Mostafa Mohamed Salaheldin Abdelkhalek

A. Zekry; Mohamed Abouelatta; Ahmed Shaker; Fathy Z. Amer; Roaa I. Mubarak

14/11/2022

https://ieeexplore.ieee.org/document/9938572

Mostafa Mohamed Salaheldin Abdelkhalek

AHMED SHAKER; ABDELHALIM ZEKRY; MOHAMED ABOUELATTA

30/08/2022

https://www.mdpi.com/1996-1073/15/17/6326/htm

Mostafa Mohamed Salaheldin Abdelkhalek

A. Zekry; Mohamed Abouelatta; Ahmed Shaker

03/08/2022

https://link.springer.com/chapter/10.1007/978-981-19-1607-6_60

Mostafa Mohamed Salaheldin Abdelkhalek

Abdelhalim Zekry , Mohamed Abouelatta , Ahmed Shaker , Fathy Z. Amer , Roaa I. Mubarak

21/06/2022

https://www.mdpi.com/2073-4352/12/7/878

Mostafa Mohamed Salaheldin Abdelkhalek

MARWA SAYED SALEM BASYONI; AHMED SHAKER; ABDELHALIM ZEKRY, (Member, IEEE); MOHAMED ABOUELATTA; MOHAMMAD T. ALSHAMMARI; KAWTHER A. AL-DHLAN; AND CHRISTIAN GONTRAND

13/09/2021

https://ieeexplore.ieee.org/abstract/document/9541403

Mostafa Mohamed Salaheldin Abdelkhalek

Fathy Z. Amer; Roaa I. Mubarak

01/09/2020

This paper presents a study of a tandem Perovskite/CIGS cell, its performance parameters, and the effect of temperature variations on these parameters. The variation of each sub-cell short-circuit current density value with absorption thickness of perovskite (top) sub-cell has been done to find the matching point, as the two sub-cells equivalent to two series cells. The combining of two sub-cells shows the ability to absorb photons spectrum up to 1120 nm and perform a conversion efficiency about 30.5% (at room temperature) higher than each sub-cell. The variation of temperature from 260 K up to 360 K shows that the power conversion efficiency decreases almost linearly from 33.5% to 26.6%. The validity of the proposed tandem cell is proved by comparing its results with the recent published results. The proposed tandem cell shows one of the highest power conversion efficiency relative to the recent published results.

Mostafa Mohamed Salaheldin Abdelkhalek

Mohamed Abouelatta, Ahmed Shaker

01/10/2019

Perovskite solar cells (PSCs) have attracted considerable attention as a competitor technology in solar cells due to the rapid enhancement in their power conversion efficiency (PCE) in recent years. PSCs have several advantages such as their bandgap tunability, lower cost, tolerance of high impurities, protracted diffusion length and wide optical absorption. In this paper, simulation of PSCs with copper oxide as a hole transport material (HTM) and different electron transport materials (ETMs) has been presented. The proposed materials are a replacement to the ordinary hole and ETMs; such as the titanium dioxide and the expensive spiro-OMeTAD. In addition, a comprehensive study for optimizing the features and parameters of the PSCs, such as the thickness and defect density of the perovskite layer, the doping concentrations, and the bandgap energy, has been introduced. The simulation and the performance evaluation of the designed PSCs have been carried out using SCAPS-1D. The results show that mixed halide PSC with zinc oxysulfide as ETM and copper oxide as HTM has an enhanced performance with a PCE of up to 30.82%.

Mostafa Mohamed Salaheldin Abdelkhalek

Mohamed Abouelatta; Ahmed Shaker

01/02/2019

https://www.sciencedirect.com/science/article/abs/pii/S0030402618315511

Mostafa Mohamed Salaheldin Abdelkhalek

Hossam E. Abou-Bakr Hassan

01/12/2018

Parametric faults in analogue circuits cause system performance degeneration and are hard to be detected. There are no clear boundaries between fault-free and faulty circuit output due to components tolerances. Therefore, a machine learning classifier needs to be learned to correctly classify circuit outputs. In this paper, the parametric fault detection method of analogue circuits based on the support vector machine (SVM) classifier is developed. The proper choice of kernel parameters for the SVM in the training process improves the classification accuracy. The penalty parameter and kernel function parameters for the radial basis function (RBF) kernel should be optimized. In addition, the Bayesian optimization methodology is used to select the hyperparameters for the SVM classifier. The Biquad filter, one of the benchmark circuits, is utilized to validate the proposed method and compare it with the other methods. Using downside minimum size detectable fault (DMSDF) and upside minimum size detectable fault (UMSDF) values, the method gives good enhancements in detecting faults due to minor changes in components values above or down the nominal component values.