Spray pressure variation effect on the properties of CdS thin films for photodetector applications

Herein, we report the photosensing property of CdS thin films. CdS thin films were coated onto glass substrates via a spray pyrolysis method using different spray pressures. Prepared films were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and optical and photoluminescence spectroscopy. XRD analysis demonstrated the growth of crystalline CdS films with crystallite sizes varying from 26 to 29 nm depending on the pressure. The SEM and EDAX analyses revealed nearly-stoichiometric CdS films with smooth surfaces and slight variation in grain morphology due to pressure changes. Optical measurements showed a direct bandgap varying from 2.37 eV to 2.42 eV due to pressure changes. A photodetector was also fabricated using the grown CdS films; the fabricated photodetector exhibited good performance depending on the spray pressure. A spray pressure of 1.5 GPa resulted in high photoresponsivity and external quantum efficiency.     

Application of EPR-MOGA in computing the liquefaction-induced settlement of a building subjected to seismic shake

Accurate prediction of the liquefaction-induced settlement (\({S}_{\mathrm{lc}}\)) is an essential requirement for a good design of buildings resting on liquefiable ground and subjected to seismic shake. However, prediction of the \({S}_{\mathrm{lc}}\) is not straightforward process and it requires advanced soil models and calibrated soil parameters that are not readily available for designers/practitioners. In addition, the available empirical models to estimate the \({S}_{\mathrm{lc}}\) have been developed using either classical regression analysis or multivariate adaptive regression splines and such techniques produce complicated models. Also, these empirical models have been developed utilizing results of numerical modelling. To overcome these limitations, novel model has been developed in this paper utilizing robust regression analysis driven by artificial intelligence called the evolutionary polynomial regression analysis. The new model has been developed using centrifuge results (real laboratory measurements) and can be easily used to accurately estimate the liquefaction induced settlement. The developed model scored a mean absolute error, root mean square error, mean, standard deviation of the predicted to measured values, coefficient of determination, \(a20 - \mathrm{index}\), and EPR coefficient of determination of 2.12 cm, 2.84 cm, 1.06, 0.19, 0.98, 0.77, and 97%, respectively, for the learning data and 1.73 cm, 3.31 cm, 0.99, 0.17, 0.97, 0.75, and 97%, respectively, for the examination data. The developed model has also been used in a parametric study to provide an insight into the sensitivity of the \({S}_{\mathrm{lc}}\) to the foundation width, building height, pressure applied on the foundation, thickness and relative density of the liquefiable layer, and earthquake intensity. The results obtained from the parametric study are reasonable and in agreement with previous studies in the literature. Thus, the developed model can be employed to optimize designs and to reduce design costs as it does not require complicated analyses and/or expensive computational facilities.

     

Investigation of structural,optical, electrical,and magnetic properties of Fe-doped La0.7Sr0.3MnO3 manganites

In this work, the physical properties of nanocrystalline samples of La_0.7Sr_0.3Mn_1−xFe_xO₃ (0.0 ≤ x ≤ 0.20) perovskite manganites synthesized by the reverse micelle (RM) technique were explored in detail. The phase purity, crystal structure, and crystallite size of the samples were determined using X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy. All the samples had rhombohedral crystal structure and crystallite size increased with increase in Fe content in La_0.7Sr_0.3MnO₃. The scanning electron micrographs (SEMs) exhibited smooth surface morphology and nonuniform shape of the particles. The optical properties studied using UV-visible absorption spectroscopy revealed a decrease in the absorbance and optical band gap with an increase in Fe content in La_0.7Sr_0.3MnO₃ compound. The temperature-dependent resistivity measurements revealed semiconducting nature of x = 0 and 0.1 samples up to the studied temperature range, while a metal-to-insulator transition was observed at higher Fe doping. Magnetic studies revealed weak ferromagnetism in all the samples and a reduction in the maximum magnetization with an increase in Fe content. A close correlation between electrical transport and magnetic properties was observed with the doping of Fe ion in La_0.7Sr_0.3MnO₃ at Mn site. These results advocate strong interactions associated with the double exchange mechanism among Fe³⁺ and Mn³⁺ ions.     

Hybrid Secure Equivalent Computing Model for Distributed Computing Applications

Wireless Personal Communications - Distributed computing applications provide concurrent processing and services executed from different systems through a common cloud platform. However, without...     

Boosting the activity of FeOOH via integration of ZIF-12 and graphene to efficiently catalyze the oxygen evolution reaction

Transition metal oxyhydroxides have been used as promising electrocatalysts for water splitting however, their catalytic activity is restricted due to low surface area and poor conductivity. Herein, we report novel composite FeOOH@ZIF-12/graphene composite as electrocatalyst for water oxidation, whereby ZIF-12 provide extra surface for the FeOOH dispersion whilst graphene act as excellent electron mediator. The composite shows a low overpotential value of 291 mV to attain a current density of 10 mA cm^?2 and a low Tafel slope value of 78 mV dec^?1. The catalyst offers a maximum current density of 101 mA cm^?2, while it gives a turnover frequency (TOF) value of 0.031 s^?1 at an overpotential of 291 mV only. The excellent activity and remarkable stability of composite is attributed to highly conductive and porous support.     

Bond graph modeling,design and experimental validation of a photovoltaic/fuel cell/ electrolyzer/battery hybrid power system

This work presents a complete bond graph modeling of a hybrid photovoltaic-fuel cell-electrolyzer-battery system. These are multi-physics models that will take into account the influence of temperature on the electrochemical parameters. A bond graph modeling of the electrical dynamics of each source will be introduced. The bond graph models were developed to highlight the multi-physics aspect describing the interaction between hydraulic, thermal, electrochemical, thermodynamic, and electrical fields. This will involve using the most generic modeling approach possible for managing the energy flows of the system while taking into account the viability of the system. Another point treated in this work is to propose. In this work, a new strategy for the power flow management of the studied system has been proposed. This strategy aims to improve the overall efficiency of the studied system by optimizing the decisions made when starting and stopping the fuel cell and the electrolyzer. It was verified that the simulation results of the proposed system, when compared to simulation results presented in the literature, that the hydrogen demand is increased by an average of 8%. The developed management algorithm allows reducing the fuel cell degradation by 87% and the electrolyzer degradation by 65%. As for the operating time of the electrolyzer, an increment of 65% was achieved, thus improving the quality of the produced hydrogen. The Fuel Cell's running time has been decreased by 59%. With the ambition to validate the models proposed and the associated commands, the development of this study gave rise to the creation of an experimental platform. Using this high-performance experimental platform, experimental tests were carried out and the results obtained are compared with those obtained by simulation under the same metrological conditions.     

Sol-Gel Preparation and Spectroscopic Properties of Modified Sodium Silicate /Tartrazine Dye Nanocomposite

Silicon - Thin film nanocomposites of sodium silicate (80 SiO2 –20 Na2O)/ tartrazine dye (E102) prepared using sol gel process in acidic system. The change in the physicochemical properties...