Abstract
A standard canonical Markov Chain Monte Carlo method implemented with a single-macrospin movement Metropolis dynamics was conducted to study the hysteretic properties of an ensemble of independent and non-interacting magnetic nanoparticles with uniaxial magneto-crystalline anisotropy randomly distributed. In our model, the acceptance-rate algorithm allows accepting new updates at a constant rate by means of a self-adaptive mechanism of the amplitude of Néel rotation of magnetic moments. The influence of this proposal upon the magnetic properties of our system is explored by analyzing the behavior of the magnetization versus field isotherms for a wide range of acceptance rates. Our results allows reproduction of the occurrence of both blocked and superparamagnetic states for high and low acceptance-rate values respectively, from which a link with the measurement time is inferred. Finally, the interplay between acceptance rate with temperature in hysteresis curves and the time evolution of the saturation processes is also presented and discussed.
Highlights
The theoretical study of magnetic nanoparticle systems dates to the pioneering work of E
This section explores the dependence of magnetization both as function of a timedependent field and the respective Monte Carlo step (MCS) dependence when a constant magnetic field is applied
At the beginning of each time-dependent field experience, all the magnetic moments are randomly oriented, and they are thermalized until saturation
Summary
This paper aims to build on this research to investigate the role of the acceptance rate and how affects the properties of a magnetic nanoparticles ensemble
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