Slow dynamics of interacting antiferromagnetic nanoparticles

TL;DR

This paper investigates the slow magnetic relaxation, memory, and aging effects in interacting antiferromagnetic NiO nanoparticles, highlighting how different interactions influence these phenomena through theoretical modeling and simulations.

Contribution

It introduces a master equation approach to analyze the effects of dipolar, NNSR, and LRMF interactions on nanoparticle magnetic dynamics, revealing interaction-dependent memory effects.

Findings

LRMF interactions enhance memory dip

Dipolar interactions weaken memory dip

Memory effects indicate glassy behavior in nanoparticles

Abstract

We study magnetic relaxation dynamics, memory and aging effects in interacting polydisperse antiferromagnetic NiO nanoparticles by solving a master equation using a two-state model. We investigate the effects of interactions using dipolar, Nearest-Neighbour Short-Range (NNSR) and Long-Range Mean-Field (LRMF) interactions. The magnetic relaxation of the nanoparticles in a time-dependent magnetic field has been studied using LRMF interaction. The size-dependent effects are suppressed in the ac-susceptibility, as the frequency is increased. We find that the memory dip, that quantifies the memory effect is about the same as that of non-interacting nanoparticles for the NNSR case. There is a stronger memory-dip for LRMF, and a weaker memory-dip for the dipolar interactions. We have also shown a memory effect in the Zero-field-cooled magnetization for the dipolar case, a signature of glassy behaviour, from Monte-Carlo studies.