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Topological magnonic properties of an antiferromagnetic chain

Physical Review B 2024年第14期110卷 144448页

作者： Topojit Debnath Shri Hari Soundararaj Sohee Kwon Alexander A. Balandin Roger K. Lake Laboratory for Terahertz & Terascale Electronics (LATTE) Department of Electrical and Computer Engineering Materials Science and Engineering Department of Materials Science and Engineering

The magnonic excitations of a dimerized, one-dimensional, antiferromagnetic chain can be trivial or topological depending on the signs and magnitudes of the alternating exchange couplings and the anisotropy. The topological phase that occurs when the signs of the two different exchange couplings alternate is qualitatively different from that of the Su-Schrieffer-Heeger model. A material that may exhibit these properties is the quasi-one-dimensional material MoI3 that consists of dimerized chains weakly coupled to adjacent chains. The magnetic ground state and its excitations are analyzed both analytically and numerically using exchange and anisotropy parameters extracted from density functional theory calculations.

关键词： First-principles calculations Magnetic anisotropy Magnetic coupling Magnetic interactions Magnetic order Magnetic phase transitions Magnetic texture Magnetism Magnons Topological phase transition 1-dimensional spin chains Antiferromagnets Classical spin chains Density functional calculations Heisenberg model Holstein-Primakoff method Linear spin wave theory Quantum spin chains

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Optimizing Different Methods of Fabricating 3D Printed UV Blocking Sheets for Solar Cells 1

Optimizing Different Methods of Fabricating 3D Printed UV Bl...

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1st Renewable Energy Technologies and Modern Communications Systems: Future and Challenges Conference, RETMCS 2024

作者： Alhindi, Amjad Fawzi Elatab, Nazek Baawad, Lujain Khalid Bahabry, Rabab R. Allam, Fahad Laboratory Electrical and Computer Engineering Computer Electrical Mathematical Science and Engineering Thuwal Saudi Arabia College of Science Department of Physical Sciences Jeddah21589 Saudi Arabia Materials Science and Engineering Department King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia

ISBN: (纸本)9798331519445

This study investigates the fabrication of innovative UV-blocking sheets that effectively transmit visible light while simultaneously obstructing harmful ultraviolet (UV) radiation, utilizing Cerium Oxide (CeO2) and Zinc Oxide (ZnO) nanoparticles as UV-blocking agents. Three distinct fabrication methods were explored: The Powder Method, where nanoparticles were incorporated directly into polydimethylsiloxane (PDMS);the Ball milling Mixture method, which involved mixing nanoparticles through ball milling;and the Solvent-Based Mixture method, where nanoparticles were dissolved, mixed, and dried;before incorporation into PDMS. Samples were produced using a 3D printing technique, which is Direct Ink Writing (DIW) and characterized for their optical properties via UV-Vis spectroscopy. The results indicated CeO2 demonstrated superior UV-blocking capabilities (a maximum blockage of ~99%) compared to ZnO, while maintaining high transmittance for visible light (a maximum of ~90%). Notably, the solvent-based method exhibited better results than the ball milling method;however, the powder method had the best results. Therefore, this investigation offers a promising solution for solar panel protection that aligns with Saudi Arabia's Vision 2030 energy objectives. The relentless exposure of devices, particularly solar cells, to harmful UV radiation poses a formidable challenge and leads to annual degradation rates of between −0.8% and −4.9%, besides other factors. These findings underscore the critical importance of developing effective UV-blocking solutions. ©2024 IEEE.

关键词： Polydimethylsiloxane

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Design Study Evaluating Impact of Gap Loss on Nanocrystalline Inductor Cores with Experimental Validation 14

Design Study Evaluating Impact of Gap Loss on Nanocrystallin...

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14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Sturdivant, Maurice Grainger, Brandon Bracken, Christopher Ohodnicki, Paul University of Pittsburgh Department of Electrical and Computer Engineering United States University of Pittsburgh Department of Mechanical Engineering and Materials Science United States

ISBN: (纸本)9798331516116

As electric vehicle (EV) technology matures, the need for compact and efficient power electronics will continue to grow. To increase power density and efficiency, it is ideal to minimize the size and power loss of components, including inductors. A standard inductor design technique is placing an air gap in the magnetic core, allowing designers to tune the inductance and allow higher levels of magnetic field without saturation. The inclusion of gaps can increase the total magnetic core loss beyond those predicted by common models such as the Steinmetz equation, creating the need for accurate gap loss models. In this study, the losses of a nanocrystalline inductor core are experimentally measured and compared to an existing gap loss model, showing significant agreement with predicted values. The model was then integrated into a multi-objective optimization framework to evaluate the fitness of nanocrystalline cores against ferrite cores at different switching frequencies. This work finds that gap losses can increase the total loss of nanocrystalline inductors by up to an order of magnitude as frequency increases, implying that consideration of gap losses is vital to selecting the appropriate core material for design applications. © 2025 IEEE.

关键词： Magnetic cores

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Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of Rock Mechanics and Geotechnical engineering 2024年第9期16卷 3812-3840页

作者： M.E.Al-Atroush A.E.Aboelela Ezz El-Din Hemdan Civil and Environmental Engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia Department of Structural Engineering Faculty of EngineeringAin Shams UniversityCairoEgypt Structure and Materials Research Lab Prince Sultan UniversityRiyadhSaudi Arabia Computer Science and Engineering Department Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2023,pivotal advancements in artificial intelligence(AI)have significantly *** that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled *** study undertakes a rigorous evaluation of machine learning(ML)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVMs),and least squares support vector machines(LSSVMs).It was found that despite ML approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these ***,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter *** extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure mechanisms Physics-informed neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset

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Metasurfaces for next-generation wireless communication systems

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National science Review 2023年第8期10卷 17-19页

作者： Younes Ra'di Nikita Nefedkin Petar Popovski Andrea Alù Department of Electrical Engineering and Computer Science Syracuse University Photonics Initiative Advanced Science Research Center City University of New York Department of Electronic Systems Aalborg University Physics Program Graduate Center City University of New York

The pace of development in the world of 5G communication systems has proven to be much more demanding than previous generations, with 5G-Advanced seemingly around the corner [1]. Extensive research is already underway to structure the next generation of wireless systems(i.e. 6G), which may potentially enable an unprecedented level of human–machine interaction [2].

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A flexible capacitive photoreceptor for the biomimetic retina

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Light(science & Applications) 2022年第1期11卷 38-49页

作者： Mani Teja Vijjapu Mohammed E.Fouda Agamyrat Agambayev Chun Hong Kang Chun-Ho Lin Boon S.Ooi Jr-Hau He Ahmed M.Eltawil Khaled N.Salama Sensors lab Advanced Membranes and Porous Materials CenterComputerElectrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Communication and Computing Systems Lab ComputerElectrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Department of Electrical Engineering and Computer Science University of California-IrvineIrvineCA 92612USA Department of Electrical Computer and Energy EngineeringArizona State UniversityTempeAZUSA Computer Electrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Department of Materials Science and Engineering City University of Hong KongHong Kong SARChina

Neuromorphic vision sensors have been extremely beneficial in developing energy-efficient intelligent systems for robotics and privacy-preserving security *** is a dire need for devices to mimic the retina's photoreceptors that encode the light illumination into a sequence of spikes to develop such ***,we develop a hybrid perovskite-based flexible photoreceptor whose capacitance changes proportionally to the light intensity mimicking the retina's rod cells,paving the way for developing an efficient artificial retina *** proposed device constitutes a hybrid nanocomposite of perovskites(methyl-ammonium lead bromide)and the ferroelectric terpolymer(polyvinylidene fluoride trifluoroethylene-chlorofluoroethylene).A metal-insulator-metal type capacitor with the prepared composite exhibits the unique and photosensitive capacitive behavior at various light intensities in the visible light *** proposed photoreceptor mimics the spectral sensitivity curve of human photopic *** hybrid nanocomposite is stable in ambient air for 129 weeks,with no observable degradation of the composite due to the encapsulation of hybrid perovskites in the hydrophobic *** functionality of the proposed photoreceptor to recognize handwritten digits(MNIST)dataset using an unsupervised trained spiking neural network with 72.05%recognition accuracy is *** demonstration proves the potential of the proposed sensor for neuromorphic vision applications.

关键词： perovskite illumination preserving

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Bi_(2)O_(2)Se nanoplates for broadband photodetector and full-color imaging applications

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Nano Research 2023年第5期16卷 7638-7645页

作者： Han Wang Songqing Zhang Xingxuan Wu Huijia Luo Junliang Liu Zesheng Mu Ruirui Liu Guang Yuan Yujun Liang Jin Tan Yongling Ren Wen Lei Department of Electrical Electronic and Computer EngineeringThe University of Western AustraliaCrawley 6009Australia Department of Electronic Engineering School of IOT engineeringJiangnan UniversityWuxi 214122China College of Information Science and Engineering Ocean University of ChinaQingdao 266100China Faculty of Materials Science and Chemistry China University of GeosciencesWuhan 430074China

Broadband light detection and sensing are widely applied in modern *** a promising candidate for next-generation two-dimensional(2D)optoelectronic material,bismuth oxyselenide(Bi_(2)O_(2)Se)nanoplates exhibit many prospects in the application of visible light detection due to their peculiar *** this work,we report the photodetection performance of single-crystal 2D Bi_(2)O_(2)Se nanoplates grown on SiO_(2)based on a ternary-alloy growth model by utilizing chemical vapor deposition(CVD).The Bi_(2)O_(2)Se nanoplates were found to have an even and uniform square shape with side lengths up to 15μm and an approximate thickness of 15 nm.A visible-light photodetector was fabricated based on a CVD-grown Bi_(2)O_(2)Se nanoplate,and characterized by a set of illumination experiments using a 400 nm laser at temperatures ranging from 77 to 370 *** device exhibited superior performance at the temperature of 77 K,with a responsivity of 523 A/W,a specific detectivity of 1.37×10^(11)Jones,a response time of 0.2175 ms,an external quantum efficiency of 162,119.44%,resulting in high-quality and fullcolor imaging in the visible *** results indicate that the single-crystalline Bi_(2)O_(2)Se nanoplates have excellent potential in broadband photodetection and non-cryogenic imaging.

关键词： two-dimensional(2D)nanomaterial Bi_(2)O_(2)Se nanoplates chemical vapor deposition broadband light detection full-color imaging

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Effect of electrolyte anions on the cycle life of a polymer electrode in aqueous batteries

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escience 2022年第1期2卷 110-115页

作者： Ye Zhang Lihong Zhao Yanliang Liang Xiaojun Wang Yan Yao Department of Electrical and Computer Engineering Materials Science and Engineering ProgramUniversity of HoustonHoustonTX77204USA Texas Center for Superconductivity at the University of Houston HoustonTX77204USA

Redox polymers are a class of high-capacity, low-cost electrode materials for electrochemical energy storage, butthe mechanisms governing their cycling stability are not well understood. Here we investigate the effect of anionson the longevity of a p-dopable polymer through comparing two aqueous zinc-based electrolytes. Galvanostaticcycling studies reveal the polymer has better capacity retention in the presence of triflate anions than that withsulfate anions. Based on electrode microstructural analysis and evolution profiles of the cell stacking pressure, theorigin of capacity decay is ascribed to mechanical fractures induced by volume change of the polymer activematerials during repeated cycling. The volume change of the polymer with the triflate anion is 61% less than thatwith the sulfate anion, resulting in fewer cracks in the electrodes. The difference is related to the different anionsolvation structures—the triflate anion has fewer solvated water molecules compared with the sulfate anion,leading to smaller volume expansion. This work highlights that anions with low solvation degree are preferablefor long-term cycling.

关键词： Aqueous batteries Polymer electrode Anions Volume chang

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Modeling the effects of salt concentration on aqueous and organic electrolytes

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npj Computational materials 2023年第1期9卷 546-552页

作者： Stephanie C.C.van der Lubbe Pieremanuele Canepa Department of Materials Science and Engineering National University of Singapore9 Engineering Drive 1117575 SingaporeSingapore Department of Chemical and Biomolecular Engineering National University of Singapore4 Engineering Drive 4117585 SingaporeSingapore Department of Electrical and Computer Engineering and Texas Center for Superconductivity University of HoustonHoustonTX 77204USA

Understanding the thermodynamic properties of electrolyte solutions is of vital importance for a myriad of physiological and technological *** mean activity coefficientγ±is associated with the deviation of an electrolyte solution from its ideal behavior and may be obtained by combining the Debye-Hückel(DH)and Born(B)***,the DH and B equations depend on the concentration and temperature-dependent static permittivity of the solutionεr(c,T)and the size of the solvated ions ri,whose experimental data is often not ***,we use a combination of molecular dynamics and density functional theory to predictεr(c,T)and ri,which enables us to apply the DH and B equations to any technologically relevant aqueous and nonaqueous electrolyte at any concentration and temperature of interest.

关键词： equations electrolyte apply

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ConvNeXt Model for Breast Cancer Image Classification 6

ConvNeXt Model for Breast Cancer Image Classification

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Setiawan, Devin Karnyoto, Andrea Stevens Intan, Indo Pardamean, Bens Department of Electrical Engineering and Computer Science University of Kansas Lawrence United States Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Informatics Engineering Universitas Dipa Makassar Makassar Indonesia Computer Science Department BINUS Graduate Program Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798331539603

Breast cancer is an occurrence of cancer that attacks breast tissue and is the most common cancer among women worldwide, affecting one in eight women. In this modern world, breast cancer image classification simplifies the process of analyzing, providing objective and accurate results. By leveraging machine learning algorithms and computer vision techniques, we developed breast cancer detection. The dataset is histopathology dataset from BreakHis and UNHAS Hospital. We chose the ConvNeXt-Tiny model then modified the classifier head as the proposed method. Before the dataset is processed by the model, we augment the images by applying random horizontal and vertical flips, adjustments to brightness, contrast, saturation, and hue using color jitter. The augmentation process simulates real-world variance and enhances the model's ability to generalize to unseen data. Our proposed model gained better performance (accuracy, F1-Score) results compared two other techniques to VGG16 and SVM. According to our experiments, the F1-Score for the ConvNeXt-Tiny model with classifier head modification is higher at 0.9516, than the gain for VGG16 at 0.9292, and the gain for the SVM at 0.83. © 2024 IEEE.

关键词： Lung cancer

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