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| 1 | Fault di agnosis for internal combustion engines using intake mani fold pressure and artificial neural network显示文摘 | WU Jianda HUANG Chengkai CHANG Yowei | 2010 | Expert Sys terns with Applications2010，37，2： | 1 |
| 2 | An Engine Fault Diagnosis System Using Intake Manifold Pressure Signal and Wigner-Ville Distribution Technique 显示文摘 | Wu Jianda Huang Chengkai | 2011 | Expert Systems with Applications2011，38，1： | 1 |
| 3 | Parallel Elite Genetic Algorithm and Application to Global Path Planning for Autonomous Robot Navigation 显示文摘 | Tsai Chingchih Huang Hsuchih Chan Chengkai | 2011 | IEEE Transactions on Industrial Electronics2011，58，10： | 1 |
| 4 | Nonlinear strong commutativity preserving maps on skew elements of prime rings with involution 显示文摘 | Liau Paokuei Huang Weilu Liu Chengkai | 2011 | Lin Alg Appl2011，436，9： | 1 |
| 5 | Multi-channel laser interferometer based on automatic frequency stabilization system for improving coordinate measurement accuracy显示文摘A multi-channel laser interferometer(MCLI)is proposed to improve the coordinate measurement accuracy.A 780 nm external cavity laser is locked on the D2 line of ^(87)Rb atom by polarization spectroscopy,and a high frequency stabilized laser source is obtained with a linewidth of 385.8 k Hz at root mean square(RMS).The interferometers share the stabilized source and individually install on 4 axes of a coordinate measuring system.As a result,the measurement uncertainty is reduced from 1.2μm to 0.2μm within the dynamic measurement range of 1.0 m.The MCLI is adept at integrate and flexible installation,which caters to various applications on precision measurement. | PANG Chengkai ZHANG Qiongqiong ZHANG Hongqiao HUANG Haiyan DENG Zejiang WU Guang | 2022 | Optoelectronics Letters2022，18，10： | 0 |
| 6 | Erratum to:Efficient flexible perovskite solar cells and modules using a stable SnO_(2)-nanocrystal isopropanol dispersion显示文摘Erratum to Nano Research,2024,17(4):2704-2711 http://gffzzd3cc09b8251d45dfskk69c9o5fvvq6von.ffgz.tsg.suse.edu.cn/10.1007/s12274-023-6115-y(1)In the article,the table of contents(TOC)image was unfortunately mispresented. | Zhiwei Su Jing Li Ruixuan Jiang Shujie Zhang Chengkai Jin Feng Ye Bingcan Ke Mengjun Zhou Jinhui Tong Hyesung Park Fuzhi Huang Yi-Bing Cheng Tongle Bu | 2024 | Nano Research2024，17，5： | 0 |
| 7 | Improving luminescence and thermometric performance of Ba_(2)CaWO_(6):Er^(3+) by tri-doping with Yb^(3+) and Na^(+)显示文摘The Er3+doped double perovskite Ba_(2)CaWO_(6) crystal is a promising ratiometric thermometer based on the fluorescence intensity ratio(FIR) of transitions from ^(2)H_(11/2) and ^(4)S_(3/2) to the lowered ^(4)I_(15/2) level.However,the Ca^(2+) vacancy defect caused by the charge difference between rare-earth ions and the substituted alkaline-earth ions gives rise to the non-radiative probability and limits the thermal sensitivity.Here,the up-conversion luminescence and thermometric performance of Er^(3+),Yb^(3+) dopedBa_(2)CaWO_(6) are tuned by tri-doping with alkaline ions.The Ca^(2+) vacancy defect can be eliminated by the introduction of Na^(+),which occupies the Ca^(2+) site when it is doped into Ba_(2)CaWO_(6) with Er^(3+) and Yb^(3+).On the contrary,the doping of Cs^(+) into Ba_(2)CaWO_(6) with Er^(3+) and Yb^(3+) enhances the defect concentration because it occupies the site of Ba^(2+).Thus,the tri-doping of Na^(+) reduces the non-radiative probability and enhances the quantum efficiency of Er^(3+),leading to the improvement of the thermometric sensitivity of Ba_(2)CaWO_(6).As a result,we get an excellent thermometric Ba_(2)CaWO_(6):8%Yb^(3+),3.5%Er^(3+),6%Na^(+) powder with a luminescence lifetime of 515 μs and maximum thermal sensitivity(S_(r)) of 1.45%/K,which is more than three times higher than that of the BCWO:Er^(3+) powder. | Lingyun Li Ziwei Zhou Fazheng Huang Senlin Peng Yantang Huang Guoqiang Wang Xinxu Li Fei-Fei Chen Chengkai Yang Xin-Xiong Li Yan Yu | 2023 | Journal of Rare Earths2023，41，1： | 0 |
| 8 | Efficient flexible perovskite solar cells and modules using a stable SnO_(2)-nanocrystal isopropanol dispersion显示文摘The outstanding advantages of lightweight and flexibility enable flexible perovskite solar cells(PSCs)to have great application potential in mobile energy devices.Due to the low cost,low-temperature processibility,and high electron mobility,SnO_(2) nanocrystals have been widely employed as the electron transport layer in flexible PSCs.To prepare high-quality SnO_(2) layers,a monodispersed nanocrystal solution is normally used.However,the SnO_(2) nanocrystals can easily aggregate,especially after long periods of storage.Herein,we develop a green and cost-effective strategy for the synthesis of high-quality SnO_(2) nanocrystals at low temperatures by introducing small molecules of glycerol,obtaining a stable and well-dispersed SnO_(2)-nanocrystal isopropanol dispersion successfully.Due to the enhanced dispersity and super wettability of this alcohol-based SnO_(2)-nanocrystal solution,large-area smooth and dense SnO_(2) films are easily deposited on the plastic conductive substrate.Furthermore,this contributes to effective charge transfer and suppressed non-radiative recombination at the interface between the SnO_(2) and perovskite layers.As a result,a greatly enhanced power conversion efficiency(PCE)of 21.8%from 19.2%is achieved for small-area flexible PSCs.A large-area 5 cm×5 cm flexible perovskite solar mini-module with a champion PCE of 16.5%and good stability is also demonstrated via this glycerol-modified SnO_(2)-nanocrystal isopropanol dispersion approach. | Zhiwei Su Jing Li Ruixuan Jiang Shujie Zhang Chengkai Jin Feng Ye Bingcan Ke Mengjun Zhou Jinhui Tong Hyesung Park Fuzhi Huang Yi-Bing Cheng Tongle Bu | 2024 | Nano Research2024，17，4： | 0 |
| 9 | A machine learning model to predict unconfined compressive strength of alkali-activated slag-based cemented paste backfill显示文摘The unconfined compressive strength(UCS)of alkali-activated slag(AAS)-based cemented paste backfill(CPB)is influenced by multiple design parameters.However,the experimental methods are limited to understanding the relationships between a single design parameter and the UCS,independently of each other.Although machine learning(ML)methods have proven efficient in understanding relationships between multiple parameters and the UCS of ordinary Portland cement(OPC)-based CPB,there is a lack of ML research on AAS-based CPB.In this study,two ensemble ML methods,comprising gradient boosting regression(GBR)and random forest(RF),were built on a dataset collected from literature alongside two other single ML methods,support vector regression(SVR)and artificial neural network(ANN).The results revealed that the ensemble learning methods outperformed the single learning methods in predicting the UCS of AAS-based CPB.Relative importance analysis based on the bestperforming model(GBR)indicated that curing time and water-to-binder ratio were the most critical input parameters in the model.Finally,the GBR model with the highest accuracy was proposed for the UCS predictions of AAS-based CPB. | Chathuranga Balasooriya Arachchilage Chengkai Fan Jian Zhao Guangping Huang Wei Victor Liu | 2023 | Journal of Rock Mechanics and Geotechnical Engineering2023，15，11： | 0 |
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