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| 1 | Bioinspired MXene-Based User-Interactive Electronic Skin for Digital and Visual Dual-Channel Sensing显示文摘User-interactive electronic skin(e-skin) that could convert mechanical stimuli into distinguishable outputs displays tremendous potential for wearable devices and health care applications. However, the existing devices have the disadvantages such as complex integration procedure and lack of the intuitive signal display function. Here, we present a bioinspired user-interactive e-skin, which is simple in structure and can synchronously achieve digital electrical response and optical visualization upon external mechanical stimulus. The e-skin comprises a conductive layer with a carbon nanotubes/cellulose nanofibers/MXene nanohybrid network featuring remarkable electromechanical behaviors, and a stretchable elastomer layer, which is composed of silicone rubber and thermochromic pigments. Furthermore, the conductive nanohybrid network with outstanding Joule heating performance can generate controllable thermal energy under voltage input and then achieve the dynamic coloration of silicone-based elastomer. Especially, such an innovative fusion strategy of digital data and visual images enables the e-skin to monitor human activities with evermore intuition and accuracy. The simple design philosophy and reliable operation of the demonstrated e-skin are expected to provide an ideal platform for next-generation flexible electronics. | Wentao Cao Zheng Wang Xiaohao Liu Zhi Zhou Yue Zhang Shisheng He Daxiang Cui Feng Chen | 2022 | Nano-Micro Letters2022，14，7： | 4 |
| 2 | A step parameters prediction model based on transfer process neural network for exhaust gas temperature estimation after washing aero-engines显示文摘The prediction of Exhaust Gas Temperature Margin(EGTM)after washing aeroengines can provide a theoretical basis for airlines not only to evaluate the energy-saving effect and emission reduction,but also to formulate reasonable maintenance plans.However,the EGTM encounters step changes after washing aeroengines,while,in the traditional models,a persistence tendency exists between the prediction results and the previous data,resulting in low accuracy in prediction.In order to solve the problem,this paper develops a step parameters prediction model based on Transfer Process Neural Networks(TPNN).Especially,“step parameters”represent the parameters that can reflect EGTM step changes.They are analyzed in this study,and thus the model concentrates on the prediction of step changes rather than the extension of data trends.Transfer learning is used to handle the problem that few cleaning records result in few step changes for model learning.In comparison with Long Short-Term Memory(LSTM)and Kernel Extreme Learning Machine(KELM)models,the effectiveness of the proposed method is verified on CFM56-5B engine data. | Zhiqi YAN Shisheng ZHONG Lin LIN Zhiquan CUI Minghang ZHAO | 2022 | Chinese Journal of Aeronautics2022，35，3： | 1 |
| 3 | Organic Host-Guest Materials with Bright Red Room-Temperature Phosphorescence for Persistent Bioimaging显示文摘Organic room-temperature phosphorescence(RTP)materials have attracted immense attention in bioimaging due to their long emission lifetime and large Stokes shift.RTP materials with long emission wavelength can improve the penetration depth for bioimaging.However,the design of red persistent RTP materials is still challenging.In this study,a fused-ring structure has been proposed to effectively decrease the triplet energy level,thus extending the emission wavelength of phosphorescence.In addition,the fused-ring structure exhibits a high molar extinction coefficient(ɛ)and high luminescence efficiency due to the rigid structure.A new class of crystalline hosts(iminodibenzyl,IDB)are developed to stabilize the triplet excitons that are generated from the fused-ring molecules.The maximum RTP wavelength of doping materials can reach 635 nm with a lifetime of 9.35 ms.Water-disperse nanoparticles are successfully prepared for in vivo time-resolved bioimaging,which eliminates the background fluorescence interference from biological tissues.These reveal a delicate design strategy for the construction of long-wavelength emissive RTP materials for high-resolution bioimaging. | Yueyue Si Yeyun Zhao Wenbo Dai Shisheng Cui Peng Sun Jianbing Shi Bin Tong Zhengxu Cai Yuping Dong | 2023 | Chinese Journal of Chemistry2023，41，13： | 1 |
| 4 | Synthesis and Characterization of a Series of Functionalized Macrocycles Containing Oxygen and Nitrogen Heteroatoms and Their Metal - Complexes 显示文摘 | Xu Jide Ni Shisheng Cui Keshun Xu Zhiqiang | 1990 | Inorganica Chimica Acta1990，171，2： | 1 |
| 5 | Non-LOS target localization via millimeter-wave automotive radar显示文摘This paper considers the non-line-of-sight(NLOS)vehicle localization problem by using millimeter-wave(MMW)automotive radar.Several preliminary attempts for NLOS vehicle detection are carried out and achieve good results.Firstly,an electromagnetic(EM)wave NLOS multipath propagation model for vehicle scene is established.Subsequently,with the help of available multipath echoes,a complete NLOS vehicle localiza-tion algorithm is proposed.Finally,simulation and experimental results validate the effectiveness of the established EM wave propagation model and the proposed NLOS vehicle localization algorithm. | LIU Zhaoyu ZHANG Wenli ZHENG Jingyue GUO Shisheng CUI Guolong KONG Lingjiang LIANG Kun | 2023 | Journal of Systems Engineering and Electronics2023，34，5： | 0 |
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