Quantitative description of complex magnetic nanoparticle arrays

TL;DR

This paper develops a new framework for quantitatively analyzing first-order reversal curves (FORC) data to better characterize complex magnetic nanostructures, including multiple magnetic phases.

Contribution

The authors introduce a robust, generalized framework for extracting quantitative parameters from FORC measurements on complex magnetic nanostructures.

Findings

Framework enables accurate interpretation of magnetic properties.

Applicable to samples with multiple magnetic phases.

Improves reproducibility and reliability of magnetic characterization.

Abstract

First-order reversal curves (FORC) measurements are broadly used for characterization of complex magnetic nanostructures, but a robust framework for quantitative analysis of the FORC data is still obscure despite numerous studies over decades. In this paper, we first establish a framework for extracting quantitative parameters from the FORC measurements conducted on samples including a single type of magnetic nanostructures to interpret their magnetic properties. We then generalize our framework for quantitative characterization of the samples including multiple types of magnetic nanostructures to determine the most reliable and reproducible parameter for detailed analysis of the samples. Our approach provides an insightful path for a more accurate quantitative description of complex magnetic nanostructures including various different magnetic subcomponents and/or magnetic phases.