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MXene-based Elastomer Mimetic StretchableSensors: Design, properties, and Applications

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Nano-Micro Letters 2024年第7期16卷 295-342页

作者： poushali Das parham Khoshbakht Marvi Sayan Ganguly Xiaowu(Shirley)Tang bo Wang Seshasai srinivasan Amin Reza Rajabzadeh Andreas Rosenkranz School of biomedical Engineering McMaster University1280 Main Street WestHamiltonON L8S 4L8Canada Department of Chemistry and Waterloo Institute for Nanotechnology(WIN) University of Waterloo200 University Ave WestWaterlooONCanada Centre for Eye and Vision Research(CEVR) 17W Hong Kong Science ParkShatinHong KongPeople’s Republic of China Chair of Functional Materials Department of Materials Science and EngineeringSaarland UniversitySaarbruckenGermany W booth School of Engineering practice and Technology McMaster University1280 Main Street WestHamiltonON L8S 4L7Canada Department for Chemical Engineering Biotechnology and MaterialsUniversity of ChileSantiagoChile

Flexible sensors based on MXene-polymer composites are highly prospective for next-generation wearable electronics used in human-machine *** of the motivating factors behind the progress of flexible sensors is the steady arrival of new conductive ***,a new family of 2D nanomaterials,have been draw-ing attention since the last decade due to their high electronic conduc-tivity,processability,mechanical robustness and chemical *** this review,we encompass the fabrication of MXene-based polymeric nanocomposites,their structure-property relationship,and applications in the flexible sensor ***,our discussion is not only lim-ited to sensor design,their mechanism,and various modes of sensing platform,but also their future perspective and market throughout the *** our article,we intend to fortify the bond between flexible matrices and MXenes thus promoting the swift advancement of flexible MXene-sensors for wearable technologies.

关键词： Flexible sensor 2D nanomaterials MXene Wearable and conductive Applications

Deceleration-stage Rayleigh–Taylor growth in a background magnetic field studied in cylindrical and Cartesian geometries

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Matter and Radiation at Extremes 2022年第2期7卷 41-52页

作者： C.Samulski b.srinivasan M.J.-E.Manuel R.Masti J.p.Sauppe J.Kline Virginia polytechnic Institute and State University BlacksburgVirginia 24060USA General Atomics P.O.Box 85608San DiegoCalifornia 92186USA Los Alamos National Laboratory P.O.Box 1663Los AlamosNew Mexico 87545USA

Experiments have identified the Rayleigh–Taylor(RT)instability as one of the greatest obstacles to achieving inertial confinement ***,mitigation strategies to reduce RT growth and fuel–ablator mixing in the hotspot during the deceleration phase of the implosion are of great *** this work,the effect of seed magnetic fields on deceleration-phase RT growth are studied in planar and cylindrical geometries under conditions relevant to the National Ignition Facility(NIF)and Omega *** magnetohydrodynamic(MHD)and resistive-MHD capabilities of the FLASH code are used to model imploding cylinders and planar blast-wave-driven *** target and laser parameters are presented that suggest the occurrence of morphological differences in late-time RT evolution in the cylindrical NIF case and a measurable difference in spike height of single-mode growth in the planar NIF *** results of this study indicate the need for target designs to utilize an RT-unstable foam–foam interface in order to achieve sufficient magnetic field amplification to alter RT *** FLASH simulations are used to study these magnetic field effects in both resistive and ideal MHD.

关键词： FLASH cylindrical magnetic

Fuzzy-based Secure Clustering with Routing Technique for VANETs

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Computer Systems Science & Engineering 2022年第10期43卷 291-304页

作者： T.S.balaji S.srinivasan S.prasanna bharathi b.Ramesh Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India Department of Electronics and Communication Engineering College of Engineering&TechnologySRM Institute of Science and TechnologyVadapalani CampusChennai600026India Institute of biomedical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India Department of Electronics and Communication Engineering SRM Institute of Science and Technology600026ChennaiIndia Department of Civil Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India

Due to the advanced developments in communication technologies,Internet of vehicles and vehicular adhoc networks(VANET)offers numerous opportunities for effectively managing transportation *** the other,the cloud environment needs to disseminate the emergency message to the vehicles which are consistently distributed on the roadway so that every vehicle gets the messages from closer vehicles in a straightforward *** resolve this issue,clustering and routing techniques can be designed using computational intelligence *** this motivation,this paper presents a new type-2 fuzzy sets based clustering with metaheuristic optimization based routing(T2FSCMOR)technique for secure communication in *** T2FSC-MOR technique aims to elect CHs and optimal routes for secure intercluster data transmission in *** proposed model involves T2FSC technique for the selection of CHs and construction of *** T2FSC technique uses different parameters namely traveling speed(TS),link quality(LQ),trust factor(TF),inter-vehicle distance(IVD),and neighboring node count(NCC).The inclusion of trust factor helps to select the proper cluster heads(CHs)for secure data dissemination ***,trust aware seagull optimization based routing(TASGOR)approach was derived for the optimal selection of routes in *** order to validate the enhanced performance of proposed technique,the set of simulations take place and the outcomes are examined interms of different *** experimental outcomes highlighted the improved performance of the proposed model over the other state of art techniques with a higher throughput of 98%.

关键词： VANET security clustering routing fuzzy logic systems metaheuristic algorithms

Hybrid Deep Learning-Improved bAT Optimization Algorithm for Soil Classification Using Hyperspectral Features

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Computer Systems Science & Engineering 2023年第4期45卷 579-594页

作者： S.prasanna bharathi S.srinivasan G.Chamundeeswari b.Ramesh Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha NagarThandalamChennai602105TamilnaduIndia Department of Electronics and Communication Engineering College of Engineering&TechnologySRM Institute of Science and TechnologyVadapalani CampusChennai600026India

Now a days,Remote Sensing(RS)techniques are used for earth observation and for detection of soil types with high accuracy and better *** technique provides perspective view of spatial resolution and aids in instantaneous measurement of soil’s minerals and its *** are a few challenges that is present in soil classification using image enhancement such as,locating and plotting soil boundaries,slopes,hazardous areas,drainage condition,land use,vegetation *** are some traditional approaches which involves few drawbacks such as,manual involvement which results in inaccuracy due to human interference,time consuming,inconsistent prediction *** overcome these draw backs and to improve the predictive analysis of soil characteristics,we propose a Hybrid Deep Learning improved bAT optimization algorithm(HDIb)for soil classification using remote sensing hyperspectral *** HDIb,we propose a spontaneous bAT optimization algorithm for feature extraction of both spectral-spatial features by choosing pure pixels from the Hyper Spectral(HS)***-spatial vector as training illustrations is attained by merging spatial and spectral vector by means of priority stacking ***,a recurring Deep Learning(DL)Neural Network(NN)is used for classifying the HS images,considering the datasets of pavia University,Salinas and Tamil Nadu Hill Scene,which in turn improves the reliability of ***,the performance of the proposed HDIb based soil classifier is compared and analyzed with existing methodologies like Single Layer perceptron(SLp),Convolutional Neural Networks(CNN)and Deep Metric Learning(DML)and it shows an improved classification accuracy of 99.87%,98.34%and 99.9%for Tamil Nadu Hills dataset,pavia University and Salinas scene datasets respectively.

关键词： HDIb bat optimization algorithm recurrent deep learning neural network convolutional neural network single layer perceptron hyperspectral images deep metric learning

High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials

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npj Computational Materials 2023年第1期9卷 2310-2321页

作者： Jong Hyun Jung prashanth srinivasan Axel Forslund blazej Grabowski Institute for Materials Science University of StuttgartPfaffenwaldring 5570569 StuttgartGermany

Accurate prediction of thermodynamic properties requires an extremely accurate representation of the free-energy *** are twofold—first,the inclusion of the relevant finite-temperature mechanisms,and second,a dense volume–temperature grid on which the calculations are performed.A systematic workflow for such calculations requires computational efficiency and reliability,and has not been available within an ab initio framework so ***,we elucidate such a framework involving direct upsampling,thermodynamic integration and machine-learning potentials,allowing us to incorporate,in particular,the full effect of anharmonic *** improved methodology has a five-times speed-up compared to state-of-the-art *** calculate equilibrium thermodynamic properties up to the melting point for bcc Nb,magnetic fcc Ni,fcc Al,and hcp Mg,and find remarkable agreement with experimental data.A strong impact of anharmonicity is observed specifically for *** introduced procedure paves the way for the development of ab initio thermodynamic databases.

关键词： harmonic point prediction

Design of QoS Aware Routing protocol for IoT Assisted Clustered WSN

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Computers, Materials & Continua 2022年第5期71卷 3785-3801页

作者： Ashit Kumar Dutta S.srinivasan bobbili prasada Rao b.Hemalatha Irina V.pustokhina Denis A.pustokhin Gyanendra prasad Joshi Department of Computer Science and Information Systems College of Applied SciencesAlmaarefa UniversityRiyadh13713Kingdom of Saudi Arabia Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha NagarThandalamChennai602105India Department of Electrical and Electronics Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Electronics and Communication Engineering Thirumalai Engineering CollegeKancheepuram631551India Department of Entrepreneurship and Logistics Plekhanov Russian University of Economics117997MoscowRussia Department of Logistics State University of Management109542MoscowRussia Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea

In current days,the domain of Internet of Things(IoT)and Wireless Sensor Networks(WSN)are combined for enhancing the sensor related data transmission in the forthcoming networking *** and routing techniques are treated as the effective methods highly used to attain reduced energy consumption and lengthen the lifetime of the WSN assisted IoT *** this view,this paper presents an Ensemble of Metaheuristic Optimization based QoS aware Clustering with Multihop Routing(EMOQoSCMR)protocol for IoT assisted *** proposed EMO-QoSCMR protocol aims to achieve QoS parameters such as energy,throughput,delay,and *** proposed model involves two stage processes namely clustering and ***,the EMO-QoSCMR protocol involves crossentropy rain optimization algorithm based clustering(CEROAC)technique to select an optimal set of cluster heads(CHs)and construct ***,oppositional chaos game optimization based routing(OCGOR)technique is employed for the optimal set of routes in the IoT assisted *** proposed model derives a fitness function based on the parameters involved in the IoT nodes such as residual energy,distance to sink node,*** proposed EMOQoSCMR technique has resulted to an enhanced NAN of 64 nodes whereas the LEACH,pSO-ECHS,E-OEERp,and iCSHS methods have resulted in a lesser NAN of 2,10,42,and 51 *** performance of the presented protocol has been evaluated interms of energy efficiency and network lifetime.

关键词： Internet of things wireless sensor networks clustering routing metaheuristics cluster head selection QoS parameters

Enhanced green emission from La＿(0.4)F＿3:Ce＿(0.45),Tb＿(0.15)/TiO＿2 core/shell structure

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Journal of Rare Earths 2015年第1期33卷 20-26页

作者： T.K.srinivasan b.S.panigrahi N.Suriyamurthy p.K.parida b.Venkatraman Indira Gandhi Centre for Atomic Research Kalpakkam–603102 India

Nano sized La0.4F3：Ce0.45,Tb0.15（core）, La0.4F3：Ce0.45,Tb0.15（Ti O2）（core） shell, La0.55F：Ce0.45, and La0.85F3：Tb0.15 particles were synthesized by adopting co-precipitation technique in acidic environment and coated with Ti O2 to form a core-shell structure by adopting a mechanical dispersion method at room temperature. The synthesized materials were characterized using X-ray diffraction（XRD）, transmission electron microscopy（TEM）, Fourier transform infrared spectroscopy（FTIR）, ultraviolet-visible spectroscopy（UV-Vis） absorption, photoluminescence and lifetime spectroscopy. The crystal structure of La0.4F3：Ce0.45,Tb0.15 remained the same as La F3 after being doped with Ce and Tb ions but with a slight decrease in the lattice parameter. TEM image confirmed the formation of a core-shell structure. The La0.4F3：Ce0.45,Tb0.15/Ti O2 exhibited Tb3＋ fluorescence enhancement by a factor of 1.76. Scintillation from the synthesized materials was also observed under X-ray excitation.

关键词： core-shell cerium terbium luminescence lanthanum fluoride scintillation rare earths

broadband ferromagnetic resonance studies on influence of interface bonding on magnetoeletric effects in ferrit e-ferroelectric composites

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Frontiers of physics 2012年第4期7卷 418-423页

作者： D.V.b.Murthy Gopalan srinivasan physics Department Oakland UniversityRochesterMI 48309USA

A systematic study has been carried out on the effects of interface bonding on the strain mediated magnetoelectric （ME） coupling in ferromagnetic-ferroelectric bilayers. The technique used involves the static electric field E tuning of the ferromagnetic resonance （FMR） in yttrium iron garnet （YIG） and lead zirconate titanate （pZT） or lead magnesium niobate-lead titanate （pMN-pT）. A broad band detection technique has been developed for studies over 1 40 GHz in three types of bilayers： epoxy bonded, eutectic bonded and YIG films directly grown onto piezoelectric substrate by electrophoretic deposition. The strength A of the converse ME effect （CME） defined as the ratio of the frequency shift 8f in FMR in E, A = 8f/E, varies over the range 0.8 to 4.3 ***/kV, and is the highest for eutectic bonded samples and is the weakest for epoxy bonded bilayers. The results presented here as of importance for dual electric and magnetic field tunable ferrite ferroelectric microwave resonators and filters.

关键词： Keywords ferrite ferroelectric magnetoelectric ferromagnetic resonance

performance of two complementary machine-learned potentials in modelling chemically complex systems

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npj Computational Materials 2023年第1期9卷 1008-1022页

作者： Konstantin Gubaev Viktor Zaverkin prashanth srinivasan Andrew Ian Duff Johannes Kästner blazej Grabowski Institute for Materials Science University of StuttgartPfaffenwaldring 5570569 StuttgartGermany Institute for Theoretical Chemistry University of StuttgartPfaffenwaldring 5570569 StuttgartGermany Scientific Computing Department STFC Daresbury LaboratoryWarrington WA44ADUK present address:NEC Laboratories Europe GmbH Kurfürsten-Anlage 3669115 HeidelbergGermany

Chemically complex multicomponent alloys possess exceptional properties derived from an inexhaustible compositional *** complexity however makes interatomic potential development *** explore two complementary machine-learned potentials—the moment tensor potential(MTp)and the Gaussian moment neural network(GM-NN)—in simultaneously describing configurational and vibrational degrees of freedom in the Ta-V-Cr-W alloy *** models are equally accurate with excellent performance evaluated against *** achieve root-mean-square-errors(RMSEs)in energies of less than a few meV/atom across 0 K ordered and high-temperature disordered configurations included in the *** for compositions not in training,relative energy RMSEs at high temperatures are within a few meV/***-temperature molecular dynamics forces have similarly small RMSEs of about 0.15 eV/Åfor the disordered quaternary included in,and ternaries not part of *** achieve faster convergence with training size;GM-NNs are faster in *** learning is partially beneficial and should be complemented with conventional human-based training set generation.

关键词： alloy faster complex