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arXiv 2024年

作者： Shen, Jialiang Chen, M. Korostelev, V. Kim, H. Fathi-Hafshejani, P. Mahjouri-Samani, M. Klyukin, K. Lee, G.-H. Dai, S. Materials Research and Education Center Department of Mechanical Engineering Auburn University AuburnAL36849 United States Department of Materials Science and Engineering Seoul National University Gwanak-ro 1 Gwanak-gu Seoul08826 Korea Republic of Department of Electrical and Computer Engineering Auburn University AuburnAL36849 United States

Charge transfer is a fundamental interface process that can be harnessed for light detection, photovoltaics, and photosynthesis. Recently, charge transfer was exploited in nanophotonics to alter plasmon polaritons by involving additional non-polaritonic materials to activate the charge transfer. Yet, direct charge transfer between polaritonic materials hasn’t been demonstrated. We report the direct charge transfer in pure polaritonic van der Waals (vdW) heterostructures of αMoO3/graphene. We extracted the Fermi energy of 0.6 eV for graphene by infrared nano-imaging of charge transfer hyperbolic polaritons in the vdW heterostructure. This unusually high Fermi energy is attributed to the charge transfer between graphene and α-MoO3. Moreover, we have observed charge transfer hyperbolic polaritons in multiple energy-momentum dispersion branches with a wavelength elongation of up to 150%. With support from the DFT calculation, we find that the charge transfer between graphene and α-MoO3, absent in mechanically assembled vdW heterostructures, is attributed to the relatively pristine heterointerface preserved in the epitaxially grown vdW heterostructure. The direct charge transfer and charge transfer hyperbolic polaritons demonstrated in our work hold great promise for developing nano-optical circuits, computational devices, communication systems, and light and energy manipulation devices. Copyright © 2024, The Authors. All rights reserved.

关键词： Charge transfer

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A model for the current-voltage characteristic of membrane/electrolyte junctions

arXiv

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arXiv 2024年

作者： Mele, L.J. Alam, M.A. Palestri, P. Department of Materials Science and Engineering Stanford University StanfordCA94305 United States School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Engineering Department "Enzo Ferrari" University of Modena and Reggio Emilia Modena41125 Italy

A model for the current-voltage characteristic of the junction between an Ion- Sensitive-Membrane and an electrolyte solution is derived and compared with numerical simulations of the Poisson-Nernst-Planck model for ion transport. The expression resembles that of a semiconductor pn junction with a non-ideality factor of 2. The non-ideality correlated to the voltage drop in the electrolyte induced by the re-arrangement of the counter-ions. © 2024, CC BY-NC-ND.

关键词： Semiconductor junctions

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Relationship between orbital moment anisotropy, magnetocrystalline anisotropy, and Dzyaloshinskii-Moriya interaction in W/Co/Pt trilayers

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Physical Review B 2024年第18期110卷 184401页

作者： Zhendong Chi Yong-Chang Lau Vanessa Li Zhang Goro Shibata Shoya Sakamoto Yosuke Nonaka Keisuke Ikeda Yuxuan Wan Masahiro Suzuki Masashi Kawaguchi Masako Suzuki-Sakamaki Kenta Amemiya Naomi Kawamura Masaichiro Mizumaki Motohiro Suzuki Hyunsoo Yang Masamitsu Hayashi Atsushi Fujimori Department of Physics Tsukuba Ibaraki 305-0047 Japan School of Physics and Technology Materials Sciences Research Center Institute for Solid State Physics Institute of Materials Structure Science Graduate School of Science and Technology Gunma University Kiryu Gunma 376-8515 Japan (JASRI) Sayo 679-5198 Japan Department of Electrical and Computer Engineering Department of Physics and Center for Quantum Science and Technology

We have studied the Co layer thickness dependences of magnetocrystalline anisotropy (MCA), Dzyaloshinskii-Moriya interaction (DMI), and orbital moment anisotropy (OMA) in W/Co/Pt trilayers, in order to clarify their correlations with each other. We find that the MCA favors magnetization along the film normal and monotonically increases with decreasing effective magnetic layer thickness (teff). The magnitude of the Dzyaloshinskii-Moriya exchange constant (|D|) increases with decreasing teff until teff∼1 nm, below which |D| decreases. The MCA and |D| scale with 1/teff for teff larger than ∼1 nm, indicating an interfacial origin. The increase of MCA with decreasing teff continues below teff∼ 1 nm, but with a slower rate. To clarify the cause of the teff dependences of MCA and DMI, the OMA of Co in W/Co/Pt trilayers is studied using x-ray magnetic circular dichroism. We find nonzero OMA when teff is smaller than ∼0.8 nm. The OMA increases with decreasing teff more rapidly than what is expected from the MCA, indicating that factors other than OMA contribute to the MCA at small teff. The teff dependence of the OMA also suggests that |D| at teff smaller than ∼1 nm is not related to the OMA at the interface. We propose that the growth of Co on W results in a strain and/or texture that reduces the interfacial DMI, and, to some extent, MCA at small teff.

关键词： Dzyaloshinskii-Moriya interaction Magnetic anisotropy Multilayer thin films X-ray absorption spectroscopy X-ray magnetic circular dichroism

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Femtosecond Laser Damage Comparison Between Silica/Hafnia Nanolaminates vs. Mixed Material Coatings for High Power Laser Optics

Femtosecond Laser Damage Comparison Between Silica/Hafnia Na...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Emma DaAngelis Mohamed Yaseen Noor Maxwell Weiss Carmen Menoni Enam Chowdhury Department of Materials Science and Engineering The Ohio State University Columbus Ohio USA Electrical and Computer Engineering Department Colorado State University Fort Collins CO USA XUV Lasers Inc. Fort Collins CO USA

Two layer anti-reflection coatings (Air/SiO 2 /HfSiO/substrate. vs Air/SiO 2 /Hf-SiO 2 nanolaminates/substrate) were tested with p-polarized 77 fs 1030 nm laser pulses. Damage threshold fluence of the sample with nan... 详细信息

ISBN: (纸本)9798350369311

关键词： Power lasers Coatings Ultrafast optics Laser pulses Electro-optical waveguides

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FDM Printing: A Fabrication Method for Fluidic Soft Circuits?

FDM Printing: A Fabrication Method for Fluidic Soft Circuits...

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IEEE International Conference on Soft Robotics (RoboSoft)

作者： Savita V. Kendre Lehong Wang Ethan Wilke Nicholas Pacheco Loris Fichera Markus P. Nemitz Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA Department of Computer Science Worcester Polytechnic Institute Worcester MA USA Department of Biomedical Engineering Worcester Polytechnic Institute Worcester MA USA Department of Mechanical and Materials Engineering Worcester Polytechnic Institute Worcester MA USA Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA

Existing fluidic soft logic gates for controlling soft robots typically depend on labor-intensive manual fabrication or costly printing methods. In our research, we utilize Fused Deposition Modeling to create fully 3D-printed fluidic logic gates, fabricating a valve from thermoplastic polyurethane. We investigate the 3D printing of tubing and introduce a novel extrusion nozzle for tubing production. Our approach significantly reduces the production time for soft fluidic valves from 27 hours using replica molding to 3 hours with FDM printing. We apply our 3D-printed valve to develop optimized XOR gates and D-latch circuits, presenting a rapid and cost-effective fabrication method for fluidic logic gates that aims to make fluidic circuitry more accessible to the soft robotics community.

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Impact of CLAHE-based image enhancement for diabetic retinopathy classification through deep learning 7

Impact of CLAHE-based image enhancement for diabetic retinop...

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7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Hayati, Mira Muchtar, Kahlil Roslidar Maulina, Novi Syamsuddin, Irfan Elwirehardja, Gregorius Natanael Pardamean, Bens Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia Universitas Syiah Kuala Banda Aceh23111 Indonesia Faculty of Medicine Universitas Syiah Kuala Banda Aceh23111 Indonesia Department of Computer and Networking Engineering Politeknik Negeri Ujung Pandang Makassar90245 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia

Diabetic retinopathy (DR) is a type of diabetes mellitus that attacks the retina of the eye. DR will cause patients to experience blindness slowly. Generally, DR can be detected by using a special instrument called an ophthalmoscope to view the inside of the eyeball. However, in conditions where there is a very small difference between the normal image and the DR image, computer-based assistance is needed for maximizing image reading value. In this research, a method of image quality improvement will be carried out which will then be integrated with a classification algorithm based on deep learning. The results of image improvement using Contrast Limited Adaptive Histogram Equalization (CLAHE) shows that the average accuracy of the method on several models is very competitive, 91% for the VGG16 model, 95% for InceptionV3, and 97% for EfficientNet compared to the results original image which only has an accuracy of 87% for VGG16 model, 90% for InceptionV3 model, and 95% for EfficientNet. However, in ResNet34 better accuracy is obtained in the original image with an accuracy of 95% while in the CLAHE image the accuracy value is only 84%. The results of this comprehensive evaluation and recommendation of famous backbone networks can be useful in the computer-Aided diagnosis of diabetic retinopathy. © 2022 Elsevier B.V.. All rights reserved.

关键词： Image enhancement

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SEMANTIC SEGMENTATION OF POROSITY IN 4D SPATIO-TEMPORAL X-RAY µCT OF TITANIUM COATED NI WIRES USING DEEP LEARNING

arXiv

引用

arXiv 2023年

作者： Elavarthi, Pradyumna Bhattacharjee, Arun Ralescu, Anca Paz y Puente, Ashley Department of Electrical Engineering and Computer Science University of Cincinnati OH45221 United States Department of Mechanical and Materials Science University of Cincinnati OH45221 United States

A fully convolutional neural network was used to measure the evolution of the volume fraction of two different Kirkendall pores during the homogenization of Ti-coated Ni wires. Traditional methods like Otsu’s thresholding and the Largest connected component analysis were used to obtain the masks for training the segmentation model. Once trained, the model was used to semantically segment the two types of pores at different stages in their evolution. Masks of the pores predicted by the network were then used to measure the volume fraction of porosity at 0mins, 240mins, and 480mins of homogenization. The model predicted an increase in porosity for one type of pore and a decrease in porosity for another type of pore due to pore sintering, and it achieved an F1 Score of 0.95. © 2023, CC BY-NC-SA.

关键词： Volume fraction

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Convergence of energy-based learning in linear resistive networks

arXiv

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arXiv 2025年

作者： Huijzer, Anne-Men Chaffey, Thomas Besselink, Bart van Waarde, Henk J. Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen Netherlands CogniGron - Groningen Cognitive Systems and Materials Center Netherlands Control Group Department of Engineering University of Cambridge United Kingdom School of Electrical and Computer Engineering University of Sydney Australia

Energy-based learning algorithms are alternatives to backpropagation and are well-suited to distributed implementations in analog electronic devices. However, a rigorous theory of convergence is lacking. We make a first step in this direction by analysing a particular energy-based learning algorithm, Contrastive Learning, applied to a network of linear adjustable resistors. It is shown that, in this setup, Contrastive Learning is equivalent to projected gradient descent on a convex function, for any step size, giving a guarantee of convergence for the *** Codes 65K10, 68T05, 93B30, 93D99 © 2025, CC BY-SA.

关键词： Contrastive Learning

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Optimizing System-on-Chip Performance Using AI and SDN: Approaches and Challenges 9

Optimizing System-on-Chip Performance Using AI and SDN: Appr...

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9th International Conference on Software Defined Systems, SDS 2022

作者： Alja'afreh, Mohammad Obaidat, Muath Karime, Ali Alouneh, Sahel United Arab Emirates Computer Science- City University of New York United States The Royal Military College of Canada Department of Electrical and Computer Engineering Canada Al Ain University German Jordanian University Cybersecurity Program Jordan Jordan

ISBN: (纸本)9798350346718

The advancement of modern multimedia and data-intensive classes of applications demands the development of hardware that delivers better performance. Due to the evolution of 5G, Edge-Computing, the Internet of Things, Software-Defined networks, etc., the data produced by the devices such as sensors are increasing. A software-Defined network is a powerful paradigm that is capable of automating networking and cloud computing. Software-Defined Network has controllers, devices, and applications which produce a huge amount of data. The processing of data inside the device as well as between the devices needs a better hardware architecture with more cores to ensure speedy performance. The System-on-Chip approach alone will not be capable to handle this dense core comprised of hardware. We have to blend Network-on-Chip along with System-on-Chip to increase the potential to include more cores capable to handle more threads. Artificial Intelligence, a key enabler in next-generation devices is capable of producing a better architecture design with optimized performance. In this paper, we are discussing and endeavouring how System-on-Chip, Network-on-Chip, Software-Defined Networks, and Artificial Intelligence can be physically, logically, and contextually incorporated to deliver improved computation and networking outcomes. © 2022 IEEE.

关键词： Network-on-chip

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Optical Wireless Integrated Sensing and Communication Based on EADO-OFDM: A Flexible Resource Allocation Perspective

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IEEE Transactions on Wireless Communications 2025年

作者： Wen, Yunfeng Yang, Fang Song, Jian Han, Zhu Tsinghua University Department of Electronic Engineering Beijing100084 China State Key Laboratory of Widegap Semiconductor Optoelectronic Materials and Technologies Beijing100084 China Tsinghua University Shenzhen International Graduate School Shenzhen518055 China University of Houston Department of Electrical and Computer Engineering Houston77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

Integrated sensing and communication (ISAC) is regarded as one key enabler in the future sixth-generation (6G) mobile communication network. While considerable attention has been paid to radio-frequency (RF)-ISAC, optical wireless (OW)-ISAC is also rapidly developing as a powerful complement to its RF counterpart. In this paper, an enhanced asymmetrically clipped direct-current-biased optical orthogonal frequency division multiplexing (EADO-OFDM) scheme is proposed for flexible waveform design and resource allocation in OW-ISAC. A generalized OW-ISAC framework is first established to describe the working principles of both communication and sensing (C&S). Then, the signal model is introduced for EADO-OFDM, where the Price theorem is adopted to model the colored clipping noise and elicit a generalized frequency-selective channel. In addition, a joint optimization problem of resource allocation for EADO-OFDM is formulated to adaptively balance C&S performance metrics, and the solution to the problem is obtained by the block coordinate descent algorithm. Finally, extensive numerical simulations demonstrate the flexibility of the proposed EADO-OFDM scheme, while the C&S trade-off is also revealed during the resource allocation. © 2002-2012 IEEE.

关键词： Orthogonal frequency division multiplexing

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