Facile decoding of quantitative signatures from magnetic nanowire arrays

Magnetic nanoparticles have been proposed as contact-free minimal-background nanobarcodes, and yet it has been difficult to rapidly and reliably decode them in an assembly. Here, high aspect ratio nanoparticles, or magnetic nanowires (MNWs), are characterized using first-order reversal curves (FORC) to investigate quantitative decoding. We have synthesized four types of nanowires (differing in diameter) that might be used for barcoding, and identified four possible “signature” functions that might be used to quickly distinguish them. To test this, we have measured the signatures of several combination samples containing two or four different MNW types, and fit them to linear combinations of the individual type signatures to determine the volume ratios of the types. We find that the signature which determines the ratios most accurately involves only the slope of each FORC at its reversal field, which requires only 2–4 data points per FORC curve, reducing the measurement time by a factor of 10 to 50 compared to measuring the full FORC.

Временная стабильность намагниченности наночастиц varepsilon-In-=SUB=-0.24-=/SUB=- Fe-=SUB=-1.76-=/SUB=-O-=SUB=-3-=/SUB=-

The kinetics of spontaneous demagnetization in nanoparticles of the exotic epsilon-phase of indium-doped iron(III) oxide (ε-In_0.24Fe_1.76O_3) has been studied using the method of accelerated testing of magnets for temporal stability in a magnetization-reversal field. Time dependences of the magnetization of nanoparticles measured in a wide range of magnetic fields exhibited rectification in semilogarithmic coordinates. The dependence of the magnetic viscosity on the magnetic field has been measured and used for determining the fluctuation field and activation volume. A relationship between the magnetic viscosity and magnetic noise caused by random thermoinduced magnetization reversal in separate nanoparticles is established.

Jiles–Atherton model used in the magnetization process study for the composite magnetoelectric materials based on cobalt ferrite and barium titanate

This paper presents the use of the Jiles–Atherton model in fitting the major magnetization curves for two classes of composite magnetoelectric materials. These materials are: (BaTiO3)x(CoFe2O4)1–x and (BaTiO3)x(CoMn0.2Fe1.8O4)1–x, with x = 0.8, 0.6, and 0.4. The model’s parameters result from finding the regression curves and give information about the micromagnetic state of the material. The dependencies of the model’s parameters on the ratio of the two phases’ concentrations have been analyzed. The values of the parameters for the two classes of materials have been compared, and the influence of Mn on the magnetic properties has been analyzed. Also presented here are the regression curves for a set of first order reversal curves using the same algorithm as the major magnetization curves. The dependence of the model’s parameters on the reversal field has been analyzed.