Modeling the differential susceptibility by Lorentzians

TL;DR

This paper introduces a simplified method for analyzing magnetic phases in materials by fitting differential susceptibility curves to Lorentzian functions, offering an alternative to the Preisach model with improved noise reduction.

Contribution

The authors propose a new, simpler approach to decompose magnetic phase information using Lorentzian fits of differential susceptibility curves, bypassing complex Preisach model calculations.

Findings

Differential susceptibility curves follow Lorentzian shapes with high accuracy.

The method enables decomposition of multi-phase materials into individual magnetic components.

Lorentzian fitting reduces noise and facilitates calculation of the Preisach distribution.

Abstract

The idea to extract information on magnetically different phases from magnetic measurements is very attractive and many efforts have been made in this area. One of the most popular direction is to use the Preisach model formalism to analyze the 2D Preisach distribution function (PDF) obtained either from first order reversal curves (FORC) or minor loops. Here we present an alternative a much simpler procedure -- the analysis of the derivative of the saturation magnetization loop, the differential susceptibility curve. It follows the Lorentzian shape with very high accuracy for ferromagnetic polycrystalline materials. This allows decomposing any differential susceptibility curve of a complex multi-phase material into individual components representing different magnetic phases by Lorenzian peaks -- in the same way as it is done in X-ray diffraction analysis of materials. We show that the minor differential susceptibility curves also have the Lorenzian shape that can facilitate calculation of the Preisach distribution function from the experimental curves and reduce noise in the resulting PDF.