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Advanced technologies in InGaN micro-LED fabrication to mitigate the sidewall effect

光：科学与应用（英文版） 2025年第2期14卷 307-332页

作者： Zhiyuan Liu Haicheng Cao Xiao Tang Tingang Liu Yi Lu Zixian Jiang Na Xiao Xiaohang Li Advanced Semiconductor Laboratory Electrical and Computer Engineering ProgramCEMSE DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia

The size of InGaN micro-LEDs is continuously decreasing to meet the demands of various emerging applications,especially in tiny micro-displays such as AR/***,the conventional pixel definition based on plasma etching significantly damages the mesa sidewalls,leading to a severe reduction in efficiency as the micro-LED size *** seriously impedes the development and application of *** this work,we comprehensively explain the origin of micro-LED sidewall effects and corresponding physical ***,we systematically review recent progress in micro-LED fabrication aiming at suppressing sidewall ***,we discuss advancements in micro-LED fabrication with"damage-free"techniques,which hold the potential to fundamentally address the issue of plasma damage in the micro-LED *** believe this review will deepen the understanding of micro-LED sidewall effects and provide a better insight into the latest associated fabrication technologies for high-efficient InGaN micro-LEDs.

关键词： technologies micro-led advanced ingan effect fabrication mitigate sidewall

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CNN-based multiplexed optical fiber sensors for multi-load mapping on 2D structures

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Optical Fiber Technology 2025年 93卷

作者： de Carvalho, Vinicius Martins, Victor Hugo Flores, Walter Oswaldo C. Muller, Marcia Fabris, José Luís Lazzaretti, André Eugenio UTFPR Graduate Program in Electrical and Computer Engineering Av. Sete de Setembro 3165 Paraná Curitiba80230-901 Brazil

This paper reports the application of a Convolutional Neural Network specifically designed for one-dimensional optical signal processing to determine the magnitude and position of loads acting on a structure instrumented with multiplexed macrobend optical fiber sensors, offering a cost-effective and low complexity alternative for force monitoring solutions. The system effectively localized and quantified one, two, or three simultaneous loads within 16 distinct sensing areas, utilizing only five in-series optical fiber sensors, which were spectrally interrogated in transmission mode. The monitored loads ranged from 1000 to 2000 gf. The use of the Huber loss function allows the model to adaptively predict values associated with regions with or without loads. Experimental results showed an average mean absolute error of 224±65 gf during testing. By applying a straightforward post-processing method for load presence detection in each region, the system achieved average F1 scores ranging from 0.84 to 0.93 across the monitored regions, and an average Hamming score of 0.93. These findings demonstrate the system's effectiveness in monitoring multiple loads, underscoring the potential of optical fiber sensors and CNNs in sensing applications. © 2025 Elsevier Inc.

关键词： Convolutional neural network Load mapping Macrobend sensor Optical fiber sensor

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Heralded optical entanglement distribution via lossy quantum channels: a comparative study

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Optics Express 2025年第6期33卷 12459-12474页

作者： Zo, Wan Chin, Seungbeom Kim, Yong-Su Seoul02792 Korea Republic of Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Okinawa Institute of Science and Technology Graduate University Okinawa904-0495 Japan Division of Quantum Information Korea University of Science and Technology KIST School Seoul02792 Korea Republic of

Quantum entanglement serves as a foundational resource for various quantum technologies. In optical systems, entanglement distribution relies on the indistinguishability and spatial overlap of photons. Heralded schemes play a crucial role in ensuring the reliability of entanglement generation by detecting ancillary photons to signal the creation of desired entangled states. However, photon losses in quantum channels remain a significant challenge, limiting the distance and capacity of entanglement distributions. This study suggests three heralded schemes for distributing multipartite Greenberger-Horne-Zeilinger (GHZ) states via lossy quantum channels. These schemes differ both qualitatively in their network architecture (centralized or decentralized) and photon source requirements (Bell states or single-photons), and quantitatively in their success probabilities and heralding efficiency. Through comprehensive analysis incorporating both practical implementation considerations and theoretical performance metrics, we find that each scheme offers distinct advantages depending on the number of parties, channel distance, and security requirements. The decentralized scheme proves particularly advantageous for networks requiring balanced information distribution, while centralized schemes may offer better performance for smaller networks. This analysis provides insights into designing resilient heralded circuits for quantum information processing over lossy channels, considering both architectural constraints and performance requirements. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Quantum channel

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Degradation of Organic LEDs Characterized with Algebraic Decay Relaxation Function

Degradation of Organic LEDs Characterized with Algebraic Dec...

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Advances in Display Technologies XV 2025

作者： Aygen, Can Richards, Michael Yazdaanpanah, Ramin Kulkarni, Sachin Tanriover, Ibrahim Onsager, Claire Lin, BoYen Lee, Jiun-Haw Aydin, Koray Grayson, Matthew A. Department of Electrical & Computer Engineering Northwestern University EvanstonIL United States Department of Opto-Electronic Engineering National Dong Hwa University Hualien Taiwan Graduate Institute of Photonics and Optoelectronics Department of Electrical Engineering National Taiwan University Taipei Taiwan Program in Applied Physics Northwestern University EvanstonIL United States

ISBN: (纸本)9781510685246

Lifetime studies of organic light emitting diodes are necessary to both understand and mitigate causes of degradation. Here, electroluminescence (EL) studies of green organic light-emitting diode (OLED) pixels are measured continuously using three different dc currents over a period of one week, and their slow EL degradation is accurately fit to an analytical expression with only two fit parameters. The slower-than-exponential EL decay is fit to an empirical unified heavy-tail function that can interpolate between power-law algebraic decays (AD) and stretched-exponential decays (SE). Whereas SE and AD are largely indistinguishable down to 50% of the initial luminance, here we report degradation down to 10% of the initial luminance which most closely fits an AD function with remarkable precision over the entire duration of the experiment. All relaxations share the same characteristic exponent β = 0.53 in the power law decay, whereas the characteristic time-scale τ for degradation decreases with a power-law exponent B = 1.9 as the current increases. The high degree of accuracy in the fit allows asymptotic predictions at time scales that are orders of magnitude longer than the duration of the data collection. The voltage across the OLED is simultaneously monitored under constant-current degradation and reveals an early-onset time scale where the voltage reaches a minimum before degradation runoff. © 2025 SPIE.

关键词： Organic light emitting diodes (OLED)

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A Design Study on Integrated Complex Coefficient Filters with Peripheral Circuits for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2025年第1期145卷 16-24页

作者： Shouno, Kazuhiro Sato, Lina Fukagawa, Kanta Tanimoto, Hiroshi Muto, Cosy Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan

This paper proposes a measurement technique for an integrated complex filter. The proposed method is based on two measurement methods with integrated circuitry for calibration. It is accomplished by applying square waves to an FUT (Filter Under Test) instead of sinusoidal waves or by superposing transfer characteristics obtained by applying a single sinusoidal wave to an FUT. In both of the above methods, the output signal connected to the external measurement equipment via a 50 Ω coaxial cable and so on. In this case, the output signal of the FUT should be amplified by internal or external amplifiers, which degrades the response. However, it is cancelled out by the proposed calibration circuitry with some analog switches. In addition to the above, for the RC polyphase filter, the source resistance and the load capacitance degrade the measurement results and their effect is discussed. The validity of the proposal is confirmed through computer simulation for a third-order RCPF whose passband is 8–40 MHz fabricated by Phenitec 0.6 µm CMOS process. It is shown that the measurement error is −1.10 dB for the square-wave method and −1.00 dB and −0.43 degrees for the superposition method at 40 MHz. © 2025 The Institute of electrical Engineers of Japan.

关键词： Capacitance

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Reward invigorates isometric gripping actions

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Journal of Neurophysiology 2025年第4期133卷 1282-1294页

作者： Marbaker, Rachel M. Schmad, Ryan C. Al-Ghamdi, Razan A. Sukumar, Shruthi Ahmed, Alaa A. Department of Mechanical Engineering University of Colorado Boulder Boulder CO United States Department of Electrical Engineering University of Colorado Boulder Boulder CO United States Department of Computer Science University of Colorado Boulder Boulder CO United States Biomedical Engineering Program University of Colorado Boulder Boulder CO United States

Individuals exhibit a propensity to move faster toward more rewarding stimuli. Although this phenomenon has been observed in movements, the effect of reward on implicit control of isometric actions, such as gripping or grasping, is relatively unknown. How reward-related invigoration generalizes to other effortful actions is an important question. Reward invigorates reaching movements and saccades, supporting the idea that reward pays the additional effort cost of moving faster. Effort in isometric force generation is less understood, so here we ask whether and how reward-related invigoration generalizes to isometric force gripping. And if so, what implicit characteristics of gripping change when there is a prospect of reward? Participants (n = 19) gripped a force transducer and the force applied was mapped to radial position of an onscreen cursor. Each trial, a target appeared in one of four locations;increasing grip force moved the cursor toward the target. The gripping action was interchangeable for all target positions. In each block of 100 trials, one target was consistently rewarded, whereas the other targets were not. When gripping to acquire the rewarded target, participants reacted faster, generated force more rapidly and to a greater extent, without increasing variance and without increasing the rising force-time integral. These findings support the generalization of reward-related invigoration in isometric force tasks, and that the brain exquisitely trades-off reward and effort costs to obtain reward more rapidly without increasing variance and without more effort costs than necessary. NEW & NOTEWORTHY Gripping actions are important for day-to-day tasks, for medical diagnostics like strength and force control, and for choice selection in decision-making experiments. Comparing isometric gripping responses to reward and nonreward cues, we observed reward-based invigoration mediated by selective increases in effort. These findings can be leveraged to provide

关键词： decision making effort grasping movement vigor speed-accuracy tradeoff

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Online Learning of Quantum States with Logarithmic Loss via VB-FTRL 36

Online Learning of Quantum States with Logarithmic Loss via ...

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36th International Conference on Algorithmic Learning Theory, ALT 2025

作者： Tseng, Wei-Fu Chen, Kai-Chun Xiao, Zi-Hong Li, Yen-Huan Department of Mathematics National Taiwan University Taiwan Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan School of Medicine National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taiwan Center for Quantum Science and Engineering National Taiwan University Taiwan

Online learning of quantum states with the logarithmic loss (LL-OLQS) is a quantum generalization of online portfolio selection (OPS), a classic open problem in online learning for over three decades. This problem also emerges in designing stochastic optimization algorithms for maximum-likelihood quantum state tomography. Recently, Jézéquel et al. (2022, arXiv:2209.13932) proposed the VB-FTRL algorithm, the first regret-optimal algorithm for OPS with moderate computational complexity. In this paper, we generalize VB-FTRL for LL-OLQS. Let d denote the dimension and T the number of rounds. The generalized algorithm achieves a regret rate of O(d2 log(d + T)) for LL-OLQS. Each iteration of the algorithm consists of solving a semidefinite program that can be implemented in polynomial time by, for example, cutting-plane methods. For comparison, the best-known regret rate for LL-OLQS is currently O(d2 log T), achieved by an exponential weight method. However, no explicit implementation is available for the exponential weight method for LL-OLQS. To facilitate the generalization, we introduce the notion of VB-convexity. VB-convexity is a sufficient condition for the volumetric barrier associated with any function to be convex and is of independent interest. © 2025 W.-F. Tseng, K.-C. Chen, Z.-H. Xiao & Y.-H. Li.

关键词： Stochastic systems

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From Vision to Motion: Translating Large-Scale Knowledge for Data-Scarce IMU Applications

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IEEE Transactions on Mobile Computing 2025年

作者： Yoon, Hyungjun Cha, Hyeongheon Nguyen, Hoang C. Gong, Taesik Lee, Sung-Ju KAIST School of Electrical Engineering Korea Republic of Stony Brook University Department of Computer Science NY United States UNIST Department of Computer Science and Engineering Artificial Intelligence Graduate School Korea Republic of

Pre-training representations acquired via self-supervised learning could achieve high accuracy on even tasks with small training data. Unlike in vision and natural language processing domains, pre-training for IMU-based applications is challenging, as there are few public datasets with sufficient size and diversity to learn generalizable representations. To overcome this problem, we propose IMG2IMU that adapts pre-trained representation from large-scale images to diverse IMU sensing tasks. We convert the sensor data into visually interpretable spectrograms for the model to utilize the knowledge gained from vision. We further present a sensor-aware pre-training method for images that enables models to acquire particularly impactful knowledge for IMU sensing applications. This involves using contrastive learning on our augmentation set customized for the properties of sensor data. Our evaluation with four different IMU sensing tasks shows that IMG2IMU outperforms the baselines pre-trained on sensor data by an average of 9.6%p F1-score, illustrating that vision knowledge can be usefully incorporated into IMU sensing applications where only limited training data is available. © 2002-2012 IEEE.

关键词： Contrastive Learning

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Accelerated Dynamic Event-Triggered Algorithm for Online Power System Optimization by Using Powerball Technique

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IEEE Transactions on Smart Grid 2025年第3期16卷 2348-2360页

作者： Hu, Chuanhao Zhang, Xuan Wu, Qiuwei Central South University School of Transportation Changsha410075 China Tsinghua University Smart Grid and Renewable Energy Laboratory Tsinghua Shenzhen International Graduate School Shenzhen518055 China Queen’s University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT8 5BN United Kingdom

Nowadays, online optimization for power systems has gained increasing attention due to many time-varying scenarios in practical applications. This paper proposes a novel feedback-based online algorithm for power system optimization problems by combining the powerball technique and a dynamic event-triggered mechanism, aiming to achieving a faster convergence rate and high communication efficiency simultaneously. In particular, a measurement-based prima-dual approach is utilized to solve the considered time-varying optimization problem. Taking the constrained resource issue, a more flexible triggering condition with a dynamic threshold is designed for dual variables to reduce communication burden. By further employing the powerball strategy, the primal-dual iteration is modified with an improved convergence rate. Finally, numerical experiments on test systems are conducted to demonstrate the effectiveness of the proposed online algorithm. It is shown that the proposed approach has superior convergence property especially in the initial process. Meanwhile, a better trade-off between the satisfactory system performance and communication resources consumption can be achieved. © 2010-2012 IEEE.

关键词： Optimization algorithms

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A Performance Study of Selected Machine Learning Techniques for Predicting Heart Diseases 2nd

A Performance Study of Selected Machine Learning Techniques ...

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2nd International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications, SITAIBA 2023

作者： Olorunfemi, Blessing Oluwatobi Ogunde, Adewale Opeoluwa Adeniyi, Abidemi Emmanuel Awotunde, Joseph Bamidele Imoize, Agbotiname Lucky Li, Chun-Ta Faculty of Natural Sciences Department of Computer Science Redeemer’s University Osun Nigeria Department of Computer Science Bowen University Iwo Nigeria Faculty of Information and Communication Sciences Department of Computer Science University of Ilorin Ilorin240003 Nigeria Faculty of Engineering Department of Electrical and Electronics Engineering University of Lagos Lagos Akoka100213 Nigeria Bachelor’s Program of Artificial Intelligence and Information Security Fu Jen Catholic University New Taipei City24206 Taiwan

ISBN: (纸本)9789819777853

Heart Disease remains a leading cause of mortality worldwide. It alarmingly rises at a quick rate, making early heart disease prediction crucial for effective prevention and timely intervention. Heart disease diagnosis is a difficult process that requires technical skills and accuracy to complete. With improvements in technology, computing has lent its voice to simplify the diagnosis of various health problems. Machine learning uses past or existing history to predict future results. Various machine learning techniques have been developed over the years and used in predicting heart diseases with various levels of performance. Identifying the best-suited machine learning technique to use for prediction purposes can be a challenging task. This research work analyses the performance of seven (7) machine learning techniques, comprising AdaBoost Algorithm, KNN, Logistic Regression, Naïve Bayes Classifier, Random Forest, SVM, and XGBoost. The heart disease dataset was downloaded from the UCI repository and analysed using Python programming language in the Jupyter Notebook environment. A comparative analysis of the seven (7) techniques was performed based on Accuracy, Precision, and Recall. From the results obtained, KNN, Random Forest, and XGBoost showed superior performance over the others with an accuracy of 100%, AdaBoost Algorithm followed with an accuracy of 92.2%, SVM followed with an accuracy of 91.71%, Naïve Bayes Classifier followed with an accuracy of 88.29% while Logistic Regression has the least accuracy of 86.34%. KNN, RF, and XGBoost outperformed AdaBoost, SVN, and LR. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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