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Lithiophilic Li-Si alloy-solid electrolyte interface enabled by high-concentration dual salt-reinforced quasi-solid-state electrolyte

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Journal of Energy Chemistry 2024年第8期95卷 216-230页

作者： Yuanxing zhang Ling zhang Zhiguang Zhao yuxiang zhang Jingwen Cui Chengcai Liu Daobin Mu Yuefeng Su Borong Wu Feng Wu School of Materials Science and Engineering Beijing Institute of Technology Chongqing Innovation Center Beijing Institute of Technology Collaborative Innovation Center of Electric Vehicles in Beijing

Solid polymer electrolytes（SPEs） are urgently required to achieve practical solid-state lithium metal batteries（LMBs） and lithium-ion batteries（LIBs）,Herein,we proposed a mechanism for modulating interfacial conduction and anode interfaces in high-concentration SPEs by LiDFBOP.Optimized electrolyte exhibits superior ionic conductivity and remarkable interface compatibility with salt-rich clusters:（1）polymer-plastic crystal electrolyte（P-PCE,TPU-SN matrix） dissociates ion pairs to facilitate Li+transport in the electrolyte and regulates Li+diffusion in the SEI.The crosslinking structure of the matrix compensates for the loss of mechanical strength at high-salt concentrations;（2） dual-anion TFSI-_n-DFBOP-min the Li+solvation sheath facilitates facile Li+desolvation and formation of salt-rich clusters and is conducive to the formation of Li conductive segments of TPU-SN matrix;（3） theoretical calculations indicate that the decomposition products of LiDFBOP form SEI with lower binding energy with LiF in the SN system,thereby enhancing the interfacial electrochemical redox kinetics of SPE and creating a solid interface SEI layer rich in LiF.As a result,the optimized electrolyte exhibits an excellent ionic conductivity of9.31 × 10-4S cm-1at 30℃ and a broadened electrochemical stability up to 4.73 V.The designed electrolyte effectively prevents the formation of Li dendrites in Li symmetric cells for over 6500 h at0.1 mA cm-2.The specific Li-Si alloy-solid state half-cell capacity shows 711.6 mAh g-1after 60 cycles at 0.3 A g-1. Excellent rate performance and cycling stability are achieved for these solid-state batteries with Li-Si alloy anodes and NCM 811 cathodes.NCM 811‖ Prelithiated silicon-based anode solid-state cell delivers a discharge capacity of 195.55 mAh g-1and a capacity retention of 97.8% after 120 cycles.NCM 811‖Li solid-state cell also delivers capacity retention of 84.2% after 450 cycles.

关键词： Li-Si alloy anode Prelithiation SEI layer Solid-state electrolyte

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Clinical characteristics and risk factors for mortality in Candida auris infections

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iLABMED 2024年第2期2卷 79-87页

作者： Kang Li Xin Liu Danfeng Liu Yuqi Zhi Chang Dong Pengrui Sun Yueming Dong Hongfang Pan yuxiang zhang Hong Lei Laboratory Medicine Center The Eighth Medical Center of Chinese PLA General HospitalBeijingChina Medical College Wuhan University of Science and TechnologyWuhanChina Lingyuan Central Hospital LingyuanLiaoningChina Department of Critical Care Medicine The Eighth Medical Center of Chinese PLA General HospitalBeijingChina

Background:Candida auris infections pose a threat to public health,necessitating increased awareness in China.This study aimed to analyze the strains of C.auris,assess the infection status,and investigate clinical characteristics and risk factors for mortality.Methods:A retrospective analysis was conducted on 18 patients with Candida auris infection.We focused on evaluating basic characteristics,strain sources,and antibacterial susceptibility test results.Statistical methods were used to determine clinical features and identify risk factors for death.Results:The strain type,composition ratio,and specimen source of C.auris were not associated with mortality.Neither the infection index nor the length of hospitalization showed an association with the prognosis.However,significant risk factors for mortality included cerebral infarction,cardiac disease,renal dysfunction,hypoproteinemia,and anemia(all p<0.05).Conclusions:Cerebral infarction,cardiac disease,renal dysfunction,hypoproteinemia,and anemia are significant risk factors for death in C.auris infections.These findings indicate the importance of recognizing and addressing these factors in the clinical management of C.auris infection.

关键词： Candida auris clinical characteristic antimicrobial susceptibility test risk factor

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Adversarial Training-Aided Time-Varying Channel Prediction for TDD/FDD Systems

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China Communications 2023年第6期20卷 100-115页

作者： Zhen zhang yuxiang zhang Jianhua zhang Feifei Gao State Key Lab of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Institute for Artificial Intelligence Tsinghua UniversityBeijing 100084China

In this paper, a time-varying channel prediction method based on conditional generative adversarial network(CPcGAN) is proposed for time division duplexing/frequency division duplexing(TDD/FDD) systems. CPc GAN utilizes a discriminator to calculate the divergence between the predicted downlink channel state information(CSI) and the real sample distributions under a conditional constraint that is previous uplink CSI. The generator of CPcGAN learns the function relationship between the conditional constraint and the predicted downlink CSI and reduces the divergence between predicted CSI and real CSI.The capability of CPcGAN fitting data distribution can capture the time-varying and multipath characteristics of the channel well. Considering the propagation characteristics of real channel, we further develop a channel prediction error indicator to determine whether the generator reaches the best state. Simulations show that the CPcGAN can obtain higher prediction accuracy and lower system bit error rate than the existing methods under the same user speeds.

关键词： channel prediction time-varying channel conditional generative adversarial network multipath channel deep learning

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Prior-guided GAN-based interactive airplane engine damage image augmentation method

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Chinese Journal of Aeronautics 2022年第10期35卷 222-232页

作者： Rui HUANG Bokun DUAN yuxiang zhang Wei FAN School of Computer Science and Technology Civil Aviation University of ChinaTianjin 300300China

Deep learning-based methods have achieved remarkable success in object detection,but this success requires the availability of a large number of training images.Collecting sufficient training images is difficult in detecting damages of airplane engines.Directly augmenting images by rotation,flipping,and random cropping cannot further improve the generalization ability of existing deep models.We propose an interactive augmentation method for airplane engine damage images using a prior-guided GAN to augment training images.Our method can generate many types of damages on arbitrary image regions according to the strokes of users.The proposed model consists of a prior network and a GAN.The Prior network generates a shape prior vector,which is used to encode the information of user strokes.The GAN takes the shape prior vector and random noise vectors to generate candidate damages.Final damages are pasted on the given positions of background images with an improved Poisson fusion.We compare the proposed method with traditional data augmentation methods by training airplane engine damage detectors with state-ofthe-art object detectors,namely,Mask R-CNN,SSD,and YOLO v5.Experimental results show that training with images generated by our proposed data augmentation method achieves a better detection performance than that by traditional data augmentation methods.

关键词： Airplane engine Damage detection Data augmentation GAN Interactive

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Implementation Framework and Validation of Cluster-Nuclei Based Channel Model Using Environmental Mapping for 6G Communication Systems

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China Communications 2022年第4期19卷 1-13页

作者： Li Yu yuxiang zhang Jianhua zhang Zhiqiang Yuan State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China

With the research of the upcoming sixth generation(6 G) systems, new technologies will require wider bandwidth, larger scale antenna arrays and more diverse wireless communication scenarios on the future channel modeling. Considering channel model is prerequisite for system design and performance evaluation of 6 G technologies, we face a challenging task: how to accurately and efficiently model 6 G channel for various scenarios? This paper tries to answer it. Firstly, the features of cluster-nuclei(CN) and principle of cluster-nuclei based channel model(CNCM) are introduced. Then, a novel modeling framework is proposed to implement CNCM,which consists four steps: propagation environment reconstruction, cluster-nuclei identification, multipath parameters generation, and channel coefficients generation. Three-dimensional environment with material information is utilized to map CN with scatterers in the propagation pathway. CN are identified by geometrical and electric field calculation based on environmental mapping, and multipath components within CN are calculated by statistical characteristics of angle, power and delay domains. Finally, we present a three-level verification structure to investigate the accuracy and complexity of channel modeling comprehensively. Simulation results reveal that CNCM can perform higher accuracy than geometrybased stochastic model while lower complexity compared with ray-tracing model for practical propagation environment.

关键词： channel model 6G cluster-nuclei environmental mapping scatterer ray-tracing geometrybased stochastic model

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Mastering lanthanide energy states for next-gen photonic innovation

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中国科学:化学英文版 2023年第9期66卷 2460-2479页

作者： Yuyang Gu Chang Gu yuxiang zhang Zhen Mu Xiaogang Liu Department of Chemistry National University of SingaporeSingapore 117543Singapore Institute of Materials Research and Engineering Agency for ScienceTechnology and ResearchSingapore 138634Singapore

Lanthanide-based photonic materials have been extensively explored for use in laser crystals,lighting,fiber-optic communications,bioimaging,diagnostics,and many other fields.In recent years,they have enabled numerous breakthroughs in areas such as single-particle spectroscopy,super-resolution imaging,micro-lasing,lifetime multiplexing,and detection.Here,we summarize recent advances in lanthanide photonic materials from an energy state perspective,focusing on the interplay between energy state manipulation and advanced photonic applications.We then discuss the challenges and prospects for controlling energy states at the single-particle level.We wish to highlight the importance of quantifying and understanding the energy states of lanthanides for future innovations.

关键词： lanthanide nanomaterials super-resolution lifetime lasing

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Environment Information-Based Channel Prediction Method Assisted by Graph Neural Network

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China Communications 2022年第11期19卷 1-15页

作者： Yutong Sun Jianhua zhang yuxiang zhang Li Yu Qixing Wang Guangyi Liu State Key Lab of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Future Research Laboratory China Mobile Research InstituteBeijing 100053China

Recently,whether the channel prediction can be achieved in diverse communication scenarios by directly utilizing the environment information gained lots of attention due to the environment impacting the propagation characteristics of the wireless channel.This paper presents an environment information-based channel prediction(EICP)method for connecting the environment with the channel assisted by the graph neural networks(GNN).Firstly,the effective scatterers(ESs)producing paths and the primary scatterers(PSs)generating single propagation paths are detected by building the scatterercentered communication environment graphs(SCCEGs),which can simultaneously preserve the structure information and highlight the pending scatterer.The GNN-based classification model is implemented to distinguish ESs and PSs from other scatterers.Secondly,large-scale parameters(LSP)and small-scale parameters(SSP)are predicted by employing the GNNs with multi-target architecture and the graphs of detected ESs and PSs.Simulation results show that the average normalized mean squared error(NMSE)of LSP and SSP predictions are 0.12 and 0.008,which outperforms the methods of linear data learning.

关键词： channel prediction propagation environment graph scatterer detection GNN

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Molecular basis and homeostatic regulation of Zinc taste

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Protein & Cell 2022年第6期13卷 462-469页

作者： Rui Luo yuxiang zhang Yinjun Jia Yan zhang Zongyang Li Jieqing Zhao Ting Liu Wei zhang School of Life Sciences IDG/McGovern Institute for Brain ResearchTsinghua UniversityBeijing 100084China Tsinghua-Peking Center for Life Sciences Beijing 100084China

Dear Editor,Among all the essential trace metals,zinc is of particular importance for its huge panoply of biological functions.As a pivotal element for hundreds of enzymes,either scarcity or accumulation of body zinc can lead to severe disorders(Maret,2017).Therefore,body zinc must be tightly regulated in order to keep a precise amount that is sufficient for cells’survival but does not cause toxicity.As diet is the major source of trace elements including zinc,animals must adjust their feeding amount and preference to avoid scarcity or accumulation.However,how animal utilize their gustatory organs to detect zinc in food and whether the taste is regulated with body zinc level are unknown.Metals often cause the sense of taste termed as metallic taste.While sodium of certain concentration range delivers hedonic salty taste,salt solutions of most metals taste aversive.It was reported that zinc,copper and other heavy metal ions trigger an unpleasant sense of astringent/drying,sour or bitter.Although taste receptor cells were found essential for the detection of some divalent ions,the molecular mechanisms for this detection are largely elusive.Recently,the receptors for calcium were unambiguously identified in fruit fly(Lee et al.,2018).However,a full repertoire of receptors for sensing divalent ions is still lacking.

关键词： metals utilize precise

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Topology and Semantic Information Fusion Classification Network Based on Hyperspectral Images of Chinese Herbs

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Journal of Beijing Institute of Technology 2023年第5期32卷 551-561页

作者： Boyu Zhao yuxiang zhang Zhengqi Guo Mengmeng zhang Wei Li School of Information and Electronics Beijing Institute of Technologyand Beijing Kay Laboratory of Fractional Signals and SystemsBeijing 100081China

Most methods for classifying hyperspectral data only consider the local spatial relation-ship among samples,ignoring the important non-local topological relationship.However,the non-local topological relationship is better at representing the structure of hyperspectral data.This paper proposes a deep learning model called Topology and semantic information fusion classification network(TSFnet)that incorporates a topology structure and semantic information transmis-sion network to accurately classify traditional Chinese medicine in hyperspectral *** uses a convolutional neural network(CNN)to extract features and a graph convolution network(GCN)to capture potential topological relationships among different types of Chinese herbal medicines.The results show that TSFnet outperforms other state-of-the-art deep learning classification algorithms in two different scenarios of herbal medicine datasets.Additionally,the proposed TSFnet model is lightweight and can be easily deployed for mobile herbal medicine classification.

关键词： Chinese herbs hyperspectral image deep learning non-local topological relationships convolutional neural network(CNN) graph convolutional network(GCN) lightweight

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A Predictive 6G Network with Environment Sensing Enhancement:From Radio Wave Propagation Perspective

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China Communications 2022年第6期19卷 105-122页

作者： Gaofeng Nie Jianhua zhang yuxiang zhang Li Yu Zhen zhang Yutong Sun Lei Tian Qixing Wang Liang Xia State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Future Research Laboratory China Mobile Research InstituteBeijing 100053China

In order to support the future digital society,sixth generation(6G)network faces the challenge to work efficiently and flexibly in a wider range of scenarios.The traditional way of system design is to sequentially get the electromagnetic wave propagation model of typical scenarios firstly and then do the network design by simulation offline,which obviously leads to a 6G network lacking of adaptation to dynamic environments.Recently,with the aid of sensing enhancement,more environment information can be obtained.Based on this,from radio wave propagation perspective,we propose a predictive 6G network with environment sensing enhancement,the electromagnetic wave propagation characteristics prediction enabled network(EWave Net),to further release the potential of 6G.To this end,a prediction plane is created to sense,predict and utilize the physical environment information in EWave Net to realize the electromagnetic wave propagation characteristics prediction timely.A two-level closed feedback workflow is also designed to enhance the sensing and prediction ability for EWave Net.Several promising application cases of EWave Net are analyzed and the open issues to achieve this goal are addressed finally.

关键词： 6G network electromagnetic waves propagation characteristics prediction environment information sensing enhancement

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