Estimating The Relative Concentration Of Superparamagnetic And Stable Single Domain Particles In Geological, Biological, And Synthetic Materials

Obtaining an estimate of the relative proportion of superparamagnetic (SP) to stable single-domain (SSD) particle sizes in a material can be useful in evaluating environmental conditions in natural materials, or in understanding the homogeneity of particle size and the degree of agglomeration in synthesized particles. Frequency dependent magnetic susceptibility is one of the most common methods used to identify SP particles in a material. The ability to detect SP particles, however, will be dependent on the field frequencies that can be applied. This study is concerned with evaluating three methods to estimate the SP content in a mixture of SSD and SP magnetite. We examine the use of the Day-Dunlop plot, first-order reversal curves (FORC) and principal component analysis (PCA), and the relationship between the reversible and irreversible magnetization as methods to evaluate qualitatively the relative contributions of SSD and SP magnetite in a material. Two series of mixtures of coated nanoparticles with a mean diameter of 20 and 11 nm are used as the SP end member and magnetosomes or intact magnetotactic bacterium of Magnetospirillum gryphiswaldense as the SSD end member. The Day-Dunlop plot tracks the progressive change in hysteresis properties with growing SP concentration. PCA of FORC data is sensitive in detecting differences in the SP component, when the SP particle size are not too small; otherwise the ratio between the reversible and irreversible magnetization can better assess differences. The results from the series are used to evaluate the relative SP content in three further sets of samples: biological tissue, synthetic nanoparticles, and samples from natural environments, to assess the strengths and weaknesses in each approach.