The structural, optical and photoelectrical properties of fabricated diffusion heterojunction (HJ) solar cell, from n-type c-Si wafer of [400] direction with Boron, has been studied. AgAl alloys was used because of its properties that affect as a good connection materials. TiO2 has been used as a reflecting layer to increase the absorption radiation. The HJ has direct allowed energy gap equal to 3.1 eV. The c-Si/B HJ solar cell yielded has an active area conversion efficiency of 16.4% with an open circuit voltage of (Voc) 0.592V, short circuit current (Isc) of 2.042mA, fill factor (F.F) of 0.682 and % =10.54.

Fabrication of solar cell prepared by thermal spray and vacuum thermal evaporation method on silicon wafer(n-type) and studying its efficiency. The film have been deposited on three layers(ZnO then CdS and CdTe) on Si and glass respectively.Direct energy gap was calculated and equal to (4.3,3.4,3)eV and indirect energy gap equal to (3.5,2.5,1.5)eV respectively . Efficiency was calculated for the cell of area 2cm2 it was equal to 0.14%.

The purpose of this paper is to apply different transportation models in their minimum and maximum values by finding starting basic feasible solution and finding the optimal solution. The requirements of transportation models were presented with one of their applications in the case of minimizing the objective function, which was conducted by the researcher as real data, which took place one month in 2015, in one of the poultry farms for the production of eggs

A new series polymers was synthesized from reaction starting material Bisacodyl A or [(2-Pyridinylmethylene) di-4, 1-phenylene di acetate] with hydrogen bromide, then the products were polymerized by addition polymerization from used adipoyl and glutaroyl chloride. The structure of these compounds was characterized by FT-IR, melting points, TLC, X-Ray, DSC and 1H-NMR for starting material. These compounds were also screened for their antibacterial activists?

In this study, three strengthening techniques, near-surface mounted NSM-CRFP, NSM-CFRP with externally bonding EB-CFRP, and hybrid CFRP with circularization were studied to increase the seismic performance of existing RC slender columns under lateral loads. Experimentally, 1:3 scale RC models were studied and subjected to both lateral static load and seismic excitation. In the dynamic test, a model was subjected to El Centro 1940 NS earthquake excitation by using a shaking table. According to the test results, the strengthening techniques showed a significant increase in load carrying capacity, of about 86.6%, and 46.6%, for circularization and NSM-CFRP respectively, of the reference unstrengthened columns. On the other hand, column

In this work, polyvinylpyrrolidone (PVP), Multi-walled carbon nanotubes (MWCNTs) nanocomposite was prepared and hybrid with Graphene (Gr) by casting method. The morphological and optical properties were investigated. Fourier Transformer-Infrared (FT-IR) indicates the presence of primary distinctive peaks belonging to vibration groups that describe the prepared samples. Scanning Electron Microscopy (SEM) images showed a uniform dispersion of graphene within the PVP-MWCNT nanocomposite. The results of the optical study show decrease in the energy gap with increasing MWCNT and graphene concentration. The absorption coefficient spectra indicate the presence of two absorption peaks at 282 and 287 nm attributed to the π-π* electronic tr

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc