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The Impact of Hot Carrier Injection-Induced Device Degradation for Lower-Power FinFETs

Journal of Electronic Materials 2023年第2期52卷 1391-1399页

作者： Chen, Yu-Lin Yeh, Wen-Kuan Hsu, Heng-Tung Chen, Ke-Horng Lien, Der-Hsien Lin, Wen-Chin Yu, Tien-Han Chiu, Yu-Sheng Godwinraj, D. Godfrey, D. Wu, Chien-Hung International College of Semiconductor Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Microelectronics National Cheng Kung University Tainan Taiwan Department of ECE Amal Jyothi College of Engineering Kerala Kottayam India Department of Optoelectronics and Materials Engineering Chung Hua University Hsinchu Taiwan Department of Electronics and Communication Engineering Dayananda Sagar University Bengaluru India National Applied Research Laboratories Hsinchu Taiwan

The impact of hot carrier injection (HCI) on the performance of standard and low-VT FinFETs are investigated and benchmarked with each other. For this investigation, these FinFETs were fabricated with various gate lengths (L) from 16 to 36 nm. HCI-induced transconductance degradation in standard devices for gate length variations of 36 nm down to 16 nm was 75%, while it was 35% for low-VT devices. Similarly, the degradation of threshold voltage in standard devices for gate length variations of 36 nm down to 16 nm was 39%, while it was 36% for low-VT device. In this work, as the device is subject to HCI, we found that: (1) short-channel devices cause severe degradation on the threshold voltage and transconductance (gm) compared to long-channel devices, owing to the higher electric field for short-channel devices at the gate edge, (2) standard devices exhibit a more stable threshold voltage than that of low-VT power devices, since the TiN barrier layer prevents Al atom diffusion into the HfO2 layer, and (3) the transconductance efficiency of standard devices is better than that of low-VT power devices. Further, the lower-VT devices show lower transconductance degradation than standard devices. However, the transconductance degradation of the long-channel standard and low-VT devices are the same. Compared to short-channel low-VT devices, extended-channel standard devices are more immune to the HCI effect. © 2022, The Minerals, Metals & Materials Society.

关键词： Threshold voltage

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Super-Mossian Dielectrics for Nanophotonics

Super-Mossian Dielectrics for Nanophotonics

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Wang, Xielin Doiron, Chloe F. Li, Zhichao Khurgin, Jacob B. Naik, Gururaj V. Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States

Searching for high-index dielectrics, we identify materials that break the index upper bound set by Moss' rule. We highlight the promise of such super-Mossian materials by demonstrating nanophotonic devices made o... 详细信息

ISBN: (纸本)9781957171258

关键词： Layered semiconductors

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Deep Eutectic Solvent Pretreatment of Durian Peel for Enhanced Bioethanol Production 7th

Deep Eutectic Solvent Pretreatment of Durian Peel for Enhanc...

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7th Asia Conference on Environment and Sustainable Development, ACESD 2022

作者： Panakkal, Elizabeth Jayex Theegala, Manvitha Chaparla, Srihita Grashma Katam, Keerthi Kitiborwornkul, Nichaphat Sriariyanun, Malinee Department of Chemical and Process Engineering The Sirindhorn International Thai-German Graduate School of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand Department of Civil Engineering Ecole Centrale School of Engineering Mahindra University Telangana India Department of Electrical and Electronics Engineering Ecole Centrale School of Engineering Mahindra University Telangana India Biorefinery and Process Automation Engineering Center The Sirindhorn International Thai-German Graduate School of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand

ISBN: (纸本)9789819941001

Increased demand for energy coupled with the depletion of fossil fuels has shifted the focus on producing biofuel and other value-added products from the waste biomass. Being the largest exporter of durian, a huge amount of durian peel generated as waste has been a critical concern in Thailand causing environmental and health issues. As a step toward a greener economy, this study has aimed at utilizing durian peel for producing bioethanol from it. The durian peel was pretreated with acidic deep eutectic solvent, choline chloride: lactic acid (ChCl/LA) at a solid loading of 1:6.5 (w/w), at 80 ℃ for 5 h. The pretreatment was effective by retaining almost 63% cellulose in biomass which when hydrolyzed resulted in 88.7% glucose yield from the pretreated biomass. In addition to this, fermentation studies of pretreated biomass could generate 8.4 g/L bioethanol confirming the potential of durian peel in producing value-added chemicals from it. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Bioethanol

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Energy-Efficient Detection Using Message Passing Algorithm with Dynamic Factor Graph for Uplink MIMO Communications in Cell-Free Networks

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IEEE Transactions on Wireless Communications 2025年

作者： Chen, Ti-Yu Yu, Chia-Hao Chiueh, Tzi-Dar National Taiwan University Graduate Institute of Electronics Engineering Taipei Taiwan Mediatek Inc Hsinchu Taiwan National Taiwan University Department of Electrical Engineering and Graduate School of Advanced Technology Taipei Taiwan

Cell-free (CF) multiple input multiple output (MIMO) is gaining traction for B5G/6G wireless communication systems due to its heightened connectivity, spectral efficiency, and quality of service (QoS). Developing an efficient data detector is imperative to harness these attributes effectively in uplink transmissions. In this paper, we propose the DMPACT2 detector, a message-passing algorithm (MPA) variant that dynamically adjusts the factor graph (FG) based on achievable rate, allocating computing resources judiciously. Additionally, two low-complexity techniques are employed to save 99% of DMPACT2's complexity, namely local minimum mean-squared error (MMSE)-based initial constellation truncation and log-likelihood ratio (LLR)-based constellation truncation. Simulation results demonstrate that the self-Adopting FG boosts DMPACT2's bit error rate (BER) to approach the BER lower bound of the optimal maximum likelihood (ML) detector under high Signal-To-Noise Ratio (SNR), indicating that DMPACT2 is very competitive with the optimal detection. Moreover, DMPACT2 attains a 10-2 BER with a 3dB lower SNR than the best competitor using the same computational complexity. Furthermore, a novel metric, power-normalized bit rate, is proposed, considering multiple metrics concurrently in the cell-free context: Throughput, BER, complexity, transmission power, and backhaul traffic. In terms of the power-normalized bit rate, DMPACT2 exhibits superior performance compared to all other detectors. © 2002-2012 IEEE.

关键词： Mean square error

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Multi-modal Multitask Learning Model for Simultaneous Classification of Two Epilepsy Biomarkers 27th

Multi-modal Multitask Learning Model for Simultaneous Classi...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Broti, Nawara Mahmood Sawada, Masaki Takayama, Yutaro Iijima, Keiya Iwasaki, Masaki Ono, Yumie Electrical Engineering Program Graduate School of Science and Technology Meiji University Kanagawa Kawasaki Japan Department of Neurosurgery Yokohama City University Hospital Kanagawa Yokohama Japan Department of Neurosurgery National Center Hospital National Center of Neurology and Psychiatry Tokyo Kodaira Japan Department of Electronics and Bioinformatics School of Science and Technology Meiji University Kanagawa Kawasaki Japan

ISBN: (纸本)9783031781971

Accurate estimation of the epileptogenic zone is critical for surgical treatment of drug-resistant epilepsy. While epilepsy biomarkers detection for epileptogenic zone localization has traditionally relied on expert clinician knowledge, the use of deep learning in this context has recently gained appeal for objective diagnosis and reducing clinician burden. However, previously proposed classifiers for electrocorticogram data focused on only single biomarkers among many types, requiring separate models and large datasets for each. To minimize clinicians’ workload and patients’ sufferings, innovative methods to classify multiple biomarkers using small training datasets and minimal computation time is required. This research marks the first implementation of multi-modal multitask learning in epilepsy biomarker classification, proposing a model to automatically classify two biomarkers—high-frequency oscillations (HFO) and interictal epileptiform discharges (IED)—from separate datasets simultaneously. We validated the proposed model on 1500 annotated HFO and IED candidate signals each, obtained from 5 patients. Our proposed model can perform both HFO and IED classification simultaneously, with cross-validation accuracies of 90.99% and 93.99%;F1 scores were reported as 0.80 and 0.82, respectively. Our leave-one-patient-out experiments achieved 78.03% and 81.19% accuracy for HFO and IED classification, respectively. Compared to existing state-of-the-art classification architectures, our model is shown to be efficient and robust, yet simple and lightweight. The usefulness of sharing parameters between the two classifiers was confirmed in this practical clinical setting of epileptic biomarker detection, potentially contributing to minimizing the number of annotated datasets and realizing robust, accurate, and simultaneous identification of two biomarkers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

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Revolutionizing Neurological Diagnostics: Integrating 6G Technology with Deep Learning for Enhanced Detection of Multiple Sclerosis and Myelitis

Revolutionizing Neurological Diagnostics: Integrating 6G Tec...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Noureldeen, Rana M. Elshshtawy, Rahma A. Elgohary, Omnia A. Wahba, Fatma Alzahraa A. Attia, Marco K. Abo Elazm, Zeinab B. Khattap, Mohamed G. Galal Eldeen Mohamed Ali Hassan, Hend Mostafa, Mariam Ibrahim, Nayra Ramadan, Reem Refaat, Yomna Khaled, Mennatallah Maher, Ali Abd Elaziz, Mohamed Gamal Abdellatif Ibrahim, Ahmed Faculty of Applied Health Sciences Galala University Suez435611 Egypt Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Air Defense College Department of Electronics and Electrical Communications Engineering Alexandria Egypt

ISBN: (纸本)9798350351408

This paper proposes an alternative detection frame-work for multiple sclerosis (MS) and idiopathic acute transverse myelitis (ATM) within the 6G-enabled Internet of Medical Things (IoMT) environment. The developed framework relies on the implementation of a deep learning technique known as Dense Convolutional Networks (DenseNets) in the 6G-enabled IoMT to enhance prediction performance. To validate the performance of DenseNets, we compared it with other deep learning techniques, including Convolutional Neural Networks (CNN) and MobileNet, using real-world datasets. The experimental results show the high performance of DenseNets in predicting MS and ATM compared to other methods, achieving an accuracy of nearly 90 %. © 2024 IEEE.

关键词： Convolutional neural networks

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Design of a 2–18 GHz vector modulator using novel switchable balun based bi-phase modulation technique

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AEU - International Journal of electronics and Communications 2024年 178卷

作者： Hasturk, Ahmet Akcam, Nursel ASELSAN INC. Ankara06200 Turkey Department of Electrical and Electronics Engineering Graduate School of Natural and Applied Sciences Gazi University Ankara06500 Turkey Department of Electrical and Electronics Engineering Gazi University Ankara06570 Turkey

Phased array communication and radar systems employ vector modulators (VM) to simultaneously control both phase and amplitude. This paper presents an innovative technique to alternate the RF signal into four quadrants using switchable balun based bi-phase modulators. This switchable balun topology offers a compact Printed Circuit Board (PCB) based VM design as an alternative solution to high-dimensional hybrid couplers or reflection-type pin diodes. Thanks to the balun, the VM circuit dimensions are only 12.7 mm × 25.4 mm with wide frequency bandwidth coverage. Additionally, the total power consumption is only 3 mW due to its entirely passive topology. The developed VM consists of a 90° power divider, switchable balun based bi-phase modulators, digitally controlled attenuators (DCA), and an in-phase power combiner. The proposed VM achieves a 360° phase shift without any dead zones and 31.5 dB attenuation in 9:1 operation bandwidth with lower rms phase and amplitude errors than the other previously reported state of the arts. Also, this design exhibits a calculated better than −31 dB rms error vector magnitude (EVM). Detailed characterization results show that the proposed VM can be used in transmit or receive beamforming networks that operate from 2 GHz to 18 GHz. © 2024 Elsevier GmbH

关键词： Topology

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Four-transmitter time-switching symmetric TX antenna array for stable power reception under 1D rotation and 3D location variation

Four-transmitter time-switching symmetric TX antenna array f...

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Asia-Pacific Conference on Microwave

作者： Ching-Ya Tseng Hsin-Chia Lu Department of Electrical Engineering Graduate Institute of Communication Engineering Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan

When a bee is flying in the air, its abdomen is at a fixed angle relative to the ground. If a dipole is attached to a bee horizontally, its polarization is always on the horizontal direction regardless of its fly direction. Vertical polarization radiation is therefore not required for the transmitting array. A four-transmitter array that radiates only at horizontal polarization is proposed at this paper. Under the same total input power to the transmitting array, the proposed four-transmitter array can increase received power by 50% as compared with the previously proposed 6T array under 1D rotation and 3D location variation. The 4T array, therefore, has better service area and volume performance than the 6T array. The 4T array also eliminates the need to install antennas at +z and −z directions, this can reduce the wiring complexity. Measurement results at 915 MHz also confirm the calculation results using the Friis equation.

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Exploring Shifted Domain Problem within MNIST Dataset

Exploring Shifted Domain Problem within MNIST Dataset

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2023 International Conference on Computer Science, Information Technology and engineering, ICCoSITE 2023

作者： Hidayaturrahman Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Bina Nusatara University BINUS Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350320954

Domain data can be shifted in any direction so it will be shared in different distributions to its original domain. This could be a problem since the model was trained with different distributions. It is found that adversarial domain adaptation using domain adversarial neural networks (DANN) can help to solve this problem on some scale. DANN can minimize the discrepancy between source and target data so the model can work well in both domains. The experiment is done by utilizing MNIST dataset that shifted into some conditions. In a condition when the shifting of distribution is too far, DANN is struggling to maintain the knowledge extracted from source data which leads to underperformance in the source and target domain. In contrast, when the shifting is closer, DANN can easily fit the model so it can perform well in both domains. It proves DANN is one of the good approaches to performing domain adaptation in small discrepancies. © 2023 IEEE.

关键词： Adversarial Domain Adaptation Domain Shifting Problem MNIST Transfer Learning

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Curriculum-based Reinforcement Learning for an Effective Multi-Agent Path Planning Algorithm in Warehouse Scenarios 15

Curriculum-based Reinforcement Learning for an Effective Mul...

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15th IEEE International Conference on Industry Applications, INDUSCON 2023

作者： de Oliveira, Iure Rosa L. de Carvalho, Kevin B. Brandão, Alexandre S. Graduate Program in Computer Science Universidade Federal de Viçosa Viçosa Brazil Electrical Engineering Department Universidade Federal de Viçosa Viçosa Brazil

ISBN: (纸本)9798350314182

Multi-robot systems can provide substantial increase in efficiency and/or flexibility in different scenarios. Applications in various settings have been studied in the literature, such as disaster management, surveillance, object transportation as well as search-and-rescue. A particular case that can highly benefit from the employment of multiple agents is the logistics in a warehouse scenario. This work proposes an multi-agent Q-learning based algorithm with curriculum learning and transfer learning to perform the path planning process. With progressively more complex stages of training as well as knowledge transfer from one stage to another, the algorithm is capable of achieve high success rates. In order to validate the proposed method, simulations were done to compare it to other combinations of the used techniques, as well as using Q-learning only. Scalability tests were also performed. The proposed method achieved up to 94% success rate after training. © 2023 IEEE.

关键词： Curriculum Learning Mobile Robotics Multi-Agent System Reinforcement Learning Transfer Learning

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