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Conference on Lasers and Electro-Optics (CLEO)

作者： Alexandra Maria Palici Xiyuan Lu Kartik Srinivasan Xinda Lu Fabien Labbe Yunhong Ding Hugo Laroque Ryan Hamerly Carlos Errando-Herranz Minhao Pu Dirk Englund Mikkel Heuck Department of Electrical and Photonics Engineering Technical University of Denmark Lyngby Denmark Microsystems and Nanotechnology Division Physical Measurement Laboratory National Institute of Standards and Technology Gaithersburg Maryland USA Joint Quantum Institute NIST/University of Maryland College Park Maryland USA Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge MA USA Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands

We demonstrate a hybrid device consisting of a thin film lithium niobate membrane transfer-printed onto a silicon nitride ring resonator. We measure quality factors in the 10 5 range at telecom wavelengths.

ISBN: (纸本)9798350369311

关键词： Q-factor Lithium niobate Wavelength measurement Multichip modules Silicon nitride Ring lasers Silicon photonics Telecommunications Optical ring resonators Nonlinear optics

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Interfacial charge and energy transfer in van der Waals heterojunctions

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InfoMat 2022年第3期4卷 64-84页

作者： Zehua Hu Xue Liu Pedro Ludwig Hernandez-Martínez Shishu Zhang Peng Gu Wei Du Weigao Xu Hilmi Volkan Demir Haiyun Liu Qihua Xiong Division of Physics and Applied Physics School of Physical and Mathematical SciencesNanyang Technological UniversitySingaporeSingapore Institutes of Physical Science and Information Technology Anhui UniversityHefeiP.R.China LUMINOUS Center of Excellence for Semiconductor Lighting and DisplaySchool of Electrical and Electronics EngineeringNanyang Technological UniversitySingaporeSingapore State Key Laboratory of Low-Dimensional Quantum Physics Department of PhysicsTsinghua UniversityBeijingP.R.China Beijing Academy of Quantum Information Sciences BeijingP.R.China Institute of Functional Nano and Soft Materials(FUNSOM) Soochow UniversitySuzhouP.R.China Key Laboratory of Mesoscopic Chemistry of MOE School of Chemistry and Chemical EngineeringNanjing UniversityNanjingP.R.China Department of Physics Department of Electrical and Electronics EngineeringUNAM-National Nanotechnology Research Center and Institute of Materials Science and NanotechnologyBilkent UniversityAnkaraTurkey Beijing Innovation Center for Future Chips Tsinghua UniversityBeijingP.R.China

Van der Waals heterojunctions are fast-emerging quantum structures fabricated by the controlled stacking of two-dimensional(2D)*** to the atomically thin thickness,their carrier properties are not only determined by the host material itself,but also defined by the interlayer interactions,including dielectric environment,charge trapping centers,and stacking *** abundant constituents without the limitation of lattice constant matching enable fascinating electrical,optical,and magnetic properties in van der Waals heterojunctions toward next-generation devices in photonics,optoelectronics,and information *** review focuses on the charge and energy transfer processes and their dynamics in transition metal dichalcogenides(TMDCs),a family of quantum materials with strong excitonic effects and unique valley properties,and other related 2D materials such as graphene and hexagonalboron *** the first part,we summarize the ultrafast charge transfer processes in van der Waals heterojunctions,including its experimental evidence and theoretical understanding,the interlayer excitons at the TMDC interfaces,and the hot carrier injection at the graphene/TMDCs *** the second part,the energy transfer,including both Förster and Dexter types,are reviewed from both experimental and theoretical ***,we highlight the typical charge and energy transfer applications in photodetectors and summarize the challenges and opportunities for future development in this field.

关键词： 2-dimensional semiconductors carrier dynamics charge and energy transfer optical spectroscopy optoelectronics

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Parameter Estimation for Partially Observed McKean-Vlasov Diffusions

arXiv

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arXiv 2024年

作者： Jasra, Ajay Maama, Mohamed Tempone, Raul School of Data Science The Chinese University of Hong Kong CN Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Chair of Mathematics for Uncertainty Quantification RWTH Aachen University Aachen52062 Germany

In this article we consider likelihood-based estimation of static parameters for a class of partially observed McKean-Vlasov (POMV) diffusion process with discrete-time observations over a fixed time interval. In particular, using the framework of [5] we develop a new randomized multilevel Monte Carlo method for estimating the parameters, based upon Markovian stochastic approximation methodology. New Markov chain Monte Carlo algorithms for the POMV model are introduced facilitating the application of [5]. We prove, under assumptions, that the expectation of our estimator is biased, but with expected small and controllable bias. Our approach is implemented on several examples. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Spintronic Terahertz Emitters in Silicon-Based Heterostructures

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physical Review Applied 2022年第3期18卷 034056-034056页

作者： Jiayun Liu Kyusup Lee Yingshu Yang Ziqi Li Raghav Sharma Lifei Xi Teddy Salim Chris Boothroyd Yeng Ming Lam Hyunsoo Yang Marco Battiato Elbert E.M. Chia Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link 637371 Singapore Department of Electrical and Computer Engineering National University of Singapore 117576 Singapore School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore

Integration of active elements into silicon wafers is the first step towards their usage in modern electronic devices based on nanometric structures. Spintronic terahertz emitters, typically composed of nanometer-thin magnetic multilayer, have the outstanding capability of producing high-quality, broadband terahertz pulses using extremely simple heterostructures. A question remains on whether an efficient and cheap integration with other silicon-based technologies can be achieved. We show here that simply having a ferromagnetic layer on silicon produces remarkably efficient spintronic terahertz emission despite the low spin-orbit coupling of the individual components. We achieve this by leveraging on the natural formation of silicides at the interface of a transition metal and silicon. The cobalt silicide layer has good spin-to-charge conversion efficiency that reaches around 1/6 as that of the prototypical spintronics THz-emitter heterostructure cobalt/platinum.

关键词： Spintronics Ultrafast magnetic effects Magnetic multilayers Terahertz sources

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Challenges of measuring spin Seebeck noise

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physical Review B 2024年第10期109卷 104429-104429页

作者： Renjie Luo Xuanhan Zhao Tanner J. Legvold Liyang Chen Changjiang Liu Deshun Hong Anand Bhattacharya Douglas Natelson Department of Physics and Astronomy Rice University Houston Texas 77005 USA Applied Physics Program Smalley-Curl Institute Rice University Houston Texas 77005 USA Materials Science Division Argonne National Laboratory Lemont Illinois 60439 USA Department of Electrical and Computer Engineering Rice University Houston Texas 77005 USA Department of Materials Science and NanoEngineering Rice University Houston Texas 77005 USA

Just as electronic shot noise in driven conductors results from the granularity of charge and the statistical variation in the arrival times of charge carriers, there are predictions for fundamental noise in magnon currents due to angular momentum being carried by discrete excitations. The inverse spin Hall effect as a transduction mechanism to convert spin current into charge current raises the prospect of experimental investigations of such magnon shot noise. Spin Seebeck effect measurements have demonstrated the electrical detection of thermally driven magnon currents and have been suggested as an avenue for accessing spin current fluctuations. Using spin Seebeck structures made from yttrium iron garnet on gadolinium gallium garnet, we demonstrate the technical challenges inherent in such noise measurements. While there is a small increase in voltage noise in the inverse spin Hall detector at low temperatures associated with adding a magnetic field, the dependence on field orientation implies that this is not due to magnon shot noise. We describe theoretical predictions for the expected magnitude of magnon shot noise, highlighting ambiguities that exist. Further, we show that magnon shot noise detection through the standard inverse spin Hall approach is likely impossible due to geometric factors. Implications for future attempts to measure magnon shot noise are discussed.

关键词： Spin Seebeck effect Spin current Magnetic insulators Noise measurements

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ENTROPY IS NOT ENOUGH FOR TEST-TIME ADAPTATION: FROM THE PERSPECTIVE OF DISENTANGLED FACTORS

arXiv

引用

arXiv 2024年

作者： Lee, Jonghyun Jung, Dahuin Lee, Saehyung Park, Junsung Shin, Juhyeon Hwang, Uiwon Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Korea Republic of School of Computer Science and Engineering Soongsil University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of Division of Digital Healthcare Yonsei University Korea Republic of AIIS ASRI INMC and ISRC Seoul National University Korea Republic of

Test-time adaptation (TTA) fine-tunes pre-trained deep neural networks for unseen test data. The primary challenge of TTA is limited access to the entire test dataset during online updates, causing error accumulation. To mitigate it, TTA methods have utilized the model output’s entropy as a confidence metric that aims to determine which samples have a lower likelihood of causing error. Through experimental studies, however, we observed the unreliability of entropy as a confidence metric for TTA under biased scenarios and theoretically revealed that it stems from the neglect of the influence of latent disentangled factors of data on predictions. Building upon these findings, we introduce a novel TTA method named Destroy Your Object (DeYO), which leverages a newly proposed confidence metric named Pseudo-Label Probability Difference (PLPD). PLPD quantifies the influence of the shape of an object on prediction by measuring the difference between predictions before and after applying an object-destructive transformation. DeYO consists of sample selection and sample weighting, which employ entropy and PLPD concurrently. For robust adaptation, DeYO prioritizes samples that dominantly incorporate shape information when making predictions. Our extensive experiments demonstrate the consistent superiority of DeYO over baseline methods across various scenarios, including biased and wild. Project page is publicly available at https://***/DeYO/. Copyright © 2024, The Authors. All rights reserved.

关键词： Entropy

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Detecting and Classifying Defective Products in Images Using YOLO

arXiv

引用

arXiv 2024年

作者： Qi, Zhen Ding, Liwei Li, Xiangtian Hu, Jiacheng Lyu, Bin Xiang, Ao Northeastern University Electrical and Computer Engineering Boston United States Florida International University Computer Science Miami United States University of California San Diego Electrical and Computer Engineering San Diego United States Tulane University Business Analytics New Orleans United States Kanazawa University Division of Mathematical and physical sciences Ishikawa Japan Northern Arizona University Information Security and Assurance AZ United States

With the continuous advancement of industrial automation, product quality inspection has become increasingly important in the manufacturing process. Traditional inspection methods, which often rely on manual checks or simple machine vision techniques, suffer from low efficiency and insufficient accuracy. In recent years, deep learning technology, especially the YOLO (You Only Look Once) algorithm, has emerged as a prominent solution in the field of product defect detection due to its efficient real-time detection capabilities and excellent classification performance. This study aims to use the YOLO algorithm to detect and classify defects in product images. By constructing and training a YOLO model, we conducted experiments on multiple industrial product datasets. The results demonstrate that this method can achieve real-time detection while maintaining high detection accuracy, significantly improving the efficiency and accuracy of product quality inspection. This paper further analyzes the advantages and limitations of the YOLO algorithm in practical applications and explores future research directions. Copyright © 2024, The Authors. All rights reserved.

关键词： Inspection

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Binary Grating and Deep Learning for Phase Reconstruction: Enhancing Normal Camera Imaging

Binary Grating and Deep Learning for Phase Reconstruction: E...

引用

IEEE Photonics Conference (IPC)

作者： Redha H. Al Ibrahim Shuiqin Zheng Tien Khee Ng Boon S. Ooi Photonics Laboratory Division of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal Kingdom of Saudi Arabia Full-Stack Photonics Laboratory School of Physical Sciences Great Bay University Dongguan China

This work investigates the use of a binary grating integrated on a camera assisted by deep learning for phase imaging. Holographic images generated by overlapping 4 diffraction orders from the gratings were employed w...

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Monitoring blood pressure through a single hybrid hemodynamic signal with a flexible optoelectronic patch

Device

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Device 2025年

作者： Zhong, Yizhou Zhang, Yongcao Pu, Jing Wustoni, Shofarul Uribe, Johana Lopez-Larrea, Naroa Marks, Adam McCulloch, Iain Mecerreyes, David Baran, Derya Inal, Sahika Organic Bioelectronics Laboratory Biological and Environmental Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Materials Science and Engineering Program (MSE) Physical Sciences and Engineering Division (PSE) KAUST Thuwal 23955-6900 Saudi Arabia POLYMAT University of the Basque Country UPV/EHU Avenida Tolosa 72 Guipuzcoa Donostia-San Sebastian 20018 Spain Department of Chemistry University of Oxford Oxford OX1 3TF United Kingdom Andlinger Center for Energy and the Environment and Department of Electrical and Computer Engineering Princeton University Princeton 08544 NJ United States IKERBASQUE Basque Foundation for Science Plaza Euskadi 5 Bilbao 48009 Spain

Hemodynamics, the study of blood flow and circulatory forces, is fundamental for assessing cardiovascular health, disease states, and therapeutic outcomes. Here, we introduce a skin-conformable organic optoelectronic thin-film patch (ePatch) designed to simultaneously capture electrocardiography (ECG) and photoplethysmography (PPG) signals as a single hybrid signal, named the electrocardio-photoplethysmogram (EC-PPG). The ePatch integrates an organic electrochemical transistor (OECT), an organic photodiode, surface-mounted light-emitting diodes, and electrochemical electrodes on a flexible, skin-conforming substrate. By training deep learning models on the hybrid EC-PPG data, we achieved accurate arterial blood pressure estimations, with mean errors of just 1.69 mmHg for systolic and 0.89 mmHg for diastolic blood pressure, outperforming traditional predictions that rely on individual physiological signals as inputs. Our findings underscore the potential of EC-PPG as a compound hemodynamic signal for AI-driven vital sign monitoring and integrated, solution-processable soft electronics for clinical and point-of-care applications. © 2025 The Authors

关键词： DTI-3: Develop electrocardiography electrophysiology flexible electronics OECT OPD organic electrochemical transistor photoplethysmography wearable electronics

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Dementia Detection by Shopping Refugees Support Robot 2

Dementia Detection by Shopping Refugees Support Robot

引用

2nd IEEE Global Conference on Life sciences and Technologies, LifeTech 2020

作者： Kishimoto, Yuta Arai, Kenichi Imai, Tetsuo Kobayashi, Toru Nagasaki University Computer and Information Science Program Graduate School of Engineering Nagasaki Japan Nagasaki University Division of Electrical Engineering and Computer Science Graduate School of Engineering Nagasaki Japan

ISBN: (纸本)9781728170633

We have developed the Shopping Refugees Support Robot that enables the elderly to order items through Social Networking Service (SNS) by voice conversation without relying on smartphones. This paper proposes a detection method of dementia signs using this Robot. Concretely, deterioration of cognitive function is detected by the evaluation of short-term memory utilizing order history of the Robot. We expect detection of dementia signs on a daily basis without making the elderly person conscious of having a dementia test, by information that only the person knows. We implemented a prototype and confirmed its functional validity. © 2020 IEEE.

关键词： Internet of things

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