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Transfer learning approach to modeling multichannel gate-all-around nanosheet field-effect transistors under work function fluctuations

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engineering Applications of Artificial Intelligence 2025年 148卷

作者： Dash, Sagarika Li, Yiming Parallel and Scientific Computing Laboratory National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Communications Engineering National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Biomedical Engineering National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Artificial Intelligence Innovation National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Department of Microelectronics National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan

Deep learning (DL) has significantly advanced various industries, including semiconductors, by providing sophisticated methods for analyzing emerging device data. Transfer learning (TL), a prominent DL topology, leverages knowledge from a pre-trained model to improve the performance of a specific target task. This study aims to apply TL to predict the impact of work function fluctuation (WKF) on the variability of threshold voltage (σVTH) in gate-all-around silicon nanosheet field-effect transistors (GAA Si NS FETs). We used TL to transfer knowledge from models trained on 1-channel (1ch) GAA Si NS FETs to more complex 4-channel (4ch) counterparts. The prediction accuracy is evaluated by using the mean square error(MSE), root mean square error (RMSE), and the mean absolute error(MAE) metrics. Our TL approach achieved an error rate of less than 1%, demonstrating high accuracy in predicting WKF effects on σ VTH of 4ch GAA Si NS FETs using only 500 samples. This study presents a pioneering application of TL using a one-dimensional (1D) convolutional neural network (CNN) long short-term memory (LSTM) topology in semiconductor device technology. The results effectively address the challenge of predicting σ VTH variations in advanced GAA Si NS FETs because of WKF, which eliminates the need for extensive semiconductor device simulations. © 2025 Elsevier Ltd

关键词： Convolutional neural networks

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Electrochemical biosensor based on an atomic layered composite of graphene oxide/graphene as an electrode material towards selective and sensitive detection of miRNA-21

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Microchemical Journal 2024年 199卷

作者： Huang, Min-Shin Govindasamy, Mani Chinnapaiyan, Sathishkumar Lin, Yi-Ting Lu, Shao-Yang Samukawa, Seiji Huang, Chi-Hsien Department of Materials Engineering Ming Chi University of Technology New Taipei City 243303 Taiwan International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City 24303 Taiwan Centre for Applied Research Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai-602105 Tamil Nadu India Institute of Fluid Science Tohoku University Sendai 980-8577 Japan College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu 300093 Taiwan Division of Rheumatology Allergy and Immunology Chang Gung Memorial Hospital Taoyuan City 33305 Taiwan College of Engineering Chang Gung University Taoyuan City 33302 Taiwan

Development of an efficient technique towards the detection of miRNAs is highly significant for the timely diagnosis and prognosis of cancers. In this study, we utilized the chemical vapor deposition (CVD) technique to grow bilayer graphene (BLG) on copper foil and subsequently transferred the BLG to fluorine doped tin oxide (FTO) substrate via a facile wet transfer technique. The upper layer of the BLG was modified to graphene oxide (GO) with a low damage plasma treatment (LDPT) process to serve as a biomolecule receiving layer and the lower graphene layer (G) serves as an electron transport layer. The developed GO/G/FTO platform offers superior sensing ability towards the miRNA-21. The results demonstrated that the proposed GO/G/FTO substrate detect the miRNA-21 with a wide linear range (10 fM ∼ 1 nM), low limit of detection (3.18 fM), high sensitivity (0.6 mApM⁻¹cm⁻²), selectivity and stability via the differential pulse voltammetry method. Additionally, the sensors can efficiently discriminate the target miRNA-21 from its complementary base mismatched counterparts. The proposed approach serves as an excellent tool for the early diagnosis of diseases. © 2024 Elsevier B.V.

关键词： Atomic layer oxidation Biosensor Cancer biomarkers Electrochemical Graphene oxide Plasma treatment

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Improving STEM education for lower-division college students at HSI by utilizing relevant sociocultural and academic experiences: First year results from ASSURE-US project

Improving STEM education for lower-division college students...

引用

2020 ASEE Virtual Annual Conference, ASEE 2020

作者： Huang, Jidong Kurwadkar, Sudarshan Bein, Doina Bai, Yu Mayoral, Salvador Department of Electrical Engineering California State University Fullerton FullertonCA United States Department of Civil and Environmental Engineering California State University Fullerton FullertonCA United States Department of Computer Science California State University Fullerton FullertonCA United States Computer Engineering Program California State University Fullerton FullertonCA United States Department of Mechanical Engineering California State University Fullerton FullertonCA United States

Despite national efforts in increasing representation of minority students in STEM disciplines, disparities prevail. Hispanics account for 17.4% of the U.S. population, and nearly 20% of the youth population (21 years and below) in the U.S. is Hispanic, yet they account for just 7% of the STEM workforce. To tackle these challenges, the National Science Foundation (NSF) has granted a 5-year project - ASSURE-US, that seeks to improve undergraduate education in engineering and computer Science (ECS) at California State University, Fullerton. The project seeks to advance student success during the first two years of college for ECS students. Towards that goal, the project incorporates a very diverse set of approaches, such as socio-cultural and academic interventions. Multiple strategies including developing early intervention strategies in gateway STEM courses, creating a nurturing faculty-student interaction and collaborative learning environment, providing relevant, contextual-based learning experiences, integrating project-based learning with engineering design in lower-division courses, exposing lower-division students to research to sustain student interests, and helping students develop career-readiness skills. The project also seeks to develop an understanding of the personal, social, cognitive, and contextual factors contributing to student persistence in STEM learning that can be used by STEM faculty to improve their pedagogical and student-interaction approaches. This paper summarizes the major approaches the ASSURE-US project plans to implement to reduce the achievement gap and motivate ECS students to remain in the program. Preliminary findings from the first-year implementation of the project including pre- and post- data were collected and analyzed from about one hundred freshmen and sophomore ECS students regarding their academic experience in lower-division classes and their feedback for various social support events held by the ASSURE-US project during

关键词： Students

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Quantum Logic Enhanced Sensing in Solid-State Spin Ensembles

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Physical Review Letters 2023年第10期131卷 100801-100801页

作者： Nithya Arunkumar Kevin S. Olsson Jner Tzern Oon Connor A. Hart Dominik B. Bucher David R. Glenn Mikhail D. Lukin Hongkun Park Donhee Ham Ronald L. Walsworth Department of Physics Harvard University Cambridge Massachusetts 02138 USA John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts 02138 USA Quantum Technology Center University of Maryland College Park Maryland 20742 USA Department of Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA Intelligence Community Postdoctoral Research Fellowship Program University of Maryland College Park Maryland 20742 USA Department of Physics University of Maryland College Park Maryland 20742 USA Department of Chemistry Technical University of Munich Lichtenbergstraße 4 85748 Garching Germany Department of Chemistry and Chemical Biology Harvard University Cambridge Massachusetts 02138 USA

We demonstrate quantum logic enhanced sensitivity for a macroscopic ensemble of solid-state, hybrid two-qubit sensors. We achieve over a factor of 30 improvement in the single-shot signal-to-noise ratio, translating to an ac magnetic field sensitivity enhancement exceeding an order of magnitude for time-averaged measurements. Using the electronic spins of nitrogen vacancy (NV) centers in diamond as sensors, we leverage the on-site nitrogen nuclear spins of the NV centers as memory qubits, in combination with homogeneous and stable bias and control fields, ensuring that all of the ∼109 two-qubit sensors are sufficiently identical to permit global control of the NV ensemble spin states. We find quantum logic sensitivity enhancement for multiple measurement protocols with varying optimal sensing intervals, including XY8 and DROID-60 dynamical decoupling, as well as correlation spectroscopy, using an applied ac magnetic field signal. The results are independent of the nature of the target signal and broadly applicable to measurements using NV centers and other solid-state spin ensembles. This work provides a benchmark for macroscopic ensembles of quantum sensors that employ quantum logic or quantum error correction algorithms for enhanced sensitivity.

关键词： NV centers Nuclear & electron resonance Quantum memories Quantum metrology Quantum sensing

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Comparison design of electric motorcycles using hybrid systems (BLDC motor) on 150Cc motorcycles based on parameter testing

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AIP Conference Proceedings 2023年第1期2592卷

作者： Pawenary S. Azzahra Hastuti Azis H. Andre A. S. Prabuwono Electrical Technology Study Program Faculty of Electricity and Renewable Energy PLN Institute of Technology Jakarta Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Andalas Padang Indonesia Rabigh Faculty of Computer and Information Technology (FCITR) King Abdulaziz University Jeddah Saudi Arabiaa

This study aims to know the comparison design of electric motorcycle using hybrid systems (BLDC Motor) based on parameter testing, i.e., with and without load. The design of electric motorcycles is centered on determining a feasibility study comparing engine drive with electric drive. Electric vehicles are the answer to decreasing petroleum supplies and environmental concerns that are worsening every year due to oil-fueled cars’ exhaust emissions. The proportion of motor vehicle exhaust as an air pollution source is between 60 and 70 percent. The global decrease of fossil fuels is also a critical issue that has yet to be handled. A descriptive statistic methodology was employed in this work as an analytical tool. The results showed when the speed increases, the efficiency of the BLDC motor would increase; this is, of course, following the principle of Orsted’s law and Lorentz force. When compared to the no-load test, the efficiency by using the load will be greater because when the BLDC motor works with a load, it will require greater torque due to an increase in load so that it takes a large amount of power so that it will increase the efficiency of the BLDC motor. When compared in terms of using the battery, the time of using the battery with no load will be longer because it does not require too much current.

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Development of automatic rice plant pest detection system based on convolutional neural network

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AIP Conference Proceedings 2023年第1期2482卷

作者： Matthew Sjarah Winda Astuti Lie Zener Ari Fadli 1)Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia 11480 2)Electrical Departement Faculty of Engineering Jenderal Soedirman University Purwokerto Jawa Tengah Indonesia 53122

Rice is the most important food crop in Indonesia, one of the plants that is quite significant and as a daily staple food for the people of Indonesia. The Indonesia government through the ministry of Agriculture tries to maintain the rice production by maintaining of the rice field. One the challenging situation that can involve the rice production is pest. Pests became one of the reasons which can reduce rice production. The decrease in rice production due to pest attack is an important problem in rice plant care. In this work, a pest detection system in rice plants developed using an intelligent system technique. The system involved image processing and intelligent technique. The system recognizes the kind of pests of the rice plant based on the feature of the image of the pets. Rice plant pest detection systems based on the pest image proceed by image procession technique and Convolution Neural Network (CNN). The system is working properly, since it resulting the training and testing accuracy of 99% and 90%, respectively.

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Dynamic nitrogen vacancy magnetometry by single-shot optical streaking microscopy

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Photonics Research 2022年第9期10卷 2147-2156页

作者： MARK A.KEPPLER ZACHARY A.STEELMAN ZACHARY N.COKER MILOŠNESLÁDEK PHILIP R.HEMMER VLADISLAV V.YAKOVLEV JOEL N.BIXLER Department of Biomedical Engineering Texas A&M UniversityCollege StationTexas 77843USA SAIC JBSA Fort Sam HoustonTexas 78234USA National Research Council Research Associateship Program WashingtonDC 20001USA IMOMEC Division IMECB-3590 DiepenbeekBelgium Institute for Materials Research(IMO) Hasselt UniversityB-3590 DiepenbeekBelgium Czech Technical University in Prague 27201 KladnoCzech Republic Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTexas 77843USA Bioeffects Division Airman System DirectorateAir Force Research LaboratoryJBSA Fort Sam HoustonTexas 78234USA

Nitrogen vacancy diamonds have emerged as sensitive solid-state magnetic field sensors capable of producing diffraction limited and sub-diffraction field ***,for the first time,to our knowledge,we extend those measurements to high-speed imaging,which can be readily applied to analyze currents and magnetic field dynamics in circuits on a microscopic *** overcome detector acquisition rate limitations,we designed an optical streaking nitrogen vacancy microscope to acquire two-dimensional spatiotemporal *** demonstrate magnetic field wave imaging with micro-scale spatial extent and~400μs temporal *** validating this system,we detected magnetic fields down to 10μT for 40 Hz magnetic fields using single-shot imaging and captured the spatial transit of an electromagnetic needle at streak rates as high as 110μm/*** design has the capability to be readily extended to full 3D video acquisition by utilizing compressed sensing techniques and a potential for further improvement of spatial resolution,acquisition speed,and *** device opens opportunities to many potential applications where transient magnetic events can be isolated to a single spatial axis,such as acquiring spatially propagating action potentials for brain imaging and remotely interrogating integrated circuits.

关键词： vacancy utilizing overcome

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Non-Hermitian selective thermal emitter for thermophotovoltaics

npj Nanophotonics

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npj Nanophotonics 2024年第1期1卷 1-6页

作者： Ciril Samuel Prasad Gururaj V. Naik Applied Physics Graduate Program Smalley-Curl Institute Rice University 6100 Main Street Houston 77005 TX USA Electrical & Computer Engineering Rice University 6100 Main Street Houston 77005 TX USA

For a sustainable future, efficient, compact, and solid-state energy converters are critical. Thermophotovoltaics (TPV)—a solid-state scheme to convert heat into electricity—is promising for thermal storage and generation1. TPV systems employing selective thermal emitters allow compact designs for various terrestrial and space applications and, hence, have garnered much attention. Despite significant research efforts, these systems have low efficiency. The selective thermal emitter and the low-bandgap photovoltaic cell contribute to this problem. Here, we solve the shortcomings of the thermal emitter by using a novel approach inspired by non-Hermitian optics. We demonstrate a hybrid metal-dielectric non-Hermitian selective emitter (NHE) with high spectral efficiency (> 60%) and employ the NHE in a TPV system operating at 1273 K. We show that a maximum TPV conversion efficiency of 12% is possible at 1273 K, though our preliminary experiments employing an uncooled PV cell showed a much lower efficiency.

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Correction: Unbiased and multilevel methods for a class of diffusions partially observed via marked point processes

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Statistics and Computing 2024年第6期34卷 1-1页

作者： Alvarez, Miguel Jasra, Ajay Ruzayqat, Hamza Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia School of Data Science The Chinese University of Hong Kong Shenzhen China

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Hybridization of colloidal handlebodies with singular defects and topological solitons in chiral liquid crystals

arXiv

引用

arXiv 2025年

作者： Lee, Jun-Yong Kumari, Asha Yuan, Ye Tasinkevych, Mykola Smalyukh, Ivan I. International Institute for Sustainability with Knotted Chiral Meta Matter Hiroshima University 1-3-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8526 Japan Department of Physics and Mathematics School of Science and Technology Nottingham Trent University Clifton Lane NottinghamNG11 8NS United Kingdom Department of Physics University of Colorado BoulderCO80309 United States Department of Electrical Computer and Energy Engineering Materials Science and Engineering Program and Soft Materials Research Center University of Colorado BoulderCO80309 United States Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado BoulderCO80309 United States

Topology can manifest itself in colloids when quantified by invariants like Euler characteristics of nonzero-genus colloidal surfaces, albeit spherical colloidal particles are most often studied, and colloidal particles with complex topology are rarely considered. On the other hand, singular defects and topological solitons often define the physical behavior of the molecular alignment director fields in liquid crystals. Interestingly, nematic liquid crystalline dispersions of colloidal particles allow for probing the interplay between topologies of surfaces and fields, but only a limited number of such cases have been explored so far. Here, we study the hybridization of topological solitons, singular defects, and topologically nontrivial colloidal particles with the genus of surfaces different from zero in a chiral nematic liquid crystal phase. Hybridization occurs when distortions separately induced by colloidal particles and LC solitons overlap, leading to energy minimization-driven redistribution of director field deformations and defects. As a result, hybrid director configurations emerge, combining topological features from both components. We uncover a host of director field configurations complying with topological theorems, which can be controlled by applying electric fields. Rotational and translational dynamics arise due to the nonreciprocal evolution of the director fields in response to alternating electric fields of different frequencies. These findings help define a platform for controlling topologically hyper-complex colloidal structures and dynamics with electrically reconfigurable singular defects and topological solitons induced by colloidal handlebodies. Copyright © 2025, The Authors. All rights reserved.

关键词： Topology

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