, in case of Mg-0.48ZnO), it remained largely unaffected under compressive loads. The microstructural characteristics studied in order to comprehend the mechanical response showed significant grain refinement due to grain boundary pinning effect of nano-ZnO particles which resulted in strengthening of Mg. Texture analysis using X-ray and EBSD methods indicated weakening of basal fibre texture in Mg/ZnO nanocomposites which contributed towards the reduction in tension-compression yield asymmetry and enhancement in tensile ductility when compared to pure Mg. (C) 2014 Elsevier B.V. All rights reserved.