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Crack Catcher AI — Enabling Smart Fracture Mechanics Approach for Damage Control in Thin Silicon Wafers for 3D Semiconductor Integrated Devices/Packages

Crack Catcher AI — Enabling Smart Fracture Mechanics Approa...

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Annual International Symposium on Reliability Physics

作者： Gabriel Preston Greer Gonzolez Andrea S. Karnyoto Fitya S. Mozar Matthew M. Henry Mahmud Isnan Kuncahyo S. Nugroho Henry Candra Muhamad Doris Dianing N. N. Putri Tyas K Sari Bens Pardamean Endang Djuana Derrric Speaks Arief S. Budiman Oregon Renewable Energy Center (OREC) Oregon Institute of Technology (Oregon Tech) Klamath Falls OR USA Dept. of Manufacturing & Mechanical Eng. & Tech. (MMET) Oregon Institute of Technology Klamath Falls OR USA Bioinformatics & Data Science Research Center (BDSRC) Bina Nusantara University Jakarta Indonesia Computer Sci. Dept. BINUS Grad. Program - Master of Computer Sci. Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Center for Artificial Intelligence and Advanced Technology (CAPTIVATE) Universitas TRISAKTI Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Universitas TRISAKTI Jakarta Indonesia Industrial Eng. Dept. BINUS Grad. Program – Master of Industrial Eng. Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331504779

ISBN: (纸本)9798331504786

The importance of silicon cannot be undermined - in photovoltaics (PV) as well as in semiconductor industries. However, silicon is very brittle. Silicon cells/wafers crack easily during manufacturing assembly and/or during device operations. Crack Catcher AI uses novel smart fracture mechanics approach with Artificial Intelligence (AI) methodologies to predict and control crack/damage evolution in thin silicon cells/wafers. This is critical as semiconductor 3D integration technology calls for wafer-to-wafer bonding with utmost alignment accuracy and yield/reliability.

关键词： Semiconductor device measurement Three-dimensional displays Accuracy Semiconductor device reliability Silicon Artificial intelligence Bonding Stress Three-dimensional integrated circuits Stress measurement

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Landau Polaritons in a Full-Dielectric Three-Dimensional Photonic-Crystal Cavity

Landau Polaritons in a Full-Dielectric Three-Dimensional Pho...

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CLEO: Science and Innovations, S and I 2022

作者： Tay, Fuyang Mojibpour, Ali Liang, Shuang Baydin, Andrey Ahmadivand, Arash Peraca, Nicolas Marquez Xu, Hongjing Gardner, Geoff C. Manfra, Michael J. Hagenmüller, David Kono, Junichiro Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Physics and Astronomy Purdue University West LafayetteIN47907 United States Birck Nanotechnology Center Purdue University West LafayetteIN47907 United States Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States Microsoft Quantum Purdue Purdue University West LafayetteIN47907 United States School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States School of Materials Engineering Purdue University West LafayetteIN47907 United States Université de Strasbourg CNRS Strasbourg67000 France Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

ISBN: (纸本)9781557528209

We fabricated a full-dielectric three-dimensional photonic-crystal cavity containing an ultrahigh-mobility two-dimensional electron gas. By applying a strong perpendicular magnetic field, we created Landau polaritons originating from the ultrastrong coupling of electrons with cavity modes. © Optica Publishing Group 2022, © 2022 The Author(s)

关键词： Polariton

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Photon avalanche-driven multicolor emission: yttrium vanadate upconversion phosphors for optical thermometry, forensics, and healing light applications

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Chemical engineering Journal 2025年 516卷

作者： Pavitra, Eluri Antony, Lintymol Park, Jin Young Hwang, Seung Kyu Lee, Jeong-Hwan Chandra, Gogineni Rajesh Basaveswara Rao, M.V. Raju, Ganji Seeta Rama Han, Young-Kyu Huh, Yun Suk NanoBio High-Tech Materials Research Center Department of Biological Sciences and Bioengineering Inha University Incheon22212 Korea Republic of 3D Convergence Center Inha University Incheon22212 Korea Republic of Department of Energy and Materials Engineering Dongguk University-Seoul Seoul04620 Korea Republic of Department of Electrical Electronics and Software Engineering Pukyong National University Yongdang Campus Busan48547 Korea Republic of Department of Materials Science and Engineering Inha University Incheon22212 Korea Republic of Program in Semiconductor Convergence Inha University Incheon22212 Korea Republic of Department of Computer Science and Engineering Vignan's Lara Institute of Technology & Science Andhra Pradesh Guntur India Department of Chemistry Krishna University Andhra Pradesh Machillipatnam521001 India

The exploration of photon upconversion has led to the development of multifunctional lanthanide-based materials, particularly through the mechanism of photon avalanche, marking a transformative advancement in material science. In this study, yttrium vanadate upconversion nanocrystalline phosphors (UCNCPs) activated by Ho3+/Er3+/Tm3+/Yb3+ ions are reported. These UCNCPs demonstrate a remarkable ability in the photon avalanche, offering highly intense and tunable emissions across the visible spectrum at room temperature under low excitation power of 980 nm laser. The average number of photons involved in the UC process at threshold pump power, highlighting the intricate interplay of cross-relaxation and energy transfer loops in avalanche mechanism. Notably, these UCNCPs have shown exceptional temperature sensing capabilities, where non-thermally coupled levels of the Ho3+ and Tm3+ ions provide higher relative sensitivity and accuracy than thermally coupled levels of Er3+ ions. The versatility of these UCNCPs is further established by their application in solid-state lighting, where they can produce vibrant red, green, blue, and warm-white light, and in security, serving as multi-level anti-counterfeiting inks that respond to 980 nm laser illumination. These developments not only pave the way for more energy-efficient lighting solutions but also offer new avenues for enhancing the security of valuable items. The temperature sensing capabilities of these phosphors add another layer of functionality, making them ideal for high-tech applications ranging from medical diagnostics to environmental monitoring. © 2025 Elsevier B.V.

关键词： Phosphors

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Deep Learning with Greedy Layer-Wise Compound Scaling for Temperature and Humidity Prediction in Solar Dryer Dome

SSRN

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SSRN 2022年

作者： Cenggoro, Tjeng Wawan Elwirehardja, Gregorius Natanael Dominic, Nicholas Setiawan, Karli Eka Rahutomo, Reza Djuana, Endang Gunawan, Fergyanto E. Budiman, Arief S. Romeli, Sugiarto Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Department of Manufacturing and Mechanical Engineering and Technology Oregon Institute of Technology Klamath FallsOR97601 United States PT. Impack Pratama Industri Jakarta Indonesia

Drying has been an eco-friendly and cost-efficient method to reduce post-harvest losses of agricultural crops. In various countries, the technique has been widely utilized in the form of Solar Dryer Dome (SDD) buildings. Accurate indoor microclimate forecasting is very important to implement smart control systems in SDDs that can maintain the ideal conditions, as the availability of solar energy is limited only at daytimes and the temperature may drop significantly during nighttimes in remote areas. The microclimate variables that play an important role in maintaining ideal environmental conditions include temperature and relative humidity. © 2022, The Authors. All rights reserved.

关键词： Forecasting

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Observation of Photonic Chiral Flatbands

arXiv

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arXiv 2024年

作者： Choi, Minho Alù, Andrea Majumdar, Arka Department of Electrical and Computer Engineering University of Washington SeattleWA98195 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10031 United States Department of Physics University of Washington SeattleWA98195 United States

Distinct selectivity to the spin angular momenta of photons have garnered significant attention in recent years, for their relevance in basic science and for imaging and sensing applications. While nonlocal metasurfaces with strong chiral responses to the incident light have been reported, these responses are typically limited to a narrow range of incident angles. In this study, we demonstrate a nonlocal metasurface that showcases strong chirality, characterized by circular dichroism larger than 0.6, over a wide range of incident angles ±5o. Its quality factor, circular dichroism and resonant frequency can be optimized by design. These findings pave the way to further advance the development of valley-selective optical cavities and augmented reality applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Natural frequencies

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Smartphone sensing of multiple heavy metal ion contaminants in drinking water

Smartphone sensing of multiple heavy metal ion contaminants ...

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Optics and Photonics for Sensing the Environment, ES 2020 - Part of Optical Sensors and Sensing Congress 2020

作者： Nguyen, Hoang Misbah, Ibrahim Shih, Wei-Chuan Department of Electrical and Computer Engineering University of Houston 4800 Calhoun Rd HoustonTX77204 United States Program of Materials Science and Engineering University of Houston 4800 Calhoun Rd HoustonTX77204 United States

We report an array-based smartphone sensor for multiplex detection and quantitation of lead and mercury ions in drinking water without the addition of any solution reagent. The detection limits for lead and mercury ar... 详细信息

ISBN: (纸本)9781557528209

关键词： Potable water

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Metamaterial assisted speckle illumination nanoscopy for high-resolution biological imaging

Metamaterial assisted speckle illumination nanoscopy for hig...

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Novel Techniques in Microscopy, NTM 2021 - Part of Biophotonics Congress: Optics in the Life Sciences 2021

作者： Zhao, Junxiang Lee, Yeon Ui Ma, Qian Khorashad, Larousse Khosravi Posner, Clara Li, Guangru Wisna, Bimananda G.M. Burns, Zachary Zhang, Jin Liu, Zhaowei Department of Electrical and Computer Engineering University of California San Diego 9500 Gilman Drive San diegoCA92093 United States Department of Pharmacology University of California San Diego 9500 Gilman Drive San diegoCA92093 United States Material Science and Engineering Program University of California San Diego 9500 Gilman Drive San diegoCA92093 United States

We developed a wide field of view super resolution microscopy technology, i.e. speckle metamaterial-assisted illumination nanoscopy (speckle-MAIN), showing biological imaging with resolution down to 40nm. © 2021 ... 详细信息

ISBN: (纸本)9781557528209

关键词： Metamaterials

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A Conceptual Exploration of Generative AI-Induced Cognitive Dissonance and its Emergence in University-Level Academic Writing

arXiv

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arXiv 2025年

作者： Seran, Carl Errol Tan, Myles Joshua Toledo Karim, Hezerul Abdul AlDahoul, Nouar Biology Program College of Arts and Sciences University of St. La Salle Bacolod Philippines Department of Natural Sciences College of Arts and Sciences University of St. La Salle Bacolod Philippines Faculty of Education University of the Philippines Open University Los Baños Philippines Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Department of Epidemiology College of Public Health and Health Professions College of Medicine University of Florida GainesvilleFL United States Department of Chemical Engineering College of Engineering and Technology University of St. La Salle Bacolod Philippines Department of Electronics Engineering College of Engineering and Technology University of St. La Salle Bacolod Philippines Yo-Vivo Corporation Bacolod Philippines Faculty of Engineering Multimedia University Persiaran Multimedia Cyberjaya Malaysia Department of Computer Science Division of Science New York University Abu Dhabi Abu Dhabi United Arab Emirates

The integration of Generative Artificial Intelligence (GenAI) intouniversity-level academic writing presents both opportunities and challenges,particularly in relation to cognitive dissonance (CD). This work explores howGenAI serves as both a trigger and amplifier of CD, as students navigateethical concerns, academic integrity, and self-efficacy in their writingpractices. By synthesizing empirical evidence and theoretical insights, weintroduce a hypothetical construct of GenAI-induced CD, illustrating thepsychological tension between AI-driven efficiency and the principles oforiginality, effort, and intellectual ownership. We further discuss strategiesto mitigate this dissonance, including reflective pedagogy, AI literacyprograms, transparency in GenAI use, and discipline-specific task *** approaches reinforce critical engagement with AI, fostering a balancedperspective that integrates technological advancements while safeguarding humancreativity and learning. Our findings contribute to ongoing discussions on AIin education, self-regulated learning, and ethical AI use, offering aconceptual framework for institutions to develop guidelines that align AIadoption with academic values. © 2025, CC BY.

关键词： Generative adversarial networks

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Fault Diagnosis of Wind Energy Conversion Systems Using Gaussian Process Regression-based Multi-Class Random Forest

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IFAC-PapersOnLine 2022年第6期55卷 127-132页

作者： Majdi Mansouri Radhia Fezai Mohamed Trabelsi Hajji Mansour Hazem Nounou Mohamed Nounou Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Department of Mathematics and Sciences Prince Sultan University Riyadh 11586 Saudi Arabia Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir 5019 Tunisia Electronic and Communications Engineering Department Kuwait College of Science and Technology P. O. Box 27235 Kuwait Higher Institute of Applied Science and Technology of Kasserine University of Kairouan PO Box 471 1200 Kasserine Tunisia Chemical Engineering Program Texas A&M University at Qatar Doha Qatar

This work proposes a new fault diagnosis approach for a wind energy conversion (WEC) system. The proposed technique merges the benefits of feature extraction based on Gaussian Process Regression (GPR) and Multi-Class Random Forest (MCRF)-based fault classification where instances are classified into one or more classes. In the developed GPR-MCRF approach, the nonlinear statistical features including the mean vector M GPR and the variance matrix C GPR are computed using the GPR model with aim of extracting the most relevant features from the WEC system. Then, these features are introduced to the RF classifier for classification and diagnosis purposes. Therefore, the application of the GPR-MCRF technique for WEC systems aims to enhance the use of the classical raw data-based MCRF and diagnosis accuracy. Three kinds of faults (wear-out, open-circuit, and short-circuit faults) are considered in this work. Different case studies are investigated in order to illustrate the effectiveness and robustness of the developed technique compared to the state-of-the-art methods. The obtained results show that the the developed GPR-MCRF technique is an effective feature extraction and fault diagnosis technique for WEC systems.

关键词： Random Forest (RF) Multi-Class Gaussian Process Regression (GPR) Fault Diagnosis Wind Energy Conversion Systems

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Application of Deep Artificial Neural Network to Model Characteristic Fluctuation of Multi-Channel Gate-All-Around Silicon Nanosheet and Nanofin MOSFETs Induced by Random Nanosized Metal Grains

Application of Deep Artificial Neural Network to Model Chara...

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IEEE Electron Devices Technology and Manufacturing Conference (EDTM)

作者： Sagarika Dash Yiming Li Wen-Li Sung Parallel and Scientific Computing Laboratory National Yang-Ming Chiao Tung University Hsinchu Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang-Ming Chiao Tung University Hsinchu Taiwan Institute of Communications Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Department of Electronics and Electrical Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Institute of Biomedical Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Center for mm Wave Smart Radar System and Technologies National Yang-Ming Chiao Tung University Hsinchu Taiwan

In this work, we propose a deep artificial neural network (D-ANN) to estimate the work function fluctuation (WKF) on 4-channel stacked gate-all-around (GAA) silicon (Si) nanosheet (NS) and nanofin (NF) MOSFET devices for the first time. The 2-layered simple deep model can well predict the transfer characteristics for both NS/NF FET with a large number of (128) input features, utilizing considerably lesser (1100 samples) data uniformly. The resultant model is evaluated by the $\mathrm{R}^{2}$ score and RMSE to witness its competency and the average error is $< 4\%$ . We do also discuss the circuit simulation possibility by applying the ANN approach.

关键词： Semiconductor device modeling MOSFET Gallium arsenide Artificial neural networks Predictive models Logic gates Silicon

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