Related papers: Novel Giant Magnetoresistance Model using Multiple…
Linear magnetoresistance occurs in semiconductors as a consequence of strong electrical disorder and is characterized by nonsaturating magnetoresistance that is proportional to the applied magnetic field. By investigating a disordered…
Machine learning methods on graphs have proven useful in many applications due to their ability to handle generally structured data. The framework of Gaussian Markov Random Fields (GMRFs) provides a principled way to define Gaussian models…
The longitudinal magnetoresistance (MR) is assumed to be hardly realized as the Lorentz force does not work on electrons when the magnetic field is parallel to the current. However, in some cases, longitudinal MR becomes large, which…
Spin-transfer torques (STTs) can be exploited in order to manipulate the magnetic moments of nanomagnets, thus allowing for new consumer-oriented devices to be designed. Of particular interest here are tuneable radio-frequency (RF)…
We reconsider the theory of magnetoresistance in hopping semiconductors. First, we have shown that the random potential of the background impurities affects significantly preexponential factor of the tunneling amplitude which becomes to be…
Extremely large non-saturating magnetoresistance has recently been reported for a large number of both topologically trivial and non-trivial materials. Different mechanisms have been proposed to explain the observed magnetotransport…
A model describing the influence of torsion stress on the giant magnetoimpedance in amorphous wires with negative magnetostriction is proposed. The wire impedance is found by means of the solution of Maxwell equations together with the…
Gaussian process regression (GPR) is a popular nonparametric Bayesian method that provides predictive uncertainty estimates and is widely used in safety-critical applications. While prior research has introduced various uncertainty bounds,…
Accurate prediction of blood-brain barrier permeability (BBBP) is essential for central nervous system (CNS) drug development. While graph neural networks (GNNs) have advanced molecular property prediction, they often rely on molecular…
We present a study of the magnetoresistance of highly oriented pyrolytic graphite (HOPG) as a function of the sample size. Our results show unequivocally that the magnetoresistance reduces with the sample size even for samples of hundreds…
We present a circuit-design compatible large-signal compact model of metal-insulator-graphene (MIG) diodes for describing its dynamic response for the first time. The model essentially consists of a voltage-dependent diode intrinsic…
Interference prediction and resource allocation are critical challenges in mission-critical applications where stringent latency and reliability constraints must be met. This paper proposes a novel Gaussian process regression (GPR)-based…
Wireless power transfer (WPT) with coupled resonators offers a promising solution for the seamless powering of electronic devices. Interactive design approaches that visualize the magnetic field and power transfer efficiency based on system…
The magnetoimpedance effect is a versatile tool to investigate ferromagnetic materials, revealing aspects on the fundamental physics associated to magnetization dynamics, broadband magnetic properties, important issues for current and…
A new type of self-similar potential is used to study a multibarrier system made of graphene. Such potential is based on the traditional middle third Cantor set rule combined with a scaling of the barriers height. The resulting transmission…
Understanding magnetoresistance, the change in electrical resistance upon an external magnetic field, at the atomic level is of great interest both fundamentally and technologically. Graphene and other two-dimensional layered materials…
In this paper we study the threshold model of \emph{geometric inhomogeneous random graphs} (GIRGs); a generative random graph model that is closely related to \emph{hyperbolic random graphs} (HRGs). These models have been observed to…
Microgrids are resources that can be used to restore critical loads after a natural disaster, enhancing resilience of a distribution network. To deal with the stochastic nature of intermittent energy resources, such as wind turbines (WTs)…
In this paper, we attempt the theoretical modeling of the magnetic tunnel junctions with embedded magnetic and nonmagnetic nanoparticles (NPs). A few abnormal tunnel magnetoresistance (TMR) effects, observed in related experiments, can be…
We have performed magnetoresistance (MR) measurements of granular ferromagnets having lateral dimensions smaller than 0.5 $\mu$m and containing a small number of grains (down to about 100). Compared to macroscopic samples, these granular…