Density of states effective mass of n-type CuInSe2 from the temperature dependence of Hall coefficient in the activation regime

The Hall coefficient R_H of n-type CuInSe₂ single crystals is measured between 10 and 300 K in pulsed magnetic field up to 35 T. The threshold field B_th, above which the magnetic freezeout starts to occur, varies linearly with temperature. From the analysis of the temperature dependence of electron concentration in the activation regime above 100 K at different field values, it is established that the density of states effective mass is independent of the magnetic field B and the activation energy E_D, above around 6 T, varies as B^1/3. Similar B^1/3 dependence of the magnetoresistance in the high magnetic field regime, reported earlier in the same material, suggests that theoretical work that could explain this coincidence is needed.     

Experimentally determined temperature–concentration phase diagrams of monodisperse alkanes with chains containing between 100 and 200 carbons

The temperature–concentration phase (T–c) diagrams of the uniform n-alkanes C₁₀₂H₂₀₆, C₁₂₂H₂₄₆, C₁₆₂H₃₂₆, and C₁₉₈H₃₉₈ in toluene have been determined for solution concentrations in the range 0.1 to 6% (w/w). The shorter alkanes display a “classical” behavior with the expected, strong dependence of dissolution temperature on solution concentration. The longest alkane displays a very different, “polymeric” type behavior with a concentration independent dissolution temperature (for both extended and folded chain crystals). It is argued that no current theory of polymer dissolution is able to explain this behavior. It is suggested that a locally higher concentration occurs when molecules are partially attached to a crystal either during crystallization or dissolution, and that this increased local concentration accounts for the independence of dissolution temperature on the global concentration. There are some small variations in the dissolution temperature of crystals of the same thickness grown at the same concentration, but at different temperatures. These are ascribed to differences in the stacking of the separate layers. © 1999 John Wiley & Sons, Inc. J Polym Sci B: Polym Phys 37: 3188–3200, 1999     

GammaLab: a suite of programs for k0-NAA and gamma-ray spectrum analysis

The GammaLab is a collection of computer codes, written in MATLAB, for performing calculations involved in k ₀ neutron activation analysis. The main features of the program include calibrations including energy-channel, energy-FWHM and energy-efficiency for different geometries, background subtraction, nuclide identification, spectral interference correction, elemental concentration and limit of detection determination. The data input is taken from two files one is the spectrum file stored in IAEA ASCII format and other is report file containing peak energy and peak area data. The information about sample, irradiation and counting conditions, background spectra are retrieved from QAQCData database. GammaLab takes nuclear data such as gamma lines, emission probabilities, half-lives, and k ₀ factors from NucData database. The sample results which contain elemental concentrations with uncertainties are stored in the QAQCData database. The program has been evaluated by analyzing several hundred spectra and results were found satisfactory.     

Development of methodologies for the analysis of uranium ores by k 0-instrumental neutron activation analysis and inductively coupled plasma atomic emission spectrometry

Journal of Radioanalytical and Nuclear Chemistry - Analytical methodologies were developed for the determination of elemental contents in four uranium ore samples (S-8, S-12, S-13 and S-17) from...     

Electrospray mass spectrometry for detailed mechanistic studies of a complex organocatalyzed triple cascade reaction

The development of modular combinations of organocatalytic reactions into cascades has been shown to be an effective tool despite the fact that the mechanism of such a complex organocatalytic multistep cascade reaction still remains poorly understood. Here the detailed mechanistic studies of a complex organocatalytic triple cascade reaction for the synthesis of tetra-substituted cyclohexene carbaldehydes are reported. The investigation has been carried out using a triple quadrupole mass spectrometer with electrospray ionization. Important intermediates were detected and characterized through MS/MS studies. A detailed formation pathway is presented based on these characterized intermediates, and supporting the proposed mechanism of the formation of the substituted cyclohexene carbaldehydes.     

Synthetic Photoelectrochemistry

Photoredox catalysis (PRC) and synthetic organic electrochemistry (SOE) are often considered competing technologies in organic synthesis. Their fusion has been largely overlooked. We review state‐of‐the‐art synthetic organic photoelectrochemistry, grouping examples into three categories: 1) electrochemically mediated photoredox catalysis (e‐PRC), 2) decoupled photoelectrochemistry (dPEC), and 3) interfacial photoelectrochemistry (iPEC). Such synergies prove beneficial not only for synthetic “greenness” and chemical selectivity, but also in the accumulation of energy for accessing super‐oxidizing or ‐reducing single electron transfer (SET) agents. Opportunities and challenges in this emerging and exciting field are discussed.     

Speckle-photography study of nuclear-waste vault deformations

White-light speckle photography was applied to measure the viscoplastic deformation of a proposed nuclear-waste repository. The repository vaults are carved into bedded salt deep in the earth, and deform extremely slowly. The research demonstrates the feasibility of using whole-field techniques to detect mine wall strains, confirms certain, but not all, measurements of point-by-point instruments, and also confirms the predictions of a site-specific numerical model.Paper was presented at the 1994 SEM Spring Conference on Experimental Mechanics held in Baltimore, MD on June 6–9.     

Heat transfer analysis of MHD rotating flow of Fe_3O_4 nanoparticles through a stretchable surface

The flow of a magnetite-H_2O nanofluid has been considered among two rotating surfaces,assuming porosity in the upper plate. Furthermore, the lower surface is considered to move with variable speed to induce the forced convection. Centripetal as well as Coriolis forces impacting on the rotating fluid are likewise taken into account. Adequate conversions are employed for the transformation of the governing partial-differential equations into a group of non-dimensional ordinary-differential formulas. Numerical solution of the converted expressions is gained by means of the shooting technique. It is theoretically found that the nanofluid has less skin friction and advanced heat transport rate when compared with the base fluid. The effect of rotation causes the drag force to elevate and reduces the heat transport rate. Streamlines are portrayed to reveal the impact of injection/suction.     

Design of Nonlinear Autoregressive Exogenous Model Based Intelligence Computing for Efficient State Estimation of Underwater Passive Target

In this study, an intelligent computing paradigm built on a nonlinear autoregressive exogenous (NARX) feedback neural network model with the strength of deep learning is presented for accurate state estimation of an underwater passive target. In underwater scenarios, real-time motion parameters of passive objects are usually extracted with nonlinear filtering techniques. In filtering algorithms, nonlinear passive measurements are associated with linear kinetics of the target, governing by state space methodology. To improve tracking accuracy, effective feature estimation and minimizing position error of dynamic passive objects, the strength of NARX based supervised learning is exploited. Dynamic artificial neural networks, which contain tapped delay lines, are suitable for predicting the future state of the underwater passive object. Neural networks-based intelligence computing is effectively applied for estimating the real-time actual state of a passive moving object, which follows a semi-curved path. Performance analysis of NARX based neural networks is evaluated for six different scenarios of standard deviation of white Gaussian measurement noise by following bearings only tracking phenomena. Root mean square error between estimated and real position of the passive target in rectangular coordinates is computed for evaluating the worth of the proposed NARX feedback neural network scheme. The Monte Carlo simulations are conducted and the results certify the capability of the intelligence computing over conventional nonlinear filtering algorithms such as spherical radial cubature Kalman filter and unscented Kalman filter for given state estimation model.