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Step-edge-guided nucleation and growth mode transition of α-Ga_(2)O_(3) heteroepitaxy on vicinal sapphire

Chinese Physics B 2024年第8期33卷 397-403页

作者：郝景刚张彦芳张贻俊徐科韩根全叶建东 Test&Analysis Platform Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China Wuxi Institute of Technology Wuxi 214121China School of Microelectronics Xidian UniversityXi'an 710071China Suzhou National Laboratory for Materials Science Jiangsu Institute of Advanced SemiconductorsSuzhou 215123China

Controlling the epitaxial growth mode of semiconductor layers is crucial for optimizing material properties and device *** this work,the growth mode ofα-Ga_(2)O_(3) heteroepitaxial layers was modulated by tuning miscut angles(θ)from 0°to 7°off the(1010)direction of sapphire(0002)*** flat sapphire surfaces,the growth undergoes a typical three-dimensional(3D)growth mode due to the random nucleation on wide substrate terraces,as evidenced by the hillock morphology and high dislocation *** the miscut angle increases toθ=5°,the terrace width of sapphire substrate is comparable to the distance between neighboring nuclei,and consequently,the nucleation is guided by terrace edges,which energetically facilitates the growth mode transition into the desirable two-dimensional(2D)coherent ***,the mean surface roughness decreases to only 0.62 nm,accompanied by a significant reduction in screw and edge dislocations to 0.16×10^(7) cm^(-2)and 3.58×10^(9) cm^(-2),***,the further increment of miscut angles toθ=7°shrink the terrace width less than nucleation distance,and the step-bunching growth mode is *** this circumstance,the misfit strain is released in the initial growth stage,resulting in surface morphology degradation and increased dislocation densities.

关键词： growth mode miscut angle crystalline quality surface morphology

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Deciphering urban traffic impacts on air quality by deep learning and emission inventory

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Journal of Environmental Sciences 2023年第2期124卷 745-757页

作者： Wenjie Du Lianliang Chen Haoran Wang Ziyang Shan Zhengyang Zhou Wenwei Li Yang Wang School of Software Engineering University of Science and Technology of ChinaHefei 230026China Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhou 215123China Alibaba Inc. Hangzhou 310052China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230026China CAS Key Laboratory of Urban Pollutant Conversion Department of environmental science and EngineeringUniversity of Science and Technology of ChinaHefei 230026China USTC-CityU Joint Advanced Research Center Suzhou 215123China

Air pollution is a major obstacle to future sustainability,and traffic pollution has become a large drag on the sustainable developments of future ***,combined with the large volume of real-time monitoring data,we propose a deep learning model,iDeepAir,to predict surface-level PM2.5 concentration in Shanghai megacity and link with MEIC emission inventory creatively to decipher urban traffic impacts on air *** model exhibits high-fidelity in reproducing pollutant concentrations and reduces the MAE from 25.355μg/m^(3) to 12.283μg/m^(3) compared with other *** identifies the ranking of major factors,local meteorological conditions have become a nonnegligible ***-wise relevance propagation(LRP)is used here to enhance the interpretability of the model and we visualize and analyze the reasons for the different correlation between traffic density and PM_(2.5) concentration in various regions of ***,As the strict and effective industrial emission reduction measurements implementing in China,the contribution of urban traffic to PM_(2.5) formation calculated by combining MEIC emission inventory and LRP is gradually increasing from 18.03%in 2011 to 24.37% in 2017 in Shanghai,and the impact of traffic emissions would be ever-prominent in 2030 according to our *** also infer that the promotion of vehicular electrification would achieve further alleviation of PM_(2.5) about 8.45% by 2030 *** insights are of great significance to provide the decision-making basis for accurate and high-efficient traffic management and urban pollution control,and eventually benefit people’s lives and high-quality sustainable developments of cities.

关键词： PM_(2.5)concentration forecast Traffic emissions Deep learning Attention mechanism New energy vehicles

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Controlled Fabrication of Uniform Digital Nanorods from Precise Sequence-Defined Amphiphilic Polymers in Aqueous Media

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Chinese Journal of Polymer Science 2023年第5期41卷 768-777,I0010页

作者： Qiang-Qiang Shi Xin Zhou Jie Xu Ning Wang Jia-Lin Zhang Xiang-Long Hu Shi-Yong Liu CAS Key Laboratory of Soft Matter Chemistry Department of Polymer Science and EngineeringUniversity of Science and Technology of ChinaHefei 230026China School of Biomedical Engineering and Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhou 215123China

Compared with spherical micelles,rod/worm-like micelles not only have extended blood circulation duration,but also exhibit favorable cellular uptake behavior,which is promising for next-generation nanomedicine and ***,the controllable fabrication of narrowly dispersed nanorods in aqueous media is still ***,the methodology of thermal annealing was developed for the fabrication of helical nanorods as well as a series of nanorods with different *** thermal annealing process generally consisted of adding a percentage of organic solvent(10%(V/V)or 20%(V/V))to the digital micellar aqueous dispersion,followed by heating at 90℃for 1 h,then cooling naturally to room temperature,and dialyzing against water to remove the organic ***-handed helical nanorods were afforded by the treatment of 45 nm digital micelles in the presence of 10%(V/V)dioxane,while left-handed helical nanorods were obtained in the presence of 20%(V/V)***,the controlled growth of rod-like digital micelles was achieved after thermal annealing in the presence of different types of organic solvents,and the length of the annealed nanorods was correlated with the types of organic ***,no matter the size of initial digital micelles,they all exhibited similar trend of rod growth in the presence of a certain amount of organic solvent,allowing for controllable formulation of narrowly dispersed *** addition,supramolecular self-assembly by amphiphilic dendritic oligourethane readily fabricated diverse uniform nanorods in aqueous ***,this work provided an attractive methodology to fabricate uniform digital nanorods.

关键词： Sequence-defined amphiphilic polymers Digital nanorods Thermal annealing Dendritic oligourethane Self-assembly

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Intelligent Recognition of Geometric Tolerance Symbol Annotation Blocks 4

Intelligent Recognition of Geometric Tolerance Symbol Annota...

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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Li, Congxin Xu, Yuanping Zhang, Chaolong Kong, Chao Jin, Jin Wang, Weiye Xu, Zhijie Guo, Benjun Tang, Dan School of Software Engineering Chengdu University of Information Technology Chengdu China School of Advanced Technology Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9798331541729

In previous mechanical design drawings, the geometric tolerance symbol annotation block was directly annotated on the mechanical design drawing by engineers, resulting in the symbol annotation block being non-editable and non-shareable. To achieve digitization, this study proposes an improved Swin_YOLOv5_GE model based on YOLOv5 to realize the positioning of the symbol annotation block. Compared with the original YOLOv5, the accuracy is increased by 4%. Then, image processing is performed on the located and cropped symbol annotation block to achieve denoising and tilt correction of the symbol annotation block. Finally, it is input into CRNN for the recognition of the symbol annotation block. The final experimental results prove that the method in this paper can obtain an overall recognition accuracy of 94%, proving the feasibility of this method. © 2024 IEEE.

关键词： Machine design

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Point Cloud Implicit 3D Reconstruction Based on Adaptive Threshold Optimal Transport 4

Point Cloud Implicit 3D Reconstruction Based on Adaptive Thr...

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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Li, Qinyun Jin, Jin Xu, Yuanping Kong, Chao Wang, Weiye Xu, Zhijie Zhang, Chaolong Guo, Benjun School of Software Engineering Chengdu University of Information Technology Chengdu China School of Advanced Technology Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9798331541729

To achieve high precision reconstruction of complex point cloud data, this paper presents a novel method based on an adaptive threshold. Firstly, a pre trained neural network is used to initially segment the point cloud, and an adaptive threshold is introduced into the discrete optimal transport to effectively detect feature regions such as edges and corners based on local geometric information. Subsequently, a zero level set smoothing loss function and a normal alignment loss function are introduced into the implicit neural network to optimize the feature region and the smooth region respectively. Finally, the optimized point cloud is reconstructed through the Marching Cubes algorithm. Experimental results show that compared with DeepSDF and Occupancy Networks, the accuracy of the proposed method on the corresponding data sets is improved by 3.33% and 1.2% respectively. © 2024 IEEE.

关键词： Cloud platforms

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EPipe: Pipeline Inference Framework with High-quality Offline Parallelism Planning for Heterogeneous Edge Devices 24

EPipe: Pipeline Inference Framework with High-quality Offlin...

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43rd International Conference on Computer-Aided Design, ICCAD 2024

作者： Xiong, Yi Liu, Weihong Zhang, Rui Zu, Yulong Zhu, Zongwei Zhou, Xuehai School of Computer Science and Technology University of Science and Technology of China China Suzhou Institute for Advanced Research University of Science and Technology of China China School of Software Engineering University of Science and Technology of China China

ISBN: (纸本)9798400710773

Pipeline parallelism is essential for edge computing as it effectively consolidates the limited resources of edge devices, enabling the deployment of large Deep Neural Network (DNN) models and accelerating inference processes without compromising the performance of models. Accurate computation and communication latency estimation on heterogeneous edge devices is essential for searching for a superior parallelism plan. However, existing heterogeneous pipeline inference approaches either incur substantial resource wastage during online parallelism planning, as they utilize profiling strategies that occupy physical devices;or rely on cost models with inadequate representational capabilities, leading to inaccurate predictions, thereby harming the result of pipeline planning. This paper proposes EPipe, a novel pipeline inference framework that supports high-quality offline planning in heterogeneous edge environments. EPipe integrates two core components: the Task-Device Co-analyzer (TDC) and the Multi-pipeline Parallelism Planner (MPP). TDC utilizes an undirected connected graph to depict the compatibility of DNNs across device groups and precisely estimates inference and communication latencies through fine-grained modeling. Based on TDC, MPP utilizes a dynamic programming-based genetic algorithm to explore multi-pipeline solutions, extending beyond traditional single-pipeline methods. A comprehensive experimental evaluation on an edge testbed confirms the effectiveness of EPipe, demonstrating significant speedups in inference tasks for both task streams and single tasks. © 2024 Copyright is held by the owner/author(s).

关键词： Edge detection

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An Improved SlowFast Model for Violence Detection 4

An Improved SlowFast Model for Violence Detection

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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Huang, Qinxue Zhang, Chaolong Xu, Yuanping Wang, Weiye Xu, Zhijie Guo, Benjun Jin, Jin Kong, Chao School of Software Engineering Chengdu University of Information Technology Chengdu China School of Advanced Technology Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9798331541729

As social safety concerns become increasingly prominent, the importance of violence detection has become increasingly significant. Accurately identifying violent behavior helps facilitate timely interventions, reducing harm and losses, thereby enhancing public safety. To minimize the interference from irrelevant actions (e.g., those from spectators and uninvolved individuals) during violence detection, this study proposes an improved SlowFast method that enhances the robustness of the model by modifying the network structure of the Slow Pathway and lateral connections. In the Slow Pathway, the original residual block is replaced with an SE-Res residual block, which strengthens the weighting of channel importance, making the model more stable in complex scenarios. The lateral connections are improved by integrating a 3D-Convolutional Block Attention Module(3DCBAM), enhancing feature fusion and increasing the model's sensitivity to key features across different temporal scales. Furthermore, to address the class imbalance issue within the dataset, the Focal Loss function has been modified, effectively improving the performance of each class. The improved model demonstrates excellent performance in violence detection tasks, achieving an accuracy of 96.67%, which is a 1.12% improvement over the classical model. © 2024 IEEE.

关键词： Feature extraction

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A Lightweight Convolutional Dual-Channel Transformer Framework for Efficient Part Segmentation of Point Cloud Data 4

A Lightweight Convolutional Dual-Channel Transformer Framewo...

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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Li, Jianhua Xu, Yuanping Zhang, Chaolong Kong, Chao Jin, Jin Wang, Weiye Xu, Zhijie Guo, Benjun Tang, Dan School of Software Engineering Chengdu University of Information Technology Chengdu China School of Advanced Technology Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9798331541729

In recent years, transformer-based models have made significant breakthroughs in natural language processing and computer vision. However, these models have encountered challenges when dealing with point cloud data because the irregular and disordered structure of point cloud data leads to a huge computational and memory burden. To address this problem, this paper proposes a Multidimensional Convolution-Dual Channel Transformer Network for efficient processing of point cloud data. The MCDTN framework consists of two branches: the main channel enhances the modeling of cross-channel features through dynamic attention to optimize feature representation;the auxiliary channel further improves fine-grained segmentation capabilities through encoders, multi-scale information interaction, and spatial attention. Experimental results show that MCDTN performs excellently in shape classification and part segmentation tasks, effectively reducing computational costs. © 2024 IEEE.

关键词： Natural language processing systems

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Speech enhancement based on emphasizing the fundamental frequency integrated with SNMF/DNN

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Multimedia Tools and Applications 2025年第14期84卷 13157-13175页

作者： Shi, Tao Ullah, Rizwan Jia, Hongbo Advanced Institute for Brain and Intelligence and School of Physical Science and Technology Guangxi University Nanning530004 China School of Mechanical and Automotive Engineering South China University of Technology Guangzhou510640 China School of Mechanical Engineering Dongguan University of Technology Dongguan523808 China Brain Research Instrument Innovation Center Suzhou Institute of Biomedical Engineering and Technology Chinese Academy of Sciences Suzhou215163 China Leibniz Institute for Neurobiology Magdeburg39118 Germany

Single-channel speech enhancement is a popular problem in speech enhancement and related fields, but the traditional research direction is to improve the data structure, which always faces the problem of heavily relying on training data sets. This paper proposes and tests a unique method of improving the traditional speech enhancement algorithm based on the features of speech and hearing. This method is designed based on the fundamental frequency (F0) and harmonic features of speech to emphasize the F0 (EFF) like the human auditory system (neural lateral inhibition mechanism). Therefore, it does not depend on the training data and has good scalability, which can be easily embedded in the traditional algorithm. In this paper, the Chinese speech library, the English speech library, and a variety of noise are used in the experiments. When tested, this method can improve the performance of the original algorithm in speech enhancement, especially in the case of low SNR. However, since it is an additional process, therefore the increase in intelligibility of speech may not be high sometimes compared with the increase in perception quality in the case of high SNR, like the STOI scores. But the auditory perception index, like the PESQ scores, are significantly improved, and the WSS scores are reduced as desired. After embedding the algorithm into DNN-based or SNMF-based speech enhancement algorithms, the enhancement in the PESQ scores is improved by about 5% on average, and WSS scores are reduced, while having less negative impact on the increase in STOI in the case of high SNR. The EFF is not related to the training process of the model, but it can improve the PESQ and STOI scores, and lowers the WSS scores. This suggests that fundamental frequency is an important feature in speech processing that affects speech quality. It is necessary to actively introduce fundamental frequency as a feature in speech processing. The proposed algorithm is tested on both the Chinese and En

关键词： Speech enhancement

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Direct orientational epitaxy of wafer-scale 2D van der Waals heterostructures of metal dichalcogenides

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National Science Review 2025年第5期12卷 315-324页

作者： Shenghong Liu Ke Qin Jiashu Yang Tao Hu Hao Luo Jingsong Wu Zhen Cui Taotao Li Feng Ding Xinran Wang Yuan Li Tianyou Zhai State Key Laboratory of Materials Processing and Die & Mould Technology School of Materials Science and EngineeringHuazhong University of Science and Technology School of Materials Science and Engineering Xi'an University of Technology Suzhou Laboratory State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Nanostructure Research CenterWuhan University of Technology School of Integrated Circuits Nanjing University Research Institute of Huazhong University of Science and Technology in Shenzhen

Two-dimensional（2D） van der Waals（vdW） heterostructures have emerged as a groundbreaking candidate for future integrated circuits due to their tunable band structures,atomically sharp interfaces and seamless compatibility with complementary metal-oxide-semiconductor *** their promise,existing synthesis methods,such as mechanical transfer and vapor-phase conversion,struggle to achieve the high-quality,scalable production for practical *** response to these longstanding challenges,our study unveils for the first time the direct epitaxial growth of wafer-scale 2D vdW heterostructures（MoS2/SnS2） with exceptional quality and *** achievement is made possible through fundamentally enhancing the adsorption interactions between intermediates and the underlying *** heterostructures display pristine,defect-free interfaces,consistent crystal orientation and wafer-level thickness *** Raman peak shifts of MoS2and SnS2are constrained to below 0.5 cm-1across the entire wafer,with intensity deviations maintained within an impressive 2%,and thickness uniformity surpassing 99.5%.Owing to their exceptional crystallinity and interface quality,the heterostructures demonstrate extraordinary electron and hole transfer capabilities,showcasing a prominent rectification effect and an astounding responsivity of 6.28 ± 10～3 A/W,averaged from 30 *** study signifies a pivotal advancement for the integration of 2D materials into semiconductor technologies,paving the way for next-generation integrated circuits.

关键词： two-dimensional material heterostructure epitaxy growth optoelectronic device

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