journal article·2011-10

Correlation between structural and giant magnetoresistance properties of Fe–Ag nanogranular films

M. Tamisari, F. Spizzo, M. Sacerdoti, G. Battaglin, F. Ronconi

Journal of Nanoparticle Research· Volume 13· Issue 10
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Abstract

Fe x Ag1−x granular thin-films, with the atomic Fe concentration, x, ranging from 0 up to 0.5, were deposited by dc magnetron co-sputtering. The giant magnetoresistance (GMR) intensity is maximum at x I = 0.32, while the maximum of GMR efficiency, γ, i.e., the change of GMR intensity for a unit change of reduced squared magnetization, is observed at x γ = 0.26. Owing to the spin-dependent scattering features, the GMR intensity and γ depend on both the concentration and the arrangement of the magnetic material. Therefore, to explain the difference between x I and x γ and to understand how the structural properties affect the magnetoresistive behaviour, we performed magnetization, Mossbauer and X-ray diffraction measurements as a function of x. X-ray data indicate that the granular films exhibit three different regimes: for x 0.32, a Fe–Ag saturated solid solution is detected, containing bcc Fe clusters whose size is about 10 nm. Differently, for all the concentrations, magnetization data show the presence of Fe precipitates, whose size increases with x, and the Mossbauer investigation confirms this picture. We find that the samples grown at x = x γ display the finest Fe dispersion within the Ag matrix, as the Fe–Ag solid solution is nearly at saturation and the Fe cluster size is of the order of a few nanometers; this arrangement possibly maximizes the magnetic/non-magnetic interface extension thus enhancing the GMR efficiency. If x is slightly increased, the increase in total Fe content compensates the GMR efficiency reduction, so the GMR intensity maximum is observed.
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Research context

OpenAlex topics: Magnetic properties of thin films · Metallic Glasses and Amorphous Alloys · Magnetic Properties and Synthesis of Ferrites

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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