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Effect of LiCoO_(2)on the positive temperature coefficient effect(PTC)properties of semiconductive composites and its ability to inhibit space charge injection

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High Voltage 2022年第5期7卷 1016-1022页

作者： Ciyao Wang Shumei Chen Yu Long Yujia Liu Chuncheng Hao qingquan lei Institute of Advanced Electrical Materials Qingdao University of Science and TechnologyQingdaoChina

The semiconductive shield layer is between the conductive core and the insulation layer of high voltage direct current transmission cables and plays an important role in suppressing the accumulation of space charge in the insulation layer.Since the prevalent positive temperature coefficient effect(PTC)of the semiconducting layer leads to cable ageing and failure,this paper proposes the use of lithium cobaltate to modify the semiconducting shield to suppress its PTC effect and improve its ability to inhibit space charge injection.The ionic conductor LiCoO_(2)was prepared by the sol–gel method.LiCoO_(2)particles with particle sizes ranging from tens to hundreds of nanometres were obtained by ball milling.The prepared LiCoO_(2)was used as a filler to modify the carbon black(CB)/ethylene vinyl acetate copolymer(EVA)/low density polyethylene(LDPE)composites.After melt blending and moulding cross-linking,LiCoO_(2)/CB/EVA/LDPE semiconductive shielding specimens were successfully fabricated.Resistivity,Thermally Stimulated Depolarisation Currents(TSDC),and pulsed electroacoustic measurements were conducted for the prepared specimens.The PTC effect,which is common in polymer composites,was successfully suppressed,and the PTC strength was reduced by 17%.The resistivity of the semiconductive shielding layer was significantly reduced.The ability of the semiconducting shield to inhibit space charge injection from the conductive core to the insulation layer was significantly improved.When LiCoO_(2)content is 0.5 wt%,the semiconductive shielding layer has the best performance,and the space charge in the insulation layer was reduced by 70%compared to the undoped semiconducting shield.

关键词： composites conductive effect

Insulation structure design and electric field simulation of 500 kV isolation energy supply transformer for HVDC breaker

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High Voltage 2022年第1期7卷 185-196页

作者： Sheng Zhang Yadong Fan qingquan lei Jianguo Wang Yuan Liu Ting Zhan School of Electrical Engineering and Automation Wuhan UniversityWuhanChina Global Energy Interconnection Research Institute Co. LtdBeijingChina Institute of Advanced Electrical Materials Qingdao University of Science and TechnologyQingdaoChina China EPRI Electric Power Engineering Co.Ltd. BeijingChina

The high‐voltage isolated energy supply transformer(HIET)is the key component of the HVDC breaker,which is used for energy transmission and the potential isolation.There is a lack of research results that can meet engineering applications at home and abroad.The design of a 500 kV HIET with dry‐type insulation is proposed,using 10 cascade connected 50 kV sub‐transformers(STs),which uses silicon rubber suitable for DC voltage as the main insulation material.High‐voltage(HV)winding of ST adopts double‐shielding structure of coil semi‐conductive shielding and inner semi‐conductive shielding to improve electric field distribution.The simulation analysis of an electric field at different insulation thicknesses and temperatures shows that the electric field decreases with an increase in thickness of insulation.When the thickness is greater than 25 mm,the electric field reduction effect is significantly weakened.The electric field is closely related to temperature,when at 20℃,the electric field between double‐shielding is relatively uniform.When at 70℃,the inner shielding electric field is much higher than coil shielding,and undergoes obvious reversal.In addition,the 500 kV HIET's electric field has been analysed.The 500kV HIET prototype has been manufactured and passed the type test,and successfully applied to the 500 kV Zhangbei DC grid project.

关键词： winding insulation field

Machine learning and microstructure design of polymer nanocomposites for energy storage application

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High Voltage 2022年第2期7卷 242-250页

作者： Yu Feng Wenxin Tang Yue Zhang Tiandong Zhang Yanan Shang Qingguo Chi Qingguo Chen qingquan lei Department of High Voltage Key Laboratory of Engineering Dielectrics and Its ApplicationMinistry of EducationHarbin University of Science and TechnologyHarbinChina School of Electrical and Electronic Engineering Harbin University of Science and TechnologyHarbinChina

Film dielectric capacitors have been widely used in high‐power electronic equipment.The design of microstructure and the choice of fillers play an important role in nano-composites'energy storage density.Machine learning methods can classify and summarise the limited data and then explore the promising composite structure.In this work,a dataset has been established,which contained a large amount of data on the maximum energy storage density of nanocomposites.Though using processed visual image infor-mation to express the internal information of composite,the prediction accuracy of the prediction models built by three machine learning algorithms increase from 84.1%to 91.9%,80.9%to 68.9%,70.6%to 81.6%,respectively.By calculating the branch weight in the random forest prediction model,the influence degree of different descriptors on the energy storage performance of nanocomposites is analysed.A total of 10 groups of composites with different structure and filler amount were prepared in the laboratory,which were used to verify the reliability of prediction models.Finally,the effective filler's structure is explored by three prediction models and some suggestions for the interface design of filler are given.

关键词： composites composite prediction

Effect of graphene modified semi-conductive shielding layer on space charge accumulation in insulation layer for high-voltage direct current cable

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High Voltage 2022年第3期7卷 545-552页

作者： Guochang Li Xuejing Li Fan Zhang Xiaojian Liang Mingyue Liu Yanhui Wei Shengtao Li Chuncheng Hao qingquan lei Institute of Advanced Electrical Materials Qingdao University of Science and TechnologyQingdaoChina State Key Laboratory of Electrical Insulation and Power Equipment Xi'an Jiaotong UniversityXi'anChina

Space charge accumulation in the insulation layer of high-voltage direct current(HVDC)cable is one of the key factors restricting the development of HVDC cable.The inner semi-conductive layer as an important structure of cable will affect the charge accumu-lation characteristics in the insulation layer.This work intends to explore the method of modifying the semi-conductive layer with graphene,to suppress charge accumulation in the insulation layer.First,the semi-conductive layer with different contents of Graphene(G)and carbon black(CB)are prepared.Second,the morphology and surface roughness of the cross section are analysed.Further,the effects of the semi-conductive layer on space charge accumulation of the insulation layer are studied by pulsed electro-acoustic method and thermal stimulation depolarisation current method.The experimental re-sults show that a moderate amount of graphene replacing CB can effectively reduce charge accumulation in the insulation layer and inhibit positive temperature coefficient(PTC)effect at the same time.The surface roughness of specimens decreases with the increase of G content from 0 to 3 phr(parts per hundreds of resin),when the CB content decreases from 25 to 10 phr,the surface roughness of specimen increases.The resistivity test shows that doping G can significantly inhibit the PTC effect of the semi-conductive layer.The volume resistivity of the semi-conductive layer decreases with the increase of G content and CB content.In addition,charge accumulation of the insulation layer rises and then drops under the action of the semi-conductive layer.

关键词： insulation conductive layer

Recent advances in cancer-associated fibroblast:Biomarkers,signaling pathways,and therapeutic opportunities

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Chinese Medical Journal 2024年第6期137卷 638-650页

作者： Donger Zhou lei Zheng Department of Hepatobiliary-Pancreatic Surgery The Second Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang 310009China Sidney Kimmel Comprehensive Cancer Center The Skip Viragh Pancreatic Cancer Center for Clinical Research and Careand The Bloomberg-Kimmel Institute for Immunotherapy at Johns Hopkins University School of MedicineBaltimoreMD 21287USA

Anti-cancer therapies usually focus on tumor cells,but non-tumor stromal components in the tumor microenvironment also play vital roles in tumor initiation and progression,which may be the prognostic factors and potential therapeutic targets.Cancer-associated fibroblasts(CAFs)are the essential component in the tumor environment,exhibiting high heterogeneity in their cell origin and phenotype with diverse functions that influence tumor angiogenesis,immune systems,and metabolism.Single-cell RNA sequencing and genetically engineered mouse models have increased our understanding of CAF diversity,and many subtypes have been defined.However,the precise functions of these subtypes need to be studied and validated.Studies of signaling pathways and epigenetic changes in CAFs facilitate understanding of the phenotypes of CAFs and the crosstalk between tumor cells and CAFs to provide potential therapeutic targets.Some clinical trials,including phase III trials targeting CAFs,have been performed recently.However,few of these trials have generated promising results,which indicates that the complexity of CAFs in the tumor microenvironment remains largely unknown,and in-depth investigations of CAFs should be performed.This review summarizes the research on CAFs,focusing on the heterogeneity of their phenotypes and functions,specific signaling pathways,and the therapeutic strategies involving CAFs.Additionally,we briefly discuss the current technologies commonly used in CAF studies and describe the challenges and future perspectives of CAF research.

关键词： Cancer-associated fibroblasts Tumor microenvironment Anti-cancer therapy Targeted therapy

Metarelation2vec:A Metapath-Free Scalable Representation Learning Model for Heterogeneous Networks

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Tsinghua Science and Technology 2024年第2期29卷 553-575页

作者： lei Chen Yuan Li Yong lei Xingye Deng School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China

Metapaths with specific complex semantics are critical to learning diverse semantic and structural information of heterogeneous networks(HNs)for most of the existing representation learning models.However,any metapaths consisting of multiple,simple metarelations must be driven by domain experts.These sensitive,expensive,and limited metapaths severely reduce the flexibility and scalability of the existing models.A metapath-free,scalable representation learning model,called Metarelation2vec,is proposed for HNs with biased joint learning of all metarelations in a bid to address this problem.Specifically,a metarelation-aware,biased walk strategy is first designed to obtain better training samples by using autogenerating cooperation probabilities for all metarelations rather than using expert-given metapaths.Thereafter,grouped nodes by the type,a common and shallow skip-gram model is used to separately learn structural proximity for each node type.Next,grouped links by the type,a novel and shallow model is used to separately learn the semantic proximity for each link type.Finally,supervised by the cooperation probabilities of all meta-words,the biased training samples are thrown into the shallow models to jointly learn the structural and semantic information in the HNs,ensuring the accuracy and scalability of the models.Extensive experimental results on three tasks and four open datasets demonstrate the advantages of our proposed model.

关键词： metarelation random walk heterogeneous network metapath representation learning

Structural energy storage composites based on modified carbon fiber electrode with metal-organic frame enhancing layered double hydroxide

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Nano Research 2024年第3期17卷 1552-1563页

作者： Jinrui Ye Zhongbao Wang Qin lei lei Sun Jinfeng Gu School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Tangshan Research Institute Beijing Institute of TechnologyTangshan 063000China School of Materials Science and Engineering Shenyang Jianzhu UniversityShenyang 110168China Department of Stomatology PLA Strategic Support Force Characteristic Medical CenterBeijing 100101China Beijing Electromechanical Engineering Research Institute Beijing 100074China

Structural energy storage composites present advantages in simultaneously achieving structural strength and electrochemical properties.Adoption of carbon fiber electrodes and resin structural electrolytes in energy storage composite poses challenges in maintaining good mechanical and electrochemical properties at reasonable cost and effort.Here,we report a simple method to fabricate structural supercapacitor using carbon fiber electrodes(modified by Ni-layered double hydroxide(Ni-LDH)and in-situ growth of Co-metal-organic framework(Co-MOF)in a two-step process denoted as Co-MOF/Ni-LDH@CF)and bicontinuous-phase epoxy resin-based structural electrolyte.Co-MOF/Ni-LDH@CF as electrode material exhibits improved specific capacity(42.45 F·g^(-1))and cycle performance(93.3%capacity retention after 1000 cycles)in a three-electrode system.The bicontinuous-phase epoxy resin-based structural electrolyte exhibits an ionic conductivity of 3.27×10^(-4) S·cm^(-1).The fabricated Co-MOF/Ni-LDH@CF/SPE-50 structural supercapacitor has an energy density of 3.21 Wh·kg^(-1) at a power density of 42.25 W·kg^(-1),whilst maintaining tensile strength and modulus of 334.6 MPa and 25.2 GPa.These results show practical potential of employing modified commercial carbon fiber electrodes and epoxy resin-based structural electrolytes in structural energy storage applications.

关键词： carbon fiber electrode structural electrolyte structural energy storage composites supercapacitor

DCVAE-adv:A Universal Adversarial Example Generation Method for White and Black Box Attacks

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Tsinghua Science and Technology 2024年第2期29卷 430-446页

作者： lei Xu Junhai Zhai College of Mathematics and Information Science Hebei UniversityBaoding 071002China

Deep neural network(DNN)has strong representation learning ability,but it is vulnerable and easy to be fooled by adversarial examples.In order to handle the vulnerability of DNN,many methods have been proposed.The general idea of existing methods is to reduce the chance of DNN models being fooled by observing some designed adversarial examples,which are generated by adding perturbations to the original images.In this paper,we propose a novel adversarial example generation method,called DCVAE-adv.Different from the existing methods,DCVAE-adv constructs adversarial examples by mixing both explicit and implicit perturbations without using original images.Furthermore,the proposed method can be applied to both white box and black box attacks.In addition,in the inference stage,the adversarial examples can be generated without loading the original images into memory,which greatly reduces the memory overhead.We compared DCVAE-adv with three most advanced adversarial attack algorithms:FGSM,AdvGAN,and AdvGAN++.The experimental results demonstrate that DCVAE-adv is superior to these state-of-the-art methods in terms of attack success rate and transfer ability for targeted attack.Our code is available at https://***/xzforeverlove/DCVAE-adv.

关键词： deep neural network adversarial examples white box attack black box attack robustness

Pharmacological Effects of Botanical Drugs on Myocardial Metabolism in Chronic Heart Failure

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Chinese Journal of Integrative Medicine 2024年第5期30卷 458-467页

作者： HU Yu-xuan QIU Sheng-lei SHANG Ju-ju WANG Zi LAI Xiao-lei Beijing Hospital of Traditional Chinese Medicine Capital Medical UniversityBeijing 100010China

Although there have been significant advances in the treatment of heart failure in recent years,chronic heart failure remains a leading cause of cardiovascular disease-related death.Many studies have found that targeted cardiac metabolic remodeling has good potential for the treatment of heart failure.However,most of the drugs that increase cardiac energy are still in the theoretical or testing stage.Some research has found that botanical drugs not only increase myocardial energy metabolism through multiple targets but also have the potential to restore the balance of myocardial substrate metabolism.In this review,we summarized the mechanisms by which botanical drugs(the active ingredients/formulas/Chinese patent medicines)improve substrate utilization and promote myocardial energy metabolism by activating AMP-activated protein kinase(AMPK),peroxisome proliferator-activated receptors(PPARs)and other related targets.At the same time,some potential protective effects of botanical drugs on myocardium,such as alleviating oxidative stress and dysbiosis signaling,caused by metabolic disorders,were briefly discussed.

关键词： botanical drugs chronic heart failure myocardial metabolism pharmacological effects review