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Accelerating Temperature-Dependent Optical Response Prediction in Truncated Pyramidal GaN/AlN Quantum Dots via Polynomial Ridge Regression

Year: 2026

Type: article

Abstract: A polynomial Ridge regression model is proposed to accelerate the prediction of temperature-dependent optical responses in a GaN/AlN truncated-pyramidal quantum dot. Reference transition energies were obtained at four temperatures (0, 100, 300, and 500 K) using a combination of coordinate-transformation and finite-difference methods. Leave-one-temperature-out cross-validation was used to select a second-order model with λ=0.178, yielding an NRMSE of 0.0335 and an R2 of 0.9923. The predictions at 200 and 400 K remain independently unvalidated, whereas comparison with an independent FDM calculation at 600 K gives an absolute transition-energy error of 0.41 meV (0.35%). The reconstructed spectra exhibit the expected temperature-dependent shifts. An inference speed-up of up to 2.66×107 was obtained for three additional temperatures, excluding model training and reference-data generation costs. These predictions have not been independently validated, and the small dataset limits conclusions regarding generalization. The approach is therefore presented as a preliminary surrogate demonstration for the investigated configuration.

Source: Nanomaterials

DOI: 10.3390/nano16211446

Authors: Tesnim Brahim, Adel Bouazra, Beriham Ibrahim Basha, Fatma Aouaini

Institutions: University of Monastir, Institut Supérieur d'Informatique et des Technologies de Communication de Hammam Sousse, University of Sousse, Princess Nourah bint Abdulrahman University

Language: English

Topic: GaN-based semiconductor devices and materials

Subfield: Condensed Matter Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

OpenAlex ID: W7225650796

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