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Magnetization reversal driven by electron localization-delocalization crossover in the inverse spinel Co2VO4

Physical Review B 2022年第9期105卷 094408-094408页

作者： Abhijit Bhat Kademane Churna Bhandari Durga Paudyal Stephen Cottrell Pinaki Das Yong Liu Yuen Yiu C. M. Naveen Kumar Konrad Siemensmeyer Andreas Hoser Diana Lucia Quintero-Castro David Vaknin Rasmus Toft-Petersen Department of Mathematics and Physics Universitetet i Stavanger 4036 Stavanger Norway Ames Laboratory Iowa State University Ames Iowa 50011 USA Department of Electrical and Computer Engineering Iowa State University Ames Iowa 50011 USA ISIS Facility STFC Rutherford Appleton Laboratory Harwell Science and Innovation Campus Chilton Didcot Oxon OX11 0QX United Kingdom Institute of Solid State Physics Vienna University of Technology Wiedner Hauptstrae 810 1040 Vienna Austria AGH University of Science and Technology Faculty of Physics and Applied Computer Science 30-059 Kraków Poland Helmholtz Zentrum Berlin für Materialien und Energie D-14109 Berlin Germany Department of Physics and Astronomy Iowa State University Ames Iowa 50011 USA Department of Physics Technical University of Denmark DK-2800 Kongens Lyngby Denmark European Spallation Source Partikelgatan 2 224 84 Lund Sweden

Neutron diffraction, magnetization, and muon spin relaxation measurements, supplemented by density functional theory (DFT) calculations are employed to unravel temperature-driven magnetization reversal in inverse spinel Co2VO4. All measurements show a second-order magnetic phase transition at TC=168K to a collinear ferrimagnetic phase. Neutron diffraction measurements reveal two antiparallel ferromagnetic (FM) sublattices, belonging to magnetic ions on two distinct crystal lattice sites, where the relative balance between the two sublattices determine the net FM moment in the unit cell. As the evolution of the ordered moment with temperature differs between the two sublattices, the net magnetic moment reaches a maximum at TNC=138K and reverses its sign at TMR=65K. The DFT results suggest that the underlying microscopic mechanism for the reversal is a delocalization of the unfilled 3d-shell electrons on one sublattice just below TC, followed by a gradual localization as the temperature is lowered. This delocalized-localized crossover is supported by muon spectroscopy results, as strong T1 relaxation observed below TC indicates fluctuating internal fields.

关键词： Density of states Ferrimagnetism Metal-insulator transition Oxides Spinels Density functional calculations Magnetization measurements Muon spin relaxation & rotation Neutron scattering

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Nonlinear behavior of memristive devices for hardware security primitives and neuromorphic computing systems

arXiv

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arXiv 2024年

作者： Yarragolla, Sahitya Hemke, Torben Jalled, Fares Gergs, Tobias Trieschmann, Jan Arul, Tolga Mussenbrock, Thomas Chair of Applied Electrodynamics and Plasma Technology Ruhr University Bochum Universitätsstraße 150 Bochum44780 Germany Theoretical Electrical Engineering Faculty of Engineering Kiel University Kaiserstraße 2 Kiel24143 Germany Kiel Nano Surface and Interface Science KiNSIS Kiel University Christian-Albrechts-Platz 4 Kiel24118 Germany Chair of Reliable Distributed Systems Faculty of Computer Science and Mathematics University of Passau PassauD-94032 Germany

Nonlinearity is a crucial characteristic for implementing hardware security primitives or neuromorphic computing systems. The main feature of all memristive devices is this nonlinear behavior observed in their current-voltage characteristics. To comprehend the nonlinear behavior, we have to understand the coexistence of resistive, capacitive, and inertia (virtual inductive) effects in these devices. These effects originate from corresponding physical and chemical processes in memristive devices. A physics-inspired compact model is employed to model and simulate interface-type RRAMs such as Au/BiFeO3/Pt/Ti, Au/NbxOy/Al2O3/Nb, while accounting for the modeling of capacitive and inertia effects. The simulated current-voltage characteristics align well with experimental data and accurately capture the non-zero crossing hysteresis generated by capacitive and inductive effects. This study examines the response of two devices to increasing frequencies, revealing a shift in their nonlinear behavior characterized by a reduced hysteresis range and increased chaotic behavior, as observed through internal state attractors. Fourier series analysis utilizing a sinusoidal input voltage of varying amplitudes and frequencies indicates harmonics or frequency components that considerably influence the functioning of RRAMs. Moreover, we propose and demonstrate the use of the frequency spectra as one of the fingerprints for memristive devices. Copyright © 2024, The Authors. All rights reserved.

关键词： Current voltage characteristics

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Waste plastics derived nickel-palladium alloy filled carbon nanotubes for hydrogen evolution reaction

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Chemosphere 2023年 341卷 139982页

作者： Nangan, Senthilkumar Natesan, Thirumalaivasan Sukmas, Wiwittawin Okhawilai, Manunya Justice Babu, Kaliyamoorthy Tsuppayakorn-aek, Prutthipong Bovornratanaraks, Thiti Wongsalam, Tawan Vimal, Vrince Uyama, Hiroshi Al-Enizi, Abdullah M. Kansal, Lavish Sehgal, Satbir S. Metallurgy and Materials Science Research Institute Chulalongkorn University Bangkok10330 Thailand Saveetha University Tamilnadu Chennai600077 India Center of Excellence in Polymeric Materials for Medical Practice Devices Department of Chemical Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand Institute of Nano Science and Technology Punjab Mohali140306 India Department of Physics Faculty of Science Chulalongkorn University Bangkok10330 Thailand Computer Science and Engineering Graphic Era Deemed to be University Dehradun248002 India Department of Applied Chemistry Graduate School of Engineering Osaka University Osaka565-0871 Japan Department of Chemistry College of Science King Saud University Riyadh11451 Saudi Arabia School Electronics and Electrical Engineering Lovely Professional University Punjab Phagwara144411 India Division of Research Innovation Uttaranchal University Dehradun India

Carbon nanotubes (CNTs) composed of bimetallic nickel-palladium (NiPd) nanoparticles encapsulated in graphitic carbon shells (NdPd@CNT) are prepared by the chemical vapour deposition method using waste polyethylene terephthalate (PET) plastic carbon sources and NiPd-decorated carbon sheets (NiPd@C) catalyst. The characterization results reveal that the face-centered cubic crystalline (fcc)-structured NiPd bimetallic alloy nanoparticles are encased by thin carbon nanotubes. The bimetallic synergism of NiPd nanoparticles actuates the outer CNT layers and accelerates the electrical conductivity, stimulating the electrochemical activity toward an effective hydrogen evolution reaction (HER). By virtue of the collective individualities of highly conductive aligned carbon walls and bimetallic active sites, the NiPd@CNT-equipped HER delivers a minimum overpotential of 87 mV and a Tafel slope value of 95 mV dec−1. The existing intact contact between NiPd and CNT facilitates continuous electron and ion transportation and firm stability toward long-term hydrogen production in HER. Notably, the NiPd@CNT reported here produces excellent electrochemical activity with minimal charge transference resistance, substantiating the efficacy of NiPd@CNT for futuristic green hydrogen production. © 2023 Elsevier Ltd

关键词： Carbon nanotubes

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RECOMED: A Comprehensive Pharmaceutical Recommendation System

arXiv

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arXiv 2022年

作者： Zomorodi, Mariam Ghodsollahee, Ismail Martin, Jennifer H. Talley, Nicholas J. Salari, Vahid Plawiak, Pawel Rahimi, Kazem Acharya, U. Rajendra Department of Computer Science Faculty of Computer Science and Telecommunications Cracow University of Technology Krakow Poland Department of Computer Engineering Ferdowsi University of Mashhad Iran The University of Newcastle CallaghanNSW Australia Institute for Quantum Science and Technology Department of Physics and Astronomy University of Calgary Alberta Canada Institute of Theoretical and Applied Informatics Polish Academy of Sciences Gliwice Poland Deep Medicine Nuffield Department of Women’s and Reproductive Health University of Oxford Oxford United Kingdom School of Mathematics Physics and Computing University of Southern Queensland ToowoombaQLD Australia

OBJECTIVES: To build datasets containing useful information from drug databases and recommend a list of drugs to physicians and patients with high accuracy by considering features of a spectrum of people, diseases, and chemicals. METHODS: A comprehensive pharmaceutical recommendation system was designed based on the features of a spectrum of people, diseases, and medicines extracted from two major drug databases, a dataset of patients and drug information. Then the recommendation was given, and the response was analysed using patient and caregiver ratings and the knowledge obtained from drug specifications and interactions. Sentiment analysis was employed by natural language processing approaches in pre-processing, along with neural network-based methods and recommender system algorithms for modelling the system. Patient conditions and medicine features were used for making two models based on matrix factorisation. Then we used drug interaction criteria to filter drugs with severe or mild interactions with other drugs. We developed a deep learning model for recommending drugs by using data from 2304 patients as a training set, and then we used data from 660 patients as our validation set. We used knowledge from critical drug information and combined the model’s outcome into a knowledge-based system with the rules obtained from constraints on taking medicine. RESULTS: The results show that our recommendation system can recommend an acceptable combination of medicines according to the existing real-life prescriptions available. Compared with conventional matrix factorisation, our proposed model improves the accuracy, sensitivity, and hit rate by 26%, 34%, and 40%, respectively. In addition, it improves the accuracy, sensitivity, and hit rate by an average of 31%, 29%, and 28% compared to other machine learning methods. We have open-sourced our implementation in Python. CONCLUSION: Compared to conventional machine learning approaches, we obtained average accuracy, sens

关键词： Recommender systems

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Exploiting Optical Nonlinear Temporal Coupling for Implementing Physical Unclonable Functions

Exploiting Optical Nonlinear Temporal Coupling for Implement...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Stavros G. Stavrinides Lydia Bush-Espinosa Carol de Benito Nikolaos Athanasios Anagnostopoulos Tolga Arul Stefan Katzenbeisser Christos Tjortjis M. Moner Al Chawa Rodrigo Picos Physics Department International Hellenic University Kavala Greece Industrial Engineering Department Universitat de les Illes Balears Palma Spain Faculty of Computer Science and Mathematics University of Passau Passau Germany School of Science and Technology International Hellenic University Thessaloniki Greece Institute of Circuits and Systems Technical University Dresden Dresden Germany

ISBN: (数字)9798350311617

ISBN: (纸本)9798350311624

In this work, we study the possibility of utilizing an LED-LDR pair for generating a Physical Unclonable Function. Towards this, the nonlinear response between an optically cou-pled LED-LDR pair, as well as the dynamic behavior of the LDR, were considered. The resulting behavior was highly nonlinear and strongly dependent on the actual physical properties of the components. We tested the idea using different LEDs (red, green, and blue; two of each color), and an LDR. Using a low-cost system (an Arduino development board), we showed that although the static response is very linear, the dynamic response is highly unpredictable, when the system is driven by random values. However, this response is identical for the same LED-LDR pairs, but different for other combinations. Additionally, the described behavior is fully repeatable. Thus, a low-cost PUF can be created using these simple components, allowing not only discrimination of the LED's color, but also for the creation of a digital fingerprint as well as authentication/verification.

关键词： Resistors Resistance Color Fingerprint recognition Physical unclonable function Light emitting diodes Nonlinear optical devices

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Effective Techniques Non-linear Dynamic Model Calibration using CNN

Effective Techniques Non-linear Dynamic Model Calibration us...

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Computing, Power and Communication Technologies (IC2PCT), IEEE International Conference on

作者： Malmarugan Devanathan D Prasannan Pooja Singh Oluwadare Joshua H Adity Pai Pankaj Jakhar Christ University Bengaluru Karnataka India Department of Civil Engineering Karpagam College of Engineering Coimbatore India Department of Physics Faculty of Science SGT University Gurugram India Civil and Environmental Engineering Afe Babalola University Ado-Ekiti Ekiti Nigeria Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Indian Institute of Technology Jodhpur Jodhpur Rajasthan India

This paper proposes an efficient method to estimate nonlinear dynamic models using convolutional neural networks (CNNs). The proposed method combines the power of statistical optimization and machine learning to obtain more accurate and efficient estimates of complex models by training CNNs to recognize maps featuring input models and between results, thereby reducing the computational cost of measurements and then using the trained CNN to generate surrogate models -The method can determine accuracy for a range of exposed cases in various nonlinear dynamic models, including differential equation model of chemical reactor and stochastic model of biological systems The results show that the proposed methods are effective for measuring these models, if at most with such accuracy and reducing the computational cost in terms of both frequency and magnitude, the proposed method represents a promising method for estimating nonlinear dynamic models, offering significant advantages in terms of accuracy, efficiency and in scalability

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LIGHT-BY-LIGHT SCATTERING CROSS-SECTION MEASUREMENTS AT THE LHC

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Acta Physica Polonica B 2023年第1期16卷

作者： Krintiras, G.K. Grabowska-Bold, I. Klusek-Gawenda, M. Chapon, É. Chudasama, R. Granier de Cassagnac, R. Department of Physics and Astronomy The University of Kansas Malott Hall 1251 Wescoe Hall Dr. LawrenceKS66045 United States Department of Physics and Applied Computer Science AGH University of Science and Technology Al. Mickiewicza 30 Kraków30-059 Poland Institute of Nuclear Physics Polish Academy of Sciences Radzikowskiego 152 Kraków31-342 Poland IRFU CEA Université Paris-Saclay Gif-sur-Yvette France Department of High Energy Physics Tata Institute of Fundamental Research Mumbai400005 India Laboratoire Leprince-Ringuet Ecole Polytechnique CNRS IN2P3 Palaiseau France

Light-by-light (LbyL) scattering, γγ → γγ, is a rare Standard Model (SM) process, also proposed as a sensitive channel to study physics beyond the SM. In these proceedings, we perform a statistical combination of existing γγ → γγ cross section measurements at the LHC with the aim of checking the consistency with different SM predictions. Using a simplified set of assumptions, we find the averaged result of 115 ± 19 nb, consistent with SM predictions within two standard deviations. For the first time, we also consider the contribution from the ηb(1S) meson production to the diphoton invariant mass distribution. © 2023 Jagiellonian university. All rights reserved.

关键词： Light scattering

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Quasi Q-Balls in massless scalar fields

arXiv

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arXiv 2025年

作者： Romańczukiewicz, Tomasz Shnir, Yakov Faculty of Theoretical Physics Astronomy and Applied Computer Science Jagiellonian University Kraków Poland Instituto de Física de São Carlos IFSC/USP Universidade de São Paulo USP Caixa Postal 369 São Carlos-SPCEP 13560-970 Brazil

We study long-term evolution of radiating quasi-Q-balls in 1+1 dimensional models without mass threshold. Two different models are considered, the model with a rational modification of the usual Q-ball sextic potential and the model of a Q-ball in a box with outgoing boundary conditions. We find that the outgoing boundary conditions modify the angular frequency of quasi-Q-balls which becomes complex-valued. The quasi-Q-balls decay initially very similarly, but in the last stage quasi-Q-balls in a box become linear resonances, whereas in the rationally modified model, they decay according to some power law. © 2025, CC BY.

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Observation of the J/ψ→μ+μ−μ+μ− decay in proton-proton collisions at s=13 TeV

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Physical Review D 2024年第11期109卷 L111101-L111101页

作者： A. Hayrapetyan A. Tumasyan W. Adam J. W. Andrejkovic T. Bergauer S. Chatterjee K. Damanakis M. Dragicevic P. S. Hussain M. Jeitler N. Krammer A. Li D. Liko I. Mikulec J. Schieck R. Schöfbeck D. Schwarz M. Sonawane S. Templ W. Waltenberger C.-E. Wulz M. R. Darwish T. Janssen P. Van Mechelen N. Breugelmans J. D’Hondt S. Dansana A. De Moor M. Delcourt F. Heyen S. Lowette I. Makarenko D. Müller S. Tavernier M. Tytgat G. P. Van Onsem S. Van Putte D. Vannerom B. Clerbaux A. K. Das G. De Lentdecker H. Evard L. Favart P. Gianneios D. Hohov J. Jaramillo A. Khalilzadeh F. A. Khan K. Lee M. Mahdavikhorrami A. Malara S. Paredes M. A. Shahzad L. Thomas M. Vanden Bemden C. Vander Velde P. Vanlaer M. De Coen D. Dobur G. Gokbulut Y. Hong J. Knolle L. Lambrecht D. Marckx G. Mestdach K. Mota Amarilo A. Samalan K. Skovpen N. Van Den Bossche J. van der Linden L. Wezenbeek A. Benecke A. Bethani G. Bruno C. Caputo J. De Favereau De Jeneret C. Delaere I. S. Donertas A. Giammanco A. O. Guzel Sa. Jain V. Lemaitre J. Lidrych P. Mastrapasqua T. T. Tran S. Wertz G. A. Alves M. Alves Gallo Pereira E. Coelho G. Correia Silva C. Hensel T. Menezes De Oliveira A. Moraes P. Rebello Teles M. Soeiro A. Vilela Pereira W. L. Aldá Júnior M. Barroso Ferreira Filho H. Brandao Malbouisson W. Carvalho J. Chinellato E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao S. Fonseca De Souza R. Gomes De Souza M. Macedo J. Martins C. Mora Herrera L. Mundim H. Nogima J. P. Pinheiro A. Santoro A. Sznajder M. Thiel C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores I. Maietto Silverio P. G. Mercadante S. F. Novaes B. Orzari Sandra S. Padula A. Aleksandrov G. Antchev R. Hadjiiska P. Iaydjiev M. Misheva M. Shopova G. Sultanov A. Dimitrov L. Litov B. Pavlov P. Petkov A. Petrov E. Shumka S. Keshri S. Thakur T. Cheng T. Javaid L. Yuan Z. Hu Z. Liang J. Liu K. Yi G. M. Chen H. S. Chen M. Chen F. Iemmi C. H. Jiang A. Kapoor H. Liao Z.-A. Liu R. Sharma J. N. Song J. Tao C. Wang J. Wang Z. Wang H. Zhang J. Zhao A. Agapitos Y. Ban S. Deng B. Guo C. Jian Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Indian Institute of Technology Madras Madras India Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Korea University Seoul Korea Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China California Institute of Technology Pasadena California USA University of Florida Gainesville Florida USA Massachusetts Institute of Technology Cambridge Massachusetts USA State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Deutsches Elektronen-Synchrotron Hamburg Germany Kyung Hee University Department of Physics Seoul Korea Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University Nanjing China Florida State University Tallahassee Florida USA Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE)—Fudan University Shanghai China Zhejiang University Hangzhou Zhejiang China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of C

The J/ψ→μ+μ−μ+μ− decay has been observed with a statistical significance in excess of five standard deviations. The analysis is based on an event sample of proton-proton collisions at a center-of-mass energy of 13 TeV, collected by the CMS experiment in 2018 and corresponding to an integrated luminosity of 33.6 fb−1. Normalizing to the J/ψ→μ+μ− decay mode leads to a branching fraction of [10.1−2.7+3.3(stat)±0.4(syst)]×10−7, a value that is consistent with the standard model prediction.

关键词： Muons Quarkonia Hadron colliders

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Vision Transformer for Parkinson’s Disease Classification using Multilingual Sustained Vowel Recordings

Vision Transformer for Parkinson’s Disease Classification u...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Daria Hemmerling Marek Wodzinski Juan Rafael Orozco-Arroyave David Sztaho Mateusz Daniol Pawel Jemiolo Magdalena Wojcik-Pedziwiatr Daria Hemmerling Marek Wodzinski Mateusz Daniol and Pawel Jemiolo are With the AGH University of Science and Technology Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Krakow Poland Information Systems Institute University of Applied Sciences Western Switzerland (HES-SO Valais) Sierre Switzerland Universidad de Antioquia Medellin Colombia and With the Pattern Recognition Lab at the University of Erlangen Erlangen Germany Department of Telecommunications and Media Informatics Budapest University of Technology and Economics Hungary Department of Neurology Andrzej Frycz Modrzewski Krakow University Krakow Poland

Parkinson’s disease (PD) is the 2 nd most prevalent neurodegenerative disease in the world. Thus, the early detection of PD has recently been the subject of several scientific and commercial studies. In this paper, we propose a pipeline using Vision Transformer applied to mel-spectrograms for PD classification using multilingual sustained vowel recordings. Furthermore, our proposed transformed-based model shows a great potential to use voice as a single modality biomarker for automatic PD detection without language restrictions, a wide range of vowels, with an F1-score equal to 0.78. The results of our study fall within the range of the estimated prevalence of voice and speech disorders in Parkinson’s disease, which ranges from 70-90%. Our study demonstrates a high potential for adaptation in clinical decision-making, allowing for increasingly systematic and fast diagnosis of PD with the potential for use in *** relevance— There is an urgent need to develop non invasive biomarker of Parkinson’s disease effective enough to detect the onset of the disease to introduce neuroprotective treatment at the earliest stage possible and to follow the results of that intervention. Voice disorders in PD are very frequent and are expected to be utilized as an early diagnostic biomarker. The voice analysis using deep neural networks open new opportunities to assess neurodegenerative diseases’ symptoms, for fast diagnosis-making, to guide treatment initiation, and risk prediction. The detection accuracy for voice biomarkers according to our method reached close to the maximum achievable value.

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