Topological close packed mu phase formation and the determination of diffusion parameters in the Co-Mo system

The study on the formation and growth of topological close packed (TCP) compounds is important to understand the performance of turbine blades in jet engine applications. These deleterious phases grow mainly by diffusion process in the superalloy substrate. Significant volume change was found because of growth of the p phase in Co-Mo system. Growth kinetics of this phase and different diffusion parameters, like interdiffusion, intrinsic and tracer diffusion coefficients are calculated. Further the activation energy, which provides an idea about the mechanism, is determined. Moreover, the interdiffusion coefficient in Co(Mo) solid solution and impurity diffusion coefficient of Mo in Co are determined.

Apsidal motion in 4U 0115+63 and orbital parameters of 2S 1417-624 and V0332+53

Be/X-ray binary pulsars have wide eccentric orbits and hence the angle of periastron of the orbit is very well defined in these sources. The presence of an X-ray pulsar allows for accurate measurements of orbital elements. A Be star usually is a rapidly rotating star and hence will deviate from spherical geometry. The tidal interaction between the neutron star and the Be star will add to the distortion of the Be star and alter its mass distribution. Thus a measurable rate of apsidal motion is expected from these systems. In this paper, we present the first conclusive detection of apsidal motion of the binary 4U 0115+63. We also present new and accurate orbital parameters of the Be/X-ray binaries V0332+53 and 2S 1417-624.

Light scattering in random media with wavelength-scale structures : astronomical and industrial applications

Light scattering, or scattering and absorption of electromagnetic waves, is an important tool in all remote-sensing observations. In astronomy, the light scattered or absorbed by a distant object can be the only source of information. In Solar-system studies, the light-scattering methods are employed when interpreting observations of atmosphereless bodies such as asteroids, atmospheres of planets, and cometary or interplanetary dust. Our Earth is constantly monitored from artificial satellites at different wavelengths. With remote sensing of Earth the light-scattering methods are not the only source of information: there is always the possibility to make in situ measurements. The satellite-based remote sensing is, however, superior in the sense of speed and coverage if only the scattered signal can be reliably interpreted. The optical properties of many industrial products play a key role in their quality. Especially for products such as paint and paper, the ability to obscure the background and to reflect light is of utmost importance. High-grade papers are evaluated based on their brightness, opacity, color, and gloss. In product development, there is a need for computer-based simulation methods that could predict the optical properties and, therefore, could be used in optimizing the quality while reducing the material costs. With paper, for instance, pilot experiments with an actual paper machine can be very time- and resource-consuming. The light-scattering methods presented in this thesis solve rigorously the interaction of light and material with wavelength-scale structures. These methods are computationally demanding, thus the speed and accuracy of the methods play a key role. Different implementations of the discrete-dipole approximation are compared in the thesis and the results provide practical guidelines in choosing a suitable code. In addition, a novel method is presented for the numerical computations of orientation-averaged light-scattering properties of a particle, and the method is compared against existing techniques. Simulation of light scattering for various targets and the possible problems arising from the finite size of the model target are discussed in the thesis. Scattering by single particles and small clusters is considered, as well as scattering in particulate media, and scattering in continuous media with porosity or surface roughness. Various techniques for modeling the scattering media are presented and the results are applied to optimizing the structure of paper. However, the same methods can be applied in light-scattering studies of Solar-system regoliths or cometary dust, or in any remote-sensing problem involving light scattering in random media with wavelength-scale structures.

Friction and transfer layer formation in polymer-steel tribo-system: Role of surface texture and roughness parameters

In the present investigation, various kinds of surface textures were attained on the steel plates. Roughness of the textures was varied using various grinding or polishing methods. The surface textures were characterized in terms of roughness parameters using an optical profilometer. Then experiments were conducted using an inclined pin-on-plate sliding apparatus to identify the role of surface texture and its roughness parameters on coefficient of friction and transfer layer formation. In the experiments, a soft polymer (polypropylene) was used for the pin and hardened steel was used for the plate. Experiments were conducted at a sliding velocity of 2 minis in ambient conditions under both dry and lubricated conditions. The normal load was varied from 1 to 120 N during the tests. The morphologies of the worn surfaces of the pins and the formation of a transfer layer on the steel plate surfaces were observed using a scanning electron microscope. Based on the experimental results, it was observed that the transfer layer formation and the coefficient of friction along with its two components, namely adhesion and plowing, were controlled by the surface texture of the harder mating surfaces and were less dependent of surface roughness (R(a)) of the harder mating surfaces. The effect of surface texture on the friction was attributed to the variation of the plowing component of friction for different surfaces. Among the various surface roughness parameters studied, the mean slope of the profile, Delta(a), was found to most accurately characterize variations in the friction and wear behavior. (C) 2011 Elsevier B.V. All rights reserved.

Vibrational pooling and constrained equilibration on surfaces

In this thesis, we provide a statistical theory for the vibrational pooling and fluorescence time dependence observed in infrared laser excitation of CO on an NaCl surface. The pooling is seen in experiment and in computer simulations. In the theory, we assume a rapid equilibration of the quanta in the substrate and minimize the free energy subject to the constraint at any time t of a fixed number of vibrational quanta N(t). At low incident intensity, the distribution is limited to one- quantum exchanges with the solid and so the Debye frequency of the solid plays a key role in limiting the range of this one-quantum domain. The resulting inverted vibrational equilibrium population depends only on fundamental parameters of the oscillator (ω_e and ω_eχ_e) and the surface (ω_D and T). Possible applications and relation to the Treanor gas phase treatment are discussed. Unlike the solid phase system, the gas phase system has no Debye-constraining maximum. We discuss the possible distributions for arbitrary N-conserving diatom-surface pairs, and include application to H:Si(111) as an example.

Computations are presented to describe and analyze the high levels of infrared laser-induced vibrational excitation of a monolayer of absorbed ¹³CO on a NaCl(100) surface. The calculations confirm that, for situations where the Debye frequency limited n domain restriction approximately holds, the vibrational state population deviates from a Boltzmann population linearly in n. Nonetheless, the full kinetic calculation is necessary to capture the result in detail.

We discuss the one-to-one relationship between N and γ and the examine the state space of the new distribution function for varied γ. We derive the Free Energy, F = NγkT − kTln(∑P_n), and effective chemical potential, μn ≈ γkT, for the vibrational pool. We also find the anti correlation of neighbor vibrations leads to an emergent correlation that appears to extend further than nearest neighbor.

The Madden-Julian Oscillation : observation, modeling, and theory

The Madden-Julian Oscillation (MJO) is a pattern of intense rainfall and associated planetary-scale circulations in the tropical atmosphere, with a recurrence interval of 30-90 days. Although the MJO was first discovered 40 years ago, it is still a challenge to simulate the MJO in general circulation models (GCMs), and even with simple models it is difficult to agree on the basic mechanisms. This deficiency is mainly due to our poor understanding of moist convection—deep cumulus clouds and thunderstorms, which occur at scales that are smaller than the resolution elements of the GCMs. Moist convection is the most important mechanism for transporting energy from the ocean to the atmosphere. Success in simulating the MJO will improve our understanding of moist convection and thereby improve weather and climate forecasting.

We address this fundamental subject by analyzing observational datasets, constructing a hierarchy of numerical models, and developing theories. Parameters of the models are taken from observation, and the simulated MJO fits the data without further adjustments. The major findings include: 1) the MJO may be an ensemble of convection events linked together by small-scale high-frequency inertia-gravity waves; 2) the eastward propagation of the MJO is determined by the difference between the eastward and westward phase speeds of the waves; 3) the planetary scale of the MJO is the length over which temperature anomalies can be effectively smoothed by gravity waves; 4) the strength of the MJO increases with the typical strength of convection, which increases in a warming climate; 5) the horizontal scale of the MJO increases with the spatial frequency of convection; and 6) triggered convection, where potential energy accumulates until a threshold is reached, is important in simulating the MJO. Our findings challenge previous paradigms, which consider the MJO as a large-scale mode, and point to ways for improving the climate models.

Superconductivity, spin-glass properties, and ferromagnetism in amorphous La-Gd-Au alloys

The superconducting and magnetic properties of splat cooled amorphous alloys of composition (La_100-xGd_x)₈₀Au₂₀ (0 ≤ x ≤ 100) have been studied. The La₈₀Au₂₀ alloys are ideal type II super-conductors (critical temperature T_c = 3.5° K ). The concentration range (x less than 1) where superconductivity and spin-glass freezing n1ight coexist has been studied in detail. The spin-glass alloys (0 less than x less than 70) exhibit susceptibility maxima and thermomagnetic history effects. In the absence of complications due to crystal field and enhanced matrix effects, a phenomenological model is proposed in which the magnetic clusters are treated as single spin entities interacting via random forces using the molecular field approach. The fundamental parameters (such as the strength of the forces and the size of clusters) can be deduced from magnetization measurements. The remanent magnetization is shown to arise from an interplay of the RKKY and dipolar forces. Magnetoresistivity results are found to be consistent with the aforementioned picture. The nature of magnetic interactions in an amorphous matrix is also discussed. The moment per Gd atom (7µ_B) is found to be constant and close to that of the crystalline value throughout the concentration range investigated. Finally, a detail study is made of the critical phenomena and magnetic properties of the amorphous ferromagnet: Gd₈₀Au₂₀. The results are compared with recent theories on amorphous magnetism.

Estimation of catalyst activity profiles and deactivation parameters from reactor operating data with applications to naphtha reforming

Techniques are developed for estimating activity profiles in fixed bed reactors and catalyst deactivation parameters from operating reactor data. These techniques are applicable, in general, to most industrial catalytic processes. The catalytic reforming of naphthas is taken as a broad example to illustrate the estimation schemes and to signify the physical meaning of the kinetic parameters of the estimation equations. The work is described in two parts. Part I deals with the modeling of kinetic rate expressions and the derivation of the working equations for estimation. Part II concentrates on developing various estimation techniques.

Part I: The reactions used to describe naphtha reforming are dehydrogenation and dehydroisomerization of cycloparaffins; isomerization, dehydrocyclization and hydrocracking of paraffins; and the catalyst deactivation reactions, namely coking on alumina sites and sintering of platinum crystallites. The rate expressions for the above reactions are formulated, and the effects of transport limitations on the overall reaction rates are discussed in the appendices. Moreover, various types of interaction between the metallic and acidic active centers of reforming catalysts are discussed as characterizing the different types of reforming reactions.

Part II: In catalytic reactor operation, the activity distribution along the reactor determines the kinetics of the main reaction and is needed for predicting the effect of changes in the feed state and the operating conditions on the reactor output. In the case of a monofunctional catalyst and of bifunctional catalysts in limiting conditions, the cumulative activity is sufficient for predicting steady reactor output. The estimation of this cumulative activity can be carried out easily from measurements at the reactor exit. For a general bifunctional catalytic system, the detailed activity distribution is needed for describing the reactor operation, and some approximation must be made to obtain practicable estimation schemes. This is accomplished by parametrization techniques using measurements at a few points along the reactor. Such parametrization techniques are illustrated numerically with a simplified model of naphtha reforming.

To determine long term catalyst utilization and regeneration policies, it is necessary to estimate catalyst deactivation parameters from the the current operating data. For a first order deactivation model with a monofunctional catalyst or with a bifunctional catalyst in special limiting circumstances, analytical techniques are presented to transform the partial differential equations to ordinary differential equations which admit more feasible estimation schemes. Numerical examples include the catalytic oxidation of butene to butadiene and a simplified model of naphtha reforming. For a general bifunctional system or in the case of a monofunctional catalyst subject to general power law deactivation, the estimation can only be accomplished approximately. The basic feature of an appropriate estimation scheme involves approximating the activity profile by certain polynomials and then estimating the deactivation parameters from the integrated form of the deactivation equation by regression techniques. Different bifunctional systems must be treated by different estimation algorithms, which are illustrated by several cases of naphtha reforming with different feed or catalyst composition.

Comparison of spectroscopic parameters of 15 at% Yb : YAlO3 and 15 at% Yb : Y3Al5O12

Yb: YAlO3 (YAP) (15 at %) and Yb: Y3Al5O12 (YAG)(15 at %) have been grown using the Czochralski method. Their absorption and fluorescence spectra were measured at room temperature and important spectroscopic parameters were calculated. Through the comparison of spectroscopic parameters of Yb:YAP and Yb: YAG, all results indicate that 15 at % Yb:YAP crystal is a potential candidate used for compact, efficient thin chip lasers when the laser output wavelength is 1012 or 103 8 nm. (C) 2004 Elsevier B.V. All rights reserved.

Natural actor and belief critic: Reinforcement algorithm for learning parameters of dialogue systems modelled as POMDPs

This article presents a novel algorithm for learning parameters in statistical dialogue systems which are modeled as Partially Observable Markov Decision Processes (POMDPs). The three main components of a POMDP dialogue manager are a dialogue model representing dialogue state information; a policy that selects the system's responses based on the inferred state; and a reward function that specifies the desired behavior of the system. Ideally both the model parameters and the policy would be designed to maximize the cumulative reward. However, while there are many techniques available for learning the optimal policy, no good ways of learning the optimal model parameters that scale to real-world dialogue systems have been found yet. The presented algorithm, called the Natural Actor and Belief Critic (NABC), is a policy gradient method that offers a solution to this problem. Based on observed rewards, the algorithm estimates the natural gradient of the expected cumulative reward. The resulting gradient is then used to adapt both the prior distribution of the dialogue model parameters and the policy parameters. In addition, the article presents a variant of the NABC algorithm, called the Natural Belief Critic (NBC), which assumes that the policy is fixed and only the model parameters need to be estimated. The algorithms are evaluated on a spoken dialogue system in the tourist information domain. The experiments show that model parameters estimated to maximize the expected cumulative reward result in significantly improved performance compared to the baseline hand-crafted model parameters. The algorithms are also compared to optimization techniques using plain gradients and state-of-the-art random search algorithms. In all cases, the algorithms based on the natural gradient work significantly better. © 2011 ACM.

Ecology and production in two sandy beaches of Goa. Part (A) Distribution of bacteria in Colva and Siridaon in relation to certain environmental parameters

Qualitative and quantitative studies on the bacterial flora of two beaches viz., Colva and Siridaon at high tide, mid-tide and low tide levels during the pre-monsoon period were made. Estimations of important nutrients, like inorganic phosphates and nitrates and organic carbon have been made and correlation with the bacterial counts is being attempted. Definite correlation between bacterial population and organic carbon is seen however, no correlation is observed between bacterial counts and other physicochemical parameters.

Biological characteristics and determination of population dynamics parameters of Nemipterus japonicus in the coastal waters of Province Bushehr, Persian Gulf

This study was conducted to determine biological characteristics and population dynamics parameters of threadfin bream (Nemipterus japonicus) in Persian Gulf (Bushehr Province), during November 2006 and October 2007. The minimum and maximum specimens were 75-273 mm FL and their weight was 7.6 - 351.9 g. Based on the exponential relationship between fork length and weight, slope (b) for individuals, males and females was 2.987321, 2.992546 and 3.007314, respectively. The emptiness value (V) was 45.6% and it shows that N. japonicus is a moderate feeder. The results of Fp indicates that crustacean with 78.2% are main foods, mollusca (27.7%), fishes (20.7%), polychaeta (19.2%) and Foraminifera (11.7%) were identified as minor foods and phytoplanktons (9.9%), nematoda(8.0%), echinodermata (2.3%) and sea weeds (0.3%) were random foods. The reproduction studies showed the spawning season extended within 2 peaks, from April- May and September and main spawning occurs in spring season.The mean absolute and relative fecundities were 472388±42633 and 3817±293 (X±SE), respectively. The maximum, minimum and mean of oocyte diameter were 0.448, 0.022 and 0.221mm (SE=0.071), respectively.The fork length at 50% maturity estimated to be 20.25 cm for females. The growth coefficient (K) , length infinity (L∞ ) and ɸ' was estimated 0.42/yr , 34.17 cm and 2.69, respectively. The coefficient of total mortality, fishing mortality, natural mortality and E was 1.37, 0.43, 0.94 and 0.31, respectively.

Bayesian non-parametrics and the probabilistic approach to modelling.

Modelling is fundamental to many fields of science and engineering. A model can be thought of as a representation of possible data one could predict from a system. The probabilistic approach to modelling uses probability theory to express all aspects of uncertainty in the model. The probabilistic approach is synonymous with Bayesian modelling, which simply uses the rules of probability theory in order to make predictions, compare alternative models, and learn model parameters and structure from data. This simple and elegant framework is most powerful when coupled with flexible probabilistic models. Flexibility is achieved through the use of Bayesian non-parametrics. This article provides an overview of probabilistic modelling and an accessible survey of some of the main tools in Bayesian non-parametrics. The survey covers the use of Bayesian non-parametrics for modelling unknown functions, density estimation, clustering, time-series modelling, and representing sparsity, hierarchies, and covariance structure. More specifically, it gives brief non-technical overviews of Gaussian processes, Dirichlet processes, infinite hidden Markov models, Indian buffet processes, Kingman's coalescent, Dirichlet diffusion trees and Wishart processes.

Phosphine-Free Synthesis of High-Quality CdSe Nanocrystals in Noncoordination Solvents: "Activating Agent" and "Nucleating Agent" Controlled Nucleation and Growth

CdSe nanocrystals (NCs) are prepared in noncoordination solvents (1-octadecene (ODE) and paraffin liquid) with Ion g-chain primary alkylamine as the sole ligand, ODE-Se, and cadmium fatty acid salt as precursors. The obtained NCs meet the four fundamental parameters for high-quality NCs: high crystallinity, narrow size distribution, moderate photoluminescence quantum yield, and broad range size tunableness. Further, by simply regulating the relative molar ratio of alkylamine to cadmium precursor, the regular sized "nuclei" and final obtained NCs can be produced predictably within a certain size range.

GLASS-TRANSITION TEMPERATURE AND MOLECULAR-PARAMETERS OF POLYMER

A new relationship, which correlates the glass transition temperature (T(g)) with other molecular parameters, is developed by using Flory's lattice statistics of polymer chain and taking the dynamic segment as the basic statistical unit. The dependences of T(g) on the chain stiffness factor (sigma-2), dynamic stiffness factor (beta = -d ln-sigma-2/dT) and molecular weight of polymer are discussed in detail based on the theory. The theory is compared with experimental data for many linear polymers and good agreement is obtained. It is shown that T(g) is essentially governed by the chain stiffness factor at T(g). Moreover, a simple correlation between the parameter K(g) of the Fox-Flory equation (T(g) = T(g)infinity - K(g)/M(n)) and other molecular parameters is deduced. The agreement between theoretical predictions and experimental measurements of K(g) has been found to be satisfactory for many polymers.