Abstract:Magnetoelectric coupling is the material based coupling between electric and magnetic fields without recurrence to electrodynamics. It can arise in intrinsic multiferroics as well as in composites. Intrinsic multiferroics rely on atomistic coupling mechanisms, or coupled crystallographic order parameters, and even more complex mechanisms. They typically require operating temperatures much below T = 0°C in order to exhibit their coupling effects. Room temperature applications are thus excluded. Consequently, co… Show more
“…The shape of the M ME ( H ) curve is typical for bulk multiferroic composites containing CFO4445. Indeed, since the ME effect in such composites is due to strain coupling at the interface, the magnetoelectric coefficient can be written as , where q imn is the piezomagnetic coefficient, is an effective stiffness of the microstructure, and d jkl is the piezoelectric coefficient43. For our experimental conditions, the magnetic field and measured magnetic moment are perpendicular to the electroded sample faces, the shape of the M ME ( H ) curve should follow the magnetic field dependence of the longitudinal piezomagnetic coefficient, q l , that in turn is determined by the field dependence of magnetostriction λ , q l = dλ / dH (here the effective uniaxial value of a sample).…”
The lead-free ferroelectric 0.5Ba(Zr0.2Ti0.8)O3 − 0.5(Ba0.7Ca0.3)TiO3 (BCZT) is a promising component for multifunctional multiferroics due to its excellent room temperature piezoelectric properties. Having a composition close to the polymorphic phase boundary between the orthorhombic and tetragonal phases, it deserves a case study for analysis of its potential for modern electronics applications. To obtain magnetoelectric coupling, the piezoelectric phase needs to be combined with a suitable magnetostrictive phase. In the current article, we report on the synthesis, dielectric, magnetic, and magnetoelectric characterization of a new magnetoelectric multiferroic composite consisting of BCZT as a piezoelectric phase and CoFe2O4 (CFO) as the magnetostrictive phase. We found that this material is multiferroic at room temperature and manifests a magnetoelectric effect larger than that of BaTiO3 −CoFe2O4 bulk composites with similar content of the ferrite phase.
“…The shape of the M ME ( H ) curve is typical for bulk multiferroic composites containing CFO4445. Indeed, since the ME effect in such composites is due to strain coupling at the interface, the magnetoelectric coefficient can be written as , where q imn is the piezomagnetic coefficient, is an effective stiffness of the microstructure, and d jkl is the piezoelectric coefficient43. For our experimental conditions, the magnetic field and measured magnetic moment are perpendicular to the electroded sample faces, the shape of the M ME ( H ) curve should follow the magnetic field dependence of the longitudinal piezomagnetic coefficient, q l , that in turn is determined by the field dependence of magnetostriction λ , q l = dλ / dH (here the effective uniaxial value of a sample).…”
The lead-free ferroelectric 0.5Ba(Zr0.2Ti0.8)O3 − 0.5(Ba0.7Ca0.3)TiO3 (BCZT) is a promising component for multifunctional multiferroics due to its excellent room temperature piezoelectric properties. Having a composition close to the polymorphic phase boundary between the orthorhombic and tetragonal phases, it deserves a case study for analysis of its potential for modern electronics applications. To obtain magnetoelectric coupling, the piezoelectric phase needs to be combined with a suitable magnetostrictive phase. In the current article, we report on the synthesis, dielectric, magnetic, and magnetoelectric characterization of a new magnetoelectric multiferroic composite consisting of BCZT as a piezoelectric phase and CoFe2O4 (CFO) as the magnetostrictive phase. We found that this material is multiferroic at room temperature and manifests a magnetoelectric effect larger than that of BaTiO3 −CoFe2O4 bulk composites with similar content of the ferrite phase.
“…12 In Voigt notation, 30 expression (A1.1) can be written as: 12 In Voigt notation, 30 expression (A1.1) can be written as:…”
Section: Appendixmentioning
confidence: 99%
“…One factor that is fundamentally critical is the demagnetizing factor. 12,27,29 In our microstructure for low CFO content we naturally obtain isolated more or less spherical CFO inclusions. For them the external field is reduced within the magnetic particle.…”
Section: (6) Comparison Between the Direct And Converse Me Effectsmentioning
We report on a systematic study of the magnetoelectric effect in cobalt ferrite (CoFe2O4)—barium titanate (BaTiO3) ceramic composites with (0‐3) connectivity. Both the converse magnetoelectric coefficient, αC, and the direct voltage magnetoelectric coefficient, αE, were measured in dependence on composition and electric and magnetic bias fields. The strongest ME effect was observed in the composition (1−x) CoFe2O4–xBaTiO3 with x = 0.5 yielding values αC = 25 psm−1 and αE = 3.2 mV/(cm·Oe). We show that the proper conversion between these two coefficients demands knowledge about the dielectric permittivity of the sample. For low BaTiO3 content the dielectric coefficient of the composite yields a better correspondence, whereas for high BaTiO3 content the sample's average dielectric coefficient yields a better match. The influence of mutual orientation of polarization and magnetization on the ME effect is addressed. We found that for measurements performed parallel to the polarization direction (longitudinal effect), the ME coefficient is approximately twice as large and of opposite sign in comparison to the measurements perpendicular to the polarization direction (transverse effect). This difference has been rationalized in terms of the different contributions of the material coefficient tensor components to the ME effect, the demagnetizing factor, and losses. The obtained results provide a better understanding of peculiarities of the ME effect in bulk ceramic composites.
“…[29][30][31] The ME effect in such composites takes place via stress mediation, where the field induced strain in one phase leads to a stress on the adjacent phase, which ultimately varies the order parameter (polarization/magnetization) of the other phase. [32][33][34][35][36] Interestingly, the performance of such composites, gauged by the ME coupling coefficient α, is found to be highly sensitive to microstructure. [37][38][39][40] On the other hand, modeling predicts complex domain evolution in composites.…”
Section: Introductionmentioning
confidence: 99%
“…In the variable-field PFM experiment one effectively measures Δd eff (x, y) = f (x, y, H 0 , E 0 , ΔH), 32 and hence an exact observation of equation 3 is not trivial. Despite this limitation, PFM can reveal the intensity of the ME effect at a local scale, which could be useful information to relate the ME coupling to the material properties, as well as microstructure.…”
The term big-data in the context of materials science not only stands for the volume, but also for the heterogeneous nature of the characterization data-sets. This is a common problem in combinatorial searches in materials science, as well as chemistry. However, these data-sets may well be 'small' in terms of limited step-size of the measurement variables. Due to this limitation, application of higher-order statistics is not effective, and the choice of a suitable unsupervised learning method is restricted to those utilizing lower-order statistics. As an interesting case study, we present here variable magnetic-field Piezoresponse Force Microscopy (PFM) study of composite multiferroics, where due to experimental limitations the magnetic field dependence of piezoresponse is registered with a coarse step-size. An efficient extraction of this dependence, which corresponds to the local magnetoelectric effect, forms the central problem of this work. We evaluate the performance of Principal Component Analysis (PCA) as a simple unsupervised learning technique, by pre-labeling possible patterns in the data using Density Based Clustering (DBSCAN). Based on this combinational analysis, we highlight how PCA using non-central second-moment can be useful in such cases for extracting information about the local material response and the corresponding spatial distribution.
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