Conical boron nitride nanorods synthesized via the ball-milling and annealing method

A boron nitride (BN) nanostructure, conical BN nanorod, has been synthesized in a large quantity on Si substrates for the first time via the ball-milling and annealing method. Nitridation of milled boron carbide (B₄C) powders was performed in nitrogen gas at 1300°C on the surface of the substrates to form the BN nanorods. The highly crystallized nanorods consist of conical BN basal layers stacked along the nanorod axis. Ball milling of the B₄C powders can significantly enhance the nitridation of the powders and thus facilitate the formation of nanorods during the annealing process.

Effect of substructure characteristics on the dislocation annihilation process during post-deformation annealing

Two distinct substructures were produced in a Ni-30Fe austenitic model alloy by different thermomechanical processing routes. The first substructure largely displayed organized, banded subgrain arrangements with alternating misorientations, resulting from the deformation at a strain just before the initiation of dynamic recrystallization (DRX). By contrast, the second substructure was more random in character and exhibited complex subgrain/cell arrangements characterized by local accumulation of misorientations, formed through DRX. During the post-deformation annealing, the latter substructure revealed a rapid disintegration of dislocation boundaries leading to the formation of dislocation-free grains within a short holding time, though the former largely preserved its characteristics till becoming replaced by growing statically recrystallized grains.

Análise de escalabilidade de uma implementação paralela do simulated annealing acoplado

This paper analyzes the performance of a parallel implementation of Coupled Simulated Annealing (CSA) for the unconstrained optimization of continuous variables problems. Parallel processing is an efficient form of information processing with emphasis on exploration of simultaneous events in the execution of software. It arises primarily due to high computational performance demands, and the difficulty in increasing the speed of a single processing core. Despite multicore processors being easily found nowadays, several algorithms are not yet suitable for running on parallel architectures. The algorithm is characterized by a group of Simulated Annealing (SA) optimizers working together on refining the solution. Each SA optimizer runs on a single thread executed by different processors. In the analysis of parallel performance and scalability, these metrics were investigated: the execution time; the speedup of the algorithm with respect to increasing the number of processors; and the efficient use of processing elements with respect to the increasing size of the treated problem. Furthermore, the quality of the final solution was verified. For the study, this paper proposes a parallel version of CSA and its equivalent serial version. Both algorithms were analysed on 14 benchmark functions. For each of these functions, the CSA is evaluated using 2-24 optimizers. The results obtained are shown and discussed observing the analysis of the metrics. The conclusions of the paper characterize the CSA as a good parallel algorithm, both in the quality of the solutions and the parallel scalability and parallel efficiency

Annealing effects on optical properties of natural alexandrite

Natural alexandrite (BeAl2O4:Cr3+) crystals are investigated as regards the effects of annealing on their optical properties. Optical absorption spectra are measured from the ultraviolet (190 nm) to the near infrared (900 nm), for a sample subjected to consecutive annealing processes, where time and temperature are varied. Besides this, luminescence spectra are simultaneously obtained for this sample, excited with a Kr+ laser source, tuned on an ultraviolet multi-line mode (337.5, 350.7 and 356.4 nm). We observe from absorption as well as from emission data that annealing mainly influences the distribution of Cr3+ and Fe3+ ions, located on sites of a mirror plane (C-s symmetry), which are responsible for the optical properties of alexandrite. The results obtained lead to the conclusion that annealing induces a modification of the population of Cr3+ on C-s sites as well as on sites located on an inversion plane (C-i). Annealing could improve the optical properties of this material, as regards its application as a tunable laser.

Self-optimization of dense wireless sensor networks based on simulated annealing

Wireless sensor network (WSN) Is a technology that can be used to monitor and actuate on environments in a non-intrusive way. The main difference from WSN and traditional sensor networks is the low dependability of WSN nodes. In this way, WSN solutions are based on a huge number of cheap tiny nodes that can present faults in hardware, software and wireless communication. The deployment of hundreds of nodes can overcome the low dependability of individual nodes, however this strategy introduces a lot of challenges regarding network management, real-time requirements and self-optimization. In this paper we present a simulated annealing approach that self-optimize large scale WSN. Simulation results indicate that our approach can achieve self-optimization characteristics in a dynamic WSN. © 2012 IEEE.

Extrapolation of zircon fission-track annealing models

One of the purposes of this study is to give further constraints on the temperature range of the zircon partial annealing zone over a geological time scale using data from borehole zircon samples, which have experienced stable temperatures for ∼1 Ma. In this way, the extrapolation problem is explicitly addressed by fitting the zircon annealing models with geological timescale data. Several empirical model formulations have been proposed to perform these calibrations and have been compared in this work. The basic form proposed for annealing models is the Arrhenius-type model. There are other annealing models, that are based on the same general formulation. These empirical model equations have been preferred due to the great number of phenomena from track formation to chemical etching that are not well understood. However, there are two other models, which try to establish a direct correlation between their parameters and the related phenomena. To compare the response of the different annealing models, thermal indexes, such as closure temperature, total annealing temperature and the partial annealing zone, have been calculated and compared with field evidence. After comparing the different models, it was concluded that the fanning curvilinear models yield the best agreement between predicted index temperatures and field evidence. © 2012 Elsevier Ltd. All rights reserved.

Estudo do annealing de traços de fissão em epídoto

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Obtenção de um ataque químico padrão, zona de annealing parcial e temperatura de fechamento para o epídoto através do método dos traços de fissão

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A self-learning simulated annealing algorithm for global optimizations of electromagnetic devices

A self-learning simulated annealing algorithm is developed by combining the characteristics of simulated annealing and domain elimination methods. The algorithm is validated by using a standard mathematical function and by optimizing the end region of a practical power transformer. The numerical results show that the CPU time required by the proposed method is about one third of that using conventional simulated annealing algorithm.

Cr+3 distribution in Al1 and Al2 Sites of alexandrite (BeAl2O4: Cr3+) induced by annealing, investigated by optical spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

The migration of Mn2+ ions in Cd1-xMnxS nanocrystals: Thermal annealing control

This work reports evidence of the induced migration of Mn2+ ions in Cd(1-x)MnxS nanocrystals (NCs) by selecting a specific thermal treatment for each sample. The growth and characterization of these magnetic dots were investigated by atomic force microscopy (AFM), optical absorption (OA), and electronic paramagnetic resonance (EPR) techniques. The comparison of experimental and simulated EPR spectra confirms the incorporation of Mn2+ ions both in the core and at the dot surface regions. The thermal treatment of a magnetic sample, via selected annealing temperature and/or time, affects the fine and hyperfine interaction constants which modify the shape and the intensity of the EPR transition spectrum. The identification of these changes has allowed tracing the magnetic ion migration from core to surface regions of a dot as well as inferring the local density of the magnetic impurity ions. (C) 2011 Elsevier Ltd. All rights reserved.

Detecting and resolving position-dependent temperature effects in real-time quantitative polymerase chain reaction

Real-time quantitative polymerase chain reaction (qPCR) depends on precise temperature control of the sample during cycling. In the current study, we investigated how temperature variation in plate-based qPCR instruments influences qPCR results. Temperature variation was measured by amplicon melting analysis as a convenient means to assess well-to-well differences. Multiple technical replicates of several SYBR Green I-based qPCR assays allowed correlation of relative well temperature to quantification cycle. We found that inadequate template denaturation results in an inverse correlation and requires increasing the denaturation temperature, adding a DNA destabilizing agent, or pretreating with a restriction enzyme. In contrast, inadequate primer annealing results in a direct correlation and requires lowering the annealing temperature. Significant correlations were found in 18 of 25 assays. The critical nature of temperature-dependent effects was shown in a blinded study of 29 patients for the diagnosis of Prader-Willy and Angelman syndromes, where eight diagnoses were incorrect unless temperature-dependent effects were controlled. A method to detect temperature-dependent effects by pairwise comparisons of replicates in routine experiments is presented and applied. Systematic temperature errors in qPCR instruments can be recognized and their effects eliminated when high precision is required in quantitative genetic diagnostics and critical complementary DNA analyses.

Enhanced iron gettering by short, optimized low-temperature annealing after phosphorus emitter diffusion for industrial silicon solar cell processing

The introduction of a low-temperature (LT) tail after P emitter diffusion was shown to lead to considerable improvements in electron lifetime and solar cell performance by different researchers. So far, the drawback of the investigated extended gettering treatments has been the lack of knowledge about optimum annealing times and temperatures and the important increase in processing time. In this manuscript, we calculate optimum annealing temperatures of Fe-contaminated Si wafers for different annealing durations. Subsequently, it is shown theoretically and experimentally that a relatively short LT tail of 15 min can lead to a significant reduction of interstitial Fe and an increase in electron lifetime. Finally, we calculate the potential improvement of solar cell efficiency when such a short-tail extended P diffusion gettering is included in an industrial fabrication process.

Energy-based de novo protein folding by conformational space annealing and an off-lattice united-residue force field: Application to the 10-55 fragment of staphylococcal protein A and to apo calbindin D9K

The conformational space annealing (CSA) method for global optimization has been applied to the 10-55 fragment of the B-domain of staphylococcal protein A (protein A) and to a 75-residue protein, apo calbindin D9K (PDB ID code 1CLB), by using the UNRES off-lattice united-residue force field. Although the potential was not calibrated with these two proteins, the native-like structures were found among the low-energy conformations, without the use of threading or secondary-structure predictions. This is because the CSA method can find many distinct families of low-energy conformations. Starting from random conformations, the CSA method found that there are two families of low-energy conformations for each of the two proteins, the native-like fold and its mirror image. The CSA method converged to the same low-energy folds in all cases studied, as opposed to other optimization methods. It appears that the CSA method with the UNRES force field, which is based on the thermodynamic hypothesis, can be used in prediction of protein structures in real time.