Tielin Shi
Huazhong University of Science and Technology
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Publication
Featured researches published by Tielin Shi.
Journal of Materials Chemistry | 2014
Hu Long; Tielin Shi; Shulan Jiang; Shuang Xi; Rong Chen; Shiyuan Liu; Guanglan Liao; Zirong Tang
In this paper, ZnCo2O4 nanowires have been grown and self-assembled as hierarchical structures on a 3D conductive Ni foam substrate. Both leaf-like ZnCo2O4 and dandelion-like ZnCo2O4 assemblies were synthesized through a hydrothermal process followed by a post-annealing treatment. It is shown that leaf-like assemblies are directly grown on the substrate while dandelion-like assemblies are adsorbed on the surface of the structures. A possible formation mechanism of ZnCo2O4 hierarchical structures was proposed. It is shown that these nanowires are porous structures which provide much increased specific surface area. Further work was conducted by taking these Ni foam supported ZnCo2O4 structures as binder-free electrodes for Li-ion batteries. Remarkably, the leaf-like ZnCo2O4/Ni foam electrode exhibits greatly improved electrochemical performance with high capacity and excellent cycling stability. A high reversible capacity of 1050 mA h g−1 at the rate of 100 mA g−1 was obtained after 60 cycles. Meanwhile, the electrode showed a high rate of 416 mA g−1 with a high capacity of 850 mA h g−1 even after 50 cycles. Our work demonstrates that this unique nanowire self-assembled ZnCo2O4 hierarchical structure is promising for high-performance electrochemical energy applications.
ACS Nano | 2014
Wenjun Sheng; Bo Sun; Tielin Shi; Xianhua Tan; Zhengchun Peng; Guanglan Liao
We report the fabrication of quantum dot-sensitized hierarchical structure and the application of the structure as a photoanode for photoelectrochemical water splitting. The structure is synthesized by hydrothermally growing ZnO nanowires on silicon microwires grown with the vapor-liquid-solid method. Then the hierarchical structure is further sensitized with CdS and CdSe quantum dots and modified with IrOx quantum dots. As a result, the silicon microwires, ZnO nanowires, and the quantum dot/ZnO core/shell structure form a multiple-level hierarchical heterostructure, which is remarkably beneficial for light absorption and charge carrier separation. Our experimental results reveal that the photocurrent density of our multiple-level hierarchical structure achieves a surprising 171 times enhancement compared to that from simple ZnO nanowires on a planar substrate. In addition, the photoanode shows high stability during the water-splitting experiment. These results prove that the quantum dot-sensitized hierarchical structure is an ideal candidate for a photoanode in solar water splitting applications. Importantly, the modular design approach we take to produce the photoanode allows for the integration of future discoveries for further improvement of its performance.
Expert Systems With Applications | 2009
Zengbing Xu; Jianping Xuan; Tielin Shi; Bo Wu; Youmin Hu
Considering different importance of the feature parameters to the fault conditions of bearing, a modified fuzzy ARTMAP (FAM) network model based on the feature-weight learning is presented in this paper. The features in time-domain, frequency-domain and wavelet-domain are extracted from the vibration signals to characterize the information relevant to the fault conditions of bearing. By the improved distance evaluation technique the optimal features are selected and the corresponding feature-weights which are assigned to the features to indicate their different importance to the fault conditions of bearing are obtained. Then they are combined with the modified FAM which is described by the weighted Manhattan distance and applied to the seven-class fault diagnosis of bearing. To assess the effectiveness and stability of the modified FAM network, bootstrapping method is employed to quantify the stability of the network performance statistically. Diagnosis results show that the modified FAM can more reliably and accurately recognize different fault classes.
Expert Systems With Applications | 2009
Zengbing Xu; Jianping Xuan; Tielin Shi; Bo Wu; Youmin Hu
This paper presents a novel intelligent diagnosis method based on multiple domain features, modified distance discrimination technique and improved fuzzy ARTMAP (IFAM). The method consists of three steps. To begin with, time-domain, frequency-domain and wavelet grey moments are extracted from the raw vibration signals to demonstrate the fault-related information. Then through the modified distance discrimination technique some salient features are selected from the original feature set. Finally, the optimal feature set is input into the IFAM incorporated with similarity based on the Yus norm in the classification phase to identify the different fault categories. The proposed method is applied to the fault diagnosis of rolling element bearing, and the test results show that the IFAM identify the fault categories of rolling element bearing more accurately and has a better diagnosis performance compared to the FAM. Furthermore, by the application of the bootstrap method to the diagnosis results it can testify that the IFAM has more capacity of reliability and robustness.
Journal of Quality in Maintenance Engineering | 2003
Weihua Li; Tielin Shi; Guanglan Liao; Shuzi Yang
Feature extraction is a key issue to machine condition monitoring and fault diagnosis. The features must contain the necessary discriminative information for the fault classifier to have any chance of accurate classification. This paper presents a study that uses principal component analysis to reduce dimensionality of the feature space and to get an optimal subspace for machine fault classification. Industrial gearbox vibration signals measured from different operating conditions are analyzed using the above method. The experimental results indicate that the method extracts diagnostic information effectively for gear fault classification and has a good potential for application in practice.
Scientific Reports | 2015
Hu Long; Tielin Shi; Hao Hu; Shulan Jiang; Shuang Xi; Zirong Tang
Mesoporous NiO nanosheets were directly grown on three-dimensional (3D) carbon cloth substrate, which can be used as binder-free anode for lithium-ion batteries (LIBs). These mesoporous nanosheets were interconnected with each other and forming a network with interval voids, which give rise to large surface area and efficient buffering of the volume change. The integrated hierarchical electrode maintains all the advantageous features of directly building two-dimensional (2D) nanostructues on 3D conductive substrate, such as short diffusion length, strain relaxation and fast electron transport. As the LIB anode, it presents a high reversible capacity of 892.6 mAh g−1 after 120 cycles at a current density of 100 mA g−1 and 758.1 mAh g−1 at a high charging rate of 700 mA g−1 after 150 cycles. As demonstrated in this work, the hierarchical NiO nanosheets/carbon cloth also shows high flexibility, which can be directly used as the anode to build flexible LIBs. The introduced facile and low-cost method to prepare NiO nanosheets on flexible and conductive carbon cloth substrate is promising for the fabrication of high performance energy storage devices, especially for next-generation wearable electronic devices.
Journal of Materials Chemistry | 2016
Zhiyong Liu; Bo Sun; Tielin Shi; Zirong Tang; Guanglan Liao
We report the encapsulation of low temperature carbon counter electrode based hole-conductor-free mesoscopic methylammonium lead iodide perovskite/TiO2 heterojunction solar cells with polydimethylsiloxane. The solar cells demonstrate improved photovoltaic performance, where we obtain an optimal short-circuit photocurrent JSC = 23.5 mA cm−2, open-circuit photovoltage VOC = 0.97 V, and fill factor FF = 0.474, corresponding to a light to electric power conversion efficiency of 10.8% under a standard AM 1.5 solar light of 100 mW cm−2 intensity. The results exhibit a remarkable 54% enhancement over those without encapsulation. The cross-sectional SEM images indicate that the PDMS layer can condense the carbon electrode by filling the gaps in the mesoscopic carbon film during the solidification of PDMS, resulting in an improved MAPbI3/carbon interface condition. The photoluminescence and electrical impedance spectroscopy measurements prove that the improved efficiency is ascribed to a more efficient charge transfer process and slower charge recombination between interfaces. In addition, the robust polydimethylsiloxane isolates water in air, avoiding the degradation of the CH3NH3PbI3 perovskite and leading to an impressive stability during a testing period of 3000 h. Our work paves the way for realizing low cost, highly efficient and stable hybrid photovoltaic cells.
Scientific Reports | 2016
Yuanyuan Huang; Tielin Shi; Shulan Jiang; Siyi Cheng; Xiangxu Tao; Yan Zhong; Guanglan Liao; Zirong Tang
As a new class of pseudocapacitive material, metal sulfides possess high electrochemical performance. However, their cycling performance as conventional electrodes is rather poor for practical applications. In this article, we report an original composite electrode based on NiCo2S4@NiO core-shell nanowire arrays (NWAs) with enhanced cycling stability. This three-dimensional electrode also has a high specific capacitance of 12.2 F cm−2 at the current density of 1 mA cm−2 and excellent cycling stability (about 89% retention after 10,000 cycles). Moreover, an all-solid-state asymmetric supercapacitor (ASC) device has been assembled with NiCo2S4@NiO NWAs as the positive electrode and active carbon (AC) as the negative electrode, delivering a high energy density of 30.38 W h kg−1 at 0.288 KW kg−1 and good cycling stability (about 109% retention after 5000 cycles). The results show that NiCo2S4@NiO NWAs are promising for high-performance supercapacitors with stable cycling based on the unique core-shell structure and well-designed combinations.
Journal of The Optical Society of America A-optics Image Science and Vision | 2009
Chuanwei Zhang; Shiyuan Liu; Tielin Shi; Zirong Tang
Model-based infrared reflectrometry (MBIR) has been introduced recently for characterization of high-aspect-ratio deep trench structures in microelectronics. The success of this technique relies heavily on accurate modeling of trench structures and fast extraction of trench parameters. In this paper, we propose a modeling method named corrected effective medium approximation (CEMA) for accurate and fast reflectivity calculation of deep trench structures. We also develop a method combining an artificial neural network (ANN) and a Levenberg-Marquardt (LM) algorithm for robust and fast extraction of geometric parameters from the measured reflectance spectrum. The simulation and experimental work conducted on typical deep trench structures has verified the proposed methods and demonstrated that the improved MBIR metrology achieves highly accurate measurement results as well as fast computation speed.
Journal of Vibration and Control | 2014
Li Jiang; Tielin Shi; Jianping Xuan
Feature extraction plays an important role in fault diagnosis. It is critical to extract the representative features for improving the classification performance. An intelligent fault diagnosis method based on Marginal Fisher analysis (MFA) is put forward and applied to rolling bearings. The high-dimensional features in time-domain, frequency-domain and wavelet-domain are extracted from the raw vibration signals to obtain rich faulty information. Subsequently, MFA excavates the underlying low-dimensional fault characteristics embedded in the high-dimensional feature space by preserving local manifold structure. Thus, the optimal low-dimensional features are obtained to characterize the various fault conditions of rolling bearings and finally fed into the simplest k-nearest neighbor classifier to recognize different fault categories. The diagnosis results validate the feasibility and effectiveness of the proposed fault diagnosis method, compared with the other three similar approaches.