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Excited-state and Steric Hindrances Engineering Enable Fast Spin-Flip Narrowband Thermally Activated Delayed Fluorescence Emitters with Enhanced Quenching Resistance

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Angewandte Chemie 2025年第11期137卷

作者： Rui-Zhi An Fang-Ming Zhao Changjiao Shang Prof. Meng Zhou Prof. Lin-Song Cui State Key Laboratory of Precision and Intelligent Chemistry University of Science and Technology of China Hefei Anhui 230026 China CAS Key Laboratory of Soft Matter Chemistry Department of Polymer Science and Engineering University of Science and Technology of China Hefei Anhui 230026 China Hefei National Research Center for Physical Sciences at the Microscale Department of Chemical Physics University of Science and Technology of China Hefei Anhui 230026 China

Multi-resonance thermally activated delayed fluorescence (MR-TADF) materials have great potential for applications in ultrahigh-definition (UHD) organic light-emitting diode (OLED) displays, that benefit from their narrowband emission characteristic. However, key challenges such as aggregation-caused quenching (ACQ) effect and slow triplet-to-singlet spin-flip process, especially for blue MR-TADF materials, continue to impede their development due to planar skeletons and relatively large Δ E ST s. Here, an effective strategy that incorporates multiple carbazole donors into the parent MR moieties is proposed, synergistically engineering their excited states and steric hindrances to enhance both the spin-flip process and quenching resistance. As expected, the designed materials namely 5Cz-BNO and 5Cz-BN exhibit bright blue and green emissions with narrow full-width at half-maximums (FWHMs) around 23 nm, together with significantly improved reverse intersystem crossing (RISC) rates. The OLEDs based on 5Cz-BNO and 5Cz-BN with doping concentrations from 5 to 20 wt % achieve high maximum external quantum efficiency (EQE max ) values exceeding 30 % with suppressed efficiency roll-offs and improved operational stability. This work offers an effective approach for designing doping-insensitive blue and green MR-TADF materials with fast spin-flip processes by integrating the engineering of excited states and steric hindrances.

关键词： aggregation-caused quenching multiple resonance organic light-emitting diode spin-flip process thermally activated delayed fluorescence

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The rising promise of organic photodetectors in emerging technologies

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Nature Reviews Materials 2025年 1-3页

作者： Kai Zhang ( Dae Sung Chung ( School of Materials Science and Engineering State Key Laboratory of Advanced Materials for Intelligent Sensing Tianjin Key Laboratory of Molecular Optoelectronic Sciences Key Laboratory of Organic Integrated Circuits Ministry of Education Collaborative Innovation Center of Chemical Science and Engineering Tianjin University Tianjin China Department of Chemical Engineering Pohang University of Science and Technology (POSTECH) Pohang Republic of Korea

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TASL-Net: Tri-Attention Selective Learning Network for intelligent Diagnosis of Bimodal Ultrasound Video

arXiv

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arXiv 2024年

作者： Zhao, Chengqian Yao, Zhao Hu, Zhaoyu Xie, Yuanxin Zhang, Yafang Wang, Yuanyuan Li, Shuo Zhou, Jianhua Zhou, Jianqiao Wang, Yin Yu, Jinhua Center for Biomedical Engineering School of Information Science and Technology Fudan University Shanghai200438 China Department of Ultrasound Shanghai Pulmonary Hospital Tongji University School of Medicine Shanghai200433 China Department of Biomedical Engineering The Department of Computer and Data Science Case Western Reserve University ClevelandOH44106 United States Department of Ultrasound Sun Yat-Sen University Cancer Center State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine Guangzhou510060 China Department of Ultrasound Ruijin Hospital Shanghai Jiaotong University School of Medicine Shanghai200025 China

In the intelligent diagnosis of bimodal (gray-scale and contrast-enhanced) ultrasound videos, medical domain knowledge such as the way sonographers browse videos, the particular areas they emphasize, and the features they pay special attention to, plays a decisive role in facilitating precise diagnosis. Embedding medical knowledge into the deep learning network can not only enhance performance but also boost clinical confidence and reliability of the network. However, it is an intractable challenge to automatically focus on these person- and disease-specific features in videos and to enable networks to encode bimodal information comprehensively and efficiently. This paper proposes a novel Tri-Attention Selective Learning Network (TASL-Net) to tackle this challenge and automatically embed three types of diagnostic attention of sonographers into a mutual transformer framework for intelligent diagnosis of bimodal ultrasound videos. Firstly, a time-intensity-curve-based video selector is designed to mimic the temporal attention of sonographers, thus removing a large amount of redundant information while improving computational efficiency of TASL-Net. Then, to introduce the spatial attention of the sonographers for contrast-enhanced video analysis, we propose the earliest-enhanced position detector based on structural similarity variation, on which the TASL-Net is made to focus on the differences of perfusion variation inside and outside the lesion. Finally, by proposing a mutual encoding strategy that combines convolution and transformer, TASL-Net possesses bimodal attention to structure features on gray-scale videos and to perfusion variations on contrast-enhanced videos. These modules work collaboratively and contribute to superior performance. We conduct a detailed experimental validation of TASL-Net's performance on three datasets, including lung, breast, and liver, with a total of 791 cases. A comprehensive ablation experiment and comparison with five state-of-the-

关键词： Diagnosis

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Dual Functional Mesoporous Silica Colloidal Electrolyte for Lithium-Oxygen Batteries

SSRN

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SSRN 2022年

作者： Mu, Hailiang Zhuge, Xiangqun Ren, Guogang Luo, Kun Ding, Zhengping Ren, Yurong Luo, Zhihong Bayati, Maryam Xu, Ben Bin Liu, Xiaoteng Changzhou Key Laboratory of Intelligent Manufacturing and Advanced Technology for Power Battery School of Materials Science ＆ Engineering Changzhou University Changzhou213164 China Department of Engineering and Technology School of Physics Engineering and Computer Science University of Hertfordshire Hertfordshire HatfieldAL10 9AB United Kingdom Guangxi Key Laboratory of Optical and Electronic Materials and Devices Guilin University of Technology Guilin541004 China Department of Mechanical and Construction Engineering Faculty of Engineering and Environment Northumbria University Newcastle upon TyneNE1 8ST United Kingdom

Dual functional mesoporous silica (mSiO2) colloidal electrolytes are designed for lithium-oxygen batteries (LOBs) for the purpose of protecting lithium anode and accelerating cathode reaction kinetics. It suppresses the side reactions of Li stripping/plating and enhances the cycling life performance of the LOB by relieving the attack of superoxide intermediates. The co-deposition of mesoporous mSiO2 and Li2O2 also effectively accelerated the decomposition of the discharge product by promoting the mass transfer at the cathode. Testing results show that the battery life of LOB using mSiO2 with a concentration of 80 mg L-1 in the colloidal electrolyte has been extended from 55 to 328 cycles compared with the one using conventional LiClO4/DMSO electrolyte. The rate performance and full-discharge capacity are also significantly enhanced. We discovered that the as-synthesized mSiO2 has a special well-ordered hexagonal mesoporous structure, with a high specific surface area of 1016.30 m2 g-1, which can form a stable colloid after mixing with 1.0 M LiClO4/DMSO. This is a meaningful investigation of suppressing side reactions using non-aqueous electrolytes, and the design principle also impacts research on other types of lithium metal batteries. © 2022, The Authors. All rights reserved.

关键词： Electrolytes

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Tasl-Net: Tri-Attention Selective Learning Network for intelligent Diagnosis of Bimodal Ultrasound Video

SSRN

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SSRN 2024年

关键词： Convolution

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Anomaly detection on attributed networks via contrastive self-supervised learning

arXiv

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arXiv 2021年

作者： Liu, Yixin Li, Zhao Pan, Shirui Gong, Chen Zhou, Chuan Karypis, George The Department of Data Science and AI Faculty of Information Technology Monash University ClaytonVIC3800 Australia The Alibaba Group Hangzhou310000 China The PCA Laboratory Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China The Department of Computing The Hong Kong Polytechnic University Hong Kong The Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100093 China The Department of Computer Science and Engineering University of Minnesota MinneapolisMN55455 United States

Anomaly detection on attributed networks attracts considerable research interests due to wide applications of attributed networks in modeling a wide range of complex systems. Recently, the deep learning-based anomaly detection methods have shown promising results over shallow approaches, especially on networks with high-dimensional attributes and complex structures. However, existing approaches, which employ graph autoencoder as their backbone, do not fully exploit the rich information of the network, resulting in suboptimal performance. Furthermore, these methods do not directly target anomaly detection in their learning objective and fail to scale to large networks due to the full graph training mechanism. To overcome these limitations, in this paper, we present a novel Contrastive self-supervised Learning framework for Anomaly detection on attributed networks (CoLA for abbreviation). Our framework fully exploits the local information from network data by sampling a novel type of contrastive instance pair, which can capture the relationship between each node and its neighboring substructure in an unsupervised way. Meanwhile, a well-designed graph neural network-based contrastive learning model is proposed to learn informative embedding from high-dimensional attributes and local structure and measure the agreement of each instance pairs with its outputted scores. The multi-round predicted scores by the contrastive learning model are further used to evaluate the abnormality of each node with statistical estimation. In this way, the learning model is trained by a specific anomaly detection-aware target. Furthermore, since the input of the graph neural network module is batches of instance pairs instead of the full network, our framework can adapt to large networks flexibly. Experimental results show that our proposed framework outperforms the state-of-the-art baseline methods on all seven benchmark datasets. © 2021, CC BY.

关键词： Anomaly detection

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Patterning of 2D second harmonic generation active arrays in ferroelectric nematic fluids.

arXiv

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arXiv 2024年

作者： Lovšin, M. Petelin, A. Berteloot, B. Osterman, N. Aya, S. Huang, M. Drevenšek-Olenik, I. Mandle, R.J. Neyts, K. Mertelj, A. Sebastian, N. Jožef Stefan Institute Ljubljana Slovenia University of Ljubljana Faculty of Mathematics and Physics Ljubljana Slovenia Liquid Crystals and Photonics Group ELIS Department Ghent University Ghent Belgium School of Emergent Soft Matter South China University of Technology Guangzhou China Guangdong Provincial Key Laboratory of Functional and Intelligent Hybrid Materials and Devices South China University of Technology Guangzhou China School of Physics and Astronomy University of Leeds Leeds United Kingdom School of Chemistry University of Leeds Leeds United Kingdom State Key Lab of Advanced Displays and Optoelectronics Technologies Hong Kong University of Science and Technology Hong Kong

Ferroelectric nematic liquid crystals exhibit unique non-linear optical properties, with the potential to become transformative materials for photonic applications. A promising direction relies on the fabrication of tailored polar orientational patterns via photoalignment, thus shaping the non-linear optical susceptibility through thin slabs of the ferroelectric fluid. Here, we explore the fabrication of 2D periodic SHG active arrays in ferroelectric nematic fluids, for different materials, cell thicknesses and motifs. Based on polarizing optical microscopy observations in combination with optical simulations, second harmonic generation microscopy and interferometry, the 3D structure of the motifs are revealed. Two different 2D periodic patterns are explored, showing that the balance between flexoelectric and electrostatic energy can lead to different domain structures, an effect which is rooted in the difference between the flexoelectric properties of the materials. It is shown that by combining the surface-inscribed alignment with different spontaneous degrees of twist, 2D SHG active arrays can be obtained in the micrometre scale, in which adjacent areas exhibit maximum SHG signals at opposite angles. Copyright © 2024, The Authors. All rights reserved.

关键词： Harmonic generation

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Event-triggered state estimation for T-S fuzzy affine systems based on piecewise Lyapunov-Krasovskii functionals

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Control Theory and technology 2019年第1期17卷 99-111页

作者： Meng WANG Jianbin QIU Gang FENG Department of Biomedical Engineering City University of Hong Kong Kowloon Hong Kong China State Key Laboratory of Robotics and Systems & Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin Heilongjiang 150080 China

This paper investigates the problem of event-triggered H∞state estimation for Takagi-Sugeno (T-S) fuzzy affine systems. The objective is to design an event-triggered scheme and an observer such that the resulting estimation error system is asymptotically stable with a prescribed H∞performance and at the same time unnecessary output measurement transmission can be reduced. First, an event-triggered scheme is proposed to determine whether the sampled measurements should be transmitted or not. The output measurements, which trigger the condition, are supposed to suffer a network-induced time-varying and bounded delay before arriving at the observer. Then, by adopting the input delay method, the estimation error system can be reformulated as a piecewise delay system. Based on the piecewise Lyapunov-Krasovskii functional and the Finsler's lemma, the event-triggered H∞observer design method is developed. Moreover, an algorithm is proposed to co-design the observer gains and the event-triggering parameters to guarantee that the estimation error system is asymptotically stable with a given disturbance attenuation level and the signal transmission rate is reduced as much as possible. Simulation studies are given to show the effectiveness of the proposed method.

关键词： Takagi-Sugeno (T-S) fuzzy affine systems event-triggered scheme, piecewise Lyapunov-Krasovskii functional, state estimation

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Topological Edge states at Singular Points in Non-Hermitian Plasmonic Waveguide-Cavity systems

Topological Edge States at Singular Points in Non-Hermitian ...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Yin Huang Yuecheng Shen Georgios Veronis Department of Optoelectrics Information Science and Engineering School of Physics and Electronics Central South University Changsha China State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information Technology Sun Yat-Sen University Guangzhou China School of Electrical Engineering and Computer Science Louisiana State University Baton Rouge LA USA Center for Computation and Technology Louisiana State University Baton Rouge LA USA

We show that non-Hermitian plasmonic waveguide-cavity systems can simultaneously exhibit both topological edge states and singular points. We also show that the sensitivity of the reflected light intensity is greatly ... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Sensitivity Waveguide lasers Lasers and electrooptics Plasmons Electro-optical waveguides

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Influence of Room-Temperature Oxidation on the Stability of Reactively Sputtered Tan Thin Films for Sheet Resistors

SSRN

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SSRN 2023年

作者： Zhang, Mingzhen Wang, Yue Song, Shangzhi Guo, Ruiqiang Zhang, Wenbin Li, Chengming Wei, Junjun Yang, Ronggui Jiang, Puqing School of Power and Energy Engineering Huazhong University of Science and Technology 1037 Luoyu Road Hubei Wuhan430074 China Institute for Advanced Materials and Technology University of Science and Technology Beijing No.30 Xueyuan Road Haidian District Beijing100083 China Shunde Graduate School University of Science and Technology Beijing No.2 Zhihui Road Shunde District Foshan528399 China Thermal Science Research Center Shandong Institute of Advanced Technology Shandong Jinan250103 China Department of Computer Science Michigan Technological University HoughtonMI49931 United States State Key Laboratory of Coal Combustion School of Power and Energy Engineering Huazhong University of Science and Technology 1037 Luoyu Road Hubei Wuhan430074 China

Reactively sputtered tantalum nitride (TaN) thin films are used extensively in high-precision chip resistors because of their near-zero temperature coefficients of resistance (TCR). Passivation is usually necessary to ensure the long-term stability of the films. However, room-temperature oxidation of TaN films is often unavoidable before the passivation of the resistor devices. The effect of room-temperature oxidation on the stability and properties of TaN thin films for use as resistors is still unclear. This work systematically studies room-temperature oxidation of reactively sputtered TaN thin films with different nitrogen contents (i.e., nitrogen flow ratio during film deposition). Results suggest that among different nitrogen flow ratios of 2%, 3%, 5%, and 7%, the films sputtered with a 3% N2 flow ratio are dominated by the Ta2N phase and have the most stable structure and properties, with the TCR, resistance, and thermal conductivity being unaffected by air exposure. Comparatively, the films prepared with other N2 contents are easily subject to room-temperature oxidation and result in apparent degradation of TCR. The influence of room-temperature oxidation also manifests as a reduction in the lattice thermal conductivities of the films. The films' electrical resistances, however, are little affected by room-temperature oxidation. © 2023, The Authors. All rights reserved.

关键词： Resistors

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