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Fabric-substrated capacitive biopotential sensors enhanced by dielectric nanoparticles

Nano Research 2021年第9期14卷 3248-3252页

作者： Xiangjun Chen Xiaoxiang Gao Akihiro Nomoto Keren Shi Muyang Lin Hongjie Hu Yue Gu Yangzhi Zhu Zhuohong Wu Xue Chen Xinyu Wang Baiyan Qi Sai Zhou Hong Ding Sheng Xu Materials Science and Engineering Program University of California San DiegoLa JollaCA 92093USA Department of NanoEngineering University of California San DiegoLa JollaCA 92093USA Department of Electrical and Computer Engineering University of California San DiegoLa JollaCA 92093USA Department of Bioengineering University of California San DiegoLa JollaCA 92093USA

Wearable biopotential sensing devices are essential to long-term and real-time monitoring of human ***-contact,capacitive sensing electrodes prevent potential skin iritations,and are thus beneficial for long-term *** capacitive electrodes are either connected to a separate control circuit via external wires or have limited sensing capacitances,which leads to low signal *** study demonstrates a stretchable capacitive sensing device with integrated electrodes and control electronics,with enhanced signal *** electrodes and the control electronics are fabricated on a common fabric substrate for breathability and strain-limiting *** stretchable electrodes are based on an island-bridge design with a stretchability as high as-100%,and an area ratio as high as-80%.By using a dielectric calcium copper titanate(CCTO)composite as the adhesive layer,the electrode capacitance can be increased,yielding an enhanced signal-to-noise ratio(SNR)in the acquired *** device offers a convenient and comfortable approach for long-term non-contact monitoring of biopotential signals.

关键词： capacitive sensing biopotential stretchable calcium copper titanate(CCTO) signal-to-noise ratio(SNR)

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Numerical Investigation of Optimal Buffer Layer and Performance Evaluation on CdTe Solar Cell

arXiv

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arXiv 2024年

作者： Ahamed, Tanzir Rahman, Arifa Rahaman, Imteaz Mamun, Ashraful Shiam, Istiaq Firoz Bappy, Md. Mehedi Hasan Ahammed, Tanvir Karmakar, Srabani Parash, Hasibul Hasan Ghosh, Sampad Department of Electrical and Electronic Engineering CCN University of Science and Technology Cumilla3503 Bangladesh Department of Electrical and Electronic Engineering Chittagong University of Engineering and Technology Chattogram4349 Bangladesh Department of Electrical and Computer Engineering University of Utah Salt Lake CityUT84112 United States Department of Electrical Engineering Texas State University San MarcosTX78666 United States Department of Materials Science and Engineering University of Rajshahi Rajshahi6205 Bangladesh Department of Materials Science and Engineering University of Utah Salt Lake CityUT84112 United States Department of Electrical and Electronic Engineering Rajshahi University of Engineering and Technology Rajshahi6204 Bangladesh

This study investigates the critical role of buffer layers in enhancing the efficiency of thin-film CdTe solar cells. We explore non-toxic buffer materials, specifically ZnSe, ZnMgO, 3C-SiC, and WS2, as potential replacements for the traditional Cd-based CdS buffer layer. Our analysis includes a thorough evaluation of the electrical and optical performance of these buffer materials in conjunction with CdTe absorbers. We optimize the thickness of both the buffer and absorber layers to achieve the best performance. Additionally, we examine the impact of defect density variations in the buffer materials and their corresponding temperature effects. Among the tested materials, ZnSe and ZnMgO demonstrate the highest potential, achieving power conversion efficiencies of 20.74% and 20.73%, respectively. Copyright © 2024, The Authors. All rights reserved.

关键词： II-VI semiconductors

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Long short-Term memory (LSTM) model-based reinforcement learning for nonlinear mass spring damper system control 7

Long short-Term memory (LSTM) model-based reinforcement lear...

引用

7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Wijaya, Santo Heryadi, Yaya Arifin, Yulyani Suparta, Wayan Lukas Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta55281 Indonesia Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

The Neural Networks (NN) model which is incorporated in the control system design has been studied, and the results show better performance than the mathematical model approach. However, some studies consider that only offline NN model learning and does not use the online NN model learning directly on the control system. As a result, the controller's performance decreases due to changes in the system environment from time to time. The Reinforcement Learning (RL) method has been investigated intensively, especially Model-based RL (Mb-RL) to predict system dynamics. It has been investigated and performs well in making the system more robust to environmental changes by enabling online learning. This paper proposes online learning of local dynamics using the Mb-RL method by utilizing Long Short-Term Memory (LSTM) model. We consider Model Predictive Control (MPC) scheme as an agent of the Mb-RL method to control the regulatory trajectory objectives with a random shooting policy to search for the minimum objective function. A nonlinear Mass Spring Damper (NMSD) system with parameter-varying linear inertia is used to demonstrate the effectiveness of the proposed method. The simulation results show that the system can effectively control high-oscillating nonlinear systems with good performance. © 2022 Elsevier B.V.. All rights reserved.

关键词： Model predictive control

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Robust Synergetic Observer based Fault-Tolerant Control for Electric Vehicle Applications

Robust Synergetic Observer based Fault-Tolerant Control for ...

引用

Annual Conference of Industrial Electronics Society

作者： Mohammed Kabir Billa Boumegouas Katia Kouzi Mohamed Trabelsi Atif Iqbal Mhamed Birame Mohammad B. Shadmand Laboratory of Semiconductors and Functional Materials Amar Telidji University of Laghouat Algeria Electronics and Communications Engineering Department Kuwait College of Science and Technology Kuwait Department of Electrical Engineering Qatar University Doha Qatar Department of Electrical & Computer Engineering University of Illinois Chicago IL USA

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Speed sensor faults are very common in electric vehicle (EV) applications, often disrupting system performance due to the reliance on speed sensor data by the electric drives. Consequently, fault-tolerant control approaches require robust observer structures capable of functioning effectively during faults, swiftly identifying and reconfiguring failures. Thus, this paper presents a novel fault-tolerant control design leveraging a synergetic observer (SO) to substitute the speed sensor in the event of fault. Comparative analysis with a super-twisting sliding mode observer (ST-SMO) highlights the proposed observer's superior performance in terms of tracking accuracy and ripple reduction. The presented simulation results demonstrate promising performance of the proposed observer for fault-tolerant control in EV applications.

关键词： Fault tolerance System performance Simulation Fault tolerant systems Velocity control Observers Electric vehicles Synchronous motors Vehicle dynamics Magnetosphere

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A roadmap for the commercialization of perovskite light emitters (August, 10.1038/s41578-022-00459-4, 2022)

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NATURE REVIEWS materials 2022年第10期7卷 833-833页

作者： Han, Tae-Hee Jang, Kyung Yeon Dong, Yitong Friend, Richard H. Sargent, Edward H. Lee, Tae-Woo Hanyang University Division of Materials Science and Engineering Seoul Republic of Korea (GRID:grid.49606.3d) (ISNI:0000 0001 1364 9317) Seoul National University Department of Materials Science and Engineering Seoul Republic of Korea (GRID:grid.31501.36) (ISNI:0000 0004 0470 5905) University of Toronto Department of Electrical and Computer Engineering Toronto Canada (GRID:grid.17063.33) (ISNI:0000 0001 2157 2938) University of Cambridge Cavendish Laboratory Cambridge UK (GRID:grid.5335.0) (ISNI:***) Seoul National University Department of Materials Science and Engineering Seoul Republic of Korea (GRID:grid.31501.36) (ISNI:0000 0004 0470 5905) Seoul National University School of Chemical and Biological Engineering Institute of Engineering Research Research Institute of Advanced Materials Soft Foundry Seoul Republic of Korea (GRID:grid.31501.36) (ISNI:0000 0004 0470 5905)

Metal halide perovskites (MHPs) possess advantageous optoelectronic properties, so perovskite emitters and perovskite light-emitting diodes (PeLEDs) are promising candidates for next-generation high-colour-purity displays and lighting applications. Within the past 5 years, the luminescence efficiency of MHP emitters and PeLEDs has increased rapidly. However, the industrial applications of perovskites are impeded by several technical bottlenecks, such as insufficient colour reproducibility, low operational stability, toxicity and limited large-scale production. In this Review, we survey the current status of MHP emitters and PeLEDs and provide a technical roadmap to highlight the goals and requirements for them to successfully enter the markets for vivid displays with high colour purity, augmented and virtual reality displays and general and special lighting. We also set out steps for future research in MHPs and their device *** perovskite light emitters hold promise for next-generation high-colour-purity displays and lighting applications. This Review surveys the outstanding scientific issues and the strategies to increase the efficiency and stability of perovskite light-emitting devices, tracing a roadmap for their mass production and commercialization.

关键词： Perovskite

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Fabrication of Waveguides and Gradient Index Flat Optics by Nanoimprinting Refractive Index

Fabrication of Waveguides and Gradient Index Flat Optics by ...

引用

CLEO: science and Innovations, S and I 2022

作者： Hardison, Anna L. Talukdar, Tahmid H. Kravchenko, Ivan I. Ryckman, Judson D. Holcombe Department of Electrical and Computer Engineering Clemson University SC29634 United States Center for Nanophase Materials Science Oak Ridge National Laboratory Oak RidgeTN37831 United States

ISBN: (纸本)9781557528209

We report the fabrication of gradient index flat optics and waveguides using the 'nanoimprinting refractive index' (NIRI) technique applied to mesoporous silicon substrates. Optical wavefront shaping and waveguiding are demonstrated in the visible and near-infrared respectively. © Optica Publishing Group 2022, © 2022 The Author(s)

关键词： Refractive index

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Enhancing terahertz quantum cascade laser emission by breaking the dipole approximation

Enhancing terahertz quantum cascade laser emission by breaki...

引用

2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Keidar, Shaked Sloan, Jamison Franckié, Martin Ottomaniello, Andrea Scalari, Giacomo Tredicucci, Alessandro Kurman, Yaniv Kaminer, Ido Department of Electrical and Computer Engineering Technion - Israel Institute of Technology Haifa3200003 Israel Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Institute for Quantum Electronics Department of Physics ETH Zurich Zurich8093 Switzerland Center for Materials Interfaces Istituto Italiano di Tecnologia ViaR Piaggio 34 PI Pontedera56025 Italy Dipartimento diFisica "E. Fermi" Universita di Pisa Largo Pontecorvo 3 Pisa56127 Italy

We show that transitions in quantum cascade lasers (QCLs) can achieve substantial beyond-dipole enhancements, which we quantify using macroscopic quantum electrodynamics for specially designed cavities and graphene wa... 详细信息

ISBN: (纸本)9781957171258

关键词： Quantum cascade lasers

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Cnt Forest Self-Assembly Insights from In-Situ Esem Synthesis

SSRN

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SSRN 2024年

作者： Maschmann, Matthew R. Surya, Ramakrishna Koerner, Gordon L. Hajilounezhad, Taher Safavigerdin, Kaveh Calyam, Prasad Bunyak, Filiz Palaniappan, Kannappan University of Missouri Department of Mechanical and Aerospace Engineering ColumbiaMO65211 United States Department of Electrical Engineering and Computer Science ColumbiaMO65211 United States MU Materials Science and Engineering Institute ColumbiaMO65211 United States

Understanding and controlling the dynamic self-assembly mechanisms of carbon nanotube (CNT) forests is necessary to advance their technological impact. Here, in-situ environmental scanning electron microscope (ESEM) chemical vapor deposition (CVD) synthesis observes the real-time nucleation, assembly, delamination, and self-termination of dense (> 109 CNT/cm2), tall (> 100 µm) CNT forests in real time. Forest synthesis is continuously observed from nucleation to self-termination. Assembly forces generated near the substrate detach CNTs from the substrate, which simulation suggests requires between 3-12 nN of tensile force. Delamination initiates at both the CNT-catalyst and the catalyst-substrate interfaces, indicating multiple delamination mechanisms. Delamination initiates at both the CNT-catalyst and the catalyst-substrate interfaces, indicating multiple delamination mechanisms. Digital image correlation applied to SEM image sequences measures time-invariant strain within growing forests, indicating that forests grow as rigid bodies after liftoff. The Meta CoTracker algorithm measured CNT growth rates reduce from 50 nm/sec to full termination over 150 seconds. The kinematic behaviors we observe are foundational to understanding the process-structure-property relationships of CNT forests. © 2024, The Authors. All rights reserved.

关键词： Chemical vapor deposition

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Impact of In and Ga Fractions in Lattice-Matched InAlGaN Barrier Layer on Performance of InAlGaN/GaN MISHEMT

Impact of In and Ga Fractions in Lattice-Matched InAlGaN Bar...

引用

2024 International VLSI Symposium on Technology, Systems and Applications, VLSI TSA 2024

作者： Langpoklakpam, Catherine Hsiao, Yi-Kai Lin, Chun-Hsiung Chang, Edward Yi Kuo, Hao-Chung College of Electrical and Computer Engineering National Yang-Ming Chiao Tung University Department of Photonics Institute of Electro-Optical Engineering Hsinchu30010 Taiwan Hon Hai Research Institute Semiconductor Research Center Taipei11492 Taiwan International College of Semiconductor Technology National Yang-Ming Chiao Tung University Hsinchu30010 Taiwan National Yang-Ming Chiao Tung University Department of Materials Science and Engineering Hsinchu30010 Taiwan

ISBN: (纸本)9798350360349

This study investigates the impact of lattice-matched InAlGaN (w/i GaN) top barrier layer for diverse In and Al fractions on electrical characteristics of InAlGaN/GaN MISHEMT. To maintain lattice matching with GaN, the In and Al content must increase or decrease simultaneously. Increasing In and Al fractions lead to a more negative threshold voltage and higher drain current. This can be ascribed to creating a more profound quantum well and improving carrier confinement within the two-dimensional electron gas (2DEG). Conversely, as In and Al mole fractions reduce, the on-resistance of the devices decreases due to reduced 2DEG confinement. This work suggests that the performance of InAlGaN/GaN MISHEMT can be effectively optimized by adjusting the fractions of In and Al in the lattice-matched InAlGaN barrier layer. © 2024 IEEE.

关键词： Indium compounds

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Path Signatures and Graph Neural Networks for Slow Earthquake Analysis: Better Together?

arXiv

引用

arXiv 2024年

作者： Riess, Hans Veveakis, Manolis Zavlanos, Michael M. Department of Electrical & Computer Engineering Duke University DurhamNC United States Department of Civil & Environmental Engineering Duke University DurhamNC United States Department of Mechanical Engineering & Materials Science DurhamNC United States

The path signature, having enjoyed recent success in the machine learning community, is a theoretically-driven method for engineering features from irregular paths. On the other hand, graph neural networks (GNN), neural architectures for processing data on graphs, excel on tasks with irregular domains, such as sensor networks. In this paper, we introduce a novel approach, Path Signature Graph Convolutional Neural Networks (PS-GCNN), integrating path signatures into graph convolutional neural networks (GCNN), and leveraging the strengths of both path signatures, for feature extraction, and GCNNs, for handling spatial interactions. We apply our method to analyze slow earthquake sequences, also called slow slip events (SSE), utilizing data from GPS timeseries, with a case study on a GPS sensor network on the east coast of New Zealand’s north island. We also establish benchmarks for our method on simulated stochastic differential equations, which model similar reaction-diffusion phenomenon. Our methodology shows promise for future advancement in earthquake prediction and sensor network analysis. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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