Related papers: A Device model for xMR Sensors based on the Stoner…
Recent advances in high-density magnetic storage and spin electronics are based on the use of magnetic materials along with conventional microelectronic materials (metals, insulators and semiconductors). The unit information (bit) is stored…
The Stoner-Wohlfarth is the most used model of magnetic hysteresis, but its computation is time-consuming. We use machine learning to approximate piecewise this model by easy-to-compute analytic functions. Our parametrization is suitable…
Next-generation spintronic sensors aim to overcome the limitations of traditional tunneling-magnetoresistance (TMR) devices, such as complex manufacturing, high $1/f$ noise, and significant offsets. This work presents a comprehensive…
We present the thermal Stoner-Wohlfarth (tSW) model and apply it in the context of Molecular Dynamics simulations. The model is validated against an ensemble of immobilized, randomly oriented uniaxial particles (solid superparamagnet) and a…
This work introduces a latent space method to calculate the demagnetization reversal process of multigrain permanent magnets. The algorithm consists of two deep learning models based on neural networks. The embedded Stoner-Wohlfarth method…
Magneto-mechanical resonators (MMRs) represent a recently proposed type of passive sensor that enables the estimation of its pose as well as sensing other parameters in its environment. The working principle of MMRs entails an excitation of…
In this article a detailed characterization of a magnetization motion in a single sub-micrometer and multi-terminal ferromagnetic structure in lateral geometry is performed in a GHz regime using direct DC characterization technique. We have…
Magnetic nanoparticles are useful biological probes as well as therapeutic agents. There have been several approaches used to model nanoparticle magnetization dynamics for both Brownian as well as N\'eel rotation. The magnetizations are…
We use a machine learning approach to identify the importance of microstructure characteristics in causing magnetization reversal in ideally structured large-grained Nd$_2$Fe$_{14}$B permanent magnets. The embedded Stoner-Wohlfarth method…
Magnetic sensors based on the magnetoresistance effects have a promising application prospect due to their excellent sensitivity and advantages in terms of the integration. However, competition between higher sensitivity and larger…
Solid state theory, density functional theory and its generalizations for correlated systems together with numerical simulations on supercomputers allow nowadays to model magnetic systems realistically and in detail and can be even used to…
We report two fundamental inequalities in the Stoner-Wohlfarth model. Specifically, we investigate the theoretical limit for the initial magnetic susceptibility in a system described by the Stoner-Wohlfarth approach. We also find analytical…
The physics of magnetic state change or reversal in single domain magnetic grains (called Stoner particles) is interesting from the fundamental as well as the applied points of view. A change in magnetization can be finely tuned with a…
The Stoner-Wohlfarth model is a traditional and efficient tool to calculate magnetization curves and it can provides further insights on the fundamental physics associated to the magnetic properties and magnetization dynamics. Here, we…
The quantum mechanical counterpart of the famous Stoner-Wohlfarth model -- an easy-axis magnet in a tilted magnetic field -- is studied theoretically and through simulations, as a function of the spin-size $S$ in a sweeping longitudinal…
We calculate numerically the magnetization direction as function of magnetic field in the Stoner-Wohlfart theory and are able to reproduce the shape of the low-field magnetoresistance hysteresis observed in manganite grain boundary…
The design and later use of modern spectropolarimeters and magnetographs require a number of tolerance specifications that allow the developers to build the instrument and then the scientists to interpret the data accuracy. Such…
Multivariable parametric models are essential for optimizing the performance of high-tech systems. The main objective of this paper is to develop an identification strategy that provides accurate parametric models for complex multivariable…
Domain wall (DW) devices have garnered recent interest for diverse applications including memory, logic, and neuromorphic primitives; fast, accurate device models are therefore imperative for large-scale system design and verification.…
A powerful time series analysis modeling technique is presented to describe cycle-to-cycle variability in memristors. These devices show variability linked to the inherent stochasticity of device operation and it needs to be accurately…