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Conference on Lasers and Electro-Optics (CLEO)

作者： Haoning Tang Beicheng Lou Fan Du Guangqi Gao Mingjie Zhang Xueqi Ni Amir Yacoby Yuan Cao Shanhui Fan Eric Mazur School of Engineering and Applied Sciences Harvard University Cambridge MA USA Department of Electrical Engineering and Computer Science University of California at Berkeley Berkeley CA USA National Institute for Materials Science Tsukuba Ibaraki Japan Department of Applied Physics Ginzton Laboratory Stanford University Stanford CA USA

Our MEMS-integrated twistoptics device enables precise control of interlayer gaps and twist angles in photonic crystals, achieving high-accuracy, multidimensional light manipulation with significant potential in recon... 详细信息

ISBN: (纸本)9798350369311

关键词： Nanophotonics Electric potential Photonic crystals Lasers and electrooptics Hypercubes System-on-chip Electro-optical waveguides

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Exploring Shifted Domain Problem within MNIST Dataset

Exploring Shifted Domain Problem within MNIST Dataset

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computer science, Information Technology and engineering (ICCoSITE), International Conference on

作者： Hidayaturrahman Yaya Heryadi Lukas Wayan Suparta Yulyani Arifin Computer Science Department BINUS Graduate Program – Computer Science Bina Nusatara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

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.

关键词： computer science Adaptation models Neural networks Feature extraction Data models Data mining Information technology

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Electronic structure prediction of medium and high entropy alloys across composition space

arXiv

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arXiv 2024年

作者： Pathrudkar, Shashank Taylor, Stephanie Keripale, Abhishek Gangan, Abhijeet Sadashiv Thiagarajan, Ponkrshnan Agarwal, Shivang Marian, Jaime Ghosh, Susanta Banerjee, Amartya S. Department of Mechanical and Aerospace Engineering Michigan Technological University United States Department of Materials Science and Engineering University of California Los AngelesCA90095 United States Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States Center for Artificial Intelligence Michigan Technological University United States

We propose machine learning (ML) models to predict the electron density — the fundamental unknown of a material’s ground state — across the composition space of concentrated alloys. From this, other physical properties can be inferred, enabling accelerated exploration. A significant challenge is that the number of sampled compositions and descriptors required to accurately predict fields like the electron density increases rapidly with species. To address this, we employ Bayesian Active Learning (AL), which minimizes training data requirements by leveraging uncertainty quantification capabilities of Bayesian Neural Networks. Compared to strategic tessellation of the composition space, Bayesian-AL reduces the number of training data points by a factor of 2.5 for ternary (SiGeSn) and 1.7 for quaternary (CrFeCoNi) systems. We also introduce easy-to-optimize, body-attached-frame descriptors, which respect physical symmetries and maintain approximately the same descriptor-vector size as alloy elements increase. Our ML models demonstrate high accuracy and generalizability in predicting both electron density and energy across composition space. © 2024, CC BY.

关键词： Ground state

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electrical Manipulation of Noncollinear Antiferromagnetic State via Orbital Hall Effect

Electrical Manipulation of Noncollinear Antiferromagnetic St...

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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Hang Xie Nan Zhang Yuteng Ma Xin Chen Lin Ke Yihong Wu Department of Electrical and Computer Engineering National University of Singapore Singapore Institute of Materials Research and Engineeringm Agency for Science Technology and Research Singapore National University of Singapore (Chong Qing) Research Institute China

ISBN: (数字)9798350362213

ISBN: (纸本)9798350362220

Orbital Hall effect can induce spin-orbit torque in ferromagnetic heterostructures with similar symmetry as spin Hall effect. Due to its weak dependence on spin-orbit coupling, even light metals like Cr could exhibit robust orbital Hall conductivity and generate comparable spin-orbit torque as heavy metals. In view of this, we study the electrical control of antiferromagnetic state in Mn3Sn/Cr and ferromagnetic state in CoFeB/Cr. We find that Cr can induce efficient switching in both Mn3Sn and CoFeB despite its negligible spin Hall angle. However, from terahertz emission and magnetoresistance measurements, the inverse process - spin-to-charge conversion in Cr/CoFeB is much less efficient than the heavy metal-based structures. These results suggest that the observed switching in Mn3Sn/Cr and CoFeB/Cr is mainly contributed by orbital Hall effect rather than spin Hall effect.

关键词： Couplings Torque Metals Switches Extraterrestrial measurements Orbits Hall effect

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Learning of Nash Equilibria in Risk-Averse Games

Learning of Nash Equilibria in Risk-Averse Games

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American Control Conference (ACC)

作者： Zifan Wang Yi Shen Michael M. Zavlanos Karl H. Johansson Division of Decision and Control Systems School of Electrical Enginnering and Computer Science KTH Royal Institute of Technology and also with Digital Futures Stockholm Sweden Department of Mechanical Engineering and Materials Science Duke University Durham NC USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper considers risk-averse learning in convex games involving multiple agents that aim to minimize their individual risk of incurring significantly high costs. Specifically, the agents adopt the conditional value at risk (CVaR) as a risk measure with possibly different risk levels. To solve this problem, we propose a first-order risk-averse leaning algorithm, in which the CVaR gradient estimate depends on an estimate of the Value at Risk (VaR) value combined with the gradient of the stochastic cost function. Although estimation of the CVaR gradients using finitely many samples is generally biased, we show that the accumulated error of the CVaR gradient estimates is bounded with high probability. Moreover, assuming that the risk-averse game is strongly monotone, we show that the proposed algorithm converges to the risk-averse Nash equilibrium. We present numerical experiments on a Cournot game example to illustrate the performance of the proposed method.

关键词： Reactive power Costs Estimation Games Nash equilibrium Numerical simulation Cost function

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Cantilever Actuator Module for on-Command Drug Deployment from Ingestible Capsules 22

Cantilever Actuator Module for on-Command Drug Deployment fr...

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22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Transducers 2023

作者： Levy, Joshua A. Straker, Michael A. Beardslee, Luke A. Ghodssi, Reza University Of Maryland Department Of Materials Science And Engineering College ParkMD United States University Of Maryland Institute For Systems Research College ParkMD United States University Of Maryland Robert E. Fischell Institute For Biomedical Devices College ParkMD United States University Of Maryland Fischell Department Of Bioengineering College ParkMD United States University Of Maryland Department Of Electrical And Computer Engineering College ParkMD United States

ISBN: (纸本)9784886864352

This manuscript demonstrates the first cantilever actuator for highly targeted and directionally specific delivery of drug-eluting microneedles to the gastrointestinal (GI) tract from ingestible devices. The actuator achieves the following advantages over current technology: on-command deployment in under 500 ms, low power consumption, spatial conservation, and prolonged deployment shelf life. These advancements enable integration of multiple actuators per device for multidirectional deployment. These attributes are achieved by the optimization of heater design and use of low-profile and highly relaxation resistant PEEK polymers. In all, these features enable higher delivery precision in both longitudinal and polar directions, potentiating site targeting in the GI tract. © 2023 IEEJ.

关键词： Cantilever Actuator Drug Delivery Microneedles Stress Relaxation

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Spectral Extremal Connectivity of Two-State Seizure Brain Waves

arXiv

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arXiv 2025年

作者： Talento, Mara Sherlin D. Richards, Jordan Pinto-Orellana, Marco Huser, Raphael Ombao, Hernando C. Statistics Program Computer Electrical and Mathematical Science & Engineering Division King Abdullah University of Science and Technology 23955 - 6900 Saudi Arabia Neuro-AI Laboratory Computer Electrical and Mathematical Science & Engineering Division King Abdullah University of Science and Technology 23955 - 6900 Saudi Arabia School of Mathematics Maxwell Institute for Mathematical Sciences University of Edinburgh EdinburghEH9 3FD United Kingdom Department of Biomedical Engineering University of California Irvine92697 United States

Coherence analysis plays a vital role in the study of functional brain connectivity. However, coherence captures only linear spectral associations, and thus can produce misleading findings when ignoring variations of connectivity in the tails of the distribution. This limitation becomes important when investigating extreme neural events that are characterized by large signal amplitudes. The focus of this paper is to examine connectivity in the tails of the distribution, as this reveals salient information that may be overlooked by standard methods. We develop a novel notion of spectral tail association of periodograms to study connectivity in the network of electroencephalogram (EEG) signals of seizure-prone neonates. We further develop a novel non-stationary extremal dependence model for multivariate time series that captures differences in extremal dependence during different brain phases, namely burst-suppression and non-burst-suppression. One advantage of our proposed approach is its ability to identify tail connectivity at key frequency bands that could be associated with outbursts of energy which may lead to seizures. We discuss these novel scientific findings alongside a comparison of the extremal behavior of brain signals for epileptic and non-epileptic patients. © 2025, CC BY.

关键词： Electroencephalography

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Constrained Optimization with Decision-Dependent Distributions

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IEEE Transactions on Automatic Control 2025年

作者： Wang, Zifan Liu, Changxin Parisini, Thomas Zavlanos, Michael M. Johansson, Karl H. KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures StockholmSE-10044 Sweden East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy Duke University Department of Mechanical Engineering and Materials Science DurhamNC United States

In this paper we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems with decision-dependent distributions has assumed either the absence of constraints or fixed constraints. This work considers a more general setting where the constraints can also dynamically adjust in response to changes in the decision variables. Specifically, we consider linear constraints and analyze the effect of decision-dependent distributions in both the objective function and constraints. Firstly, we establish a sufficient condition for the existence of a constrained equilibrium point, at which the distributions remain invariant under retraining. Moreover, we propose and analyze two algorithms: repeated constrained optimization and repeated dual ascent. For each algorithm, we provide sufficient conditions for convergence to the constrained equilibrium point. Furthermore, we explore the relationship between the equilibrium point and the optimal point for the constrained decision-dependent optimization problem. Notably, our results encompass previous findings as special cases when the constraints remain fixed. To show the effectiveness of our theoretical analysis, we provide numerical experiments on both a market problem and a dynamic pricing problem for parking based on real-world data. © 1963-2012 IEEE.

关键词： Optimization algorithms

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Dual Mode pMUT for Structural Health Monitoring of Piping Systems in Advanced Reactors

Dual Mode pMUT for Structural Health Monitoring of Piping Sy...

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IEEE Symposium (IUS) Ultrasonics

作者： Talha Masood Khan John Sabino Chenxi Xu Javier Obregon Joshua Wilis Adkins Matthew Daly Alexander Heifetz Derek Wiliam Kultgen Didem Ozevin Department of Civil Materials and Environmental Engineering University of Illinois Chicago Chicago IL USA Department of Electrical and Computer Engineering University of Illinois Chicago Chicago IL USA Nuclear Science and Engineering Division Argonne National Laboratory Lemont IL USA

The objective of this work is to develop a durable MEMS sensor for in situ monitoring of advanced reactor piping. Existing sensors for structural health monitoring (SHM) in nuclear reactor environments have limited temperature ranges and service lifetimes, owing to material constraints. Micromachined transducers using aluminum nitride (AlN) as a sensing element, and silicon carbide (SiC) as a substrate, have the potential to address this challenge. In this work, piezoelectric Micromachined Ultrasonic Transducers (pMUT) capable of delivering passive (acoustic emission) and active (guided wave) ultrasonic sensing for SHM in a high-temperature environment are studied. These sensors will be able to couple directly to the structures for real-time SHM of advanced reactor piping systems. A customized microfabrication process is used to produce dual-mode sensing operation at a small footprint of 5×5 mm 2 . This process involves sputtering a 1 µm thick AlN sandwiched between metal and handle layer. The frequency modes of the pMUT device are tuned to 140 kHz by varying the lateral dimensions of the sensor. Sensor locations on piping are determined by generating plane waves using finite element simulations and studying the wave dispersion. With higher sensitivity, our pMUT sensors are capable of detecting the smallest defect energy at high temperatures, while decreasing the number of sensors on piping.

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Structure, surface/interface chemistry and optical properties of W-incorporated β-Ga₂O₃ films made by pulsed laser deposition

RSC Applied Interfaces

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RSC Applied Interfaces 2024年第6期1卷 1395-1409页

作者： Sanchez, Francelia Das, Debabrata Episcopo, Nathan Manciu, Felicia S. Tan, Susheng Shutthanandan, Vaithiyalingam Ramana, C.V. Center for Advanced Materials Research (CMR) University of Texas at El Paso 500 W University Ave El Paso 79968 TX United States Department of Metallurgical Materials and Biomaterials Engineering University of Texas at El Paso 500 W University Ave El Paso 79968 TX United States Department of Aerospace and Mechanical Engineering University of Texas at El Paso 500 W University Ave El Paso 79968 TX United States Department of Physics University of Texas at El Paso 500 W University Ave El Paso 79968 TX United States Department of Electrical and Computer Engineering and Petersen Institute of Nano Science and Engineering University of Pittsburgh Pittsburgh 15261 PA United States Environmental Molecular Sciences Laboratory Pacific Northwest National Laboratory 902 Battelle Blvd Richland 99354 WA United States Physical and Computational Sciences Directorate (PCSD) Pacific Northwest National Laboratory (PNNL) Richland 99352 WA United States

Gallium oxide (Ga2O3), which is one among the ultra-wide band gap materials, is promising for the next generation of electronic and optoelectronic devices due to its fascinating material properties for utilization in ...

Gallium oxide (Ga₂O₃), which is one among the ultra-wide band gap materials, is promising for the next generation of electronic and optoelectronic devices due to its fascinating material properties for utilization in extreme environments. In this work, Ga₂O₃ films containing refractory tungsten (W) (GWO or Ga-W-O) were fabricated via pulsed laser deposition (PLD) by varying the oxygen partial pressure (pO₂), which is the most important thermodynamic parameter that governs the growth, structure and properties of the resulting multi-component oxide films. The effect of variable pO₂ on the structure, surface chemistry, chemical bonding, optical properties and photodetector device performance of the resulting Ga-W-O films was studied using X-ray photoelectron spectroscopy, Raman spectroscopy, atomic force microscopy, UV-vis spectroscopy, and photoluminescence spectroscopy measurements. The films containing Ga₂O₃ combined with W exhibited no secondary phase development. The impact of W on the chemical and optical characteristics of Ga₂O₃ films was found to be substantial. W⁵⁺ formation is prevalent when the adatom mobility is high at lower working pressure, whereas lower migration energy favors W⁶⁺ at higher working pressure. In contrast, the valance band maxima (VBM) of the films have a minor shift to higher energies with increasing pO₂, confirming the dominance of O 2p states on VBM in PLD GWO films. Additionally, there is not much change in the optical band gap, but it shows a slight blue shift of the luminescence peak, directing a selective W incorporation into the Ga₂O₃ matrix. The processing conditions were optimized to demonstrate the excellent performance UV-photodetectors based on PLD GWO films. The structure-property correlation established will be useful in the production of W-alloyed β-Ga₂

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