Relation of the average interaction field with the coercive and interaction field distributions in First order reversal curve diagrams of nanowire arrays

Tuning the magnetic properties of hard-soft Ba0.5Sr0.5Fe10Al2O19and Ni0.1Co0.9Fe2O4nanocomposites via one pot sol-gel auto combustion method for permanent magnet applications

Permanent magnets generate magnetic fields that can be sustained when a reverse field is supplied. These permanent magnets are effective in a wide range of applications. However, strategic rare-earth element demand has increased interest in replacing them with huge energy product (BH)max. Exchange-coupled hard/soft ferrite nanocomposites have the potential to replace a portion of extravagant rare earth element-based magnets. In the present, we have reported the facile auto combustion synthesis of exchange-coupled Ba0.5Sr0.5Fe10Al2O19and Ni0.1Co0.9Fe2O4nanocomposites by increasing the content of soft ferrite over the hard fromx= 0.1 to 0.4 wt%. The XRD combined with Rietveld analysis reflected the presence of hexaferrite and spinel ferrite without the existence of secondary phases. The absorption bands from the Fourier transform infrared spectrum analysis proved the presence of M-O bonds in tetrahedral sites and octahedral sites. Rod and non-spherical images from TEM represent the hexaferrite and spinel ferrite. The smoothM-Hcurve and a single peak of the switching field distribution curve prove that the material has undergone a good exchange coupling. The nanopowders displayed an increase in saturation magnetization and a decrease in coercivity with the increases in the spinel content. The prepared nanocomposites were showing higher energy products. The composite with the ratiox= 0.2 displayed a higher value of (BH)maxof 13.16 kJ m-3.

Review of Play and Preisach Models for Hysteresis in Magnetic Materials

This paper studies the properties of the Preisach model and the play model, and compare their similarities. Both are history-dependent hysteresis models that are used to model magnetic hysteresis. They are described as discrete sums of simple hysteresis operators but can easily be reformulated as integral equations of continuous distribution functions using either a Preisach weight distribution function or a play distribution function. The models are mostly seen as phenomenological or mathematical tools but can also be related to friction-like pinning of domain-wall motions, where Rayleigh's law of magnetic hysteresis can be seen as the simplest case on either the play model or the Preisach model. They are poor at modeling other domain behavior, such as nucleation-driven hysteresis. Yet another hysteresis model is the stop model, which can be seen as the inverted version of the play model. This type of model has advantages for expressions linked to energy and can be related to Steinmetz equation of hysteresis losses. The models share several mathematical properties, such as the congruency property and wiping-out property, and both models have a history of dependence that can be described by the series of past reversal points. More generally, it is shown that the many models can be expressed as Preisach models, showing that they can be treated as subcategories of the Preisach type models. These include the play model, the stop model and also the alternative KP-hysteron model.

Magnetic Nanowires for Nanobarcoding and Beyond

Multifunctional magnetic nanowires (MNWs) have been studied intensively over the last decades, in diverse applications. Numerous MNW-based systems have been introduced, initially for fundamental studies and later for sensing applications such as biolabeling and nanobarcoding. Remote sensing of MNWs for authentication and/or anti-counterfeiting is not only limited to engineering their properties, but also requires reliable sensing and decoding platforms. We review the latest progress in designing MNWs that have been, and are being, introduced as nanobarcodes, along with the pros and cons of the proposed sensing and decoding methods. Based on our review, we determine fundamental challenges and suggest future directions for research that will unleash the full potential of MNWs for nanobarcoding applications.