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Optimal Identification of Be-Doped Al0.29Ga0.71As Schottky Diode Parameters Using Dragonfly Algorithm: A Thermal Effect Study

Filali, Walid; Amrani, Rachid; Garoudja, Elyes; Oussalah, Slimane; Lekoui, Fouaz; Oukerimi, Zineb; Sengouga, Nouredine; Henini, Mohamed

Optimal Identification of Be-Doped Al0.29Ga0.71As Schottky Diode Parameters Using Dragonfly Algorithm: A Thermal Effect Study Thumbnail


Authors

Walid Filali

Rachid Amrani

Elyes Garoudja

Slimane Oussalah

Fouaz Lekoui

Zineb Oukerimi

Nouredine Sengouga



Abstract

In this work, a recent heuristic method called Dragonfly Algorithm (DA) has been employed for the first time to investigate the temperature effect on the Schottky diode electrical parameters. Beryllium-doped Al0.29Ga0.71As Schottky diodes grown by molecular beam epitaxy (MBE) have been used to validate the suggested method. The proposed approach is based on the analysis of current-voltage-temperature (I–V-T) and capacitance-voltage (C–V) characteristics. Furthermore, the interface state density (Nss) as function of the difference between the surface state energy and valence band energy (Ess – Ev) was determined. The obtained results demonstrate the high efficiency of this strategy to accurately determine the electrical parameters and investigate their temperature dependency. This efficiency can be clearly remarked from the well fit between both predicted and measured current characteristics.

Citation

Filali, W., Amrani, R., Garoudja, E., Oussalah, S., Lekoui, F., Oukerimi, Z., …Henini, M. (2021). Optimal Identification of Be-Doped Al0.29Ga0.71As Schottky Diode Parameters Using Dragonfly Algorithm: A Thermal Effect Study. Superlattices and Microstructures, 160, Article 107085. https://doi.org/10.1016/j.spmi.2021.107085

Journal Article Type Article
Acceptance Date Oct 31, 2021
Online Publication Date Nov 3, 2021
Publication Date 2021-12
Deposit Date Nov 4, 2021
Publicly Available Date Nov 4, 2022
Journal Superlattices and Microstructures
Print ISSN 0749-6036
Electronic ISSN 1096-3677
Peer Reviewed Peer Reviewed
Volume 160
Article Number 107085
DOI https://doi.org/10.1016/j.spmi.2021.107085
Public URL https://nottingham-repository.worktribe.com/output/6611105
Publisher URL https://www.sciencedirect.com/science/article/abs/pii/S0749603621002834

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