Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Rational construction of staggered InGaN quantum wells for efficient yellow light-emitting diodes

View through CrossRef
High-efficiency InGaN-based yellow light-emitting diodes (LEDs) with high brightness are desirable for future high-resolution displays and lighting products. Here, we demonstrate efficient InGaN-based yellow (∼570 nm) LEDs with optimized three-layer staggered quantum wells (QWs) that are grown on patterned sapphire substrates. Numerical simulations show that the electron–hole wavefunction overlap of staggered InGaN QWs with high In content exhibits a 1.7-fold improvement over that of square InGaN QWs. At the same injection current, LEDs with staggered QWs exhibit lower forward voltages and narrower full widths at half maximum than LEDs with square QWs. The light output power and external quantum efficiency of a staggered QW LED are 10.2 mW and 30.8%, respectively, at 15 mA. We combine atomic probe tomography (APT), time-resolved photoluminescence (TRPL), and transmission electron microscopy (TEM) with energy-dispersive x-ray (EDX) mapping spectroscopy to shed light on the origin of enhanced device performance. APT results confirm the staggered In profile of our designed staggered QWs structure, and TRPL results reveal decreased defect-state carrier trapping in staggered QWs. Furthermore, TEM with EDX mapping spectroscopy supports the viewpoint that staggered QWs exhibit uniform elemental distribution and improved crystal quality. Together, these factors above contribute to enhanced LED performance. Our study shows that staggered InGaN QWs provide a promising strategy for the development of LEDs that are efficient in the long-wavelength region.
Title: Rational construction of staggered InGaN quantum wells for efficient yellow light-emitting diodes
Description:
High-efficiency InGaN-based yellow light-emitting diodes (LEDs) with high brightness are desirable for future high-resolution displays and lighting products.
Here, we demonstrate efficient InGaN-based yellow (∼570 nm) LEDs with optimized three-layer staggered quantum wells (QWs) that are grown on patterned sapphire substrates.
Numerical simulations show that the electron–hole wavefunction overlap of staggered InGaN QWs with high In content exhibits a 1.
7-fold improvement over that of square InGaN QWs.
At the same injection current, LEDs with staggered QWs exhibit lower forward voltages and narrower full widths at half maximum than LEDs with square QWs.
The light output power and external quantum efficiency of a staggered QW LED are 10.
2 mW and 30.
8%, respectively, at 15 mA.
We combine atomic probe tomography (APT), time-resolved photoluminescence (TRPL), and transmission electron microscopy (TEM) with energy-dispersive x-ray (EDX) mapping spectroscopy to shed light on the origin of enhanced device performance.
APT results confirm the staggered In profile of our designed staggered QWs structure, and TRPL results reveal decreased defect-state carrier trapping in staggered QWs.
Furthermore, TEM with EDX mapping spectroscopy supports the viewpoint that staggered QWs exhibit uniform elemental distribution and improved crystal quality.
Together, these factors above contribute to enhanced LED performance.
Our study shows that staggered InGaN QWs provide a promising strategy for the development of LEDs that are efficient in the long-wavelength region.

Related Results

Advanced frameworks for fraud detection leveraging quantum machine learning and data science in fintech ecosystems
Advanced frameworks for fraud detection leveraging quantum machine learning and data science in fintech ecosystems
The rapid expansion of the fintech sector has brought with it an increasing demand for robust and sophisticated fraud detection systems capable of managing large volumes of financi...
Burying non-radiative defects in InGaN underlayer to increase InGaN/GaN quantum well efficiency
Burying non-radiative defects in InGaN underlayer to increase InGaN/GaN quantum well efficiency
The insertion of an InGaN underlayer (UL) is known to strongly improve the performance of InGaN/GaN quantum well (QW) based blue light emitting diodes (LEDs). However, the actual p...
Improving the quantum well properties with n-type InGaN/GaN superlattices layer
Improving the quantum well properties with n-type InGaN/GaN superlattices layer
InGaN/GaN quantum wells have been grown by metal-organic chemical vapor deposition. InGaN/GaN quantum well with n-type InGaN/GaN thin layer or InGaN/GaN superlattice layer were stu...
Observation of Band Gap Energy Fluctuation of Microcrystalline InGaN:Zn
Observation of Band Gap Energy Fluctuation of Microcrystalline InGaN:Zn
ABSTRACTThis paper describes a comparison of the optical properties of InGaN:Zn with that of GaN:Zn and InGaN by measuring photoluminescence excitation (PLE) spectra at 77 K. It is...
Advancements in Quantum Computing and Information Science
Advancements in Quantum Computing and Information Science
Abstract: The chapter "Advancements in Quantum Computing and Information Science" explores the fundamental principles, historical development, and modern applications of quantum co...
Strain-engineered N-polar InGaN nanowires: towards high-efficiency red LEDs on the micrometer scale
Strain-engineered N-polar InGaN nanowires: towards high-efficiency red LEDs on the micrometer scale
The absence of efficient red-emitting micrometer-scale light emitting diodes (LEDs), i.e., LEDs with lateral dimensions of 1 μm or less is a major barrier to the adoption of microL...
Enhancement of Structural and Optical Characteristics of Nanostructured InGaN Using Electrochemical Etching
Enhancement of Structural and Optical Characteristics of Nanostructured InGaN Using Electrochemical Etching
In this work, we used an alternating current electrochemical etching technique to fabricate nanostructured InGaN in potassium hydroxide, which serves as an electrolyte. The effects...
Integrating quantum neural networks with machine learning algorithms for optimizing healthcare diagnostics and treatment outcomes
Integrating quantum neural networks with machine learning algorithms for optimizing healthcare diagnostics and treatment outcomes
The rapid advancements in artificial intelligence (AI) and quantum computing have catalyzed an unprecedented shift in the methodologies utilized for healthcare diagnostics and trea...

Back to Top