First-order reversal curve diagrams and thermal relaxation effects in magnetic particles

We have recently developed a technique for characterizing the magnetic components within natural particle assemblages. This technique is based on the transformation of magnetization data from first-order reversal curves (FORCs) into contour plots of a 2-D distribution function (FORC diagrams). FORC diagrams are useful for obtaining information about switching fields and interactions in magnetic particle systems. Here, we examine experimental data and a theoretical model in order to provide a rigorous framework for interpreting FORC diagrams for samples that contain superparamagnetic particles. We have found four distinct manifestations of thermal relaxation on FORC diagrams. First, thermal relaxation will shift the FORC distribution to lower coercivities. Second, at intermediate temperatures, thermal relaxation can generate a secondary peak about the origin of a FORC diagram. This secondary peak indicates that part of a singledomain particle assemblage has become superparamagnetic. At high enough temperatures, the primary peak of the FORC distribution will be located about the origin of a FORC diagram. Third, thermal relaxation can produce a small, but systematic, upward shift of a FORC distribution. Fourth, thermal relaxation will produce contours that lie near and parallel to the vertical axis in the lower quadrant of a FORC diagram. These manifestations make FORC diagrams a powerful tool for studying the effects of thermal relaxation (superparamagnetism) in bulk natural samples, particularly when the samples contain mixed magnetic particle assemblages.