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Magnetite is an important magnetic remanence carrier in natural samples and therefore is of great interest in paleo-, rock-, and environmental magnetism. The magnetic properties of magnetite depend on many factors, e.g., concentration and grain size distribution (GSD). In this study, we theoretically investigated the temperature-dependent susceptibility (TDS) of magnetite nanoparticles with a lognormal GSD. Results show that the TDS is affected highly by the GSD mainly in three aspects. Firstly, the unblocking process becomes smoother with the increase of distribution width, characterizing as a wider Hopkinson peak on the TDS curve. Secondly, the blocking temperature increases with the increase of the median diameter or/and the distribution width. Thirdly, the maximum susceptibility decreases with the increase of distribution width, and has a logarithmic function relation with the standard deviation of the distribution. As a case study, this model was further applied to the thermal products of the Chinese loess/paleosol samples to determine the granulometry of newly-formed magnetite upon heating based on TDS curves. The results demonstrate the fidelity and feasibility of this method to determine the GSD of nano-sized magnetic particles.
Magnetite is an important magnetic remanence carrier in natural samples and therefore is of great interest in paleo-, rock-, and environmental magnetism. The magnetic properties of magnetite depend on many factors, eg, concentration and grain size distribution (GSD). study, we theoretically investigated the temperature-dependent susceptibility (TDS) of magnetite nanoparticles with a lognormal GSD. Results show that that TDS is affected highly by the GSD mainly in three aspects. First, the unblocking process becomes smoother with the increase of distribution width , characterizing as a wider Hopkinson peak on the TDS curve. Secondly, the blocking temperature increases with the increase of the median diameter or / and the distribution width. Thirdly, the maximum susceptibility decreases with the increase of distribution of bandwidth, and has a logarithmic function relation with the standard deviation of the distribution. As a case study, this model was further applied to the thermal pro ducts of the Chinese loess / paleosol samples to determine the granulometry of newly formed magnetite upon heating based on TDS curves. The results demonstrate the fidelity and feasibility of this method to determine the GSD of nano-sized magnetic particles.