arXiv subjects

Yongliang Chen

Publications and source records attributed to Yongliang Chen.

17 recordsLinked to original sources

arXiv2026

Facile hBN-hBN Interfacial Overlap Engineering for Enhanced Quantum Emitter Formation

Quantum emitters in two-dimensional materials, particularly hBN, are promising platforms for quantum technologies. However, achieving high-density emitters at predetermined locations while preserving optical quality remains challenging. Here, we introduce a facile, cost-effective double-layer all-dry transfer approach to deterministically create overlap regions between hBN flakes. These pre-defined capped regions exhibit a significantly enhanced emitter density, with up to a 15-fold increase compared to uncapped areas. Importantly, this method does not compromise emitter quality: emitters within overlap regions demonstrate excellent optical performance, including high signal-to-background and signal-to-noise ratios, large Debye-Waller factors, high brightness, and strong spectral stability. Possible defect configurations are also discussed to contextualize the observed emission characteristics. This scalable strategy enables preferential formation of quantum emitters in targeted regions, achieving higher densities than simple treatments such as plasma irradiation while avoiding the complexity of advanced fabrication techniques. The approach provides a practical pathway for integrating high-quality quantum emitters into scalable quantum photonic platforms.

cond-mat.mtrl-sci↗

arXiv2026

Nanoscale Fluorescence Thermometry: Probes, Recent Advances and Emerging Directions

The transition of materials and devices to nanometer, atomic, and quantum scales makes thermal characterization increasingly challenging, driving the need for advanced nanoscale thermometry. Fluorescence nanothermometry has emerged as a powerful approach, enabling remote, spatially resolved temperature measurements with sub-micrometer-to-nanometer precision across applications in nanoelectronics, microfluidics, and biological systems. In these systems, temperature is inferred from variations in fluorescence observables, including spectral position, intensity, linewidth, and excited-state dynamics. This review provides a comprehensive and critical overview of fluorescence nanothermometry, covering fundamental mechanisms, material platforms, recent advances, and emerging applications. It further presents a critical evaluation of key challenges and discusses emerging strategies and future research directions toward achieving robust, real-time thermometry. It is anticipated that this review will stimulate further advances in material platforms and system design, accelerating the development of accurate, scalable, and application-ready nanoscale thermometers.

physics.optics↗

arXiv2026

Superconductivity and Electron Correlations in Kagome Metal LuOs3B2

We report a comprehensive investigation of the physical properties of LuOs3B2, characterized by an ideal Os-based kagome lattice. Resistivity and magnetization measurements confirm the emergence of type-II bulk superconductivity with a critical temperature Tc=4.63 K. The specific heat jump and the calculated electron-phonon coupling parameter support a moderately coupled superconducting state. Electron correlation effects are supported by the enhanced Wilson ratios. First-principles calculations reveal hallmark features of kagome band structure, including Dirac points, van Hove singularities, and quasi-flat bands, primarily derived from the Os d orbitals. The inclusion of spin-orbit coupling opens a gap at the Dirac points, significantly altering the electronic properties. Furthermore, the superconductivity and electronic properties of isomorphic compounds are discussed. This work provides a thorough exploration of the superconducting and normal states of LuOs3B2, deepening the understanding of kagome superconductors.

cond-mat.supr-con↗

arXiv2025

Laser-Induced Heating in Diamonds: Influence of Substrate Thermal Conductivity and Interfacial Polymer Layers

Diamonds hosting color centers possess intrinsically high thermal conductivity; therefore, laser-induced heating has often received little attention. However, when placed on substrates with low thermal conductivity, localized heating of diamonds under laser excitation can become significant, and the presence of an interfacial polymer layer between substrate and diamond further amplifies this effect. Yet, the relationship between substrate thermal conductivity, polymer thickness, and laser heating remains to be established. Here, a systematic investigation is presented on laser-induced heating of silicon-vacancy diamond on substrates with varying thermal conductivity and interfacial polymer thickness. Results reveal that even at a low excitation power of 737~$μ$W/$μ$m$^2$, thin amorphous holey carbon -- the lowest-conductivity substrate ($\sim$0.2~W~m$^{-1}$~K$^{-1}$) studied -- exhibits substantial heating, while glass ($\sim$1.4~W~m$^{-1}$~K$^{-1}$) and polydimethylsiloxane (PDMS, $\sim$0.35~W~m$^{-1}$~K$^{-1}$) show noticeable heating only above 2.95~mW/$μ$m$^2$. For polymer interlayers, a thickness of just 2.2~$μ$m induces significant heating at 2.95~mW/$μ$m$^2$ and above, highlighting strong influence of both substrate and polymer thickness on local heating response. Experimental findings are further validated using COMSOL Multiphysics simulations with a steady-state 3D heat transfer model. These results provide practical guidance for substrate selection and sample preparation, enabling optimization of conditions for optical thermometry and quantum sensing applications.

cond-mat.mtrl-sci↗

arXiv2025

Quantum Emitters in Hexagonal Boron Nitride: Principles, Engineering and Applications

Solid-state quantum emitters, molecular-sized complexes releasing a single photon at a time, have garnered much attention owing to their use as a key building block in various quantum technologies. Among these, quantum emitters in hexagonal boron nitride (hBN) have emerged as front runners with superior attributes compared to other competing platforms. These attributes are attainable thanks to the robust, two-dimensional lattice of the material formed by the extremely strong B-N bonds. This review discusses the fundamental properties of quantum emitters in hBN and highlights recent progress in the field. The focus is on the fabrication and engineering of these quantum emitters facilitated by state-of-the-art equipment. Strategies to integrate the quantum emitters with dielectric and plasmonic cavities to enhance their optical properties are summarized. The latest developments in new classes of spin-active defects, their predicted structural configurations, and the proposed suitable quantum applications are examined. Despite the current challenges, quantum emitters in hBN have steadily become a promising platform for applications in quantum information science.

cond-mat.mtrl-sci↗

arXiv2024

Synthetic gain for electron-beam spectroscopy

Electron-beam microscopy and spectroscopy featuring atomic-scale spatial resolution have become essential tools used daily in almost all branches of nanoscale science and technology. As a natural supercontinuum source of light, free electrons couple with phonons, plasmons, electron-hole pairs, inter- and intra-band transitions, and inner-shell ionization. The multiple excitations, intertwined with the intricate nature of nanostructured samples, present significant challenges in isolating specific spectral characteristics amidst complex experimental backgrounds. Here we introduce the approach of synthetic complex frequency waves to mitigate these challenges in free-electron--light interaction. The complex frequency waves, created through causality-informed coherent superposition of real-frequency waves induced by free electrons, offer virtual gain to offset material losses. This amplifies and enhances spectral features, as confirmed by our electron energy loss and cathodoluminescence measurements on multi-layer membranes, suspended nanoparticles, and film-coupled nanostructures. Strikingly, we reveal that our approach can retrieve resonance excitation completely buried underneath the zero-loss peak, substantially enhance the quality of hyperspectral imaging, and resolve entangled multiple-photon-electron events in their quantum interaction. Our findings indicate the versatile utility of complex frequency waves in various electron-beam spectroscopy and their promising diagnostic capabilities in free-electron quantum optics.

physics.optics↗

arXiv2024

EarDA: Towards Accurate and Data-Efficient Earable Activity Sensing

In the realm of smart sensing with the Internet of Things, earable devices are empowered with the capability of multi-modality sensing and intelligence of context-aware computing, leading to its wide usage in Human Activity Recognition (HAR). Nonetheless, unlike the movements captured by Inertial Measurement Unit (IMU) sensors placed on the upper or lower body, those motion signals obtained from earable devices show significant changes in amplitudes and patterns, especially in the presence of dynamic and unpredictable head movements, posing a significant challenge for activity classification. In this work, we present EarDA, an adversarial-based domain adaptation system to extract the domain-independent features across different sensor locations. Moreover, while most deep learning methods commonly rely on training with substantial amounts of labeled data to offer good accuracy, the proposed scheme can release the potential usage of publicly available smartphone-based IMU datasets. Furthermore, we explore the feasibility of applying a filter-based data processing method to mitigate the impact of head movement. EarDA, the proposed system, enables more data-efficient and accurate activity sensing. It achieves an accuracy of 88.8% under HAR task, demonstrating a significant 43% improvement over methods without domain adaptation. This clearly showcases its effectiveness in mitigating domain gaps.

eess.SP↗

arXiv2023

Fiber-based Ratiometric Optical Thermometry with Silicon-Vacancy in Microdiamonds

Fiber optic all-optical thermometry is a promising technology to track temperature at a micro-scale while designing efficient and reliable microelectronic devices and components. In this work, we demonstrate a novel real-time ratiometric fiber optic thermometry technique based on silicon-vacancy (SiV) diamond that shows the highest temperature resolution (22.91 KHz^(-1/2) Wcm^(-2)) and spatial resolution (~7.5 um) among all-optical fiber-based thermosensors reported to date. Instead of analyzing the spectral features of temperature-dependent SiV signal, coming from SiV micro-diamond fixed on the fiber tip, an alternative parallel detection method based on filtering optics and photon counters is proposed to read out the sample temperature in real-time. The signal collection efficiency of the fiber is also investigated numerically with semi-analytic ray-optical analysis and then compared with our experimental study. We finally demonstrate the performance of the thermosensor by monitoring the temperature at distinct locations in a lab-built graphite-based microheater device. Our work introduces a reconfigurable method for temperature monitoring in microelectronic, microfluidic devices, or biological environments and unlocks a new direction for fiber-based all-optical thermometry research.

physics.optics↗

arXiv2023

Cryogenic Thermal Shock Effects on Optical Properties of Quantum Emitters in Hexagonal Boron Nitride

Solid-state quantum emitters are vital building blocks for quantum information science and quantum technology. Among various types of solid-state emitters discovered to date, color centers in hexagonal boron nitride have garnered tremendous traction in recent years thanks to their environmental robustness, high brightness and room-temperature operation. Most recently, these quantum emitters have been employed for satellite-based quantum key distribution. One of the most important requirements to qualify these emitters for space-based applications is their optical stability against cryogenic thermal shock. Such understanding has, however, remained elusive to date. Here, we report on the effects caused by such thermal shock which induces random, irreversible changes in the spectral characteristics of the quantum emitters. By employing a combination of structural characterizations and density functional calculations, we attribute the observed changes to lattice strains caused by the cryogenic temperature shock. Our study shed light on the stability of the quantum emitters under extreme conditions, similar to those countered in outer space.

physics.app-ph↗

arXiv2022

Ultralow-power cryogenic thermometry based on optical-transition broadening of a two-level system in diamond

Cryogenic temperatures are the prerequisite for many advanced scientific applications and technologies. The accurate determination of temperature in this range and at the submicrometer scale is, however, nontrivial. This is due to the fact that temperature reading in cryogenic conditions can be inaccurate due to optically induced heating. Here, we present an ultralow power, optical thermometry technique that operates at cryogenic temperatures. The technique exploits the temperature dependent linewidth broadening measured by resonant photoluminescence of a two level system, a germanium vacancy color center in a nanodiamond host. The proposed technique achieves a relative sensitivity of 20% 1/K, at 5 K. This is higher than any other all optical nanothermometry method. Additionally, it achieves such sensitivities while employing excitation powers of just a few tens of nanowatts, several orders of magnitude lower than other traditional optical thermometry protocols. To showcase the performance of the method, we demonstrate its ability to accurately read out local differences in temperatures at various target locations of a custom-made microcircuit. Our work is a definite step towards the advancement of nanoscale optical thermometry at cryogenic temperatures.

physics.optics↗

arXiv2021

Real-time ratiometric optical nanoscale thermometry

All optical nanothermometry has become a powerful, noninvasive tool for measuring nanoscale temperatures in applications ranging from medicine to nanooptics and solid-state nanodevices. The key features of any candidate nanothermometer are sensitivity and resolution. Here, we demonstrate a real time, diamond based nanothermometry technique with sensitivity and resolution much larger than those of any existing all optical method. The distinct performance of our approach stems from two factors. First, temperature sensors nanodiamonds cohosting two Group IV colour centers engineered to emit spectrally separated Stokes and AntiStokes fluorescence signals under excitation by a single laser source. Second, a parallel detection scheme based on filtering optics and high sensitivity photon counters for fast readout. We demonstrate the performance of our method by monitoring temporal changes in the local temperature of a microcircuit and a MoTe2 field effect transistor. Our work lays the foundation for time resolved temperature monitoring and mapping of micro, nanoscale devices such as microfluidic channels, nanophotonic circuits, and nanoelectronic devices, as well as complex biological environments such as tissues and cells.

physics.optics↗

arXiv2021

Deterministic fabrication of blue quantum emitters in hexagonal boron nitride

Hexagonal boron nitride (hBN) is gaining considerable attention as a solid-state host of quantum emitters from the ultraviolet to the near infrared spectral ranges. However, atomic structures of most of the emitters are speculative or unknown, and emitter fabrication methods typically suffer from poor reproducibility, spatial accuracy, or spectral specificity. Here, we present a robust, deterministic electron beam technique for site-specific fabrication of blue quantum emitters with a zero-phonon line at 436 nm (2.8 eV). We show that the emission intensity is proportional to electron dose and that the efficacy of the fabrication method correlates with a defect emission at 305 nm (4.1 eV). We attribute blue emitter generation to fragmentation of carbon clusters by electron impact and show that the robustness and universality of the emitter fabrication technique are enhanced by a pre-irradiation annealing treatment. Our results provide important insights into photophysical properties and structure of defects in hBN and a framework for deterministic fabrication of quantum emitters in hBN.

physics.optics↗

arXiv2021

Purcell enhancement of a cavity-coupled emitter in hexagonal boron nitride

Integration of solid state quantum emitters into nanophotonic circuits is a critical step towards fully on-chip quantum photonic based technologies. Among potential materials platforms, quantum emitters in hexagonal boron nitride have emerged over the last years as viable candidate. While the fundamental physical properties have been intensively studied over the last years, only few works have focused on the emitter integration into photonic resonators. Yet, for a potential quantum photonic material platform, the integration with nanophotonic cavities is an important cornerstone, as it enables the deliberate tuning of the spontaneous emission and the improved readout of distinct transitions for that quantum emitter. In this work, we demonstrate the resonant tuning of an integrated monolithic hBN quantum emitter in a photonic crystal cavity through gas condensation at cryogenic temperature. We resonantly coupled the zero phonon line of the emitter to a cavity mode and demonstrate emission enhancement and lifetime reduction, with an estimation for the Purcell factor of ~ 15.

physics.optics↗

arXiv2021

Bottom-Up Synthesis of Hexagonal Boron Nitride Nanoparticles with Intensity-Stabilized Quantum Emitters

Fluorescent nanoparticles are widely utilized in a large range of nanoscale imaging and sensing applications. While ultra-small nanoparticles (size <10 nm) are highly desirable, at this size range their photostability can be compromised due to effects such as intensity fluctuation and spectral diffusion caused by interaction with surface states. In this letter, we demonstrate a facile, bottom-up technique for the fabrication of sub-10-nm hBN nanoparticles hosting photostable bright emitters via a catalyst-free hydrothermal reaction between boric acid and melamine. We also implement a simple stabilization protocol that significantly reduces intensity fluctuation by ~85% and narrows the emission linewidth by ~14% by employing a common sol-gel silica coating process. Our study advances a promising strategy for the scalable, bottom-up synthesis of high-quality quantum emitters in hBN nanoparticles.

physics.optics↗

arXiv2020

Optical Thermometry with Quantum Emitters in Hexagonal Boron Nitride

Nanoscale optical thermometry is a promising non-contact route for measuring local temperature with both high sensitivity and spatial resolution. In this work, we present a deterministic optical thermometry technique based on quantum emitters in nanoscale hexagonal boron-nitride. We show that these nanothermometers exhibit better performance than that of homologous, all-optical nanothermometers both in sensitivity and range of working temperature. We demonstrate their effectiveness as nanothermometers by monitoring the local temperature at specific locations in a variety of custom-built micro-circuits. This work opens new avenues for nanoscale temperature measurements and heat flow studies in miniaturized, integrated devices.

physics.app-ph↗

arXiv2019

Learning Orientation-Estimation Convolutional Neural Network for Building Detection in Optical Remote Sensing Image

Benefiting from the great success of deep learning in computer vision, CNN-based object detection methods have drawn significant attentions. Various frameworks have been proposed which show awesome and robust performance for a large range of datasets. However, for building detection in remote sensing images, buildings always pose a diversity of orientations which makes it a challenge for the application of off-the-shelf methods to building detection. In this work, we aim to integrate orientation regression into the popular axis-aligned bounding-box detection method to tackle this problem. To adapt the axis-aligned bounding boxes to arbitrarily orientated ones, we also develop an algorithm to estimate the Intersection over Union (IoU) overlap between any two arbitrarily oriented boxes which is convenient to implement in Graphics Processing Unit (GPU) for accelerating computation. The proposed method utilizes CNN for both robust feature extraction and rotated bounding box regression. We present our modelin an end-to-end fashion making it easy to train. The model is formulated and trained to predict orientation, location and extent simultaneously obtaining tighter bounding box and hence, higher mean average precision (mAP). Experiments on remote sensing images of different scales shows a promising performance over the conventional one.

cs.CV↗

arXiv2017

A Labeling-Free Approach to Supervising Deep Neural Networks for Retinal Blood Vessel Segmentation

Segmenting blood vessels in fundus imaging plays an important role in medical diagnosis. Many algorithms have been proposed. While deep Neural Networks have been attracting enormous attention from computer vision community recent years and several novel works have been done in terms of its application in retinal blood vessel segmentation, most of them are based on supervised learning which requires amount of labeled data, which is both scarce and expensive to obtain. We leverage the power of Deep Convolutional Neural Networks (DCNN) in feature learning, in this work, to achieve this ultimate goal. The highly efficient feature learning of DCNN inspires our novel approach that trains the networks with automatically-generated samples to achieve desirable performance on real-world fundus images. For this, we design a set of rules abstracted from the domain-specific prior knowledge to generate these samples. We argue that, with the high efficiency of DCNN in feature learning, one can achieve this goal by constructing the training dataset with prior knowledge, no manual labeling is needed. This approach allows us to take advantages of supervised learning without labeling. We also build a naive DCNN model to test it. The results on standard benchmarks of fundus imaging show it is competitive to the state-of-the-art methods which implies a potential way to leverage the power of DCNN in feature learning.

cs.CV↗