Eu3+-activated SrMoO4 phosphors for white LEDs applications: Synthesis and structural characterization

We report the synthesis of Eu3+-activated SrMoO4 phosphors by the facile nitrate-citrate gel combustion method. Powder XRD and Rietveld refinement data confirmed that these phosphors have a monophasic scheelite-type tetragonal structure with space group I4(1)/a (No. 88). FESEM micrographs indicate the agglomerated spherical particles. FTIR spectra showed four stretching and bending vibrational modes (2A(u) and 2E(u)). UV-Visible absorption spectroscopy illustrated that the optical band gap energy (E-g) values increase with increase in Eu3+ concentration. The host SrMoO4 phosphor exhibited an intense blue emission under UV excitation (368 nm). The Eu3+-activated SrMoO4 phosphors revealed characteristic luminescence due to Eu3+ ion corresponding to D-5(1) -> F-7(J) (J = 1,2) and D-5(0) -> F-7(J) (J = 1,2,3,4) transitions upon 465 nm excitation. The electric dipole transition located at 615 nm (D-5(0) -> F-7(2)) was stronger than the magnetic dipole transition located at 592 nm (D-5(0) -> F-7(1)). Intensity parameters (Omega(2), Omega(4)) and radiative properties such as transition probabilities (A(T)), radiative lifetime (tau(rad)) and branching ratio (beta) of Eu3+-activated SrMoO4 phosphors were calculated using the Judd-Ofelt theory. Based on the CIE chromaticity diagram, these phosphors can be promising materials for the development of blue and orange-red component in white LEDs. (C) 2015 Elsevier B.V. All rights reserved.

Evaluating Methods to Predict Streamflow at Ungauged Sites using Regional Flow Duration Curves: A Case Study

Precise information on streamflows is of major importance for planning and monitoring of water resources schemes related to hydro power, water supply, irrigation, flood control, and for maintaining ecosystem. Engineers encounter challenges when streamflow data are either unavailable or inadequate at target locations. To address these challenges, there have been efforts to develop methodologies that facilitate prediction of streamflow at ungauged sites. Conventionally, time intensive and data exhaustive rainfall-runoff models are used to arrive at streamflow at ungauged sites. Most recent studies show improved methods based on regionalization using Flow Duration Curves (FDCs). A FDC is a graphical representation of streamflow variability, which is a plot between streamflow values and their corresponding exceedance probabilities that are determined using a plotting position formula. It provides information on the percentage of time any specified magnitude of streamflow is equaled or exceeded. The present study assesses the effectiveness of two methods to predict streamflow at ungauged sites by application to catchments in Mahanadi river basin, India. The methods considered are (i) Regional flow duration curve method, and (ii) Area Ratio method. The first method involves (a) the development of regression relationships between percentile flows and attributes of catchments in the study area, (b) use of the relationships to construct regional FDC for the ungauged site, and (c) use of a spatial interpolation technique to decode information in FDC to construct streamflow time series for the ungauged site. Area ratio method is conventionally used to transfer streamflow related information from gauged sites to ungauged sites. Attributes that have been considered for the analysis include variables representing hydrology, climatology, topography, land-use/land- cover and soil properties corresponding to catchments in the study area. Effectiveness of the presented methods is assessed using jack knife cross-validation. Conclusions based on the study are presented and discussed. (C) 2015 The Authors. Published by Elsevier B.V.

Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems

Prediction of queue waiting times of jobs submitted to production parallel batch systems is important to provide overall estimates to users and can also help meta-schedulers make scheduling decisions. In this work, we have developed a framework for predicting ranges of queue waiting times for jobs by employing multi-class classification of similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k-Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the class predicted using k-NN and its neighboring classes are used to provide a set of ranges of predicted wait times with probabilities. We have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. Experiments with different production supercomputer job traces show that our prediction strategies can give correct predictions for about 77-87% of the jobs, and also result in about 12% improved accuracy when compared to the next best existing method. Experiments with our meta-scheduling strategy using different production and synthetic job traces for various system sizes, partitioning schemes and different workloads, show that the meta-scheduling strategy gives much improved performance when compared to existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47%.

A New Algorithm for Nonparametric Sequential Detection

We consider nonparametric sequential hypothesis testing problem when the distribution under the null hypothesis is fully known but the alternate hypothesis corresponds to a general family of distributions. We propose a simple algorithm to address the problem. Its performance is analysed and asymptotic properties are proved. The simulated and analysed performance of the algorithm is compared with an earlier algorithm addressing the same problem with similar assumptions. Finally, we provide a justification for our model motivated by a Cognitive Radio scenario and modify the algorithm for optimizing performance when information about the prior probabilities of occurrence of the two hypotheses is available.

Detection of a quantum particle on a lattice under repeated projective measurements

We consider a quantum particle, moving on a lattice with a tight-binding Hamiltonian, which is subjected to measurements to detect its arrival at a particular chosen set of sites. The projective measurements are made at regular time intervals tau, and we consider the evolution of the wave function until the time a detection occurs. We study the probabilities of its first detection at some time and, conversely, the probability of it not being detected (i.e., surviving) up to that time. We propose a general perturbative approach for understanding the dynamics which maps the evolution operator, which consists of unitary transformations followed by projections, to one described by a non-Hermitian Hamiltonian. For some examples of a particle moving on one-and two-dimensional lattices with one or more detection sites, we use this approach to find exact expressions for the survival probability and find excellent agreement with direct numerical results. A mean-field model with hopping between all pairs of sites and detection at one site is solved exactly. For the one-and two-dimensional systems, the survival probability is shown to have a power-law decay with time, where the power depends on the initial position of the particle. Finally, we show an interesting and nontrivial connection between the dynamics of the particle in our model and the evolution of a particle under a non-Hermitian Hamiltonian with a large absorbing potential at some sites.

Synthesis, photoluminescence and Judd-Ofelt parameters of LiNa3P2O7:Eu3+ orthorhombic microstructures

We report, for the first time, the photoluminescence properties of Eu3+-doped LiNa3P2O7 phosphor, synthesized by a facile solid-state reaction method in air atmosphere. The crystal structure and phase purity of the phosphors were analyzed by X-ray diffraction analysis. Orthorhombic structural morphology was identified by scanning electron microscopy. The phosphate groups in the phosphor were confirmed by Fourier transform infrared analysis. Bandgap of the phosphor was calculated from the diffuse reflectance spectra data using Kubelka-Munk function. Under 395-nm UV excitation, the phosphors show signs of emitting red color due to the D-5(0) -> F-7(2) transition. In accordance with Judd-Ofelt theory, spectroscopic parameters such as oscillator intensity parameter Omega(t) (t = 2), spontaneous emission probabilities, fluorescence branching ratios and radiative lifetimes were calculated and analyzed for the first time in this system.

Synthesis of Eu3+-activated BaMoO4 phosphors and their Judd-Ofelt analysis: Applications in lasers and white LEDs

Eu3+-activated BaMoO4 phosphors were synthesized by the nitrate citrate gel combustion method. The Rietveld refinement analysis confirmed that all the compounds were crystallized in the scheelite-type tetragonal structure with I4(1)/a (No. 88) space group. Photoluminescence (PL) spectra of BaMoO4 phosphor reveals broad emission peaks at 465 and 605 nm, whereas the Eu3+-activated BaMoO4 phosphors show intense 615 nm (D-5(0) -> F-7(2)) emission peak. Judd-Ofelt theory was applied to evaluate the intensity parameters (Omega(2), Omega(4)) of Eu3+-activated BaMoO4 phosphors. The transition probabilities (A(T)), radiative lifetime (tau(rad)), branching ratio (beta), stimulated emission cross-section (sigma(e)), gain bandwidth (sigma(e) x Delta lambda(eff)) and optical gain (sigma(e) x tau(rad)) were investigated by using the intensity parameters. CIE color coordinates confirmed that the BaMoO4 and Eu3+-activated BaMoO4 phosphors exhibit white and red luminescence, respectively. The obtained results revealed that the present phosphors can be a potential candidate for red lasers and white LEDs applications. (C) 2015 Elsevier B.V. All rights reserved.

Comparative study of Eu3+ -activated LnOCl (Ln=La and Gd) phosphors and their Judd-Ofelt analysis

Eu3+-activated layered LnOCl (Ln=La and Gd) phosphors were synthesized by the conventional solid-state method at relatively low temperature (700 degrees C) and shorter duration of 2 h. The structural parameters were refined by the Rietveld refinement analysis and confirmed by the high resolution transmission electron microscopy (HRTEM). Both the compounds were crystallized in the tetragonal structure with space group P4/nmm (No. 129). The homogeneity of the elements were analyzed by TEM mapping and found to be uniformly distributed. The photoluminescence spectra revealed that the intensity of D-5(0)-> F-7(2) transition (619 nm) was more intense in Eu3+-activated GdOCl compared to LaOCl. This was due to the property of Gd3+ ions to act as an intermediate sublattice to facilitate the energy transfer to Eu3+ ions. Intensity parameters and radiative properties such as transition probabilities, radiative lifetime and branching ratio were calculated using the Judd-Ofelt theory. The CIE color coordinates result revealed that the Eu3+-activated GdOCl (0.641, 0.354) phosphor was close to the commercial red phosphors like, Y2O3:Eu3+ (0.645, 0.347), (Y2OS)-S-2:Eu3+ (0.647, 0.343) and National Television System Committee (NTSC) (0.67, 0.33). The results suggest that the present GdOCl:Eu3+ compound acts as a potential candidate for red phosphor materials.

1D Tight-Binding Models Render Quantum First Passage Time ``Speakable''

The calculation of First Passage Time (moreover, even its probability density in time) has so far been generally viewed as an ill-posed problem in the domain of quantum mechanics. The reasons can be summarily seen in the fact that the quantum probabilities in general do not satisfy the Kolmogorov sum rule: the probabilities for entering and non-entering of Feynman paths into a given region of space-time do not in general add up to unity, much owing to the interference of alternative paths. In the present work, it is pointed out that a special case exists (within quantum framework), in which, by design, there exists one and only one available path (i.e., door-way) to mediate the (first) passage -no alternative path to interfere with. Further, it is identified that a popular family of quantum systems - namely the 1d tight binding Hamiltonian systems - falls under this special category. For these model quantum systems, the first passage time distributions are obtained analytically by suitably applying a method originally devised for classical (stochastic) mechanics (by Schroedinger in 1915). This result is interesting especially given the fact that the tight binding models are extensively used in describing everyday phenomena in condense matter physics.

An evolutionary formalism for weak quantum measurements

Unitary evolution and projective measurement are fundamental axioms of quantum mechanics. Even though projective measurement yields one of the eigenstates of the measured operator as the outcome, there is no theory that predicts which eigenstate will be observed in which experimental run. There exists only an ensemble description, which predicts probabilities of various outcomes over many experimental runs. We propose a dynamical evolution equation for the projective collapse of the quantum state in individual experimental runs, which is consistent with the well-established framework of quantum mechanics. In case of gradual weak measurements, its predictions for ensemble evolution are different from those of the Born rule. It is an open question whether or not suitably designed experiments can observe this alternate evolution.

Probabilistic Models for Forecasting Earthquakes in the Northeast Region of India

Northeast India and its adjoining areas are characterized by very high seismic activity. According to the Indian seismic code, the region falls under seismic zone V, which represents the highest seismic-hazard level in the country. This region has experienced a number of great earthquakes, such as the Assam (1950) and Shillong (1897) earthquakes, that caused huge devastation in the entire northeast and adjacent areas by flooding, landslides, liquefaction, and damage to roads and buildings. In this study, an attempt has been made to find the probability of occurrence of a major earthquake (M-w > 6) in this region using an updated earthquake catalog collected from different sources. Thereafter, dividing the catalog into six different seismic regions based on different tectonic features and seismogenic factors, the probability of occurrences was estimated using three models: the lognormal, Weibull, and gamma distributions. We calculated the logarithmic probability of the likelihood function (ln L) for all six regions and the entire northeast for all three stochastic models. A higher value of ln L suggests a better model, and a lower value shows a worse model. The results show different model suits for different seismic zones, but the majority follows lognormal, which is better for forecasting magnitude size. According to the results, Weibull shows the highest conditional probabilities among the three models for small as well as large elapsed time T and time intervals t, whereas the lognormal model shows the lowest and the gamma model shows intermediate probabilities. Only for elapsed time T = 0, the lognormal model shows the highest conditional probabilities among the three models at a smaller time interval (t = 3-15 yrs). The opposite result is observed at larger time intervals (t = 15-25 yrs), which show the highest probabilities for the Weibull model. However, based on this study, the IndoBurma Range and Eastern Himalaya show a high probability of occurrence in the 5 yr period 2012-2017 with >90% probability.

A fast and accurate performance analysis of beaconless IEEE 802.15.4 multi-hop networks

We develop an approximate analytical technique for evaluating the performance of multi-hop networks based on beaconless IEEE 802.15.4 ( the ``ZigBee'' PHY and MAC), a popular standard for wireless sensor networks. The network comprises sensor nodes, which generate measurement packets, relay nodes which only forward packets, and a data sink (base station). We consider a detailed stochastic process at each node, and analyse this process taking into account the interaction with neighbouring nodes via certain time averaged unknown variables (e.g., channel sensing rates, collision probabilities, etc.). By coupling the analyses at various nodes, we obtain fixed point equations that can be solved numerically to obtain the unknown variables, thereby yielding approximations of time average performance measures, such as packet discard probabilities and average queueing delays. The model incorporates packet generation at the sensor nodes and queues at the sensor nodes and relay nodes. We demonstrate the accuracy of our model by an extensive comparison with simulations. As an additional assessment of the accuracy of the model, we utilize it in an algorithm for sensor network design with quality-of-service (QoS) objectives, and show that designs obtained using our model actually satisfy the QoS constraints (as validated by simulating the networks), and the predictions are accurate to well within 10% as compared to the simulation results in a regime where the packet discard probability is low. (C) 2015 Elsevier B.V. All rights reserved.