Enhancing Light Emission with Electric Fields in Polar Nitride Semiconductors

Significant effort has been devoted to mitigating polarization fields in nitride LEDs, as these fields are traditionally viewed as detrimental to light emission, particularly for red emission. Contrary to this prevailing notion, we demonstrate that strong polarization fields can enhance the optical-transition strength of red-emitting AlInGaN quantum wells, which has been historically challenging to achieve. By leveraging machine-learning surrogate models trained on multiscale quantum-mechanical simulations, we globally explore the heterostructure design space and uncover that larger fields correlate with higher electron–hole overlap. This relation arises from the quantum-confined Stark effect, which enables thinner wells without requiring higher indium compositions, thus overcoming a key limitation in nitride epitaxy. Structural and compositional engineering of internal fields offers a unique dimension for designing polychromatic nitride LEDs, crucial for miniaturizing LED pixels to the micrometer scale for extended-reality and biomedical applications. Broadly, our work demonstrates how machine learning can uncover unexpected paradigms for semiconductor design.

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Publication Details

Journal
ACS Photonics
Published
2025-05-08
DOI
https://doi.org/10.1021/acsphotonics.5c00133
Primary Topic
GaN-based semiconductor devices and materials
Type
article
Field-Weighted Citation Impact
0.00

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article

Enhancing Light Emission with Electric Fields in Polar Nitride Semiconductors

Emmanouil Kioupakis, Nick Pant, R. Armitage
ACS Photonics
GaN-based semiconductor devices and materials
article

Enhancing Light Emission with Electric Fields in Polar Nitride Semiconductors

Emmanouil Kioupakis, Nick Pant, R. Armitage
article en

Abstract

Significant effort has been devoted to mitigating polarization fields in nitride LEDs, as these fields are traditionally viewed as detrimental to light emission, particularly for red emission. Contrary to this prevailing notion, we demonstrate that strong polarization fields can enhance the optical-transition strength of red-emitting AlInGaN quantum wells, which has been historically challenging to achieve. By leveraging machine-learning surrogate models trained on multiscale quantum-mechanical simulations, we globally explore the heterostructure design space and uncover that larger fields correlate with higher electron–hole overlap. This relation arises from the quantum-confined Stark effect, which enables thinner wells without requiring higher indium compositions, thus overcoming a key limitation in nitride epitaxy. Structural and compositional engineering of internal fields offers a unique dimension for designing polychromatic nitride LEDs, crucial for miniaturizing LED pixels to the micrometer scale for extended-reality and biomedical applications. Broadly, our work demonstrates how machine learning can uncover unexpected paradigms for semiconductor design.

ACS PhotonicsVol. 12(6)
University of Michigan (US)
Office of Science, Office of Energy Efficiency and Renewable Energy, Natural Sciences and Engineering Research Council of Canada
Affordable and clean energy
Openalex Percentile: Top 94%
GaN-based semiconductor devices and materials
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