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Observation of double hysteresis in CoFe2O4/MnFe2O4 core/shell nanoparticles and its contribution to AC heat induction

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arXiv 2025年

作者： Wang, Jie Kim, Hyungsub Kim, Ji-Wook Seo, HyeongJoo Ota, Satoshi You, Chun-Yeol Takemura, Yasushi Bae, Seongtae Department of Electrical Engineering University of South Carolina ColumbiaSC29208 United States Department of Emerging Materials Science Daegu Gyeongbuk Institute of Science & Technology Daegu42988 Korea Republic of Department of Electrical and Electronic Engineering Shizuoka University Hamamatsu432-8561 Japan Department of Electrical and Computer Engineering Yokohama National University Yokohama240-8501 Japan

Magnetic core/shell nanoparticles are promising candidates for magnetic hyperthermia due to its high AC magnetic heat induction (specific loss power (SLP)). It’s widely accepted that magnetic exchange-coupling between core and shell plays the crucial role in enhancing SLP of magnetic core/shell nanoparticles. However, the physical contribution of exchange coupling to SLP has not been systematically investigated, and the underlying mechanism remains unclear. In this study, magnetic hard/soft CoFe2O4/MnFe2O4 and inverted soft/hard MnFe2O4/CoFe2O4 core/shell nanoparticles were synthesized, systematically varying the number of shell layers, to investigate the physical contribution of internal bias coupling at the core/shell interface to AC heat induction (SLP). Our results show that a unique magnetic property, double-hysteresis loop, was present and clearly observed, which was never reported in previous core/shell research literature. According to the experimentally and theoretically analyzed results, the double-hysteresis behavior in core/shell nanoparticles was caused by the difference of magnetic anisotropy between core and shell materials, separated by a non-magnetic interface. The enhanced SLP and and maximum temperature rise (TAC,max) of core/shell nanoparticles are attributed to the optimized magnetic anositropy, AC magnetic softness and double hysteresis behavior due to the internal bias coupling. These results demonstrate that the rational design capabilities to separately control the magnetic anisotropy, AC/DC magnetic properties by varying the volume ration between core and shell and by switching hard or soft phase materials between core and shell are effective modalities to enhance the AC heat induction of core/shell nanoparticles for magnetic nanoparticle hyperthermia. Copyright © 2025, The Authors. All rights reserved.

关键词： Magnetic anisotropy

Signal Processing on Platforms with Multiple Cores: Part 1-Overview and Methodologies

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IEEE SIGNAL PROCESSING MAGAZINE 2009年第6期26卷 24-25页

作者： Chen, Yen-Kuang Chakrabarti, Chaitali Bhattacharyya, Shuvra Bougard, Bruno Department of Electrical and Computer Engineering Lehigh University Bethlehem PA USA Department of Materials Science and Engineering University of Florida Gainesville FL USA Department of Materials Science and Engineering University of California–Los Angeles Los Angeles CA USA

Multicore processors are now prevalent in all major domains of signal processing. Many laptop and desktop computers today are shipped with dualcore and even quad-core processors. The number of cores is even higher for the Sony PlayStation 3, which is equipped with an 8-core IBM CELL Broadband Engine processor, Nvidia GeForce 9800 GX2, which has 256 stream processors, and SUN UltraSPARC T1/T2 processor, which has 8 cores. Technology predictions indicate that this trend will continue and that the number of cores per processor can easily double around every two or three years.

关键词： Signal processing Multicore processing computer architecture Energy consumption Clocks Signal processing algorithms Signal design Software tools Portable computers Engines

Cost-Effectiveness of Interventions for Alternate Food to Address Agricultural Catastrophes Globally

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International Journal of Disaster Risk science 2016年第3期7卷 205-215页

作者： David C.Denkenberger Joshua M.Pearce Global Catastrophic Risk Institute Department of Civil and Architectural Engineering Tennessee State University Department of Materials Science and Engineering Michigan Technological University Department of Electrical and Computer Engineering Michigan Technological University

The literature suggests there is about a 1 % risk per year of a 10 % global agricultural shortfall due to catastrophes such as a large volcanic eruption, a medium asteroid or comet impact, regional nuclear war, abrupt climate change, and extreme weather causing multiple breadbasket failures. This shortfall has an expected mortality of about 500 million people. To prevent such mass starvation, alternate foods can be deployed that utilize stored biomass. This study developed a model with literature values for variables and, where no values existed,used large error bounds to recognize uncertainty. Then Monte Carlo analysis was performed on three interventions: planning, research, and development. The results show that even the upper bound of USD 400 per life saved by these interventions is far lower than what is typically paid to save a life in a less-developed country. Furthermore, every day of delay on the implementation of these interventions costs 100–40,000 expected lives(number of lives saved multiplied by the probability that alternate foods would be required). These interventions plus training would save 1–300 million expected lives. In general, these solutions would reduce the possibility of civilization collapse, could assist in providing food outside of catastrophic situations, and would result in billions of dollars per year of return.

关键词： Agricultural catastrophe Alternate food Global catastrophic risk Intervention cost-effectiveness

Violation of Pauli Limit at KTaO3(110) Interfaces

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arXiv 2025年

作者： Poage, Samuel J. Gao, Xueshi Baksi, Merve Salmani-Rezaie, Salva Muller, David A. Kumah, Divine P. Lau, Chun Ning Lorenzana, José Gastiasoro, Maria N. Ahadi, Kaveh Department of Materials Science and Engineering The Ohio State University ColumbusOH43210 United States Department of Physics The Ohio State University ColumbusOH43210 United States Department of Physics North Carolina State University RaleighNC27695 United States School of Applied and Engineering Physics Cornell University IthacaNY14853 United States Kavli Institute at Cornell for Nanoscale Science Cornell University IthacaNY14853 United States Department of Physics Duke University DurhamNC27701 United States ISC-CNR Department of Physics Sapienza University of Rome Piazzale Aldo Moro 2 Rome00185 Italy Donostia International Physics Center Donostia-San Sebastian20018 Spain Department of Electrical and Computer engineering The Ohio State University ColumbusOH43210 United States

The superconducting order parameter at the KTaO3 interfaces and its dependence on interface orientation remains a subject of debate. The superconductivity at these interfaces exhibits strong resilience against in-plane magnetic field and violates Pauli limit. The interface orientation dependence of critical field and violation of Pauli limit, however, have not been investigated. To address this problem, we grew epitaxial LaMnO3/KTaO3 heterostructures using molecular beam epitaxy. We show that superconductivity is extremely robust against the in-plane magnetic field. Our results indicate that the interface orientation, despite impacting the critical temperature, does not affect the ratio of critical field to the Pauli limiting field. These results offer opportunities to engineer superconductors which are resilient against magnetic field. © 2025, CC BY.

关键词： Molecular beam epitaxy

Roadmap on Neuromorphic Photonics

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arXiv 2025年

作者： Brunner, Daniel Shastri, Bhavin J. Al-Qadasi, Mohammed A. Ballani, H. Barbay, Sylvain Biasi, Stefano Bienstman, Peter Bilodeau, Simon Bogaerts, Wim Böhm, Fabian Brennan, G. Buckley, Sonia Cai, Xinlun Strinati, Marcello Calvanese Canakci, B. Charbonnier, Benoit Chemnitz, Mario Chen, Yitong Cheung, Stanley Chiles, Jeff Choi, Suyeon Christodoulides, Demetrios N. Chrostowski, Lukas Chu, J. Clegg, J.H. Cletheroe, D. Conti, Claudio Dai, Qionghai Di Lauro, Luigi Diamantopoulos, Nikolaos-Panteleimon Dinc, Niyazi Ulas Ewaniuk, Jacob Fan, Shanhui Fang, Lu Franchi, Riccardo Freire, Pedro Gentilini, Silvia Gigan, Sylvain Giorgi, Gian Luca Gkantsidis, C. Gladrow, J. Goi, Elena Goldmann, M. Grabulosa, A. Gu, Min Guo, Xianxin Hejda, Matěj Horst, F. Hsieh, Jih-Liang Hu, Jianqi Hu, Juejun Huang, Chaoran Hurtado, Antonio Jaurigue, Lina Kalinin, K.P. Kamalian-Kopae, Morteza Kelly, D.J. Khajavikhan, Mercedeh Kremer, H. Laydevant, Jeremie Lederman, Joshua C. Lee, Jongheon Lenstra, Daan Li, Gordon H.Y. Li, Mo Li, Yuhang Lin, Xing Lin, Zhongjin Lis, Mieszko Lüdge, Kathy Lugnan, Alessio Lupo, Alessandro Lvovsky, A.I. Manuylovich, Egor Marandi, Alireza Marchesin, Federico Massar, Serge McCaughan, Adam N. McMahon, Peter L. Moralis-Pegios, Miltiadis Morandotti, Roberto Moser, Christophe Moss, David J. Mukherjee, Avilash Nikdast, Mahdi Offrein, B.J. Oguz, Ilker Oripov, Bakhrom O'Shea, G. Ozcan, Aydogan Parmigiani, F. Pasricha, Sudeep Pavanello, Fabio Pavesi, Lorenzo Peserico, Nicola Pickup, L. Pierangeli, Davide Pleros, Nikos Porte, Xavier Primavera, Bryce A. Prucnal, Paul Psaltis, Demetri Puts, Lukas Qiao, Fei Rahmani, B. Raineri, Fabrice Ríos Ocampo, Carlos A. Robertson, Joshua Romeira, Bruno Roques-Carmes, Charles Rotenberg, Nir Rowstron, A. Schoenhardt, Steffen Schwartz, Russell L.T. Shainline, Jeffrey M. Shekhar, Sudip Skalli, A. Sohoni, Mandar M. Sorger, Volker J. Soriano, Miguel C. Spall, James Stabile, Ripalta Stiller, Birgit Sunada, Satoshi Tefas, Anastasios Tossoun, Bassem Tsakyridis, Apostolos Turitsyn, Sergei K. Van der Sande, G Université Marie et Louis Pasteur CNRS UMR 6174 Institut FEMTO-ST Besançon25000 France Centre for Nanophotonics Department of Physics Engineering Physics & Astronomy Queen's University Canada Department of Electrical and Computer Engineering The University of British Columbia Vancouver Canada Microsoft Research Cambridge United Kingdom Université Paris-Saclay CNRS Centre de Nanosciences et de Nanotechnologies France Nanoscience Laboratory Department of Physics University of Trento Italy Photonics Research Group Department of Information Technology Ghent University imec Belgium Princeton University NJ United States Hewlett Packard Labs Hewlett Packard Enterprise Böblingen Germany National Institute of Standards and Technology BoulderCO United States State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information Technology Sun Yat-sen University China Enrico Fermi Research Center Rome Italy Université Grenoble-Alpes CEA Leti Grenoble France Leibniz-Institute of Photonic Technology Jena Germany Institute of Applied Optics and Biophysics Jena Germany Department of Automation Tsinghua University Beijing China Department of Electrical and Computer Engineering North Carolina State University NC United States Department of Electrical Engineering Stanford University CA United States University of Southern California Los AngelesCA United States Department of Physics Sapienza University Rome Italy Institute for Complex Systems National Research Council Rome Italy Varennes Canada NTT Device Technology Labs NTT Corporation Kanagawa Atsugi Japan Institute of Electrical and Microengineering School of Engineering École Polytechnique Fédérale de Lausanne Switzerland Edward L. Ginzton Laboratory Stanford University StanfordCA United States Department of Electronic Engineering Tsinghua University China Beijing National Research Center for Information Science and Technology Tsinghua University China Aston Univ

Neuromorphic photonics are processors inspired by the human brain and enabled by light (photons) instead of traditional electronics. Neuromorphic photonics and its associated concepts are experiencing a significant resurgence, building on foundational research from the 1980s and 1990s. This renewed momentum is driven by breakthroughs in photonic integration, nonlinear optics, and advanced materials, alongside the growing necessity of neuro-inspired computing in numerous applications of economic and societal relevance. The increasing demand for energy-efficient artificial intelligence (AI) solutions underscores the need for innovation and a cohesive vision to address key challenges, including scalability, energy efficiency, precision, and standardized performance benchmarks. Together, these efforts present an opportunity to establish a unique photonic advantage with practical, real-world applications. This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementation philosophies reported in the field. It emphasizes the critical role of cross-disciplinary collaboration in this rapidly evolving field. The roadmap introduces various approaches to embedding the high-complexity transformations central to neuromorphic computing, focusing on frequency, delay, and spectral embeddings. This is followed by a discussion of architectures of photonic neural networks (PNNs) and an in-depth analysis of methods for implementing these architectures in photonic hardware. Dedicated sections delve into integrated photonic hardware, the realization of photonic weights and memories, and the optimization of training processes for photonic neuromorphic architectures. The roadmap concludes by exploring numerous potential applications, highlighting the challenges and advances necessary to transition neuromorphic photonic computing from a primarily academic pursuit to a technolog

关键词： Philosophical aspects

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

Theory and Practice of“Striping”for Improved ON/OFF Ratio in Carbon Nanonet Thin Film Transistors

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Nano Research 2009年第2期2卷 167-175页

作者： Ninad Pimparkar Qing Cao John A.Rogers Muhammad A.Alam School of Electrical and Computer Engineering Purdue UniversityWest LafayetteIndiana 47907-1285USA Department of Chemistry Materials and Science Engineering Electrical and Computer Engineering Beckman Institute Frederick and Seitz Materials Res.Lab University of IllinoisUrbanaIL 61801USA

A new technique to reduce the influence of metallic carbon nanotubes(CNTs)relevant for large-scale integrated circuits based on CNT-nanonet transistorsis proposed and ***,electrical and chemical filtering of the metallic CNTs have been used to improve the ON/OFF ratio of CNT-nanonet transistors;however,the corresponding degradation in ON-current has made these techniques somewhat ***,we abandon the classical approaches in favor of a new approach based on relocation of asymmetric percolation threshold of CNT-nanonet transistors by a technique called“striping”;this allows fabrication of transistors with ON/OFF ratio>1000 and ON-current degradation no more than a factor of *** offer first principle numerical models,experimental confirmation,and renormalization arguments to provide a broad theoretical and experimental foundation of the proposed method.

关键词： Nanonet Carbon nanotube flexible electronics thin film transistors

Enhancement of Second Harmonic Generation in Monolayer WS2 by Feedback-Based Wavefront Shaping

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arXiv 2025年

作者： Berger, Russell Mavian, Alex Dimitrov, Edgar Zhang, Na Rumman, Nazifa Bassène, Pascal Terrones, Humberto Wertz, Esther A. Terrones, Mauricio Fohtung, Edwin N’Gom, Moussa Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute TroyNY12180 United States Department of Physics The Pennsylvania State University University ParkPA16802 United States Department of Electrical Computer and Systems Engineering RPI TroyNY United States The Shirley Ann Jackson Ph.D. Center for Biotechnology and Interdisciplinary Studies RPI TroyNY United States Department of Materials Science and Engineering Rensselaer Polytechnic Institute TroyNY12180 United States RPI 6015 Low Center TroyNY United States Center for Ultrafast Optical Science University of Michigan Ann ArborMI48109-2102 United States

Two-dimensional Transition-Metal Dichalcogenides (TMDs) are of great interest for second harmonic (SH) generation due to their large second-order susceptibility (χ(2)), atomically thin structure, and relaxed phase-matching conditions. TMDs are also promising candidates for miniaturizing nonlinear optical devices due to their versatile applications in photon manipulation, quantum emission and sensing, and nanophotonic circuits. However, their strong SH response is limited by nanometer-scale light-matter interaction and material impurities. Although there is considerable work towards engineering TMDs for enhancing their nonlinear responses, all-optical methods are still in the exploration stages. In this work, we incorporate, to the best of our knowledge, the first experimental demonstrations of feedback-based wavefront shaping (WFS) techniques in atomically thin media to reveal and enhance the weak SH generation of monolayer WS2. Phase tuning of the incident wavefront leads to localized regions of high-intensity fundamental light, increasing the intensity of SH generation by up to an order of magnitude in targeted regions. We enhance the local conversion efficiencies from monolayer WS2 up to 41× from phase-only modulation. Furthermore, by introducing a shift in the transverse phase structure, we generate observable SH generation at the destructively interfering grain boundaries of polycrystalline monolayers. This method allows for all-optical tuning of TMDs nonlinear responses, opening up possibilities for dynamic signal routing and on-demand enhancement in nanoscale photonic systems. © 2025, CC BY.

关键词： Nonlinear optics

Machine Learning Reveals Composition Dependent Thermal Stability in Halide Perovskites

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arXiv 2025年

作者： Hering, Abigail R. Dubey, Mansha Hosseini, Elahe Srivastava, Meghna An, Yu Correa-Baena, Juan-Pablo Homayoun, Houman Leite, Marina S. Department of Materials Science and Engineering UC Davis Davis95616 United States Department of Electrical and Computer Engineering UC Davis Davis95616 United States School of Materials Science and Engineering Georgia Institute of Technology Atlanta30332 United States Department of Chemistry and Biochemistry Georgia Institute of Technology Atlanta30332 United States

Halide perovskites exhibit unpredictable properties in response to environmental stressors, due to several composition-dependent degradation mechanisms. In this work, we apply data visualization and machine learning (ML) techniques to reveal unexpected correlations between composition, temperature, and material properties while using high throughput, in situ environmental photoluminescence (PL) experiments. Correlation heatmaps show the strong influence of Cs content on film degradation, and dimensionality reduction visualization methods uncover clear composition-based data clusters. An extreme gradient boosting algorithm (XGBoost) effectively forecasts PL features for ten perovskite films with both composition-agnostic (>85% accuracy) and composition-dependent (>75% accuracy) model approaches, while elucidating the relative feature importance of composition (up to 99%). This model validates a previously unseen anti-correlation between Cs content and material thermal stability. Our ML-based framework can be expanded to any perovskite family, significantly reducing the analysis time currently employed to identify stable options for photovoltaics. Copyright © 2025, The Authors. All rights reserved.

关键词： Dimensionality reduction