Loading…

Modeling and optimization of Sb and N resonance states effect on the band structure of mismatched III-N-V alloys using artificial neural networks

•Modeling of the band gap energy of GaNSbAs by Double Band Anticrossing method.•Modeling of the band gap energy of GaNSbAs by Artificial Neural Networks method.•Prediction of the absorption coefficient of the GaNSbAs deformed by ANN method.•Effect of pressure and temperature on the optical propertie...

Full description

Saved in:
Bibliographic Details
Published in:Materials science & engineering. B, Solid-state materials for advanced technology Solid-state materials for advanced technology, 2023-04, Vol.290, p.116312, Article 116312
Main Authors: Tarbi, Amal, Chtouki, Tarek, El kouari, Youssef, Erguig, Hassane, Migalska-Zalas, Anna, Aissat, Abdelkader
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•Modeling of the band gap energy of GaNSbAs by Double Band Anticrossing method.•Modeling of the band gap energy of GaNSbAs by Artificial Neural Networks method.•Prediction of the absorption coefficient of the GaNSbAs deformed by ANN method.•Effect of pressure and temperature on the optical properties of GaNSbAs deformed.•Optimization of optical properties for optoelectronic applications. The physical properties of the low bandgap III-V-N-Sb semiconductor elaborated on a GaAs substrate were modeled. The effect of deformation owing to lattice mismatch was considered. The artificial neural network method was used to predict the bandgap energy of the quaternary GaNySbzAs1-y-z, which showed high accuracy (RMSEANN = 0.02 and R2ANN = 99.56 %) and can replace the double band anticrossing model DBAC. The quaternary lattice disagreement, which is rich in Nitrogen and Antimony, makes it possible to design good absorbers. For Sb = 15 %, adding 1 % N increases the absorption coefficient by 1.51 × 104 cm−1. The effects of temperature and pressure on the variation of the absorption coefficient were also studied. The development of the robust artificial neural network based on the Levenberg-Maquardt backpropagation algorithm allows to estimate in a non-linear and precise way the energy of the band gap of the deformed material GaNySbzAs1-y-z, while minimizing the computational cost.
ISSN:0921-5107
1873-4944
DOI:10.1016/j.mseb.2023.116312