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Quantum-dot and organic hybrid light-emitting diodes employing a blue common layer for simple fabrication of full-color displays

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Nano Research 2022年第7期15卷 6477-6482页

作者： Suhyeon Lee Donghyo Hahm Suk-Young Yoon Heesun Yang Wan Ki Bae Jeonghun Kwak Department of Electrical and Computer Engineering Seoul National UniversitySeoul 08826Republic of Korea Inter-university Semiconductor Research Center(ISRC) Seoul National UniversitySeoul 08826Republic of Korea SKKU Advanced Institute of Nanotechnology(SAINT) School of Nano Science&TechnologySungkyunkwan University(SKKU)Suwon 16419Republic of Korea Department of Materials Science and Engineering Hongik UniversitySeoul 04066Republic of Korea

Colloidal quantum-dot(QD)light-emitting diodes(QLEDs)have been in the forefront of future display devices due to their outstanding optoelectronic ***,a complicated solution-process for patterning the red,green,and blue QDs deteriorates the QLED performance and limits the resolution of full-color ***,we report a novel concept of QD–organic hybrid light-emitting diodes by introducing an organic blue common layer(BCL)which is deposited through a common mask over the entire *** from the optimized device structure,red and green QLEDs retained their color coordinates despite the presence of the ***,adopting the BCL improved the external quantum efficiency of green and red QLEDs by 38.4%and 11.7%,respectively,due to the Förster resonance energy transfer from the BCL to the adjacent QD *** the BCL structure,we could simply demonstrate a full-color QD-organic hybrid device in a single *** believe that this device architecture is practically applicable for easier fabrication of solution-processed,highresolution,and full-color displays with reduced process steps.

关键词： quantum-dot light-emitting diode(QLEDs) organic light-emitting diode blue common layer full-color display reduced process step

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Detecting lithium plating dynamics in a solid-state battery with operando X-ray computed tomography using machine learning

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npj Computational materials 2023年第1期9卷 1402-1410页

作者： Ying Huang David Perlmutter Andrea Fei-Huei Su Jerome Quenum Pavel Shevchenko Dilworth Y.Parkinson Iryna V.Zenyuk Daniela Ushizima Department of Materials Science&Engineering University of California IrvineIrvineCaliforniaUSA National Fuel Cell Research Center University of California IrvineIrvineCaliforniaUSA Applied Math and Computational Research Division Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA Department of Chemical&Biomolecular Engineering University of California IrvineIrvineCaliforniaUSA Department of Electrical Engineering and Computer Sciences College of EngineeringUniversity of California BerkeleyBerkeleyCaliforniaUSA Advanced Photon Source Argonne National Laboratory9700 South Cass AvenueLemontIllinoisUSA Advanced Light Source Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA Berkeley Institute for Data Science University of California BerkeleyBerkeleyCaliforniaUSA

Operando X-ray micro-computed tomography(µCT)provides an opportunity to observe the evolution of Li structures inside pouch *** is an essential step to quantitatively analyzingµCT datasets but is challenging to achieve on operando Li-metal battery datasets due to the low X-ray attenuation of the Li metal and the sheer size of the ***,we report a computational approach,batteryNET,to train an Iterative Residual U-Net-based network to detect Li *** resulting semantic segmentation shows singular Li-related component changes,addressing diverse morphologies in the *** addition,visualizations of the dead Li are provided,including calculations about the volume and effective thickness of electrodes,deposited Li,and redeposited *** also report discoveries about the spatial relationships between these *** approach focuses on a method for analyzing battery performance,which brings insight that significantly benefits future Li-metal battery design and a semantic segmentation transferrable to other datasets.

关键词： battery lithium state

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Analysis of Gait Data Based on Deep Learning to Predict Multiple Balance Scale Scores

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IEEE Sensors Journal 2024年第1期24卷 920-930页

作者： Lin, Chueh-Ho Peng, Chih-Wei Lee, I-Jung Wu, Chi-Ming Lin, Bor-Shing Taipei Medical University International Ph.D. Program in Gerontology and Long-Term Care Taipei City110 Taiwan Taipei Medical University Research Center in Nursing Clinical Practice Wan Fang Hospital Taipei City110 Taiwan Taipei Medical University School of Biomedical Engineering College of Biomedical Engineering Taipei City110 Taiwan Taipei Medical University School of Gerontology and Long-Term Care College of Nursing Taipei City110 Taiwan National Taipei University Department of Computer Science and Information Engineering New Taipei City237 Taiwan National Taipei University College of Electrical Engineering and Computer Science New Taipei City237 Taiwan

Unbalanced walking is increasingly common among older adults;therefore, routinely assessing the balance of older adults is crucial. The traditional method of assessing balance uses scales, requires the supervision of a physical therapist (PT), and is time-consuming. The present study, therefore, proposes a deep learning (DL) model architecture that combines a convolutional neural network (CNN) and a long short-term memory (LSTM) network model to predict the scores of three scales, namely the Berg balance scale (BBS), timed up and go (TUG), and single-leg stance (SLS). The gait data of 15 m of walking were collected from seven inertial measurement units (IMUs) and input into the CNN-LSTM model for evaluation. The BBS and TUG only require the participants to wear two IMUs on the left and right thighs, respectively, for accurate predictions. The mean absolute errors (MAEs) of predicting the scores of the BBS and TUG are 1.2562 and 1.4016 s, respectively;however, the MAE of score predictions of SLS is higher than that of the BBS and TUG, indicating that gait data cannot be used for assessing SLS;moreover, participants only wear one IMU on the right calf for BBS and TUG evaluations, which yield MAEs of 1.4334 and 1.5229 s, respectively. The proposed system can quickly and accurately predict the scores of the BBS and TUG. The proposed model can assist PTs with making clinical decisions. © 2001-2012 IEEE.

关键词： Long short-term memory

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Adaptable physics-based super-resolution for electron backscatter diffraction maps

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npj Computational materials 2022年第1期8卷 2444-2452页

作者： Devendra K.Jangid Neal R.Brodnik Michael G.Goebel Amil Khan SaiSidharth Majeti McLean P.Echlin Samantha H.Daly Tresa M.Pollock B.S.Manjunath Electrical and Computer Engineering University California Santa BarbaraSanta Barbara93106-5050CAUSA Mechanical Engineering University California Santa BarbaraSanta Barbara93106-5050CAUSA Computer Science University California Santa BarbaraSanta Barbara93106-5050CAUSA Materials Department University California Santa BarbaraSanta Barbara93106-5050CAUSA

In computer vision,single-image super-resolution(SISR)has been extensively explored using convolutional neural networks(CNNs)on optical images,but images outside this domain,such as those from scientific experiments,are not well *** data is often gathered using non-optical methods,which alters the metrics for image *** such example is electron backscatter diffraction(EBSD),a materials characterization technique that maps crystal arrangement in solid materials,which provides insight into processing,structure,and property *** present a broadly adaptable approach for applying state-of-art SISR networks to generate super-resolved EBSD orientation *** approach includes quaternion-based orientation recognition,loss functions that consider rotational effects and crystallographic symmetry,and an inference pipeline to convert network output into established visualization formats for EBSD *** ability to generate physically accurate,high-resolution EBSD maps with super-resolution enables high-throughput characterization and broadens the capture capabilities for three-dimensional experimental EBSD datasets.

关键词： maps resolution networks

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Unveiling Phonon Dispersion Behavior of AlN/GaN Heterostructures Using EELS

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Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 354-355页

作者： Reyes-González, Joaquin E. Dellby, Niklas Plotkin-Swing, Benjamin Wang, Ping Pandey, Ayush Mi, Zetian Lagos, Maureen J. Department of Materials Science and Engineering McMaster University Hamilton Ontario Canada Nion Co. Kirkland WA United States Department of Electrical and Computer Engineering University of Michigan Ann Arbor MI United States Canadian Centre for Electron Microscopy McMaster University Hamilton Ontario Canada

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The growing memristor industry

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Nature 2025年第8059期640卷 613-622页

作者： Lanza, Mario Pazos, Sebastian Aguirre, Fernando Sebastian, Abu Le Gallo, Manuel Alam, Syed M. Ikegawa, Sumio Yang, J. Joshua Vianello, Elisa Chang, Meng-Fan Molas, Gabriel Naveh, Ishai Ielmini, Daniele Liu, Ming Roldan, Juan B. Department of Materials Science and Engineering National University of Singapore Singapore Singapore Institute for Functional Intelligent Materials National University of Singapore Singapore Singapore Centre for Advanced 2D Materials (CA2DM) National University of Singapore Singapore Singapore Materials Science and Engineering Program Physical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Intrinsic Semiconductor Technologies London United Kingdom IBM Research – Zurich Rüschlikon Switzerland Everspin Technologies Chandler AZ United States Department of Electrical and Computer Engineering University of Southern California Los Angeles CA United States CEA-Leti Université Grenoble Alpes Grenoble France Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan Weebit Nano Hod Hasharon Israel Dipartimento di Elettronica Informazione e Bioingegneria (DEIB) Politecnico di Milano and *** Milano Italy Key Laboratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing China Departamento de Electrónica y Tecnología de Computadores Universidad de Granada Facultad de Ciencias Granada Spain

The semiconductor industry is experiencing an accelerated transformation to overcome the scaling limits of the transistor and to adapt to new requirements in terms of data storage and computation, especially driven by artificial intelligence applications and the Internet of Things. In this process, new materials, devices, integration strategies and system architectures are being developed and optimized. Among them, memristive devices and circuits—memristors are two-terminal memory devices that can also mimic some basic bioelectronic functions—offer a potential approach to create more compact, energy-efficient or better-performing systems. The memristor industry is growing quickly, raising abundant capital investment, creating new jobs and placing advanced products in the market. Here we analyse the status and prospects of the memristor industry, focusing on memristor-based products that are already commercially available, prototypes with a high technological readiness level that might affect the market in the near future, and discuss obstacles and pathways to their implementation. © Springer Nature Limited 2025.

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Low-loss, nonvolatile tuning of Bragg structures with Sb2Se3

Low-loss, nonvolatile tuning of Bragg structures with Sb2Se3

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CLEO: Applications and Technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

作者： Nobile, Nicholas A. Lian, Chuanyu Sun, Hongyi Huang, Yi-Siou Mills, Brian Popescu, Cosmin Constantin Callahan, Dennis Hu, Juejun Ríos Ocampo, Carlos A. Youngblood, Nathan Electrical & Computer Engineering Department University of Pittsburgh PittsburghPA15213 United States Department of Materials Science & Engineering University of Maryland College ParkMD20742 United States Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD20742 United States Department of Materials Science & Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Draper Scholar Program The Charles Stark Draper Laboratory Inc. CambridgeMA02139 United States The Charles Stark Draper Laboratory Inc. CambridgeMA02139 United States

Sb2Se3 is used to switch between broadband transparency and enhanced index contrast in two device types leveraging Bragg gratings for tunable stop- and pass-band functionalities. Experimental results highlight fabrication challenges and efficacy of the designs. © Optica Publishing Group 2024, © 2024 The Author(s)

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A Study on the Performance Improvement of Axial Flux Permanent Magnet Machines Based on Stator and Rotor Design Modifications

A Study on the Performance Improvement of Axial Flux Permane...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Jangho Yun Brandon Grainger Paul Ohodnicki Department of Mechanical Engineering and Materials Science University of Pittsburgh Pittsburgh PA USA Department of Electrical and Computer Engineering University of Pittsburgh Pittsburgh PA USA

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

Axial flux permanent magnet (AFPM) machines have technological competitiveness for electric propulsion systems that require compact structures and high-power density. However, challenging design and manufacturing problems that reduce the cost competitiveness cause designers to limit designable variables. In this paper, the effects of slot/pole combination, semi-closed slot, magnetic wedge, and segmented PM on performance in double-sided rotor and double-sided stator geometries designed with stator open slots were investigated through 3-D finite element analysis (FEA). FEA results show that the design variables have a significant impact on torque, torque ripple, and losses. Semi-closed slots or magnetic wedges reduce PM losses for each open slot model by more than 80%, significantly reducing losses compared to segmented PMs, and also reducing torque ripple. As an alternative to stator design modification, results indicate the open slot model can be considered with a slot/pole combination for low cogging torque to reduce torque ripple and segmented PMs to reduce PM losses.

关键词： Geometry Permanent magnet machines Magnetic flux Torque Three-dimensional displays Rotors Stators Permanent magnets Magnetic analysis Torque measurement

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Distributed Fault Detection for Dynamic Systems Based on H̲/H∞Indices 4

Distributed Fault Detection for Dynamic Systems Based on H̲...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Wang, Qiang Cheng, Chao Sun, Aichen Chen, Hongtian School of Computer Science and Engineering Changchun University of Technology Changchun China Taiyuan City Vocational College Department of Mechanical and Electrical Engineering Taiyuan China University of Alberta Department of Chemical and Materials Engineering Edmonton Canada

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

With the help of the sensor networks, this paper mainly develops a model-based distributed fault detection method for dynamic systems. Specifically, each sensor node is equipped with a Luenberger observer and a post-filter for residual generation. It is worth mentioning that, the post-filter is designed to improve detection performance through the H-/H∞ indices. Moreover, the design parameters are dependent on the linear matrix inequality. Finally, a numerical example is introduced to verify the accuracy and effectiveness of the proposed distributed approach. © 2022 IEEE.

关键词： Linear matrix inequalities

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An effective communication and computation model based on a hybridgraph-deeplearning approach for SIoT

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Digital Communications and Networks 2022年第6期8卷 900-910页

作者： M.S.Mekala Gautam Srivastava Ju H.Park Ho-Youl Jung Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38544South Korea RLRC LAb for Autonomous Vehicle Parts and Materials Innovation Yeungnam UniversityGyeongsan38544South Korea Department of Math and Computer Science Brandon UniversityBrandonCanada Department of Electrical Engineering Yeungnam UniversityGyeongsanSouth Korea Research Centre for Interneural Computing China Medical UniversityTaichungTaiwanChina

Social Edge Service(SES)is an emerging mechanism in the Social Internet of Things(SIoT)orchestration for effective user-centric reliable communication and *** services are affected by active and/or passive attacks such as replay attacks,message tampering because of sharing the same spectrum,as well as inadequate trust measurement methods among intelligent devices(roadside units,mobile edge devices,servers)during computing and *** issues lead to computation and communication overhead of servers and computation *** address this issue,we propose the HybridgrAph-Deep-learning(HAD)approach in two stages for secure communication and ***,the Adaptive Trust Weight(ATW)model with relation-based feedback fusion analysis to estimate the fitness-priority of every node based on directed graph theory to detect malicious nodes and reduce computation and communication ***,a Quotient User-centric Coeval-Learning(QUCL)mechanism to formulate secure channel selection,and Nash equilibrium method for optimizing the communication to share data over edge *** simulation results confirm that our proposed approach has achieved effective communication and computation performance,and enhanced Social Edge Services(SES)reliability than state-of-the-art approaches.

关键词： Edge computing Adaptive trust weight(ATW)model Quotient user-centric coeval-learning(QUCL)mechanism Deep learning Service reliability

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