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In this work, the mechanically alloyed Fe70Zr30 (at. %) composition has been used to study the influence of milling time on its homogeneity and magnetic properties. The microstructure and Fe environment results show the formation of an almost fully amorphous alloy after 50 h of milling in a mixture of pure 70 at. % Fe and 30 at. % Zr. The soft magnetic behavior of the samples enhances with the increase of the milling time, which is ascribed to the averaging out of the magnetocrystalline anisotropy as the crystal size decreases and the amorphous fraction increases. The formation of a non-perfectly homogenous system leads to a certain compositional heterogeneity, motivating the existence of a distribution of Curie temperatures. The parameters of the distribution (the average Curie temperature, T C ¯ , and the broadening of the distribution, ∆ T C ) have been obtained using a recently reported procedure, based on the analysis of the approach towards the saturation curves and the magnetocaloric effect. The decrease of ∆ T C and the increase of T C ¯ with the milling time are in agreement with the microstructural results. As the remaining α-Fe phase decreases, the amorphous matrix is enriched in Fe atoms, enhancing its magnetic response. [ABSTRACT FROM AUTHOR]

The kinetics of amorphization during ball milling is generally analyzed using two different approaches: the classical Johnson-Mehl-Avrami-Kolmogorov (JMAK) theory and Delogu and Cocco’s model for which a region deterministically transforms after it reaches a certain number of collisions. The application of JMAK analysis to the latter model predicts Avrami exponents to be higher than the experimental ones (typically close to one). We develop simulations based on the probabilistic character of the nucleation phenomenon and concave growth of the amorphous phase in the core of a nanocrystal. The predictions of our simulations are in good agreement with the low Avrami exponents and with the size evolution of the remaining crystallites found experimentally. From these values, the parameters involved in the simulated model (growth rate and probability of nucleation) can be estimated. [ABSTRACT FROM AUTHOR]