The potential of magnetic nanoparticles for acting as efficient catalysts, imaging tracers or heating mediators relays on their superparamagnetic behaviour under alternating magnetic fields. In spite of the relevance of this magnetic phenomenon, the identification of specific fingerprints to unequivocally assign superparamagnetic behaviour to nanomaterials is still lacking. Herein, we report on novel experimental and theoretical evidences related to the superparamagnetism observed in magnetic iron oxide nanoparticle suspensions at room temperature.
View Article and Find Full Text PDFIsothermal tuning of both the magnitude and the sign of the bias field has been achieved by exploiting a new phenomenon in a system consisting of two orthogonally coupled films: SmCo5 (out-of-plane anisotropy)-CoFeB (in-plane anisotropy). This has been achieved by using the large dipolar magnetic field of the SmCo5 layer resulting in the pinning of one of the branches of the hysteresis loop (either the ascending or the descending branch) at a fixed field value while the second one is modulated along the field axis by varying the orientation of an externally applied magnetic field. This means the possibility of controlling the sign of the bias field in a manner not reported to date.
View Article and Find Full Text PDFThe evolution of the magnetic anisotropy directions has been studied in a magnetite (FeO) thin film grown by infrared pulsed-laser deposition on SrTiO(100):Nb substrate. The magnetic easy axes at room temperature are found along the in-plane 〈100〉 film directions, which means a rotation of the easy axis by 45° with respect to the directions typically reported for bulk magnetite and films grown on single-crystal substrates. Moreover, when undergoing the Verwey transition temperature, T, the easy axis orientation evolves to the 〈110〉 film directions.
View Article and Find Full Text PDFThis study examines the very short, short, medium and long-term forecasting ability of different univariate GARCH models of United Kingdom (UK)'s interest rate volatility, using a long span monthly data from May 1836 to June 2018. The main results show the relevance of considering alternative error distributions to the normal distribution when estimating GARCH-type models. Thus, we obtain that the Asymmetric Power ARCH (A-PARCH) models with skew generalized error distribution are the most accurate models when forecasting UK interest rates, while for the short, medium and long-term term forecasting horizons, GARCH models with generalized error distribution for the error term are the most accurate models in forecasting UK's interest rates.
View Article and Find Full Text PDFMost of the magnetic devices in advanced electronics rely on the exchange bias effect, a magnetic interaction that couples a ferromagnetic and an antiferromagnetic material, resulting in a unidirectional displacement of the ferromagnetic hysteresis loop by an amount called the 'exchange bias field'. Setting and optimizing exchange bias involves cooling through the Néel temperature of the antiferromagnetic material in the presence of a magnetic field. Here we demonstrate an alternative process for the generation of exchange bias.
View Article and Find Full Text PDF