scholarly journals An effective strategy for the development of multiferroic composite nanostructures with enhanced magnetoelectric coupling performance: A perovskite - spinel approach

2021 ◽  
Author(s):  
Preethy Augustine ◽  
Y. Narayana ◽  
Nandakumar Kalarikkal

An energy efficient move towards the regulation of magnetization vector solely by E - field by developing the multiferroic (MF) magnetoelectric (ME) nanostructures’ have opened up vast doors for novel...

2013 ◽  
Vol 58 (4) ◽  
pp. 1401-1403 ◽  
Author(s):  
J.A. Bartkowska ◽  
R. Zachariasz ◽  
D. Bochenek ◽  
J. Ilczuk

Abstract In the present work, the magnetoelectric coupling coefficient, from the temperature dependences of the dielectric permittivity for the multiferroic composite was determined. The research material was ferroelectric-ferromagnetic composite on the based PZT and ferrite. We investigated the temperature dependences of the dielectric permittivity (") for the different frequency of measurement’s field. From the dielectric measurements we determined the temperature of phase transition from ferroelectric to paraelectric phase. For the theoretical description of the temperature dependence of the dielectric constant, the Hamiltonian of Alcantara, Gehring and Janssen was used. To investigate the dielectric properties of the multiferroic composite this Hamiltonian was expressed under the mean-field approximation. Based on dielectric measurements and theoretical considerations, the values of the magnetoelectric coupling coefficient were specified.


2016 ◽  
Vol 01 (03n04) ◽  
pp. 1640002 ◽  
Author(s):  
Yang Wang ◽  
George J. Weng

The magneto-electro-elastic Eshelby S-tensor is the key to the study of linear effective properties of magneto-electro-elastic composites. There are eight different ways to write the constitutive relations, and each is associated with a specific kind of boundary condition and Eshelby S-tensor. In this work, we provide a general procedure to convert the magneto-electro-elastic Eshelby S-tensor from one system to another. As an application, we use it to calculate the magnetoelectric coupling coefficients of a piezoelectric–piezomagnetic multiferroic composite under stress-and strain-prescribed boundary conditions. We demonstrate that the calculated results are significantly different. In particular, it is shown that, under an applied stress, the magnetoelectric coupling coefficient [Formula: see text], is much stronger than that under an applied strain, while for [Formula: see text], the values are positive under a prescribed stress but negative under a prescribed strain. The effects of inclusion shape, volume concentration and geometrical exchange, are also examined. For ready applications, the explicit forms of S-tensor, [Formula: see text] and [Formula: see text], of 1-3 fibrous and 2-2 multilayer composites are also provided at the end.


RSC Advances ◽  
2019 ◽  
Vol 9 (35) ◽  
pp. 20345-20355 ◽  
Author(s):  
Yu Tang ◽  
Ruixin Wang ◽  
Yi Zhang ◽  
Bin Xiao ◽  
Shun Li ◽  
...  

Strong magnetoelectric coupling is realized in BaTiO3–Ni0.5Zn0.5Fe2O4 multiferroic composite thin films by tailoring the orientation of ferrite nanocrystals.


2021 ◽  
Author(s):  
Jia-Hui Yuan ◽  
Ya-Bo Chen ◽  
Shu-qing Dou ◽  
Bo Wei ◽  
Huanqing Cui ◽  
...  

Abstract Voltage-driven stochastic magnetization switching in a nanomagnet has attracted more attention recently with its superiority in achieving energy-efficient artificial neuron. Here, a novel pure voltage-driven scheme with ~27.66 aJ energy dissipation is proposed, which could rotate magnetization vector randomly using only a pair of electrodes covered on the multiferroic nanomagnet. Results show that the probability of 180° magnetization switching is examined as a sigmoid-like function of the voltage pulse width and magnitude, which can be utilized as the activation function of designed neuron. Considering the size errors of designed neuron in fabrication, it’s found that reasonable thickness and width variations cause little effect on recognition accuracy for MNIST hand-written dataset. In other words, the designed pure voltage-driven spintronic neuron could tolerate size errors. These results open a new way toward the realization of artificial neural network with low power consumption and high reliability.


2016 ◽  
Vol 858 ◽  
pp. 234-240
Author(s):  
Yue Fu ◽  
Wei Ju Yang

A shading roof can be an effective strategy to decrease the air-conditioning energy consumption as well as to improve the thermal environment inside a house in the place that is hot in summer and cold in winter. In Suzhou, a city in such place, traditional dwellings were constructed with shading roof eaves that have different sizes, allowing them adaptive to local climate. These eaves are worthy of being studied and improved. This study presents a summary of the sizes of the shading roof eaves of traditional Suzhou dwellings. The southward eave that has the greatest effect on indoor thermal environment is taken as the object of the current study, and a traditional Suzhou dwelling is selected as our case for the current study. Several comparative models are built, in which, the southward length of the roof eave is increased by 0.2m, from 0m to 2m. The effects of the length on both heating and cooling energy consumption are simulated by using the software Energyplus. As shown in the quantitative analysis of the simulation results, the structure is energy-efficient when the length is less than 0.6m, and the annual energy consumption reaches its minimum when the length is 0.4m.


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