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Frontiers in high entropy alloys and high entropy functional materials

Rare Metals 2024年第10期43卷 4639-4776页

作者： Wen-Tao Zhang Xue-Qian Wang Feng-Qi Zhang Xiao-Ya Cui Bing-Bing Fan Jia-Ming Guo Zhi-Min Guo Rui Huang Wen Huang Xu-Bo Li Meng-Ru Li Yan Ma Zhi-Hua Shen Yong-Gang Sun De-Zhuang Wang Fei-Yang Wang Li-Qiang Wang Nan Wang Tian-Li Wang Wei Wang Xiao-Yang Wang Yi-Han Wang Fu-Jie Yu Yu-Zhen Yin Ling-Kun Zhang Yi Zhang Jian-Yang Zhang Qi Zhao Yu-Ping Zhao Xin-Dong Zhu Yasir Sohail Ya-Nan Chen Tao Feng Qi-Long Gao Hai-Yan He Yong-Jiang Huang Zeng-Bao Jiao Hua Ji Yao Jiang Qiang Li Xiao-Ming Li Wei-Bing Liao Huai-Jun Lin Hui Liu Qi Liu Qing-Feng Liu Wei-Di Liu Xiong-Jun Liu Yang Lu Yi-Ping Lu Wen Ma Xue-Fei Miao Jie Pan Qing Wang Hong-Hui Wu Yuan Wu Tao Yang Wei-Ming Yang Qian Yu Jin-Yu Zhang Zhi-Gang Chen Liang Mao Yang Ren Bao-Long Shen Xun-Li Wang Zhe Jia He Zhu Zhen-Duo Wu Si Lan School of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Jiangsu Key Laboratory for Advanced Metallic Materials School of Materials Science and EngineeringSoutheast UniversityNanjing 211189China Department of Physics City University of Hong KongHongKong 999077China School of Materials Science and Engineering Tianjin UniversityTianjin 300072China School of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450001China Department of Mechanical Engineering Research Institute for Advanced ManufacturingThe Hong Kong Polytechnic UniversityHong Kong 100872China Center of Electron Microscopy and State Key Laboratory of Silicon Materials School of Materials Science and EngineeringZhejiang UniversityHangzhou 310027China Key Laboratory of Solidification Control and Digital Preparation Technology(Liaoning Province) School of Materials Science and EngineeringDalian University of TechnologyDalian 116024China Institute of Advanced Wear&Corrosion Resistance and Functional Materials Jinan UniversityGuangzhou 510632China School of Mechanics and Civil Engineering China University of Mining and TechnologyXuzhou 221116China School of Physical Sciences Great Bay UniversityDongguan 523000China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Materials-Oriented Chemical Engineering College of Chemical EngineeringNanjing Tech UniversityNanjing 211816China Beijing Advanced Innovation Center for Materials Genome Engineering Research Institute for Carbon NeutralityUniversity of Science and Technology BeijingBeijing 100083China Department of Mechanical Engineering The University of Hong KongHong Kong 999077China School of Computing Macquarie UniversitySydney 2113Australia Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China State Key Laborato

Owing to their exceptional properties,high-entropy alloys(HEAs)and high-entropy materials have emerged as promising research areas and shown diverse ***,the recent advances in the field are comprehensively reviewed,organized into five *** first section introduces the background of HEAs,covering their definition,significance,application prospects,basic properties,design principles,and *** subsequent section focuses on cutting-edge high-entropy structural materials,highlighting developments such as nanostructured alloys,grain boundary engineering,eutectic systems,cryogenic alloys,thin films,micro-nano-lattice structures,additive manufacturing,high entropy metallic glasses,nano-precipitate strengthened alloys,composition modulation,alloy fibers,and refractory *** the following section,the emphasis shifts to functional materials,exploring HEAs as catalysts,magneto-caloric materials,corrosion-resistant alloys,radiation-resistant alloys,hydrogen storage systems,and materials for ***,the review encompasses functional high-entropy materials outside the realm of alloys,including thermoelectric,quantum dots,nanooxide catalysts,energy storage materials,negative thermal expansion ceramics,and high-entropy wave absorption *** paper concludes with an outlook,discussing future directions and potential growth areas in the *** this comprehensive review,researchers,engineers,and scientists may gain valuable insights into the recent progress and opportunities for further exploration in the exciting domains of high-entropy alloys and functional materials.

关键词： High entropy alloys Cutting-edge structural materials Cutting-edgefunctional materials

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Ultra-high-Q photonic crystal nanobeam cavity for etchless lithium niobate on insulator(LNOI)platform

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Opto-Electronic Advances 2025年第1期8卷 59-70页

作者： Zhi Jiang Cizhe Fang Xu Ran Yu Gao Ruiqing Wang Jianguo Wang Danyang Yao Xuetao Gan Yan Liu Yue Hao Genquan Han State Key Laboratory of Wide-Bandgap Semiconductor Devices and Integrated Technology School of MicroelectronicsXidian UniversityXi’an 710071China Key Laboratory of Light Field Manipulation and Information Acquisition Ministry of Industry and Information Technologyand Shaanxi Key Laboratory of Optical Information TechnologySchool of Physical Science and TechnologyNorthwestern Polytechnical UniversityXi’an 710129China Hangzhou Institute of Technology Xidian UniversityHangzhou 311200China

The expansive spectral coverage and superior optical properties of lithium niobate(LN)offer a comprehensive suite of tools for exploring novel *** high-quality(Q)photonic resonator cavities is crucial for enhancing light-matter ***,this task is challenging as the device performance is heavily dependent on the fabrication quality of the *** this paper,we present experimental validation of an etchless approach to fabricating high-Q photonic crystal nanobeam cavities(PCNBCs).We successfully fabricate PCNBCs with Q factors exceeding 105 while maintaining high transmittance by capitalizing on the low waveguide loss and high fabrication tolerance of TE-polarized ***,the Q factor achieved here exceeds previous reports on etchless LN PCNBCs by over an order of *** from this advancement,we further explore a variety of optical functions,including thermo-optic tuning,optically induced bistability,and Fano line shapes *** findings present promising prospects for a versatile platform technique,facilitating the development of high-performance electro-optic or acousto-optic modulators,optical logic devices,and quantum photonics,highlighting its significant impact in the field of photonic integration.

关键词： photonic crystal nanobeam cavity LNOI platform high Q thermo-optic tuning bistability Fano line shapes

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Fabrication and Performance Assessment of High-Mobility Sige Channel P-Type SOI FinFET Transistor

Fabrication and Performance Assessment of High-Mobility Sige...

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IEEE Electron devices technology and Manufacturing Conference (EDTM)

作者： Zijing Zhang Yuchen Wu Yan Li Huaizhi Luo FanYu Liu Yongliang Li Key Laboratory of Fabrication Technologies for Integrated Circuits Chinese Academy of Sciences Beijing Chinese Academy of Sciences Institute of Microelectronics Beijing China Key Laboratory of Science and Technology on Silicon Devices Chinese Academy of Sciences Beijing China School of Applied Science Beijing Information Science and Technology University China

ISBN: (数字)9798331504168

ISBN: (纸本)9798331504175

In this work, we successfully fabricated P-type FinFET transistor featuring SiGe channel on a silicon-on-insulator (SOI) substrate by adopting the SiGe epitaxy and etching processes. Under the gate length of 40 nm, its subthreshold swing (SS) is $82 \text{mV} /$ dec and $\mathrm{I}_{\text{on}} / \mathrm{I}_{\text{off}}$ ratio is $\sim 10^{6}$ . Its excellent electrical and reliability characteristics reveal that this SiGe SOI FinFET is a potential candidate for the future advanced nodes.

关键词： Scanning electron microscopy Semiconductor device reliability Logic gates FinFETs silicon Epitaxial growth Plasmas Transistors Substrates silicon germanium

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SRAM-Based PUF with Noise Immunity Achieving 0.58% Native BER in 55-nm CMOS

SRAM-Based PUF with Noise Immunity Achieving 0.58% Native BE...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Zexin Su Bo Li Chang Liu Xiaohui Su Qian Luo Hongyu Ren Zhengsheng Han Institute of Microelectronics of the Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Key Laboratory of Science and Technology on Silicon Devices Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

In this paper, a novel static random-access memory (SRAM) based physical unclonable function (PUF) with ultra-low native bit error rate (BER) is proposed. In the conventional 6T SRAM PUF, the thermal noise weakens the effect of the inherent mismatch on the PUF cell output at the initial power-on transition time, resulting in a high native BER. To realize a low native BER, a 7T PUF with noise immunity is proposed. Through inserting a mono-stable state before the bistable state, the 7T cell avoids the noise impact during the power-on transition period and amplify the mismatch voltage, resulting a huge native BER reduction. Two custom SRAM PUFs adopting 6T cell and 7T cell respectively, were fabricated in 55nm CMOS process to evaluate BER characteristics. The experimental results show that the native BER of the proposed 7T SRAM PUF is only 0.58%, which is nearly 11X lower than the 6T PUF of 6.12%. And as temperature varying from -25°C to 75°C, the worst BER of 7T PUF is 2.31% and is around 5X lower than the 6T PUF of 11.9%. In addition, raw bits generated from the proposed 7T PUF also passed the National institute of Standards and technology (NIST) randomness tests.

关键词： Temperature Bit error rate Noise Random access memory Voltage NIST Physical unclonable function

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Comparative Study of TID Irradiation Effect on SiC Planar and Trench MOSFET 21

Comparative Study of TID Irradiation Effect on SiC Planar an...

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21st China International Forum on Solid State Lighting and 10th International Forum on Wide Bandgap Semiconductors, SSLCHINA: IFWS 2024

作者： Fu, Zhen Shen, Zhanwei Tang, Xuan Huang, Yu Xu, Jinyi Huang, Kaige Zhang, Quan Chen, Yanning Xiao, Chao Huang, Kai Yue, Shizhong Wang, Zhijie Zhang, Feng the Beijing Smartchip Microelectronics Technology Co. Ltd Beijing102200 China the Laboratory of Solid-State Optoelectronics Information Technology Key Laboratory of Semiconductor Material Sciences Beijing Key Laboratory of Low Dimensional Semiconductor Materials and Devices Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China the Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798331541149

In this work, the mechanisms of total ionizing dose irradiation (TID) induced charge collections are analyzed and compared between SiC planar and trench gate metal-oxide-semiconductor field effect transistor (DMOSFET and UMOSFET). The threshold shift and the blocking capability of the post-irradiated devices are strongly associated with degradation of the MOS channel regions. Furthermore, SiC UMOSFET with low dose irradiation of 100 Krad(Si) exhibits a higher degree of degradation of electrical characteristics than that of the DMOSFET with irradiation of 300 Krad(Si). For comparison, the fabricated DMOSFET shows negligible change in gate leakage current and stable blocking capability after 100 Krad(Si) irradiation. Also, the edge-corner topography of gate poly-Si in both of SiC MOSFETs is found to have influence on the formation of latent gate damage induced by TID irradiation. For purpose of deep understanding of these results, the charge interaction on both sides of the gate oxide is clarified by dynamic capacitance comparisons obtained by experimental and numerical methods. SiC UMOSFET with a large portion of the trench surrounded by p-type regions shows greater capacitance shift than the DMOSFET. It is indicated that the ratio of gate/p-type-regions overlap in one cell may have effects on the charge collection of post-irradiated devices. These results will provide meaningful guidance for the design and fabrication of a radiation tolerant SiC MOSFETs. ©2024 IEEE.

关键词： MOSFET devices

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Lightning Protection Stacked TVS Structure Based on a Novel Total-Ionizing-Dose Radiation-Hardened technology 17

Lightning Protection Stacked TVS Structure Based on a Novel ...

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17th IEEE International Conference on Solid-State and Integrated Circuit technology, ICSICT 2024

作者： Qi, Zhao Chen, Hongquan Jia, Yirui He, Nailong Zhang, Zhili Zhang, Sen Qiao, Ming Zhang, Bo Chongqing Institute of Microelectronics Industry Technology UESTC Chongqing China CSMC Technologies Corporation Wuxi China University of Electronic Science and Technology of China State Key Laboratory of Electronic Thin Films and Integrated Devices Chengdu China Institute of Electronic and Information Engineering of UESTC in Guangdong Dongguan China Shenzhen Institute for Advanced Study UESTC Shenzhen China

ISBN: (纸本)9798350361834

To mitigate the total ionizing dose (TID) effects of the transient voltage suppressor (TVS), a novel radiation-hardened technology that includes hardening process with oxide etch-back technology and low-voltage (LV) stacked TVS structure is proposed. In this work, the high breakdown voltage (BV) is achieved by employing a series of LV devices to replace sensitive low concentration drift-region in traditional high voltage devices. Furthermore, a novel low-trap-density oxide layer is developed by the high-temperature local oxidation of silicon (LOCOS) etch-back technology and subsequently low-temperature secondary thin oxidation, which greatly reduces the density of hole traps. By combining these two improvements, the TID-hardened lateral TVS with ultra-low clamping voltage (V CL ) and high transient power density for three voltage levels are achieved. © 2024 IEEE.

关键词： Hole traps

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3D Reservoir Computing with High Area Efficiency (5.12 TOPS/mm2) Implemented by 3D Dynamic Memristor Array for Temporal Signal Processing

3D Reservoir Computing with High Area Efficiency (5.12 TOPS/...

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2022 IEEE Symposium on VLSI technology and Circuits, VLSI technology and Circuits 2022

作者： Sun, Wenxuan Zhang, Woyu Yu, Jie Li, Yi Guo, Zeyu Lai, Jinru Dong, Danian Zheng, Xu Wang, Fei Fan, Shaoyang Xu, Xiaoxin Shang, Dashan Liu, Ming Institute of Microelectronics of Chinese Academy of Sciences Key Laboratory of Microelectronic Devices and Integrated Technology Beijing China University of Chinese Academy of Sciences Beijing China University of Science and Technology of China School of Microelectronics China

ISBN: (纸本)9781665497725

In this work, we realized a three-dimensional (3D) reservoir computing (RC) by utilizing the I-V nonlinearity and short-term memory of the dynamic memristor in 4-layer vertical array. The cycle-to-cycle variation of the dynamic reservoir is improved by parallel memristor configuration. The dimensionality of the reservoir space is increased by input strategy design. After the hardware-software co-optimization, the proposed 3D RC system exhibits high recognition accuracy (90%), low energy consumption (-0.78 pJ /operation), and high area efficiency (5.12 TOPS/mm2). © 2022 IEEE.

关键词： Memristors

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Energy-Efficient fall detection based on Spiking Neural Networks

Energy-Efficient fall detection based on Spiking Neural Netw...

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2023 International Conference on Cyber Security, Artificial Intelligence, and Digital Economy, CSAIDE 2023

作者： Xiao, Xiao Liwei, Meng Yian, Liu Shaogang, Hu Guanchao, Qiao School of Software Engineering Chongqing University of Posts and Telecommunications Chongqing China State Key Laboratory of Electronic Thin Films and Integrated Devices University of Electronic Science and Technology of China Chengdu China Chongqing Institute of Microelectronics Industry Technology University of Electronic Science and Technology of China Chongqing China

ISBN: (纸本)9781510666597

Falls have become an essential factor affecting life safety in recent years. Given the high energy consumption associated with running models over extended periods in practical engineering, this research presents a network architecture, Spiking-Rep-YOLOv3, which is more suitable for transformation into Spiking neural networks (SNNs). We redesign the RepVGG-based backbone network by improving the YOLOv3-tiny network. Second, we speed up inference by employing neuron normalization to reduce information loss during inference after neural network transformation. We experimented with Spiking-Rep-YOLOv3 on the E-FPDS public dataset and showed that the network achieved similar accuracy as YOLOv3-tiny and only 40.7% of the energy consumption of the latter. © 2023 SPIE.

关键词： Neural networks

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Arrhythmia classification method based on knowledge distillation and 2D ECG images 3

Arrhythmia classification method based on knowledge distilla...

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3rd International Conference on Neural Networks, Information and Communication Engineering, NNICE 2023

作者： Li, Renwei Meng, Liwei Liu, Yian Hu, Shaogang Qiao, Guanchao School of Software Engineering Chongqing University of Posts and Telecommunications Chongqing China University of Electronic Science and Technology of China State Key Laboratory of Electronic Thin Films and Integrated Devices Chengdu China Chongqing Institute of Microelectronics Industry Technology University of Electronic Science and Technology of China Chongqing China

ISBN: (纸本)9798350335972

Arrhythmia classification is crucial for identifying and preventing the potential risks associated with cardiovascular diseases. Currently., using deep learning for arrhythmia classification faces challenges of model complexity and deployment difficulty. To address this., We present a novel approach for classifying arrhythmias using knowledge distillation and 2D ECG images. In this study., the classification of the MIT-BIH dataset is performed according to AAMI criteria. Preprocessing., such as denoising., interception., and 2D grayscale image conversion., is first performed. Then., high-performance 2D-CNN models are pre-trained using 2D ECG images as the teacher model., and a lightweight 1D-CNN is constructed as the student model. Finally., we align raw and 2D ECG data., utilizing knowledge distillation to allow the student model to learn from the teacher model during the training process., thus enabling model compression. The final results show that the method significantly improves the performance of the student model in arrhythmia classification. For overall performance., when using Vgg16 as the teacher model., Acc and P+ improve by 1.62% and 6.64%., and Se is comparable. In addition., the F1-score values have been improved in all categories. The proposed method provides a feasible approach for low computational power device deployment for arrhythmia classification. © 2023 IEEE.

关键词： Electrocardiograms

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Siamese Network Object Tracking Based on Fusion of Visible and Event Cameras

Siamese Network Object Tracking Based on Fusion of Visible a...

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2023 International Conference on Cyber Security, Artificial Intelligence, and Digital Economy, CSAIDE 2023

作者： Hu, Qiang Meng, Liwei Liu, Yian Hu, Shaogang Qiao, Guanchao School of Software Engineering Chongqing University of Posts and Telecommunications Chongqing China State Key Laboratory of Electronic Thin Films and Integrated Devices University of Electronic Science and Technology of China Chengdu China Chongqing Institute of Microelectronics Industry Technology University of Electronic Science and Technology of China Chongqing China

ISBN: (纸本)9781510666597

Object tracking is widely used in daily life. The existing visible camera-based tracking methods are difficult to track objects accurately in the face of degraded scenes such as fast movement, high contrast, and low illumination, which will cause the loss of tracking performance. An event camera is a biologically driven sensor with higher dynamic range, smaller time delay, and higher light sensitivity than traditional visible cameras. We propose a siamese network object tracking method that fuses visible and event cameras to realize more reliable tracking. We design a feature fusion method combining visible and event camera features based on attention mechanism. It realizes the cooperation of both sensors and improves the accuracy of tracking. Experiments on the VisEvent dataset reveal that our network outperforms single-modality trackers by 5.8% and outperforms other fusion-based methods by 2.1%. © 2023 SPIE.

关键词： Cameras

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