Time quantification for Monte Carlo modeling of superparamagnetic relaxation

Melenev, P. V.; Raǐkher, Yu. L.; Rusakov, V. V.; Perzynski, R.

doi:10.1103/physrevb.86.104423

Cited by 14 publications

(7 citation statements)

References 17 publications

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“…For specific discussions about dynamical simulations of systems of MNPs not limited to the blocked state see for example Refs. [9,10] for non-interacting systems, or Ref. [11], considering interparticle interactions.…”

Section: Methodsmentioning

confidence: 99%

Orientation of the magnetization easy axes of interacting nanoparticles: Influence on the hyperthermia properties

Conde-Leborán

Serantes

Baldomir

2015

Journal of Magnetism and Magnetic Materials

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Section: Methodsmentioning

confidence: 99%

Orientation of the magnetization easy axes of interacting nanoparticles: Influence on the hyperthermia properties

Conde-Leborán

Serantes

Baldomir

2015

Journal of Magnetism and Magnetic Materials

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“…Therefore, the simulated relaxation curves are obtained as a function of time, facilitating the precise evaluation of relaxation time. In the Metropolis Monte Carlo method, on the other hand, the relationship between simulation step and time is not well defined, so the magnetic relaxation curves are obtained as a function of Monte Carlo steps, precluding a quantitative comparison with analytical models [59]. The kMC simulation has been used to study the various quantities of interest in MNPs assembly [52,[60][61][62].…”

Section: Introductionmentioning

confidence: 99%

Magnetic Relaxation in Two Dimensional Assembly of Dipolar Interacting Nanoparticles

Anand

2021

Preprint

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Using the two-level approximation of the energy barrier, we perform extensive kinetic Monte Carlo simulations to probe the relaxation characteristics in a two-dimensional (L x × L y ) array of magnetic nanoparticle as a function of dipolar interaction strength h d , aspect ratio A r = L y /L x , and temperature T . In the case of weak dipolar interaction (h d ≈ 0) and substantial temperature, the magnetic relaxation follows the Néel Brown model as expected. Interestingly, the dipolar interaction of enough strength is found to induce antiferromagnetic coupling in the square arrangement of MNPs (A r = 1.0), resulting in the fastening of magnetic relaxation with h d . There is also a rapid increase in relaxation even with A r < 100 above a particular dipolar interaction strength h d , which gets enhanced with A r . Remarkably, there is a slowing down of magnetic relaxation with h d for the highly anisotropic system such as linear chain of MNPs. It is because the dipolar interaction induces ferromagnetic interaction in such a case. The thermal fluctuations also affect the relaxation properties drastically. In the case of weak dipolar limit, magnetization relaxes rapidly with T because of enhancement in thermal fluctuations. The effect of dipolar interaction and aspect ratio on the magnetic relaxation is also clearly indicated in the variation of Néel relaxation time τ N .In the presence of strong dipolar interaction (h d > 0.3) and A r = 1.0, τ N decreases with h d for a given temperature. On the other hand, there is an increase in τ N with h d for huge A r (> 100). We believe that the concepts presented in this work are beneficial for the efficient use of self-assembled MNPs array in data storage and other related applications.

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“…In the search for MC algorithms that allow the inclusion and reproduction of dynamic quantities, some interesting proposals have emerged; among them is the one by P. V. Melenev et al (2012) [18]. In their work, authors propose that the evolution of the magnetic moments is carried out using the conventional Metropolis-Hastings algorithm, additionally, special rules are imposed on the rotations that they can perform to recreate metastable states that allow access to magnetic properties such as hysteresis.…”

Section: Introductionmentioning

confidence: 99%

Self-Adaptive Acceptance Rate-Driven Markov Chain Monte Carlo Method Applied to the Study of Magnetic Nanoparticles

Zapata

Restrepo

2021

Computation

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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.

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Time quantification for Monte Carlo modeling of superparamagnetic relaxation

Cited by 14 publications

References 17 publications

Orientation of the magnetization easy axes of interacting nanoparticles: Influence on the hyperthermia properties

Orientation of the magnetization easy axes of interacting nanoparticles: Influence on the hyperthermia properties

Magnetic Relaxation in Two Dimensional Assembly of Dipolar Interacting Nanoparticles

Self-Adaptive Acceptance Rate-Driven Markov Chain Monte Carlo Method Applied to the Study of Magnetic Nanoparticles

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