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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.
This work analyzes the effect of hydrostatic pressure on the predicting excitonic optical response of a 2D Ultra-thin GaAs-system. The data are generated from a numerical model incorporating quantum confinement and excitonic effects, capturing the system's response to incident photon energy and applied pressure. To red...
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...
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