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Peer-reviewedCC BY 4.0Nanomaterials

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

  • Tesnim Brahim1
  • Adel Bouazra1,2
  • Beriham Ibrahim Basha3
  • Fatma Aouaini3
  1. 1Condensed Matter and Nanoscience Laboratory, Faculty of Sciences of Monastir, University of Monastir, Monastir 5019, Tunisia
  2. 2Higher Institute of Computer Science and Communication Technologies of Sousse, University of Sousse, Sousse 4011, Tunisia
  3. 3Department of Physics, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
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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.

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Cite

BibTeXRIS
BibTeX
@article{brahim2026accelerating,
  title = {{Accelerating Temperature-Dependent Optical Response Prediction in Truncated Pyramidal GaN/AlN Quantum Dots via Polynomial Ridge Regression}},
  author = {Tesnim Brahim and Adel Bouazra and Beriham Ibrahim Basha and Fatma Aouaini},
  journal = {Nanomaterials},
  year = {2026},
  month = nov,
  doi = {10.3390/nano16211446},
  url = {https://www.mdpi.com/2079-4991/16/21/1446},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Accelerating Temperature-Dependent Optical Response Prediction in Truncated Pyramidal GaN/AlN Quantum Dots via Polynomial Ridge Regression
AU  - Tesnim Brahim
AU  - Adel Bouazra
AU  - Beriham Ibrahim Basha
AU  - Fatma Aouaini
PY  - 2026
DA  - 2026/11/08
JO  - Nanomaterials
DO  - 10.3390/nano16211446
UR  - https://www.mdpi.com/2079-4991/16/21/1446
AB  - 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.
SN  - 2079-4991
ER  -