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Extraction of bioactive compounds from Moringa oleifera leaves using different organic solvents

AIP Conference Proceedings 2023年第1期2601卷

作者： Madeeha Sadia Fazilah Abd Manan Norjihada Izzah Ismail Saravana Kumar Jaganathan Syafiqah Saidin School of Biomedical Engineering and Health Sciences Faculty of Engineering Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia Department of Biomedical Engineering Faculty of Electrical and Computer Engineering NED University of Engineering and Technology Karachi Pakistan Department of Biosciences Faculty of Science Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia Medical devices and Technology Centre Institute of Human Centered Engineering Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia Department of Engineering Faculty of Science and Engineering University of Hull United Kingdom Faculty of Applied Sciences Ton Duc Thang University Ho Chi Minh City Vietnam IJN-UTM Cardiovascular Engineering Centre Institute of Human Centered Engineering Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia

Flavonoid and phenolic contents present in plant leaves play a vital role in different therapeutic applications. They are also known as the most obstinate groups of plant phenolic (bioactive compounds). The leaves of Moringa oleifera (M. oleifera) contain different bioactive constituents that are valuable for remedial purposes. This study aimed to quantitatively identify and assess bioactive compounds in M. oleifera leaves extract that were discovered from different crude solvents using a maceration method. Total phenolic content (TPC) and total flavonoid content (TFC) were quantified by Folin-Ciocalteu and Aluminum chloride methods, respectively. It was noticed that by using the maceration method, 58% percentage yield was recorded in the methanolic leaves extract. The TPC (3.57±0.12 mg GAE/g) and TFC (10.83±2.73 mg QE/g) results showed, the methanolic leaves extract has attained significant maximum concentration of phenolic bioactive compounds (p≤0.05) in comparison to the ethanol and acetone leaves extract. Two important tangible aspects that have influenced the quantified results of bioactive compounds in this study were the selection of its characterization and extraction methods. Therefore, it can be concluded that methanol is a suitable solvent choice for the extraction of bioactive compounds from M. oleifera leaves.

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Monitoring Cardiac Biomarkers with Aptamer-Based Molecular Pendulum Sensors

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Angewandte Chemie 2023年第20期135卷

作者： Alam Mahmud Dr. Dingran Chang Prof. Jagotamoy Das Dr. Surath Gomis Farid Foroutan Dr. Jenise B. Chen Laxman Pandey Connor D. Flynn Hanie Yousefi Armin Geraili Prof. Heather J. Ross Prof. Edward H. Sargent Prof. Shana O. Kelley Department of Electrical and Computer Engineering Faculty of Applied Science & Engineering University of Toronto Toronto ON Canada Department of Pharmaceutical Sciences Leslie Dan Faculty of Pharmacy University of Toronto Toronto ON Canada Department of Chemistry Weinberg College of Arts and Sciences Northwestern University Evanston IL USA Ted Rogers Centre for Heart Research Toronto ON Canada Department of Chemistry Faculty of Arts & Science University of Toronto Toronto ON Canada Department of Biomedical Engineering McCormick School of Engineering Northwestern University Evanston IL USA Chan Zuckerberg Biohub Chicago Chicago IL USA

Reagent-free electronic biosensors capable of analyzing disease markers directly in unprocessed body fluids will enable the development of simple & affordable devices for personalized healthcare monitoring. Here we report a powerful and versatile nucleic acid-based reagent-free electronic sensing system. The signal transduction is based on the kinetics of an electrode-tethered molecular pendulum—a rigid double stranded DNA with one of the strands displaying an analyte-binding aptamer and the other featuring a redox probe—that exhibits field-induced transport modulated by receptor occupancy. Using chronoamperometry, which enables the sensor to circumvent the conventional Debye length limitation, the binding of an analyte can be monitored as these species increase the hydrodynamic drag. The sensing platform demonstrates a low femtomolar quantification limit and minimal cross-reactivity in analyzing cardiac biomarkers in whole blood collected from patients with chronic heart failure.

关键词： Aptamers Cardiac Diseases Molecular Pendulum Multiplexed Biosensing Reagent-Free Biosensing

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Terahertz Inverse Spin Hall Effect in Spintronic Nanostructures

SSRN

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SSRN 2023年

作者： Cheng, Jing Komissarov, Ivan Chen, Genyu Adam, Roman Chaktraborty, Debamitra Bürgler, Daniel E. Heidtfeld, Sarah Cao, Derang Büscher, Markus Hardtdegen, Hilde Mikulics, Martin Schneider, Claus Michael Gladczuk, Leszek Przyslupski, Piotr Sobolewski, Roman Materials Science Program University of Rochester RochesterNY14627-1299 United States Laboratory for Laser Energetics University of Rochester RochesterNY14623 United States Department of Electrical and Computer Engineering University of Rochester RochesterNY14627-0231 United States Research Centre Jülich Peter Grünberg Institute Jülich52425 Germany Faculty of Physics University Duisburg-Essen Duisburg47048 Germany College of Physics Center for Marine Observation and Communications National Demonstration Center for Experimental Applied Physics Education Qingdao University Qingdao266071 China Research Centre Jülich Ernst Ruska Centre for Microscopy and Spectroscopy With Electrons Jülich52425 Germany Department of Physics University of California Davis DavisCA95616-5270 United States Institute of Physics Polish Academy of Sciences WarszawaPL-02668 Poland Department of Physics and Astronomy University of Rochester RochesterNY14627-0171 United States

Bilayers of ferromagnetic and heavy metal nanolayers excited with femtosecond laser pulses emit subpicosecond bursts of electromagnetic radiation with spectral frequencies up to several THz. We fabricated such spintronic THz emitters containing various ferromagnetic materials with vastly different magnetic remanence, saturation magnetization, and coercive field. In all cases, the THz amplitude versus magnetic field dependence follows the independently measured magnetization hysteresis loops and the THz polarization direction is perpendicular to the sample’s magnetization M, both consistent with the inverse spin Hall effect as physical origin. The M(T) variation governs the temperature dependence of the THz generation. Emitters with weakly remanent ferromagnets are field-tunable, while moderately and strongly remanent ferromagnets, once magnetized, allow intense THz generation even without an external field, nevertheless exhibiting low susceptibility to magnetic perturbations, if the hysteresis loop is square. Hence, exploiting the magnetic properties of the ferromagnetic layer enables tailoring of weakly temperature-dependent spintronic THz emitters. Finally, we explored the applicability of perovskite oxide materials such as La-Sr-Mn-O (LSMO) for THz transient generation. Although we detected THz emissions from, e.g., LSMO/Au nanobilayers, the signal was attributed to the ultrafast transient demagnetization and not the inverse spin Hall effect. © 2023, The Authors. All rights reserved.

关键词： Nanostructures

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Fully automatic estimation of global left ventricular systolic function using deep learning in transoesophageal echocardiography

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European heart journal. Imaging methods and practice 2023年第1期1卷 qyad007页

作者： Erik Andreas Rye Berg Anders Austlid Taskén Trym Nordal Bjørnar Grenne Torvald Espeland Idar Kirkeby-Garstad Håvard Dalen Espen Holte Stian Stølen Svend Aakhus Gabriel Kiss Centre for Innovative Ultrasound Solutions Department of Circulation and Medical Imaging Faculty of Medicine and Health Science Norwegian University of Science and Technology Prinsesse Kristinas gate 3 Trondheim 7030 Norway. Department of Circulation and Medical Imaging Faculty of Medicine and Health Science Norwegian University of Science and Technology Prinsesse Kristinas gate 3 Trondheim 7030 Norway. Clinic of Cardiology St Olavs Hospital Trondheim University Hospital Prinsesse Kristinas gate 3 Trondheim 7030 Norway. Department of Computer Science Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Trondheim 7034 Norway. Department of Engineering Cybernetics Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Trondheim 7034 Norway. Department of Anaesthesiology and Intensive Care Medicine St Olavs Hospital Trondheim University Hospital Trondheim 7030 Norway.

Aims:To improve monitoring of cardiac function during major surgery and intensive care, we have developed a method for fully automatic estimation of mitral annular plane systolic excursion (auto-MAPSE) using deep learning in transoesophageal echocardiography (TOE). The aim of this study was a clinical validation of auto-MAPSE in patients with heart disease. Methods and results:TOE recordings were collected from 185 consecutive patients without selection on image quality. Deep-learning-based auto-MAPSE was trained and optimized from 105 patient recordings. We assessed auto-MAPSE feasibility, and agreement and inter-rater reliability with manual reference in 80 patients with and without electrocardiogram (ECG) tracings. Mean processing time for auto-MAPSE was 0.3 s per cardiac cycle/view. Overall feasibility was >90% for manual MAPSE and ECG-enabled auto-MAPSE and 82% for ECG-disabled auto-MAPSE. Feasibility in at least two walls was ≥95% for all methods. Compared with manual reference, bias [95% limits of agreement (LoA)] was -0.5 [-4.0, 3.1] mm for ECG-enabled auto-MAPSE and -0.2 [-4.2, 3.6] mm for ECG-disabled auto-MAPSE. Intra-class correlation coefficient (ICC) for consistency was 0.90 and 0.88, respectively. Manual inter-observer bias [95% LoA] was -0.9 [-4.7, 3.0] mm, and ICC was 0.86. Conclusion:Auto-MAPSE was fast and highly feasible. Inter-rater reliability between auto-MAPSE and manual reference was good. Agreement between auto-MAPSE and manual reference did not differ from manual inter-observer agreement. As the principal advantages of deep-learning-based assessment are speed and reproducibility, auto-MAPSE has the potential to improve real-time monitoring of left ventricular function. This should be investigated in relevant clinical settings.

关键词： artificial intelligence deep learning mitral annular plane systolic excursion monitoring systolic function transoesophageal echocardiography

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Hesitant bipolar fuzzy set-based decision system for electric vehicle charging station location planning

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Sustainable Energy, Grids and Networks 2025年 43卷

作者： Chakkarapani Sumathi Thilagasree Thippan Jayakumar Lakshmanaraj Ramya Krishnan Suvitha Dragan Pamucar Witold Pedrycz Joseph Varghese Kureethara Department of Mathematics Sri Ramakrishna Mission Vidyalaya College of Arts and Science Coimbatore India Department of Mathematics Bharathiar University Coimbatore 641 046 India Centre for Nonlinear Systems Chennai Institute of Technology Chennai Tamilnadu India Department of Applied Mathematical Science College of Science and Technology Korea University Sejong Republic of Korea Yuan Ze University College of Engineering Department of Industrial Engineering and Managemente Taoyuan City Taiwan Industrial Engineering Department Faculty of Engineering and Natural Sciences İstinye University İstanbul Türkiye Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Department of Mathematics CHRIST (Deemed to be University) Bangalore India

The selection of electric vehicle (EV) charging station locations is a critical challenge that significantly affects the growth and acceptance of the EV industry. As EVs offer a sustainable solution to fossil fuel depletion and environmental pollution, identifying optimal charging station sites involves dealing with uncertain, inconsistent, and conflicting criteria. To address these challenges, this paper presents an innovative decision-making framework based on Hesitant Bipolar-Valued Fuzzy Sets (HBVFSs), which account for both positive and negative hesitant membership values to better model uncertainty in expert judgments. A novel hybrid Multi-Criteria Decision-Making (MCDM) technique is proposed, combining the Step-wise Weight Assessment Ratio Analysis (SWARA) and Pivot Pairwise Relative Criteria Importance Assessment (PIPRECIA) methods to determine robust criteria weights within the HBVFS environment. The Preference Ranking Organization METHod for Enrichment Evaluation II (PROMETHEE-II) is employed for the final site ranking. This integrated approach enables a more comprehensive and reliable evaluation of potential locations by incorporating both qualitative and quantitative factors. The proposed methodology has practical applications in real-world infrastructure planning and supports more resilient decision-making in sustainable transportation networks. The results demonstrate the model’s effectiveness and adaptability in addressing the site selection problem under uncertainty.

关键词： Bipolar fuzzy set Electric vehicle Hesitant fuzzy set Multi-criteria decision-making Site selection

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The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue

arXiv

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arXiv 2023年

作者： Weitz, Philippe Valkonen, Masi Solorzano, Leslie Carr, Circe Kartasalo, Kimmo Boissin, Constance Koivukoski, Sonja Kuusela, Aino Rasic, Dusan Feng, Yanbo Pouplier, Sandra Sinius Sharma, Abhinav Eriksson, Kajsa Ledesma Robertson, Stephanie Marzahl, Christian Gatenbee, Chandler D. Anderson, Alexander R.A. Wodzinski, Marek Jurgas, Artur Marini, Niccolò Atzori, Manfredo Müller, Henning Budelmann, Daniel Weiss, Nick Heldmann, Stefan Lotz, Johannes Wolterink, Jelmer M. De Santi, Bruno Patil, Abhijeet Sethi, Amit Kondo, Satoshi Kasai, Satoshi Hirasawa, Kousuke Farrokh, Mahtab Kumar, Neeraj Greiner, Russell Latonen, Leena Laenkholm, Anne-Vibeke Hartman, Johan Ruusuvuori, Pekka Rantalainen, Mattias Department of Medical Epidemiology and Biostatistics Karolinska Insitutet Stockholm Sweden Institute of Biomedicine University of Turku Turku Finland Institute of Biomedicine University of Eastern Finland Kuopio Finland Department of Surgical Pathology Zealand University Hospital Roskilde Denmark Department of Oncology and Pathology Karolinska Institutet Stockholm Sweden Gestalt Diagnostics Spokane United States Department of Integrated Mathematical Oncology Moffitt Cancer Center Tampa United States Informatics Institute University of Applied Sciences Western Switzerland Switzerland Department of Measurement and Electronics Agh University of Kraków Poland Department of Computer Science University of Geneva Geneva Switzerland Department of Neuroscience University of Padova Italy Medical Faculty University of Geneva Switzerland Fraunhofer Institute for Digital Medicine Mevis Lübeck Germany Department of Applied Mathematics Technical Medical Centre University of Twente Enschede Netherlands Multimodality Medical Imaging Technical Medical Centre University of Twente Enschede Netherlands Department of Electrical Engineering Indian Institute of Technology Bombay India Graduate School of Engineering Muroran Institute of Technology Hokkaido Japan Faculty of Medical Technology Niigata University of Health and Welfare Niigata Japan Forxai Business Operations Konica Minolta Inc. Osaka Japan Department of Computing Science University of Alberta EdmontonAB Canada Alberta Machine Intelligence Institute Edmonton Canada MedTechLabs BioClinicum Karolinska University Hospital Stockholm Sweden Faculty of Medicine and Health Technology Tampere University Tampere Finland

The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability of large WSI datasets have revolutionised WSI analysis. Therefore, the current state-of-the-art in WSI registration is unclear. To address this, we conducted the ACROBAT challenge, based on the largest WSI registration dataset to date, including 4,212 WSIs from 1,152 breast cancer patients. The challenge objective was to align WSIs of tissue that was stained with routine diagnostic immunohistochemistry to its H&E-stained counterpart. We compare the performance of eight WSI registration algorithms, including an investigation of the impact of different WSI properties and clinical covariates. We find that conceptually distinct WSI registration methods can lead to highly accurate registration performances and identify covariates that impact performances across methods. These results establish the current state-of-the-art in WSI registration and guide researchers in selecting and developing methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Tissue

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A novel deep learning framework with artificial protozoa optimization-based adaptive environmental response for wind power prediction

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Scientific reports 2025年第1期15卷 18746页

作者： Sangkeum Lee Mohammad H Almomani Saleh Ali Alomari Kashif Saleem Aseel Smerat Vaclav Snasel Amir H Gandomi Laith Abualigah Department of Computer Engineering Hanbat National University 125 Dongseo-daero Yuseong-gu Daejeon Republic of Korea. Department of Mathematics Facility of Science The Hashemite University P.O box 330127 13133 Zarqa Jordan. Faculty of Science and Information Technology Jadara University 21110 Irbid Jordan. Department of Computer Science & Engineering College of Applied Studies & Community Service King Saud University 11362 Riyadh Saudi Arabia. Faculty of Educational Sciences Al-Ahliyya Amman University 19328 Amman Jordan. smerat.2020@***. Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University 140401 Rajpura Punjab India. smerat.2020@***. Computer Technologies Engineering Mazaya University College Nasiriyah Iraq. smerat.2020@***. Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava 70800 Poruba-Ostrava Czech Republic. Faculty of Engineering and Information Technology University of Technology Sydney 2007 Ultimo NSW Australia. gandomi@uni-obuda.hu. University Research and Innovation Center (EKIK) Óbuda University 1034 Budapest Hungary. gandomi@uni-obuda.hu. Department of Computer Science Khazar University Baku Azerbaijan. gandomi@uni-obuda.hu. Computer Science Department Al al-Bayt University 25113 Mafraq Jordan.

Accurate very short-term wind power forecasting is critical for the reliable integration of renewable energy into modern power systems. However, the inherent variability and non-linearity of wind power data pose significant challenges. To address these, this study proposes a novel hybrid deep learning framework, IAPO-LSTM, which combines Convolutional Neural Networks (CNNs) for spatial feature extraction and Gated Recurrent Units (GRUs) for temporal sequence modeling. The model is optimized using an enhanced Artificial Protozoa Optimizer (IAPO) augmented with an Adaptive Environmental Response Mechanism (AERM), which dynamically adjusts exploration and exploitation strategies based on the problem landscape to improve convergence and hyperparameter tuning efficiency. The proposed IAPO-LSTM model was evaluated on four real-world datasets-NREL WIND, EMD WIND, WWSIS, and ERCOT GRID-and benchmarked against six state-of-the-art forecasting models. Results demonstrate that IAPO-LSTM achieved the lowest forecasting errors across all datasets, with Mean Absolute Error (MAE) as low as 2.78, Root Mean Square Error (RMSE) of 4.50, and Theil's Inequality Coefficient (TIC) of 0.0292 on the ERCOT dataset. Additionally, the model demonstrated faster inference times and better statistical significance (p < 0.005) compared to baseline methods. These outcomes confirm that IAPO-LSTM is not only highly accurate but also efficient and robust for real-time wind power forecasting applications.

关键词： Adaptive environmental response mechanism Artificial Protozoa optimizer Hybrid deep learning Renewable energy integration Time series prediction Wind power forecasting

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Antenna Array Enabled Space/Air/Ground Communications and Networking for 6G

arXiv

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arXiv 2021年

作者： Xiao, Zhenyu Han, Zhu Nallanathan, Arumugam Dobre, Octavia A. Clerckx, Bruno Choi, Jinho He, Chong Tong, Wen The School of Electronic and Information Engineering Beihang University Beijing100191 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of The School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom The Faculty of Engineering and Applied Science Memorial University St. John’sNLA1C 5S7 Canada The Communications and Signal Processing Group Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom The School of Information Technology Deakin University GeelongVIC3220 Australia The Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China The Wireless Advanced System Competency Centre Huawei Technologies Co. Ltd. OttawaONK2K 3J1 Canada

Antenna arrays have a long history of more than 100 years and have evolved closely with the development of electronic and information technologies, playing an indispensable role in wireless communications and radar. With the rapid development of electronic and information technologies, the demand for all-time, all-domain, and full-space network services has exploded, and new communication requirements have been put forward on various space/air/ground platforms. To meet the ever increasing requirements of the future sixth generation (6G) wireless communications, such as high capacity, wide coverage, low latency, and strong robustness, it is promising to employ different types of antenna arrays (e.g., phased arrays, digital arrays, and reconfigurable intelligent surfaces, etc.) with various beamforming technologies (e.g., analog beamforming, digital beamforming, hybrid beamforming, and passive beamforming, etc.) in space/air/ground communication networks, bringing in advantages such as considerable antenna gains, multiplexing gains, and diversity gains. However, enabling antenna array for space/air/ground communication networks poses specific, distinctive and tricky challenges, which has aroused extensive research attention. This paper aims to overview the field of antenna array enabled space/air/ground communications and networking. The technical potentials and challenges of antenna array enabled space/air/ground communications and networking are presented first. Subsequently, the antenna array structures and designs are discussed. We then discuss various emerging technologies facilitated by antenna arrays to meet the new communication requirements of space/air/ground communication systems. Enabled by these emerging technologies, the distinct characteristics, challenges, and solutions for space communications, airborne communications, and ground communications are reviewed. Finally, we present promising directions for future research in antenna array enabled space/ai

关键词： Beamforming

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A decentralized power injection-based approach for voltage imbalance mitigation in three-phase distribution networks

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Scientific Reports 2025年第1期15卷 1-21页

作者： Tsobze, Saatong Kenfack Mbasso, Wulfran Fendzi Harrison, Ambe Khishe, Mohammad Dagal, Idriss Jangir, Pradeep Smerat, Aseel Al-Gahtani, Saad F. Elbarbary, Z.M.S. Unité de Recherche d’Automatique et d’Informatique Appliquée I.U.T. Fotso Victor University of Dschang P.O. Box 134 Bandjoun Cameroon Technology and Applied Sciences Laboratory U.I.T. of Douala University of Douala P.O. Box 8689 Douala Cameroon Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai 602 105 India Department of Electrical and Electronics Engineering College of Technology (COT) University of Buea P.O. Box Buea 63 Buea Cameroon Department of Electrical Engineering Imam Khomeini Naval Science University of Nowshahr Nowshahr Iran Beykent University Istanbul Turkey University Centre for Research and Development Chandigarh University Gharuan Mohali 140413 India Innovation Center for Artificial Intelligence Applications Yuan Ze University Taoyuan 320315 Taiwan Department of Electrical and Electronics Engineering J.J. College of Engineering and Technology Tamilnadu Tiruchirappalli India Applied Science Research Center Applied Science Private University Amman 11937 Jordan Faculty of Educational Sciences Al-Ahliyya Amman University Amman 19328 Jordan Centre for Research & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 1404010 India Computer Technologies Engineering Mazaya University College Nasiriyah Iraq Electrical Engineering Department Faculty of Engineering King Khalid University Abha Saudi Arabia Department of Electrical Engineering College of Engineering King Khalid University P.O. Box 394 KSA Abha 61421 Saudi Arabia Center for Engineering and Technology Innovations King Khalid University Abha 61421 Saudi Arabia

This voltage imbalance in four-wire, three-phase distribution networks gives rise to negative-sequence and zero-sequence voltage components which increases the total apparent power received from the network. This also increases the energy losses from the network. Traditional methods employed for load compensation provide partial fixes at the local area without any form of system-wide solution. This work presents a new decentralized control strategy for the inverter of a photovoltaic-based three-phase power source (DPS) aimed at instantaneously correcting phase voltage imbalances. The method does not require load current measurement because it depends entirely on real-time voltage measurements at the point of common coupling (PCC). The capability to mitigate the unbalance depends on the available power of the DPS. To test how effective the proposed method is, simulations have been conducted using MATLAB/SIMULINK on a distribution network with a four-leg inverter connected to a line with cascading single and three-phase loads, where a four-leg inverter enables independent phase control and mitigation of neutral current disturbances. The results show that this control enables the comparison of balancing for three-phase powers with a 96.4% improvement. The phase-to-phase voltage deviation was also reduced by around 8 V (3.6% of nominal voltage). Furthermore, the total harmonic distortion (THD) of the output current from the inverter did not rise about 3.75%, hence improving the power quality. Its real-time applicability in decentralized renewable energy integration is possible due to the method’s effectiveness in reducing voltage imbalances even when network conditions are extremely distorted. © The Author(s) 2025.

关键词： Decentralized power injection Photovoltaic system Power quality Three-Phase inverter Voltage imbalance

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Reversible modulation of metal-insulator transition in VO2 via chemically-induced oxygen migration

arXiv

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arXiv 2021年

作者： Han, Kun Wang, Hanyu Wu, Liang Cao, Yu Qi, Dong-Chen Li, Changjian Huang, Zhen Li, Xiao Wang, X. Renshaw Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore637371 Singapore School of Physics and Technology Nanjing Normal University Nanjing210023 China Faculty of Material Science and Engineering Kunming University of Science and Technology Yunnan Kunming650093 China Institute for New Materials Foshan528247 China Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore117583 Singapore Centre for Materials Science School of Chemistry and Physics Queensland University of Technology BrisbaneQLD4001 Australia Department of Materials Science and Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Ave Singapore639798 Singapore

Metal-insulator transitions (MIT), an intriguing correlated phenomenon induced by the subtle competition of the electrons' repulsive Coulomb interaction and kinetic energy, is of great potential use for electronic applications due to the dramatic change in resistivity. Here, we demonstrate a reversible control of MIT in VO2 films via oxygen stoichiometry engineering. By facilely depositing and dissolving a water-soluble yet oxygen-active Sr3Al2O6 capping layer atop the VO2 at room temperature, oxygen ions can reversibly migrate between VO2 and Sr3Al2O6, resulting in a gradual suppression and a complete recovery of MIT in VO2. The migration of the oxygen ions is evidenced in a combination of transport measurement, structural characterization and first-principles calculations. This approach of chemically-induced oxygen migration using a water-dissolvable adjacent layer could be useful for advanced electronic and iontronic devices and studying oxygen stoichiometry effects on the MIT. Copyright © 2021, The Authors. All rights reserved.

关键词： Vanadium dioxide

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