Enhanced photoluminescence of Gd2O3:Eu3+ nanophosphors with alkali (M = Li+, Na+, K+) metal ion co-doping

Gd1.95Eu0.4M0.01O3 (M = Li+ Na+ K+) nanophosphors have been synthesized by a low temperature solution combustion (LSC) method. Powder X-ray diffraction pattern (PXRD), scanning electron microscopy (SEM), UV-vis and photoluminescence (PL) measurements were carried out to characterize their structural and luminescent properties. The excitation and emission spectra indicated that the phosphor could be well excited by UV light (243 nm) and emit red light about 612 nm. The effect of alkali co-dopant on PL properties has been examined. The results showed that incorporation of Li+, Na+ and K+ in to Gd2O3:Eu3+ phosphor would lead to a remarkable increase of photoluminescence. The PL intensity of Gd2O3:Eu3+ phosphor was improved evidently by co-doping with Li+ ions whose radius is less than that of Gd3+ and hardly with Na+, K+ whose radius is larger than that of Gd3+. The effect of co-dopants on enhanced luminescence was mainly regarded as the result of a suitable local distortion of crystal field surrounding the Eu3+ activator. These results will play an important role in seeking some more effective co-dopants. (C) 2011 Published by Elsevier B.V.

High Rate Capability Lithium Iron Phosphate Wired by Carbon Nanotubes and Galvanostatic Transformed to Graphitic Carbon

Lithium iron phosphate (LiFePO4) electronically wired by multi-walled carbon nanotubes (MWCNTs) and in-situ transformed graphitic carbon for lithium-ion batteries are discussed here. Presence of MWCNTs up to a maximum of 0.5% in porous LiFePO4 (abbreviated as LFP-CNT) resulted in remarkable reversible cyclability and rate capability compared to LFP coated with highly disordered carbon (abbreviated as LFP-C). In the current range (30-1500) mAg(-1), specific capacity of LFP-CNT (approximate to 150-50 mAhg(-1)) is observed to be always higher compared to LFP-C (approximate to 120-0 mAhg(-1)). At higher currents of 250-1500 mAg(-1) LFP-C performed poorly compared to LFP-CNT. LFP-C showed considerable decay in capacity with increase in cycle number at intermediate high currents (approximate to 250 mAg(-1)) whereas at very high currents (approximate to 750 mAg(-1)) it is nearly zero. The LFP-CNT showed no such detrimental behavior in battery performance. The exemplary performance of the LFP-CNT is attributed to combination of both enhanced LFP structural stability, as revealed by Raman spectra and formation of an efficient percolative network of carbon nanotubes which during the course of galvanostatic cycling gets gradually transformed to graphitic carbon. (C) 2012 The Electrochemical Society. [DOI: 10.1149/2.015204jes] All rights reserved.

Enhanced Performance of Discharge Plasma in Raw Engine Exhaust Treatment-Operation under Different Temperatures and Loads

This paper reports improved performance of discharge plasma in raw engine exhaust treatment. For the purpose of investigation, both filtered and raw diesel engine exhaust were separately treated by the discharge plasma. In raw exhaust environment, the discharge plasma exhibits a superior performance with regard to NOx removal, energy consumption and formation of by-products. In this study, experiments were conducted at conditions of different temperatures and loads.

Synthesis of free standing carbon nanosheet using electron cyclotron resonance plasma enhanced chemical vapor deposition

Carbon nanosheets (CNSs) have been synthesized by electron cyclotron resonance (ECR) plasma enhanced chemical vapor deposition (PECVD) using a mixture of acetylene and argon gases on copper foil as the substrate. Micrometer-wide carbon sheets consisting of several atomic layers thick graphene sheets have been synthesized by controlled decomposition of carbon radicals in ECR-PECVD. Raman spectroscopy of these films revealed characteristics of a disordered graphitic sheet. Thick folded carbon-sheets and a semi transparent freestanding CNSs have been observed by scanning electron microscopy. This is a promising technique to synthesize free standing CNSs and can be used in the fabrication of nanoelecronic devices in future. (C) 2012 Elsevier B.V. All rights reserved.

Optimal static voltage stability improvement using a numerically stable SLP algorithm, for real time applications

A numerically stable sequential Primal–Dual LP algorithm for the reactive power optimisation (RPO) is presented in this article. The algorithm minimises the voltage stability index C 2 [1] of all the load buses to improve the system static voltage stability. Real time requirements such as numerical stability, identification of the most effective subset of controllers for curtailing the number of controllers and their movement can be handled effectively by the proposed algorithm. The algorithm has a natural characteristic of selecting the most effective subset of controllers (and hence curtailing insignificant controllers) for improving the objective. Comparison with transmission loss minimisation objective indicates that the most effective subset of controllers and their solution identified by the static voltage stability improvement objective is not the same as that of the transmission loss minimisation objective. The proposed algorithm is suitable for real time application for the improvement of the system static voltage stability.

Selection of Static VAR Compensator Location and Size for System Voltage Stability Improvement

This paper presents a methodology for selection of static VAR compensator location based on static voltage stability analysis of power systems. The analysis presented here uses the L-index of load buses, which includes voltage stability information of a normal load flow and is in the range of 0 (no load of system) to 1 (voltage collapse). An approach has been presented to select a suitable size and location of static VAR compensator in an EHV network for system voltage stability improvement. The proposed approach has been tested under simulated conditions on a few power systems and the results for a sample radial network and a 24-node equivalent EHV power network of a practical system are presented for illustration purposes. © 2000 Published by Elsevier Science S.A. All rights reserved.

An ANN based approach for voltage stability assessment

Artificial Neural Networks (ANNs) have recently been proposed as an alterative method for salving certain traditional problems in power systems where conventional techniques have not achieved the desired speed, accuracy or efficiency. This paper presents application of ANN where the aim is to achieve fast voltage stability margin assessment of power network in an energy control centre (ECC), with reduced number of appropriate inputs. L-index has been used for assessing voltage stability margin. Investigations are carried out on the influence of information encompassed in input vector and target out put vector, on the learning time and test performance of multi layer perceptron (MLP) based ANN model. LP based algorithm for voltage stability improvement, is used for generating meaningful training patterns in the normal operating range of the system. From the generated set of training patterns, appropriate training patterns are selected based on statistical correlation process, sensitivity matrix approach, contingency ranking approach and concentric relaxation method. Simulation results on a 24 bus EHV system, 30 bus modified IEEE system, and a 82 bus Indian power network are presented for illustration purposes.

Voltage stability : some reflections on Q-V characteristics of loads

Considering voltage stability as a static viability problem, this paper takes a particular concern of Q-V characteristics and reflects on certain notions that do not seem to have been explicitly mentioned or derived in the existing documented literature. The equations of Q-V characteristics are rederived in exactness, some salient points on the curve are discovered and analysed. The results of the analysis are illustrated through a case study

Artificial neural network application to power system voltage stability improvement

As power systems grow in their size and interconnections, their complexity increases. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems be operated closer to design limits. Hence power system voltage stability and voltage control are emerging as major problems in the day-to-day operation of stressed power systems. For secure operation and control of power systems under normal and contingency conditions it is essential to provide solutions in real time to the operator in energy control center (ECC). Artificial neural networks (ANN) are emerging as an artificial intelligence tool, which give fast, though approximate, but acceptable solutions in real time as they mostly use the parallel processing technique for computation. The solutions thus obtained can be used as a guide by the operator in ECC for power system control. This paper deals with development of an ANN architecture, which provide solutions for monitoring, and control of voltage stability in the day-to-day operation of power systems.

Novel algorithm for online voltage stability assessment based on feed forward neural network

This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices

Enhanced efficiency of tri-layered dye solar cells with hydrothermally synthesized titania nanotubes as light scattering outer layer

In the present study dye sensitized solar cells (DSSCs) have been fabricated with a tri-layer photo anode consisting of hydrothermally prepared titania nano tubes (TNT) having a diameter of 9-10 nm and length of several micrometers as outer layer, P25 TiO2 powder as transparent light absorbing middle layer and a compact TiO2 inner layer to improve the adhesion of different layers on a transparent conducting oxide coated substrate. In comparison to cells fabricated using TNTs or P25 alone, the tri-layer DSSCs exhibit an enhanced efficiency of 7.15% with a current density of 17.12 mA cm(-2) under AM 1.5 illumination. The enhancement is attributed to the light scattering generated by TNTs aggregates, reduction in electron transport resistance at the TiO2/dye/electrolyte interface and an improvement in electron life-time. (c) 2012 Elsevier B.V. All rights reserved.

Ag-Ni Nanoparticles: Synthesis and Phase Stability

The present study provides an electrodeposition based synthesis method for producing solid solution structured Ag-Ni nanoparticles. It was also observed that the room temperature stable solid solution configuration for the electrodeposited Ag-Ni nanoparticle was a kinetically frozen atomic arrangement and not a thermodynamically stable structure as upon annealing of the Ag-Ni nanoparticles in the ambient atmosphere the solid solution structure decomposed producing phases that were oxides of Ag and Ni. (C) 2012 The Electrochemical Society. [DOI: 10.1149/2.esl120008] All rights reserved.

Relevance of local parallel theory to the linear stability of laminar separation bubbles

Laminar separation bubbles are thought to be highly non-parallel, and hence global stability studies start from this premise. However, experimentalists have always realized that the flow is more parallel than is commonly believed, for pressure-gradient-induced bubbles, and this is why linear parallel stability theory has been successful in describing their early stages of transition. The present experimental/numerical study re-examines this important issue and finds that the base flow in such a separation bubble becomes nearly parallel due to a strong-interaction process between the separated boundary layer and the outer potential flow. The so-called dead-air region or the region of constant pressure is a simple consequence of this strong interaction. We use triple-deck theory to qualitatively explain these features. Next, the implications of global analysis for the linear stability of separation bubbles are considered. In particular we show that in the initial portion of the bubble, where the flow is nearly parallel, local stability analysis is sufficient to capture the essential physics. It appears that the real utility of the global analysis is perhaps in the rear portion of the bubble, where the flow is highly non-parallel, and where the secondary/nonlinear instability stages are likely to dominate the dynamics.