arXiv subjects

Quan-Shan Liu

Publications and source records attributed to Quan-Shan Liu.

5 recordsLinked to original sources

arXiv2026

Thermal Stability and Carrier Recombination Kinetics in InGaN/GaN Multiple Quantum Wells under High-Temperature Annealing

The thermal stability and carrier recombination kinetics of an as-received InGaN/GaN multiple quantum well (MQW) structure, capped with a protective AlN thin film, are studied following a series of thermal annealings at temperatures between 500 deg C and 1100 deg C. Under 325 nm focused laser excitation at room temperature, the sample's photoluminescence (PL) spectrum exhibits three emission bands: an ultraviolet peak at 363 nm, a blue peak at 455 nm, and a yellow peak at 565 nm. We find that the MQW's 455 nm emission is preserved after annealing at 1100 deg C. Moreover, room-temperature PL excitation (PLE) and time-resolved PL (TRPL) have been investigated to shed light on the sample's energy-transfer mechanisms and emission decay characteristics. Power-dependent PL spectra analysis shows that the carrier recombination mechanism of the MQW's emission has not been affected by thermal treatment. Rate equation modelling and chromaticity coordinate analysis also show limited thermal impact on the calculated equivalent emission lifetime and emissive colour. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) analysis has been performed, further evidencing the preservation of the MQW structure in the annealed sample.

physics.app-ph↗

arXiv2025

Shallow Au Implantation Into Silicon-On-Insulator Slot Ring Resonator Waveguide Devices

The optical transmission spectra of a series of micro-ring resonators (MRRs) are studied following the implantation of gold (Au) ions and subsequent thermal annealing, at temperatures between 500 °C and 700 °C. Whilst we find that this process leads to the ready formation of Au nanoparticles (NPs) on the MRR surface, the cavity optical properties; Q-factor and extinction ratio (ER) are severely degraded, for annealing between 500 °C and 600 °C, but recover again for annealing at 650 °C. For an equivalent (control) MRR, which received no Au implantation, thermal annealing alone was also found to degrade the cavity performance.

physics.optics↗

arXiv2021

High-Intensity and Uniform Red-Green-Blue Triple Reflective Bands Achieved by Rationally-Designed Ultrathin Heterostructure Photonic Crystals

The relationships between material constructions and reflective spectrum patterns are important properties of photonic crystals. One particular interesting reflectance profile is a high-intensity and uniform three-peak pattern with peak positions right located at the red, green, and blue (RGB, three original colors) region. For ease of construction, a seek for using one-dimensional photonic crystals to achieve RGB triple reflective bands is a meaningful endeavor. Only very limited previous studies exist, all relying on traditional periodic photonic crystals (PPCs) and of large thickness. The underlying physical principles remain elusive, leaving the question of thickness limit to achieve RGB bands unaddressed. Here, we present the first detailed work to explore the thickness limit issue based on both theoretical and experimental investigation. A set of heuristically derived design principles are used to uncover that the break of translational symmetry, thus introducing heterostructure photonic crystals (HPCs), is essential to reduce the total optical path difference (OPD) to ~ 3200nm (the theoretical limit) while still exhibiting high-quality RGB bands. A systematic experiment based on a 12-layer heterostructure construction was performed and well confirmed the theoretical predictions. The associated three-peak properties are successfully used to realize quantum dot fluorescent enhancement phenomena. Furthermore, the HPC exhibits unusually stability against solvent stimulus, in strong contrast to typical behaviors reported in PPCs. Our work for the first time proposes and verifies important rational rules for designing ultrathin HPCs toward RGB reflective bands, and provides insights for a wider range of explorations of light manipulation in photonic crystals.

physics.optics↗

arXiv2021

Two distinct approaches to tune multiple reflective bands of one-dimensional photonic crystal at normal incidence

One-dimensional photonic crystals (1D PC) represent a class of periodic optical material, composed of alternating media with different dielectric constants along one direction. The most important property of 1D PCs is their photonic band-gap. However, multiple reflective bands are rarely reported in this research area. In this paper we demonstrate the tunability of multiple reflective bands in conventional 1D PC structure and 1D PC heterostructure. For both two types of 1D PC construction, positions of multiple reflective bands can be regulated under certain principles. In addition, structural color is revealed by transforming reflection spectra into CIE coordinates. It is indicated that the CIE coordinate shifts caused by multiple reflective bands behave quite different compared to those caused by one major photonic band-gap. The two approaches reported in this work may provide insights for the application of 1D PC in areas such as displays, sensors, and decoration.

physics.optics↗

arXiv2021

A General Machine Learning-based Approach for Inverse Design of One-dimensional Photonic Crystals Toward Targeted Visible Light Reflection Spectrum

Data-driven methods have increasingly been applied to the development of optical systems as inexpensive and effective inverse design approaches. Optical properties (e.g., band-gap properties) of photonic crystals (PCs) are closely associated with characteristics of their light reflection spectra. Finding optimal PC constructions (within a pre-specified parameter space) that generate reflection spectra closest to a targeted spectrum is thus an interesting and meaningful inverse design problem, although relevant studies are still limited. Here we report a generally effective machine learning-based inverse design approach for one-dimensional photonic crystals (1DPCs), focusing on visible light spectra which are of high practical relevance. For a given class of 1DPC system, a deep neural network (DNN) in a unified structure is first trained over data from sizeable forward calculations (from layer thicknesses to spectrum). An iterative optimization scheme is then developed based on a coherent integration of DNN backward predictions (from spectrum to layer thicknesses), forward calculations, and Monte Carlo moves. We employ this new approach to four representative 1DPC systems including periodic structures with two-, three-, and four-layer repeating units and a heterostructure. The approach successfully converges to solutions of optimal 1DPC constructions for various targeted spectra regardless of their exact achievability. As two demonstrating examples, inverse designs toward a specially constructed "rectangle-shaped" green-light or red-light reflection spectrum are presented and discussed in detail. Remarkably, the results show that the approach can efficiently find out optimal layer thicknesses even when they are far outside the range covered by the original training data of DNN.

physics.optics↗