2019
DOI: 10.1088/1361-6463/ab01a3
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Theory of tunable magnetoelectric inductors in ferrite-piezoelectric layered composite

Abstract: A theoretical model was developed for permeability-induced inductance variations under influences of H/E field applications in bulk composite of polycrystalline spinel ferrites and piezoelectric ceramics with coil wound around. Strain-mediated magnetization changes in ferrites facilitate the permeability variations and a significant tunability in inductance from converse magnetoelectric coupling mechanisms can be achieved as expected. Modeling the inductance variations, i.e. inductance responses with frequency… Show more

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Cited by 16 publications
(6 citation statements)
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“…The Brillouin zone k-point sampling was sampled by 1 × 1 × 2 [42]. The convergence criterion for energy, forces, and displacement was set as 1 × 10 −5 Ha, 2 × 10 −3 Ha/Å and 5× 10 −3 Å, respectively [43], [44].…”
Section: Methodsmentioning
confidence: 99%
“…The Brillouin zone k-point sampling was sampled by 1 × 1 × 2 [42]. The convergence criterion for energy, forces, and displacement was set as 1 × 10 −5 Ha, 2 × 10 −3 Ha/Å and 5× 10 −3 Å, respectively [43], [44].…”
Section: Methodsmentioning
confidence: 99%
“…Currently, , the literature reports various gas-sensing materials, such as Pt-modified MoS 2 monolayer, Pt-doped WSe 2 , Au-doped MoSe 2 nanosheet, Ag 2 O-MoSe 2 , and other composite gas-sensing materials. There are also sensors for adsorbing SF 6 decomposition gas. Graphene is an ideal two-dimensional structure composed of hexagonal lattices with a theoretical specific surface area of 2600 m 2 /g . Its unique structure, outstanding electrical conductivity, and mechanical properties have attracted much attention. Theoretical studies show that pristine graphene has a very low sensitivity to most gases due to the weak interaction of gas molecules on its surface, limiting its practical application as a gas sensor. Researchers have proposed several modification methods to overcome the problem, such as doping metal atoms and introducing oxygen-containing functional groups.…”
Section: Introductionmentioning
confidence: 99%
“…Neuromorphic hardware originates from the same line of research as the DVS and realizes brain-inspired computing principles on-chip, such as: neuronal-network based computing, asynchronous event-based communication of neuronal activation with "spikes", temporal dynamics of the state of neurons, and efficient on-chip learning in form of local synaptic plasticity. Neuromorphic computing devices-such as Intel's neuromorphic research chip Loihi [20] used in this work and other systems [21], [22]-support event-based computation directly and enable low-power spiking neural network architectures with on-chip learning. Spiking Neural Networks (SNNs) have been previously explored for vision tasks required for UAV control [23], using end-toend learning and CNN to SNN conversion.…”
Section: Introductionmentioning
confidence: 99%