arXiv subjects

Teng Long

Publications and source records attributed to Teng Long.

At least 37 records · Page 2Linked to original sources

arXiv2024

Spin-valley-locked Electroluminescence for High-Performance Circularly-Polarized Organic Light-Emitting Diodes

Circularly polarized (CP) organic light-emitting diodes (OLEDs) have attracted attention in potential applications including novel display and photonic technologies. However, conventional approaches cannot meet the requirements of device performance, such as high dissymmetry factor, high directionality, narrowband emission, simplified device structure and low costs. Here, we demonstrate spin-valley-locked CP-OLEDs without chiral emitters, but based on photonic spin-orbit coupling, where photons with opposite CP characteristics are emitted from different optical valleys. These spin-valley locked OLEDs exhibit a narrowband emission of 16 nm, a high EQE of 3.65, a maximum luminance of near 98000 cd/m2 and a gEL of up to 1.80, which are among the best performances of active single-crystal CP-OLEDs, achieved with a simple device structure. This strategy opens an avenue for practical applications towards three-dimensional displays and on-chip CP-OLEDs.

cond-mat.mes-hall↗

arXiv2024

The stability of smooth solitary waves for the $b$-family of Camassa-Holm equations

The $b$-family of Camassa-Holm ($b$-CH) equation is a one-parameter family of PDEs, which includes the completely integrable Camassa-Holm and Degasperis-Procesi equations but possesses different Hamiltonian structures. Motivated by this, we study the existence and the orbital stability of the smooth solitary wave solutions with nonzero constant background to the $b$-CH equation for the special case $b=1$, whose the Hamiltonian structure is different from that of $b\neq1$. We establish a connection between the stability criterion for the solitary waves and the monotonicity of a singular integral along the corresponding homoclinic orbits of the spatial ODEs. We verify the latter analytically using the framework for the monotonicity of period function of planar Hamiltonian systems, which shows that the smooth solitary waves are orbitally stable. In addition, we find that the existence and orbital stability results for $0 1$, particularly the stability criteria are the same. Finally, combining with the results for the case $b>1$, we conclude that the solitary waves to the $b$-CH equation is structurally stable under the variation of %with respect to the parameter $b>0$.

math.AP↗

arXiv2024

An Anisotropic Constitutive Relationship by a Series of 8 Chain Models

Hyperelastic models have been widely used to model polymers and soft tissues. However, most hyperelastic models are phenomenological material models. Based on statistical mechanics and molecular chain configuration, 8 chain model or Arruda-Boyce model is a physical model which can be used to understand how microstructures of chains affect macroscopic mechanical properties of polymers and soft tissues. Mechanical properties of many polymers and soft tissues are directional dependent. Polymer matrix can be reinforced by fibers. For soft tissues, ligaments and tendons will lead to anisotropic properties. Since matrix and reinforcements are composed of similar microstructural molecular chains, they can be modeled by using the same mathematical model. In this paper, a series of 8 chain models is used to understand composite properties. That is, an isotropic 8 chain model will be used to model matrix and anisotropic 8 chain models will be used to model fibers. Replacing I_1 in isotropic 8 chain model with I_4 in anisotropic 8 chain model is physically corresponding to changing representative 8 chain cubic cell to 8 chain slender cell. This treatment not only simplifies exist anisotropic mathematical structures but also keeps microscopic physics of 8 chain model unchanged.

cond-mat.soft↗

arXiv2024

Dual orthogonally-polarized lasing assisted by imaginary Fermi arcs in organic microcavities

The polarization control of micro/nano lasers is an important topic in nanophotonics. Up to now, the simultaneous generation of two distinguishable orthogonally-polarized lasing modes from a single organic microlaser remains a critical challenge. Here, we demonstrate simultaneously orthogonally-polarized dual lasing from a microcavity filled with an organic single crystal exhibiting selective strong coupling. We show that the non-Hermiticity due to polarization-dependent losses leads to the formation of real and imaginary Fermi arcs with exceptional points. Simultaneous orthogonally-polarized lasing becomes possible thanks to the eigenstate mixing by the photonic spin-orbit coupling at the imaginary Fermi arcs. Our work provides a novel way to develop linearly-polarized lasers and paves the way for the future fundamental research in topological photonics, non-Hermitian optics, and other fields.

cond-mat.mes-hall↗

arXiv2024

Optical spin Hall effect pattern switching in polariton condensates in organic single-crystal microbelts

Topological polaritons, combining the robustness of the topological protected edge states to defects and disorder with the strong nonlinear properties of polariton bosons, represent an excellent platform to investigate novel photonic topological phases. In this work, we demonstrated the optical spin Hall effect (OSHE) and its symmetry switching in the exciton-polariton regime of pure DPAVBi crystals. Benefiting from the photonic Rashba-Dresselhaus spin-orbit coupling in organic crystals, we observed the separation of left- and right-circularly-polarized polariton emission in two-dimensional momentum space and real space, a signature of the OSHE. Above the lasing threshold, the OSHE pattern changes due to transverse quantization in the microbelt. This device without superlattice structure has great potential applications in topological polaritonics, such as information transmission, photonic integrated chips and quantum information.

cond-mat.mes-hall↗

arXiv2023

A Highly-Compact Direct-Injection Universal Power Flow and Quality Control Circuit

This paper presents a novel direct-injection modular universal power flow and quality control topology exclusively using lower power components. In addition to conventional high-voltage applications, it is particularly attractive for the distribution and secondary grids, e.g., in soft open points, down to low voltage as it can exploit the latest developments in low-voltage high-current semiconductors. In contrast to other concepts that do not interface the grid through transformers, it does not need to convert the entire line power but only the injected or extracted power difference. The proposed power flow and quality (f/q) controller comprises a shunt active front end, together with high-frequency links serving as a power supply for a series floating module per phase. Each of the floating modules is in series with one phase of the line, floating with the electric potential of that particular phase, avoiding any ground connection. Omitting bulky and dynamically limited line transformers of conventional universal power flow controllers, the presented direct-injection f/q controller enables exceptionally small size and volume, high power density, high frequency content, and fast response. In contrast to direct-injection concepts with full back-to-back converters, it only needs to handle a fraction of the power. The circuit combines grid-voltage low-current electronics in the shunt unit and low-voltage high-current modules in the floating series injection units. Simulations and experiments demonstrate and validate the concept.

eess.SY↗

arXiv2023

Effective potential engineering by emergent anisotropy in a tunable open-access microcavity

Photonic spin-orbit (SO) coupling is an important physical mechanism leading to numerous interesting phenomena in the systems of microcavity photons and exciton-polaritons. We report the effect of SO coupling in a tunable open-access microcavity embedded with anisotropic active media. The SO coupling associated with the TE-TM splitting results in an emergent anisotropy, which further leads to fine energy splittings allowing clear observation of the full set of eigenstates, in sharp contrast with the isotropic situation which leads to the isotropic eigenstates of spin vortices. We show that the photonic potential can be engineered by playing with the relation between the emergent anisotropy and the cavity ellipticity. All the experimental results are well reproduced by the degenerate perturbation theory. Our results constitute a significant extension to the research field of microcavity spinoptronics, with potential applications in polarization control and optical property measurement of photonic devices and materials.

physics.optics↗

arXiv2023

Photochemical reaction enabling the engineering of photonic spin-orbit coupling in organic-crystal optical microcavities

The control and active manipulation of spin-orbit coupling (SOC) in photonic systems is fundamental in the development of modern spin optics and topological photonic devices. Here, we demonstrate the control of an artificial Rashba-Dresselhaus (RD) SOC mediated by photochemical reactions in a microcavity filled with an organic single-crystal of photochromic phase-change character. Splitting of the circular polarization components of the optical modes induced by photonic RD SOC is observed experimentally in momentum space. By applying an ultraviolet light beam, we control the spatial molecular orientation through a photochemical reaction and with that we control the energies of the photonic modes. This way we realize a reversible conversion of spin-splitting of the optical modes with different energies, leading to an optically controlled switching between circularly and linearly polarized emission from our device. Our strategy of in situ and reversible engineering of SOC induced by a light field provides a promising approach to actively design and manipulate synthetic gauge fields towards future on-chip integration in photonics and topological photonic devices.

physics.optics↗

arXiv2023

Deep Image Harmonization with Globally Guided Feature Transformation and Relation Distillation

Given a composite image, image harmonization aims to adjust the foreground illumination to be consistent with background. Previous methods have explored transforming foreground features to achieve competitive performance. In this work, we show that using global information to guide foreground feature transformation could achieve significant improvement. Besides, we propose to transfer the foreground-background relation from real images to composite images, which can provide intermediate supervision for the transformed encoder features. Additionally, considering the drawbacks of existing harmonization datasets, we also contribute a ccHarmony dataset which simulates the natural illumination variation. Extensive experiments on iHarmony4 and our contributed dataset demonstrate the superiority of our method. Our ccHarmony dataset is released at https://github.com/bcmi/Image-Harmonization-Dataset-ccHarmony.

cs.CV↗

arXiv2023

Cross-Spatial Pixel Integration and Cross-Stage Feature Fusion Based Transformer Network for Remote Sensing Image Super-Resolution

Remote sensing image super-resolution (RSISR) plays a vital role in enhancing spatial detials and improving the quality of satellite imagery. Recently, Transformer-based models have shown competitive performance in RSISR. To mitigate the quadratic computational complexity resulting from global self-attention, various methods constrain attention to a local window, enhancing its efficiency. Consequently, the receptive fields in a single attention layer are inadequate, leading to insufficient context modeling. Furthermore, while most transform-based approaches reuse shallow features through skip connections, relying solely on these connections treats shallow and deep features equally, impeding the model's ability to characterize them. To address these issues, we propose a novel transformer architecture called Cross-Spatial Pixel Integration and Cross-Stage Feature Fusion Based Transformer Network (SPIFFNet) for RSISR. Our proposed model effectively enhances global cognition and understanding of the entire image, facilitating efficient integration of features cross-stages. The model incorporates cross-spatial pixel integration attention (CSPIA) to introduce contextual information into a local window, while cross-stage feature fusion attention (CSFFA) adaptively fuses features from the previous stage to improve feature expression in line with the requirements of the current stage. We conducted comprehensive experiments on multiple benchmark datasets, demonstrating the superior performance of our proposed SPIFFNet in terms of both quantitative metrics and visual quality when compared to state-of-the-art methods.

cs.CV↗

arXiv2023

Accelerated Screening of Ternary Chalcogenides for High-Performance Optoelectronic Materials

Chalcogenides, which refer to chalcogen anions, have attracted considerable attention in multiple fields of applications, such as optoelectronics, thermoelectrics, transparent contacts, and thin film transistors. In comparison to oxide counterparts, chalcogenides have demonstrated higher mobility and \textit{p}-type dopability, owing to larger orbital overlaps between metal-X covalent chemical bondings and higher-energy valence bands derived by p-orbitals. Despite the potential of chalcogenides, the number of successfully synthesized compounds remains relatively low compared to oxides, suggesting the presence of numerous unexplored chalcogenides with fascinating physical characteristics. In this study, we implemented a systematic high-throughput screening process combined with first-principles calculations on ternary chalcogenides using 34 crystal structure prototypes. We generated a computational material database containing over 400,000 compounds by exploiting the ion-substitution approach at different atomic sites with elements in the periodic table. The thermodynamic stabilities of the candidates were validated using the chalcogenides included in the Open Quantum Materials Database. Moreover, we trained a model based on Crystal Graph Convolutional Neural Networks to predict the thermodynamic stability of novel materials. Furthermore, we theoretically evaluated the electronic structures of the stable candidates using accurate hybrid functionals. A series of in-depth characteristics, including the carrier effective masses, electronic configuration, and photovoltaic conversion efficiency, was also investigated. Our work provides useful guidance for further experimental research in the synthesis and characterization of such chalcogenides as promising candidates, as well as charting the stability and optoelectronic performance of ternary chalcogenides.

cond-mat.mtrl-sci↗

arXiv2023

Hierarchical Explanations for Video Action Recognition

To interpret deep neural networks, one main approach is to dissect the visual input and find the prototypical parts responsible for the classification. However, existing methods often ignore the hierarchical relationship between these prototypes, and thus can not explain semantic concepts at both higher level (e.g., water sports) and lower level (e.g., swimming). In this paper inspired by human cognition system, we leverage hierarchal information to deal with uncertainty: When we observe water and human activity, but no definitive action it can be recognized as the water sports parent class. Only after observing a person swimming can we definitively refine it to the swimming action. To this end, we propose HIerarchical Prototype Explainer (HIPE) to build hierarchical relations between prototypes and classes. HIPE enables a reasoning process for video action classification by dissecting the input video frames on multiple levels of the class hierarchy, our method is also applicable to other video tasks. The faithfulness of our method is verified by reducing accuracy-explainability trade off on ActivityNet and UCF-101 while providing multi-level explanations.

cs.CV↗

arXiv2023

Constrained crystals deep convolutional generative adversarial network for the inverse design of crystal structures

Autonomous materials discovery with desired properties is one of the ultimate goals for materials science, and the current studies have been focusing mostly on high-throughput screening based on density functional theory calculations and forward modelling of physical properties using machine learning. Applying the deep learning techniques, we have developed a generative model which can predict distinct stable crystal structures by optimizing the formation energy in the latent space. It is demonstrated that the optimization of physical properties can be integrated into the generative model as on-top screening or backwards propagator, both with their own advantages. Applying the generative models on the binary Bi-Se system reveals that distinct crystal structures can be obtained covering the whole composition range, and the phases on the convex hull can be reproduced after the generated structures are fully relaxed to the equilibrium. The method can be extended to multicomponent systems for multi-objective optimization, which paves the way to achieve the inverse design of materials with optimal properties.

physics.comp-ph↗

arXiv2023

Autonomous atomic Hamiltonian construction and active sampling of x-ray absorption spectroscopy by adversarial Bayesian optimization

X-ray absorption spectroscopy (XAS) is a well-established method for in-depth characterization of the electronic structure due to its sensitivity to the local coordination and electronic states of the active ions. In practice hundreds of energy points should be sampled during the XAS measurement, most of which are redundant and do not contain important information. In addition, it is also a tedious procedure to estimate reasonable parameters in the atomic Hamiltonian for mechanistic understanding. We implemented an Adversarial Bayesian optimization (ABO) algorithm comprising two coupled BOs to automatically fit the multiplet model Hamiltonian and meanwhile to sample effectively based on active learning. Taking NiO as an example, for simulated spectra which can be well fitted by the atomic model, we found that less than 30 sampling points are enough to obtain the complete XAS with the corresponding crystal field or charge transfer model, which can be selected based on intuitive hypothesis learning. Further application on the experimental spectra, it revealed that less than 80 sampling points can already give reasonable XAS and reliable atomic model parameters. Our ABO algorithm has a great potential for future application in automated physics-driven XAS analysis and active learning sampling.

cond-mat.mtrl-sci↗

arXiv2022

Orbital stability of smooth solitary waves for the $b$-family of Camassa-Holm equations

In this paper, we study the stability of smooth solitary waves for the $b$-family of Camassa-Holm equations. We verify the stability criterion analytically for the general case $b>1$ by the idea of the monotonicity of the period function for planar Hamiltonian systems and show that the smooth solitary waves are orbitally stable, which gives a positive answer to the open problem proposed by Lafortune and Pelinovsky [S. Lafortune, D. E. Pelinovsky, Stability of smooth solitary waves in the $b$-Camassa-Holm equation].

math.AP↗

arXiv2022

Circularly Polarized Lasing from a Microcavity Filled with Achiral Single-Crystalline Microribbons

Organic circularly polarized (CP) lasers have received increasing attention due to their future photoelectric applications. Here, we demonstrate a CP laser from a pure organic crystal-filled microcavity without any chiral molecules or chiral structures. Benefited from the giant anisotropy and excellent laser gain of organic crystals, optical Rashba-Dresselhaus spin-orbit coupling effect can be induced and is conductive to the CP laser in such microcavities. The maximum dissymmetry factor of the CP lasing with opposite helicities reached, is as high as 1.2. Our strategy may provide a new idea for the design of CP lasers towards future 3D laser displays, information storage and other fields.

physics.optics↗

arXiv2022

Inharmonious Region Localization by Magnifying Domain Discrepancy

Inharmonious region localization aims to localize the region in a synthetic image which is incompatible with surrounding background. The inharmony issue is mainly attributed to the color and illumination inconsistency produced by image editing techniques. In this work, we tend to transform the input image to another color space to magnify the domain discrepancy between inharmonious region and background, so that the model can identify the inharmonious region more easily. To this end, we present a novel framework consisting of a color mapping module and an inharmonious region localization network, in which the former is equipped with a novel domain discrepancy magnification loss and the latter could be an arbitrary localization network. Extensive experiments on image harmonization dataset show the superiority of our designed framework. Our code is available at https://github.com/bcmi/MadisNet-Inharmonious-Region-Localization.

cs.CV↗

arXiv2021

Helical polariton lasing from topological valleys in an organic crystalline microcavity

Topological photonics provides an important platform for the development of photonic devices with robust disorder-immune light transport and controllable helicity. Mixing photons with excitons (or polaritons) gives rise to nontrivial polaritonic bands with chiral modes, allowing the manipulation of helical lasers in strongly coupled light-matter systems. In this work, we demonstrate helical polariton lasing from topological valleys of an organic anisotropic microcrystalline cavity based on tailored local nontrivial band geometry. This polariton laser emits light of different helicity along different angular directions. The significantly enhanced chiral characteristics are achieved by the nonlinear relaxation process. Helical topological polariton lasers may provide a perfect platform for the exploration of novel topological phenomena that involve light-matter interaction and the development of polariton-based spintronic devices.

physics.optics↗