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One-Pot Synthesis of Tetraarylpyrrolo[3,2-b]pyrrole Dopant-Free Hole-Transport Materials for Inverted Perovskite Solar Cells

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Chinese Journal of Chemical Physics 2021年第2期34卷 217-226,I0002页

作者： Liang-sheng Duan Quan-ping Wu Yuan-yuan Xu Hui Wang Zhe Sun Yu Chen Song Xue School of Materials Science and Engineering Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical SystemSchool of Mechanical EngineeringTianjin University of TechnologyTianjin 300384China

Four organic smallmolecule hole transport materials(D41, D42,D43 and D44) of tetraarylpyrrolo[3,2-b]pyrroles were prepared. They can be used without doping in the manufacture of the inverted planar perovskite solar cells. Tetraarylpyrrolo[3,2-b]pyrroles are accessible for one-pot synthesis.D42, D43 and D44 possess acceptor-π-donor-π-acceptor structure, on which the aryl bearing substitutes of cyan, fluorine and trifluoromethyl, respectively. Instead, the aryl moiety of D41 is in presence of methyl with a donor-π-donor-π-donor structure. The different substitutes significantly affected their molecular surface charge distribution and thin-film morphology, attributing to the electron-rich properties of fused pyrrole ring. The size of perovskite crystalline growth particles is affected by different molecular structures,and the electron-withdrawing cyan group of D42 is most conducive to the formation of large perovskite grains. The D42 fabricated devices with power conversion efficiency of17.3% and retained 55% of the initial photoelectric conversion efficiency after 22 days in dark condition. The pyrrolo[3,2-b]pyrrole is efficient electron-donating moiety for hole transporting materials to form good substrate in producing perovskite thin film.

关键词： Pyrrole[3,2-b]pyrrole Hole-transporting materials Organic small molecules Dopant-free Perovskite solar cells

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Ultrafast and real-time physical random bit extraction with all-optical quantization

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advanced Photonics 2022年第3期4卷 83-89页

作者： Ya Guo Qiang Cai Pu Li Ruonan Zhang Bingjie Xu K.Alan Shore Yuncai Wang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control SystemsMinistry of EducationTaiyuanChina Guangdong University of Technology School of Information EngineeringGuangdong Provincial Key Laboratory of Photonics Information TechnologyGuangzhouChina Northwestern Polytechnical University School of Electronics and InformationXi’anChina Institute of Southwestern Communication Science and Technology on Communication LaboratoryChengduChina Bangor University School of Electronic EngineeringWalesUnited Kingdom

Optical chaos generated by perturbing semiconductor lasers has been viewed,over recent decades,as an excellent entropy source for fast physical random bit generation(RBG)owing to its high bandwidth and large random ***,most optical-chaos-based random bit generators perform their quantization process in the electrical domain using electrical analog-to-digital converters,so their real-time rates in a single channel are severely limited at the level of Gb/s due to the electronic ***,we propose and experimentally demonstrate an all-optical method for RBG where chaotic pulses are quantized into a physical random bit stream in the all-optical domain by means of a length of highly nonlinear *** our proof-of-concept experiment,a 10-Gb/s random bit stream is successfully generated on-line using our *** that the single-channel real-time rate is limited only by the chaos *** that the Kerr nonlinearity of silica fiber with an ultrafast response of few femtoseconds is exploited for composing the key part of quantizing laser chaos,this scheme thus may operate potentially at much higher real-time rates than 100 Gb/s provided that a chaotic entropy source of sufficient bandwidth is available.

关键词： chaos random number generation semiconductor lasers optical signal processing.

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Study on 6D Pose Estimation system of Occlusion Targets for the Spherical Amphibious Robot based on Neural Network 20

Study on 6D Pose Estimation System of Occlusion Targets for ...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Du, Chaofeng Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory BinshuiXidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China School of Life Science Beijing Institute of Technology Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology No.5 Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

The amphibious robot needs to accurately estimate the 6D pose of the target in tasks such as target tracking, docking with the recovery module, and target grasping. The current research on target 6D pose estimation is mainly applied to unoccluded targets, but when the target is occluded, the target's pose cannot be accurately identified. Compared with other algorithms, the PVNet algorithm shows better robustness when target is occluded, but the accuracy is still low. To improve the accuracy of the PVNet algorithm, this paper adds the confidence score prediction of the prediction vector at the last layer of the PVNet network, and designs a vector confidence score loss function to train the network. Before generating the hypothetical keypoints, the pixels whose confidence score is lower than the set threshold are screened out, so that the generated hypothetical 2D keypoints are closer to the true 2D keypoints. Finally, the method in this paper is compared with the Tekin, PoseCNN, Oberweger and Pvnet algorithm, and demonstrate the superiority of the proposed method. © 2023 IEEE.

关键词： Semantics

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Tracking Performance of Networked systems with Limited Bandwidth and Colored Noise

Tracking Performance of Networked Systems with Limited Bandw...

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2022 Chinese Automation Congress, CAC 2022

作者： Zhang, Bin Jiang, Xiaowei Sun, Li Zhang, Xianhe School of Automation China University of Geosciences Wuhan430074 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Statistics and Mathematics Zhongnan University of Economics and Law Wuhan430074 China School of Electrical Engineering and Automation Hubei Normal University Huangshi435002 China

ISBN: (纸本)9781665465335

This study investigated the optimal tracking performance (OTP) of multi-input multi-output (MIMO), discrete- time networked control systems (NCSs). The limits of tracking performance (TP) under the influences of bandwidth, encoding- decoding, and additive coloured Gaussian noise (ACGN) are derived using the techniques of coprime decomposition and all-pass decomposition. The results reveal the negative impact of non-minimum phase (NMP) zeros and unstable poles of the plant as well as network communication constraints on the TP of NCSs. Finally, a numerical simulation is discussed and verifies our conclusions. © 2022 IEEE.

关键词： Networked control systems

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Compound Fault Diagnosis of Planetary Gearbox Using Capsule Network with Multi-Scale Convolutional Neural Network

Compound Fault Diagnosis of Planetary Gearbox Using Capsule ...

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Prognostics and system Health Management Conference (PHM)

作者： Guoyan Li Jingbin Zhang Guoliang Lu School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Key Laboratory of Advance Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan China Key Laboratory of High-efficiency and Clean Mechanical Manufacture of MOE National Demonstration Center for Experimental Mechanical Engineering Education School of Mechanical Engineering Shandong University Jinan China

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

Capsule network is an innovative deep learning-based model that uses neuron vectors as inputs and outputs of the network. It can achieve independent output of multiple classification labels, and solve the problem of decoupling recognition of compound fault components in planetary gearboxes. However, the single-scale feature extraction cannot fully explore multi-scale feature information in compound fault signals. This study proposes a capsule network combined with multi-scale convolutional feature fusion to diagnose the compound fault of planetary gearbox. The multi-scale features are extracted from STFT images of vibration signals using convolutional layers with different kernel sizes; secondly, a capsule network is designed to classify and identify the fault components by using the dynamic routing algorithm. The experiments are conducted to assess the performance of the proposed method, and the results indicates that it can effectively decoupling identify the compound faults with strong anti-interference and stability.

关键词： Fault diagnosis Vibrations Convolution Heuristic algorithms Feature extraction Stability analysis Vectors

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Mesenchymal stem cells loaded on 3D-printed gradient poly(e-caprolactone)/methacrylated alginate composite scaffolds for cartilage tissue engineering

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Regenerative Biomaterials 2021年第3期8卷 70-83页

作者： Yanyan Cao Peng Cheng Shengbo Sang Chuan Xiang Yang An Xiaochun Wei Zhizhong Shen Yixia Zhang Pengcui Li Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education MicroNano System Research CenterCollege of Information and ComputerTaiyuan University of TechnologyTaiyuan 030024China College of Information Science and Engineering Hebei North UniversityZhangjiakou 075000China Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair Department of OrthopedicsThe Second Hospital of Shanxi Medical UniversityTaiyuan 030001China Department of Plastic Surgery Peking University Third HospitalBeijing 100191China Department of Biomedical Engineering College of Biomedical EngineeringTaiyuan University of TechnologyTaiyuan 030024China

Cartilage has limited self-repair ability due to its avascular,alymphatic and aneural *** combination of three-dimensional(3D)printing and tissue engineering provides an up-and-coming approach to address this ***,we designed and fabricated a tri-layered(superficial layer(SL),middle layer(ML)and deep layer(DL))stratified scaffold,inspired by the architecture of collagen fibers in native cartilage *** scaffold was composed of 3D printed depth-dependent gradient poly(e-caprolactone)(PCL)impregnated with methacrylated alginate(ALMA),and its morphological analysis and mechanical properties were *** prove the feasibility of the composite scaffolds for cartilage regeneration,the viability,proliferation,collagen deposition and chondrogenic differentiation of embedded rat bone marrow mesenchymal stem cells(BMSCs)in the scaffolds were assessed by Live/dead assay,CCK-8,DNA content,cell morphology,immunofluorescence and real-time reverse transcription polymerase chain ***-loaded gradient PCL/ALMA scaffolds showed excellent cell survival,cell proliferation,cell morphology,collagen II deposition and hopeful chondrogenic differentiation compared with three individual-layer ***,our study demonstrates the potential use of the gradient PCL/ALMA construct for enhanced cartilage tissue engineering.

关键词： three-dimensional printing cartilage tissue engineering PCL methacrylated alginate bone marrow mesenchymal stem cells

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Ultrasensitive Ammonia Gas Sensor Based on Ti3c2tx/Ti3alc2 Planar Composite at Room Temperature

SSRN

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SSRN 2022年

作者： Liu, Zhihua Han, Dan Liu, Lulu Li, Donghui Han, Xiaomei Chen, Yi Liu, Xiaoru Zhuo, Kai Cheng, Yongqiang Sang, Shengbo Shanxi Key Laboratory of Micro Nano Sensors & Artificial Intelligence Perception College of Information and Computer Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System the Ministry of Education Taiyuan University of Technology Taiyuan030024 China

Two-dimensional (2D) transition metal carbides (MXene) have attracted great attention for device applications due to their unique structures and excellent properties, such as high electrical conductivity and abundant functional groups on the surface. However, gas sensors based on Ti3C2Tx MXene have the problems of high detection limit and poor long-term stability. Herein, we report a simple method to prepare Ti3C2Tx/Ti3AlC2 planar composite gas sensing materials using high molar ratio of HCl and LiF with Ti3AlC2 as a framework. The Ti3C2Tx/Ti3AlC2 planar composite gas sensor has a high sensitivity, good selectivity and low detection limit for NH3, which can detect 50 ppb (1.2%) at room temperature ((25 ± 2) °C). Furthermore, the gas sensor has good repeatability and long-term stability. After 120 days, the response of the gas sensor to 500 ppb of NH3 fluctuated little due to the Ti3AlC2 as a framework. The superior performances can be attributed to the special heterojunction between Ti3C2Tx and Ti3AlC2 and the high proportion of -O and -OH functional groups on the surface of Ti3C2Tx/Ti3AlC2 composite. This study provides an important reference for the realization of high performance NH3 sensing by Ti3C2Tx. © 2022, The Authors. All rights reserved.

关键词： Gases

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A Simulation Platform for the Brain-Computer Interface (BCI) Based Smart Wheelchair 6th

A Simulation Platform for the Brain-Computer Interface (BCI)...

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6th International Conference on Artificial Intelligence and Security, ICAIS 2020

作者： Huang, Xinru Xue, Xianwei Yuan, Zhongyun MicroNano System Research Center Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education and Shanxi Province College of Information and Computer Engineering Taiyuan University of Technology Taiyuan030024 China

ISBN: (纸本)9783030578831

In this paper, we develop a simulation platform for the Brain-Computer Interface (BCI) based smart wheelchair. The main contribution of our system is to implement an efficient simulation platform for the next generation wheelchair. Meanwhile, due to disabled people training with a real-natural environment that is difficult or costly to access, a means to synthetically recreate a virtual environment is necessary to assist patient training for the wheelchair driving. Emotiv neuroheadset provides an effective and reliable means of performing EEG testing during wheelchair training, which is inexpensive and delivers data of similar quality compared to other EEG recording equipment. © 2020, Springer Nature Switzerland AG.

关键词： Wheelchairs

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Bearing Fault Diagnosis Based on Dual-Data Input Convolutional Neural Network

SSRN

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SSRN 2022年

作者： He, Chaoqian Hao, Runfang Yang, Kun Yuan, Zhongyun Shang, Shengbo Wang, Xiaorui Shanxi Key Laboratory of Micro Nano Sensors & Artificial Intelligence Perception College of Information and Computer Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan030024 China

Previous bearing fault diagnosis models show low accuracy and unstable performance in strong noise environment, which are not suitable for the actual complex industrial scenarios. In this paper, the dual-channel convolution model (DDCNN) based on dual-data inputs is established. The model used the reconstructed two-dimensional data as inputs. In one channel, convolution with small kernel is used to extract details of FE data, and large kernel obtain global information of DE data in the other. The output is classified through the full connection layer after the data features of both channels are fused. Besides, data are mixed from different loads to avoid cross-load effects as much as possible. The results demonstrate that the proposed model has good accuracy and anti-noise performance. The accuracy is as high as 92.65% when the SNR is -10. © 2022, The Authors. All rights reserved.

关键词： Failure analysis

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Parallel Implementation of the Non-Overlapping Template Matching Test Using CUDA

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China Communications 2020年第8期17卷 234-241页

作者： Kaikai Li Jianguo Zhang Pu Li Anbang Wang Yuncai Wang Key Lab of Advanced Transducers and Intelligent Control System(Taiyuan University of Technology) Ministry of Education&Shanxi ProvinceTaiyuan 030024China College of Information Engineering Guangdong University of TechnologyGuangzhou 510006China Guangdong Provincial Key Laboratory of Photonics Information Technology Guangdong University of TechnologyGuangzhou 510006China

NIST(National Institute of Standards and Technology) statistical test recognized as the most authoritative is widely used in verifying the randomness of binary sequences. The Non-overlapping Template Matching Test as the 7 th test of the NIST Test Suit is remarkably time consuming and the slow performance is one of the major hurdles in the testing process. In this paper, we present an efficient bit-parallel matching algorithm and segmented scan-based strategy for execution on Graphics Processing Unit(GPU) using NVIDIA Compute Unified Device Architecture(CUDA). Experimental results show the significant performance improvement of the parallelized Non-overlapping Template Matching Test, the running speed is 483 times faster than the original NIST implementation without attenuating the test result accuracy.

关键词： random numbers CUDA non-overlapping template matching test parallel implementation NIST test

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