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Monolayer C7N6: Room-temperature excitons with large binding energies and high thermal conductivities

Physical Review Materials 2020年第6期4卷 064001-064001页

作者： Yu Wu Ying Chen Congcong Ma Zixuan Lu Hao Zhang Bohayra Mortazavi Bowen Hou Ke Xu Haodong Mei Timon Rabczuk Heyuan Zhu Zhilai Fang Rongjun Zhang Costas M. Soukoulis Key Laboratory of Micro and Nano Photonic Structures (MOE) and Key Laboratory for Information Science of Electromagnetic Waves (MOE) and Department of Optical Science and Engineering Fudan University Shanghai 200433 China Engineering Research Center of Advanced Lighting Technology and Academy for Engineering and Technology Fudan University Shanghai 200433 China Nanjing University National Laboratory of Solid State Microstructure Nanjing 210093 China Cluster of Excellence PhoenixD (Photonics Optics and Engineering-Innovation Across Disciplines) Gottfried Wilhelm Leibniz Universität Hannover Germany Institute of Structural Mechanics Bauhaus-Universität Weimar Marienstr. 15 D-99423 Weimar Germany Department of Physics and Astronomy and Ames Laboratory Iowa State University Ames Iowa 50011 USA

Two-dimensional (2D) carbon nitrides compounds have attracted wide attention in recent years due to their diverse structures and excellent electronic, thermal, and optical properties. Here, by using first-principles approach, we investigate in details the stability, many-body effect, electronic/thermal transport properties, and thermoelectric performance of monolayer C7N6, as a new kind of 2D carbon nitride compounds composed of sp2−hybridized carbon atoms forming hexagonal lattice. Our results show that C7N6 monolayer is a direct band-gap semiconductor with a band-gap value of 3.56 eV under the accurate G0W0 method. Ab initio molecular dynamics simulations demonstrate that C7N6 maintains stable up to 1500K. Two exciton absorption peaks can be observed within the band gap with the respective large binding energies of 0.84 and 0.09eV, which means both excitons can exist at room temperature. Monolayer C7N6 possesses high carrier mobility with the order of 102–103cm2V−1s−1. Moreover, we find that the lattice thermal conductivity for C7N6 is as high as 134.55W/mK at room temperature, thus the thermoelectric figure of merit for C7N6 is relatively low. Our work suggests that C7N6 is a promising candidate for nanoscale (opto-)electronic and heat transport devices.

关键词： First-principles calculations 2-dimensional systems Density functional theory

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MMDDI-MGPFF: Multi-Modal Drug Representation Learning with Molecular Graph and Pharmacological Feature Fusion for Drug-Drug Interaction Event Prediction

MMDDI-MGPFF: Multi-Modal Drug Representation Learning with M...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Guishen Wang Zhitong Guo Guilin You Ming Xu Chen Cao Xiaowen Hu School of Life Sciences Jilin University Changchun China College of Computer Science and Engineering Changchun University of Technology Changchun China Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Drug-drug interactions pose a significant challenge in healthcare, directly impacting patient safety and treatment efficacy. Although recent advances in computational methods have improved drug-drug interaction (DDI) event prediction, many existing models face difficulties in effectively fusing features across different DDI tasks. To address these limitations, we introduce MMDDI-MGPFF, a novel multi-modal drug representation learning framework that integrates molecular graphs and pharmacological feature fusion to improve DDI prediction. Our model leverages a graph isomorphism network (GIN) for efficient encoding of molecular structures, coupled with an autoencoder for learning sequence-based drug features, encompassing both biological and pharmacological characteristics. We propose a multi-modal fusion approach that employs multi-head attention and deep neural networks to seamlessly integrate these graph and sequence modalities. Comprehensive experiments on a benchmark dataset demonstrate that MMDDI-MGPFF significantly outperforms state-of-the-art methods in DDI prediction tasks. Ablation studies further corroborate the efficacy of our model’s components, particularly the GIN and the integration of multi-feature drug representations. This work advances the field of DDI prediction by providing a more holistic and accurate approach to drug representation and interaction modeling.

关键词： Drugs Representation learning Biological system modeling Computational modeling Medical services Predictive models Encoding Safety Biological information theory Faces

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Design of Magnetic Encoder Based on Reconstructing and Mapping Looking-up Table

Design of Magnetic Encoder Based on Reconstructing and Mappi...

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International Conference on Electrical Machines and Systems

作者： Xiaoguang Wang Haitao Wang Hongqin Xie Dezhang Lou Kai Yang State Key Laboratory of Advanced Electromagnetic Engineering and Technology * Huazhong University of Science and Technology Wuhan 430074 R.P.China Hubei University of Technology School of Mechanical Engineering

ISBN: (纸本)9781467388634

This paper proposed an integrated hall magnetic encoder error correction method. In order to eliminate the steady-state error caused by installation errors and so on, this paper proposed three-phase zero and sine symmetric reconstruction. The sum of three-phase hall signal could be constant zero through zero reconstruction. In sine symmetric reconstruction method, transform threephase hall signal into two-phase orthogonal static coordinate to make sinusoidal orthogonal reconstruction. Then Symmetrical three-phase sinusoidal signal could be obtained using Clark transform. In order to solve dynamic error in temperature drift, this paper proposed a mapping projection method. This algorithm calculates real-time signal amplitude to get temperature drift coefficient. After standardize actual signal using this proportion factor, motor position angle can be received by querying standard table. The proposed solution can solve position angle constant and jump problem near the endpoint of angle section. Moreover, it has simple realization and high response speed. The simulation and experiments were carried out to prove the performance and validity.

关键词： reconstruction mapping projection looking-up table magnetic encoder

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Mitral Regurgitation Recognition based on Unsupervised Out-of-Distribution Detection with Residual Diffusion Amplification

arXiv

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arXiv 2024年

作者： Liu, Zhe Zhu, Xiliang Han, Tong Huang, Yuhao Wang, Jian Liu, Lian Wang, Fang Ni, Dong Gou, Zhongshan Yang, Xin National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Medical School Shenzhen University China Lab Shenzhen University China Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics School of Biomedical Engineering and Informatics Nanjing Medical University China Shenzhen RayShape Medical Technology Co. Ltd China Center for Cardiovascular Disease The Affiliated Suzhou Hospital of Nanjing Medical University China

Mitral regurgitation (MR) is a serious heart valve disease. Early and accurate diagnosis of MR via ultrasound video is critical for timely clinical decision-making and surgical intervention. However, manual MR diagnosis heavily relies on the operator’s experience, which may cause misdiagnosis and inter-observer variability. Since MR data is limited and has large intra-class variability, we propose an unsupervised out-of-distribution (OOD) detection method to identify MR rather than building a deep classifier. To our knowledge, we are the first to explore OOD in MR ultrasound videos. Our method consists of a feature extractor, a feature reconstruction model, and a residual accumulation amplification algorithm. The feature extractor obtains features from the video clips and feeds them into the feature reconstruction model to restore the original features. The residual accumulation amplification algorithm then iteratively performs noise feature reconstruction, amplifying the reconstructed error of OOD features. This algorithm is straightforward yet efficient and can seamlessly integrate as a plug-and-play component in reconstruction-based OOD detection methods. We validated the proposed method on a large ultrasound dataset containing 893 non-MR and 267 MR videos. Experimental results show that our OOD detection method can effectively identify MR samples. Copyright © 2024, The Authors. All rights reserved.

关键词： Diagnosis

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Research and Design of High Power Factor Induction Motor Drive Based on V/f Control

Research and Design of High Power Factor Induction Motor Dri...

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International Conference on Electrical Machines and Systems

作者： Xiaoguang Wang Fang Wei Jun Yang Cheng Luo Dezhang Lou Kai Yang State Key Laboratory of Advanced Electromagnetic Engineering and Technology *Huazhong University of Science and Technology Wuhan 430074 R.P.China Wuhan Polytechnic

ISBN: (纸本)9781467388634

This paper presented the design and implementation of an induction motor drive. In order to improve energy efficiency of this drive, system configuration comprised a single to three-phase converter with additional circuitry for PFC. In this design, using TI's UC3854 as the PFC controller chip, and the related parameters were designed. The control scheme was based on V/f control using two low-cost resistance current sensors. Only stator current measurements were needed to compensate for stator resistance drop. Regardless of changes in frequency or load, the magnitude of the stator flux can be constant by vectorially modifying the stator voltage. Furthermore, the hardware and software design were presented in detail. Experiments results showed that the proposed control system had high power factor and excellent performance.

关键词： induction motor PFC V/f control

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Study on Voltage Maintaining Performance of Metalized Film Capacitors under High Electric Fields

Study on Voltage Maintaining Performance of Metalized Film C...

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Annual Report Conference on Electrical Insulation and Dielectric Phenomena

作者： Hua Li Yaohong Chen Fuchang Lin Fei Lv Zhiwei Li Miao Zhang State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan Hubei P. R. China 430074

ISBN: (纸本)9781457709852

The metalized film capacitor can work under a high electric field due to its self-healing characteristic. But when the capacitor is charged rapidly to a specified high voltage (under a high electric field) and then it is disconnected from the power supply, a significant voltage drop will be observed, so the capacitor energy efficiency will reduce. It can be observed that the general curve of the voltage decay has a rapid initial drop and then the curve can usually be fit to a pure exponential. Firstly, this paper analyses the factors which cause the voltage decay through experimental study. The research results show that electric field strength, operating temperature and hold time play important roles in the voltage decay process. The higher the electric field or operating temperature is, the more significant the voltage drop is. If the voltage of the capacitor is maintained for a specified period of time, the voltage drop will reduce significantly. Through these experimental results, it is revealed that the voltage drop is mainly related to leakage and polarization. So the insulation resistance at various temperatures under high electric field is tested by the special technique. The results of insulation resistances are consistent with the voltage decay at various temperatures. Moreover, the interfacial polarization which exists in the charging process of metalized film capacitor is discussed. The interfacial polarization causes the rapid initial voltage decay.

关键词： Metalized Capacitors Maintaining

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Recent Advances in Research on Low Temperature Lithium Ion Batteries Power Source for Grid Equipments

Recent Advances in Research on Low Temperature Lithium Ion B...

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IEEE International Conference on Power and Power and Renewable Energy (ICPRE)

作者： Jian Wang Chen Bing Xiaojun Zhang Heming Deng Shouding Li Shun Tang State Grid Xinjiang Company Limited Electric Power Research Institute Urumqi P.R. China State Grid Electric Power Research Institute Wuhan P.R. China Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan P. R. China

ISBN: (数字)9781728145747

ISBN: (纸本)9781728145754

This paper summarized the recent developments in temperature-tolerance power supply for grid equipment, through the theoretical prediction, design synthesis and verification of key material systems, cell structure design, core mechanism and battery preparation engineering process, this report can develop batteries suitable for power source in grid equipments in low temperature regions to meet Xinjiang Power Grid. The demand for technology to achieve the leap-forward development of grid power quality services.

关键词： Electrodes Temperature Lithium Electrolytes Conductivity Lithium-ion batteries

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A Novel Physics-Assisted Genetic Algorithm (PAGA) for Decoupling Capacitor Optimization

TechRxiv

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TechRxiv 2023年

作者： Jiang, Li Zhang, Ling Tan, Shurun Li, Da Hwang, Chulsoon Fan, Jun Li, Er-Ping The Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems and Applications College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China The Electromagnetic Compatibility Laboratory Missouri University of Science and Technology RollaMO65409 United States ZJU-UIUC Institute Zhejiang University Haining314400 China

This article proposes a new physics-assisted genetic algorithm (PAGA) for decoupling capacitor (decap) optimization in power distribution networks (PDNs), which is, by far, the most powerful approach to efficiently minimizing the number of decaps within an enormous search space. In the proposed PAGA method, the priority of the decap ports is first determined based on their physical loop inductances. Then, an initial solution is quickly obtained by placing decaps sequentially on the port with the highest priority. Subsequently, a GA with prior physical knowledge is developed to find better decap solutions progressively. A port removal scheme that eliminates the low-priority ports and a modified mutation operation that better guides the mutation direction is proposed to accelerate the convergence of the GA. The initial solution and the proposed auxiliary schemes can significantly narrow the search space and incorporate physical knowledge into the GA, thus greatly accelerating the convergence process. Several representative state-of-the-art algorithms and commercial tools are thoroughly compared with the proposed PAGA in different application scenarios. The proposed PAGA shows remarkably better performance in efficiently finding high-quality decap solutions and exhibits strong robustness to handle real-world and large-scale problems, which brings decap optimization algorithms to a new benchmark. © 2023, CC BY.

关键词： Genetic algorithms

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Cellulose Hydrogel-Based Biodegradable and Recyclable Magnetoelectric Composites for Electromechanical Conversion

SSRN

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SSRN 2022年

作者： Hu, Sanming Zheng, Min Wang, Qi Li, Ling Xing, Jun Chen, Kun Qi, Fuyu He, Pengyu Mao, Lin Shi, Zhijun Su, Bin Yang, Guang School of Biomedical Engineering and Imaging Xianning Medical College Hubei University of Science and Technology Xianning437100 China College of Life Science and Technology Huazhong University of Science and Technology Wuhan430074 China Huazhong University of Science and Technology China State Key Laboratory of Material Processing and Die & Mould Technology School of Materials Science and Engineering Huazhong University of Science and Technology Hubei Wuhan430074 China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Hubei Wuhan430074 China College of Life Sciences Henan Agricultural University Zhengzhou450002 China

Flexible electromechanical conversion devices have attracted enormous attention as energy harvesters and self-powered sensors in the fields of wearable electronics and robotics. However, current flexible devices composed of plastic polymers and metals suffer from non-degradability and limited recyclability. Herein, a biodegradable and recyclable hydrogel-based magnetoelectric (ME) composite is fabricated via introducing NdFeB magnetic particles and copper wires into the regenerated bacterial cellulose (rBC) hydrogel. The developed hydrogel-based ME composites can effectively convert the mechanical kinetic energy into electrical energy based on the principle of electromagnetic induction, which maximum voltage reaches 15 µV. In addition, degradation experiments are conducted in this work to demonstrate the hydrogel can be rapidly degraded within 3 hours under the condition of enzyme and completely natural degraded within 49 days in water, respectively. Moreover, the left NdFeB particles and copper wires can be recyclable and reused for the same devices, leaving no environmentally hazardous electronic waste. © 2022, The Authors. All rights reserved.

关键词： Iron alloys

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ACQ-to-AIE Transformation: Tuning Molecular Packing by Regioisomerization for Two-Photon NIR Bioimaging

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Angewandte Chemie 2020年第31期132卷 12922-12926页

作者： Li Y. Liu S. Ni H. Zhang H. Chuah C. Ma C. Wong K.S. Lam J.W.Y. Kwok R.T.K. Qian J. Lu X. Tang B.Z. Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction Institute for Advanced Study Department of Chemical and Biological Engineering State Key Laboratory of Molecular Neuroscience and Division of Life Science The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong HKUST-Shenzhen Research Institute No. 9 Yuexing 1st RD South Area Hi-tech Park Nanshan Shenzhen 518057 China State Key Laboratory of Modern Optical Instrumentations Centre for Optical and Electromagnetic Research College of Optical Science and Engineering Zhejiang University Hangzhou 310058 China Department of Physics The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Department of Materials Science Fudan University Shanghai 200438 China Center for Aggregation-Induced Emission SCUT-HKUST Joint Research Institute State Key Laboratory of Luminescent Materials and Devices South China University of Technology Guangzhou 510640 China

The traditional design strategies for highly bright solid-state luminescent materials rely on weakening the intermolecular π–π interactions, which may limit diversity when developing new materials. Herein, we propose a strategy of tuning the molecular packing mode by regioisomerization to regulate the solid-state fluorescence. TBP-e-TPA with a molecular rotor in the end position of a planar core adopts a long-range cofacial packing mode, which in the solid state is almost non-emissive. By shifting molecular rotors to the bay position, the resultant TBP-b-TPA possesses a discrete cross packing mode, giving a quantum yield of 15.6±0.2 %. These results demonstrate the relationship between the solid-state fluorescence efficiency and the molecule's packing mode. Thanks to the good photophysical properties, TBP-b-TPA nanoparticles were used for two-photon deep brain imaging. This molecular design philosophy provides a new way of designing highly bright solid-state fluorophores. © 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

关键词： ACQ-to-AIE transformation aggregation-induced emission cross packing regioisomerization two-photon imaging

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