Monte Carlo study of the transverse susceptibility in ordered arrays of magnetic nanoparticles

TL;DR

This study uses Monte Carlo simulations to analyze how the transverse susceptibility of ordered magnetic nanoparticle arrays varies with temperature, interactions, and geometry, revealing key features of magnetic behavior relevant to experimental systems.

Contribution

It provides new insights into the temperature-dependent evolution of RTS curves and the effects of dipolar interactions and geometry in nanoparticle arrays.

Findings

RTS curves evolve from three-peak to single-peak with increasing temperature

Dipolar interactions suppress the coercivity peak at low temperature

Peak positions shift with interparticle separation and geometry

Abstract

We present Monte Carlo simulations of the reversible transverse susceptibility (RTS) for a hexagonal array of dipolar interacting magnetic nanoparticles with random anisotropy. RTS curves with the bias-field in-plane and out-of-plane are compared. With increasing temperature the RTS curves evolve from a three-peak structure to a double-peak and eventually a single-peak at the blocking temperature of the system. This trend is preserved for weak interactions. Dipolar interactions at low temperature are responsible for the suppression of the coercivity peak in the out-of-plane geometry and its progressive merge to the anisotropy peak with decreasing interparticle separation in the in-plane geometry. The anisotropy peaks are located at higher field values in the out-of-plane geometry relative to the in-plane one. When the bias field lies in-plane (out-of-plane) the anisotropy peaks are shown to shift to lower (higher) field values with decreasing interparticle separation. The coercivity peak shifts to lower field values in both geometries. Our results are compared with recent experimental findings in self-assembled arrays of Fe nanoparticles.