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| 1 | Effects of PE-g-DBM as a Compatiblizer on Mechanical Properties and Crystallization Behaviors of Magnesium Hydroxide-based LLDPE Blends显示文摘 | Qu Baojun Fan Weicheng Hu Yuan Shen Xiaofeng | 2002 | Polym Degrad Stab2002，76，： | 1 |
| 2 | Experimen- tal verification of the new ultimate strength equation of spher- ical pressure hulls显示文摘 | PAN Binbin CUI Weicheng SHEN Yunsheng | 2012 | Marine Structures2012，，5： | 1 |
| 3 | Genetic Variants in Cyclooxygenase-2 : Expression and Risk of Gastric Cancer and Its Precursors in a Chinese Population显示文摘 | Fen Liu Kaifeng Pan Xuemei Zhang Yang Zhang Lian Zhang Junling Ma Caixuan Dong Lin Shen Jiyou Li Dajun Deng Dongxin Lin Weicheng You | 2006 | Gastroenterology2006，，7： | 1 |
| 4 | Sparse Adversarial Learning for FDIA Attack Sample Generation in Distributed Smart显示文摘False data injection attack(FDIA)is an attack that affects the stability of grid cyber-physical system(GCPS)by evading the detecting mechanism of bad data.Existing FDIA detection methods usually employ complex neural networkmodels to detect FDIA attacks.However,they overlook the fact that FDIA attack samples at public-private network edges are extremely sparse,making it difficult for neural network models to obtain sufficient samples to construct a robust detection model.To address this problem,this paper designs an efficient sample generative adversarial model of FDIA attack in public-private network edge,which can effectively bypass the detectionmodel to threaten the power grid system.A generative adversarial network(GAN)framework is first constructed by combining residual networks(ResNet)with fully connected networks(FCN).Then,a sparse adversarial learning model is built by integrating the time-aligned data and normal data,which is used to learn the distribution characteristics between normal data and attack data through iterative confrontation.Furthermore,we introduce a Gaussian hybrid distributionmatrix by aggregating the network structure of attack data characteristics and normal data characteristics,which can connect and calculate FDIA data with normal characteristics.Finally,efficient FDIA attack samples can be sequentially generated through interactive adversarial learning.Extensive simulation experiments are conducted with IEEE 14-bus and IEEE 118-bus system data,and the results demonstrate that the generated attack samples of the proposed model can present superior performance compared to state-of-the-art models in terms of attack strength,robustness,and covert capability. | Fengyong Li Weicheng Shen Zhongqin Bi Xiangjing Su | 2024 | Computer Modeling in Engineering & Sciences2024，139，5： | 0 |
| 5 | In situ electrochemical reconstruction of Sr_(2)Fe_(1.45)Ir_(0.05)Mo_(0.5)O_(6-δ)perovskite cathode for CO_(2)electrolysis in solid oxide electrolysis cells显示文摘Solid oxide electrolysis cells provide a practical solution for the direct conversion of CO_(2)to other chemicals(i.e.CO),however,an in-depth mechanistic understanding of the dynamic reconstruction of active sites for perovskite cathodes during CO_(2)electrolysis remains a great challenge.Herein,we identify that iridium-doped Sr_(2)Fe_(1.45)Ir_(0.05)Mo_(0.5)O_(6-δ)(SFIrM)perovskite displays a dynamic electrochemical reconstruction feature during CO_(2)electrolysis with abundant exsolution of highly dispersed IrFe alloy nanoparticles on the SFIrM surface.The in situ reconstructed IrFe@SFIrM interfaces deliver a current density of 1.46 A cm^(−2)while maintaining over 99%CO Faradaic efficiency,representing a 25.8%improvement compared with the Sr_(2)Fe_(1.5)Mo_(0.5)O_(6-δ)counterpart.In situ electrochemical spectroscopy measurements and density functional theory calculations suggest that the improved CO_(2)electrolysis activity originates from the facilitated formation of carbonate intermediates at the IrFe@SFIrM interfaces.Our work may open the possibility of using an in situ electrochemical poling method for CO_(2)electrolysis in practice. | Yuxiang Shen Tianfu Liu Rongtan Li Houfu Lv Na Ta Xiaomin Zhang Yuefeng Song Qingxue Liu Weicheng Feng Guoxiong Wang Xinhe Bao | 2023 | National Science Review2023，10，9： | 0 |
| 6 | In-situ exsolution of cobalt nanoparticles from La_(0.5)Sr_(0.5)Fe_(0.8)Co_(0.2)O_(3-δ) cathode for enhanced CO_(2) electrolysis performance显示文摘Solid oxide electrolysis cell(SOEC)is a promising technology for CO_(2) conversion and renewable energy storage with high efficiency.It is highly desirable to develop catalytically active cathodes for CO_(2) electrolysis.Herein,cathode materials with different structural stabilities are designed by Nb substitution on La_(0.5)Sr_(0.5)Fe_(0.8)Co_(0.2)O_(3-δ)(LSFC82)to obtain La_(0.5)Sr_(0.5)Fe_(0.7)Co_(0.2)Nb_(0.1)O_(3-δ)(LSFCN721)and La_(0.5)Sr_(0.5)Fe_(0.8)Co_(0.1)Nb_(0.1)O_(3-δ)(LSFCN811),respectively.LSFC82-Sm_(0.2)Ce_(0.8)O_(2-δ)(SDC)cathode with inferior structural stability(ability to maintain the structure)shows desirable CO_(2) electrolysis performance with the generated current density of 1.80 A cm^(-2)2 at 1.6 V and stable performance during 110 h operation at 1.2 V and 800℃.However,LSFC82 particles are collapsed into pieces after stability test with the generation of Co nanoparticles simultaneously.The frameworks of LSFCN721 and LSFCN811 particles maintain well because of the high-valent niobium,but Co exsolution,ox-ygen vacancy content and the corresponding CO_(2) electrolysis performance are restricted.This work confirms that Co nanoparticles can be exsolved from LSFC82-SDC cathode during CO_(2) electrolysis,providing references for constructing metallic nanoparticles decorated-perovskite cathodes for SOECs. | Jingwei Li Qingxue Liu Yuefeng Song Houfu Lv Weicheng Feng Yuxiang Shen Chengzhi Guan Xiaomin Zhang Guoxiong Wang | 2022 | Green Chemical Engineering2022，3，3： | 0 |
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