Author

A. El Moussaouy

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Jul 2026

Predicting electronic properties of cylindrical, spherical, and toroidal quantum dots with neural networks

A hybrid approach combining the finite difference method to solve the Schrödinger equation and artificial intelligence models was used to predict the electronic properties of the quantum dot, offering a faster and more efficient alternative for modeling QDs.

M. el Hadi, M. Hbibi, S. Chouef et al. · Quantum Machine Intelligence · 0 citations

Open access Aug 2026

Machine Learning Prediction of Optical Absorption in GaAs 2D Nanostructure under Hydrostatic Pressure

This work focuses on the modeling and prediction of the optical absorption coefficient in GaAs 2D nanostructure subjected to hydrostatic pressure. The database is generated from numerical calculations describing the optical absorption of exciton confined in GaAs 2D nanostructure. The obtained data are exploited to deve...

I. Lamrini, M. Hbibi, S. Chouef et al. · Materials Science Forum · 0 citations