Two-Dimensional Porous PdO/Co3O4 Nanocomposites for Highly Effective Photocatalysts Under Visible-Light Exposure

Journal of Inorganic and Organometallic Polymers and Materials - Recently, great efforts have been dedicated to the construct and design of low cost and high-performance photocatalysts for the...     

Hilbert Transform and Statistical Analysis for Channel Selection and Epileptic Seizure Prediction

This paper is concerned with Electroencephalography (EEG) seizure prediction, which means the detection of the pre-ictal state prior to ictal activity occurrence. The basic idea of the proposed approach for EEG seizure prediction is to work on the signals in the Hilbert domain. The operation in the Hilbert domain guarantees working on the low-pass spectra of EEG signal segments to avoid artifacts. Signal attributes in the Hilbert domain including amplitude, derivative, local mean, local variance, and median are analyzed statistically to perform the channel selection and seizure prediction tasks. Pre-defined prediction and false-alarm probabilities are set to select the channels, the attributes, and bins of probability density functions (PDFs) that can be useful for seizure prediction. Due to the multi-channel nature of this process, there is a need for a majority voting strategy to take a decision for each signal segment. Simulation results reveal an average prediction rate of 96.46%, an average false-alarm rate of 0.028077/h and an average prediction time of 60.1595 min for a 90-min prediction horizon.

     

Automated High Throughput Screening of Fluorescent Imaging Plate Reader (FLIPR) Assays Using Assay Platform™ Integrated with Activity Base for ‘on the fly’ Compound Reconfirmation

Advances in the field of automation have meant hitherto complex manual cell-based assays can now be automated. These improvements have brought significant enhancements in throughput, data fidelity and consistency, and allowed a reallocation of constrained resources.Building upon these improvements, we have linked our automated cell-based screening system, Assay Platform™, to Activity Base (IDBS), a software package designed to automate the analysis of HTS data. Customisation of this package has resulted in software that can identify ‘active’ compounds and re-pick them ‘on the fly’ from the original compound plates for triplicate re-testing without operator intervention.Based on an operator initially defining ‘normal’ parameters for assay activity in Activity Base, combined with an automated quality control software module that checks data fidelity, wells containing ‘active’ compounds can be re-picked and re-tested at the end of an automated screening run. Automating cell-based assays has significantly improved productivity, and, with the synergism of Activity Base, has given us greater power to complete each screening run and report ‘active’ compounds to Chemistry more rapidly. This article presents our approach to the automation of cell-based Fluorescent Imaging Plate Reader (FLIPR) screening together with automated active re-test confirmation using Activity Base.     

Computational investigation of hydraulic performance variation with geometry in gabion stepped spillways

Over recent years, there has been a clear increase in the frequency of reported flooding events around the world. Gabion structures offer one means of flood mitigation in dam spillways. These types of structures provide an additional challenge to the computational modeller in that flow through the porous gabions must be simulated. We have used a computational model to investigate the flow over gabion stepped spillways. The model was first validated against published experimental results. Then, gabion stepped spillways with four different step geometries were tested under the same conditions in order to facilitate inter-comparisons and to choose the best option in terms of energy dissipation. The results show that normal gabion steps can dissipate more energy than overlap, inclined, and pooled steps. An intensive set of tests with varying slope, stone size, and porosity were undertaken. The location of the inception point and the water depth at this point obtained from this study were compared with those from existing formulae. Two new empirical equations have been derived, on the basis of a regression analysis, to provide improved results for gabion stepped spillways.     

Induction Motors Broken Rotor Bars Diagnosis Through the Discrete Wavelet Transform of the Instantaneous Reactive Power Signal under Time-varying Load Conditions

Abstract—In this article, a method based on the application of the discrete wavelet transform to the instantaneous reactive power signal, for diagnosing the occurrence of broken rotor bars in induction motors operating under time-varying load conditions, is presented. This method is based on the decomposition of the instantaneous reactive power signal, from which wavelet approximation and detail coefficients are extracted. The energy evaluation of known bandwidths permits to de?ne a fault severity factor. This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. These simulation results are complemented by experimental tests conducted on an induction motor with several faulty rotors that can be interchanged and both simulation and experimental results have shown the effectiveness of the proposed method for broken rotor bars diagnosis in induction motors even under time-varying load conditions.     

A New and Accurate Modeling Technique for Glass Resistance in Multiphase Multielectrode Glass Furnaces

One of the design elements involved in sizing the electrical power equipment for glass furnaces is the determination of the glass resistances between the operating electrodes. All methods used for this purpose to date are approximate and are based on a simple model considering the resistance between only two electrodes at the time. This paper presents a technique to develop a resistance model for any general configuration of electrodes and supply voltages in glass furnaces. The technique is based on relating the glass conductivity as represented by Ohm's law to the electrostatic property as represented by Gauss's law. The resistance model is then derived in a matrix form using the bus admittance frame of reference. A digital computer program has been developed to implement the proposed technique and example results are presented.     

Effects of the electrolyte content on the electrical permittivity,thermal stability,and optical dispersion of poly(vinyl alcohol)–cesium copper oxide–lithium perchlorate nanocomposite solid‐polymer electrolytes

Solid‐polymer electrolytes (SPEs) in the form of poly(vinyl alcohol) (PVA) doped with various amounts (5, 10, and 15 wt %) of lithium perchlorate trihydrate (LiClO₄·3H₂O) and 2 wt % cesium copper oxide (Cs₂CuO₂) nanoparticles were fabricated by a solvent intercalation method. The obtained nanocomposites were evaluated for their chemical structure and microstructural and morphological behaviors via Fourier transform infrared spectroscopy, X‐ray diffraction, and scanning electron microscopy methods, respectively. The obtained dielectric behaviors, alternating‐current conductivity, dielectric modulus, and dielectric relaxation of the SPEs depended on the volume fraction of the electrolyte. Linear behavior of the current–voltage characteristics for all of the SPE films was observed with a slight deviation at a higher voltage. The thermal behaviors of the PVA–Cs₂CuO₂–LiClO₄ films were evaluated by differential scanning calorimetry and thermogravimetric analysis. The refractive index, band‐gap energy, and optical dispersion were examined with UV–visible spectroscopy. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 45852.     

Effect of Adding Transition Metals to Copper on the Dehydrogenation Reaction of Ethanol

The present work aims to investigate the effect adding Ag, Co, Ni, Cd and Pt to copper on ethanol dehydrogenation. The catalysts synthesized by deposition–precipitation method were characterized using various physicochemical methods such as N₂ adsorption–desorption, TPR, SEM–EDX, XRD, XPS and TGA–DSC-MS. Catalytic evaluation results revealed that the predominant product of the reaction was acetaldehyde. Monometallic copper or mixed with Cd, Ag or Co show good catalytic performances. Adding nickel to copper improves the process conversion but reduces acetaldehyde selectivity, giving rise to methane in produced hydrogen. Pt-Cu/SiO₂ catalyst guides the reaction towards diethyl ether. Time on stream tests performed during 12 h at 260 °C, showed that adding Cd to Cu enhances its stability by over 30% of conversion, this is explained by the reduction of copper crystallites sintering, which makes Cd-Cu/SiO₂ a promising catalyst for the production of acetaldehyde by ethanol dehydrogenation.

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133Cs and 23Na MAS NMR Spectroscopy of Molybdate Crystallization in Model Nuclear Glasses

Sodium borosilicate base glasses modeled on French nuclear waste materials were prepared to test the dependence of crystallization product quantity and distribution on cesium‐ and molybdenum‐loading and glass cooling rate. Scanning electron microscopy shows the presence of micrometer‐sized domains of Mo‐rich crystalline precipitates. X‐ray diffraction patterns are complex but reveal the presence of sodium molybdates and CsNaMoO₄·2H₂O. ¹³³Cs and ²³Na magic‐angle spinning NMR spectroscopy exhibit distinct peaks for glassy and crystalline phases which can be quantified to obtain the identities of the individual compounds that are formed as well as the fractions of these nuclei in particular crystalline phases. In these model systems, 1 mol% Mo can be entirely incorporated into the glassy network whereas 2.5 and 5 mol% Mo produce significant quantities of crystalline phases, with little dependence on cooling rate. Cesium content appears to have a weak influence on crystallization behavior. Sodium molybdate and sodium‐cesium molybdate hydrate are the dominant devitrification phases in all cases.     

A flexible air separation process: 1. Design and steady-state optimizations

The flexible operation of energy-intensive processes, such as cryogenic air separation, has economic potential due to increasing fluctuations of the electricity markets. Multiproduct air separation processes with high ratios of liquid product are very promising for flexible operation due to storable products. We present a process design with an integrated liquefication cycle and liquid assist operation, that facilitates a high liquid product ratio and a flexible process operation. We use a mechanistic dynamic process model in steady-state process optimizations covering the wide operational range of the proposed process. The optimization results show that the power demand can be varied in a range from 3.5 to 28 MW without violating operational constraints by changing the nitrogen and oxygen production rates. Thus, the proposed process is a promising air separation candidate for flexible operation with respect to fluctuating electricity markets.