The objective of the work was the design of a Wheatstone bridge current sensor using MTJ as magnetoresistive elements. Each one of the four resistances of the bridge consists on 360 MTJ single elements connected in series for improved electrical robustness. A printed circuit board (PCB) was designed with a U-shaped copper trace placed under the PCB maintaining a 1.1 mm separation distance between sensor and trace. A 160% of tunnel magnetoresistance effect in the single junction and a 120% in its corresponding series elements connection has been achieved with a sensitivity of 9.2 Ω/Oe in a 65 Oe linear range. The DC sensor sensitivity in response to an external DC current sweeps of ±10, ±20, and ±30 A gave an average of 9.8 mV/A. The measured AC sensor response in all the tested cases corresponded to a - 3 dB frequency close to 200 kHz. The sensor was submitted to a DC current excursion under different temperatures showing a TC(S) sensitivity temperature coefficient of 0.031%/° C rather lower compared with the spin-valve technology. The work shows that MTJ sensor technology provides a promising tool in the R+D areas of power management and energy consumption like electric vehicles or energy metering.

In this work, arrays of MgO-based magnetic tunnel junction elements (5×20 μm²) connected in series are studied for sensor applications. Linearization is obtained by combining shape anisotropy with a longitudinal hard bias field set by CoCrPt permanent magnets integrated on the sides of the array. We show that this architecture has the drawback of a large footprint in the chip, but is largely compensated by the weak bias voltage dependence and huge electric robustness, when comparing with individual magnetic tunnel junctions.

Recent studies highlight the ability of inductive architectures to deliver therapeutic magnetic stimuli to target tissues and to be embedded into small-scale intracorporeal medical devices. However, to date, current micro-scale biomagnetic devices require very high electric current excitations (usually exceeding 1 A) to ensure the delivery of efficient magnetic flux densities. This is a critical problem as advanced implantable devices demand self-powering, stand-alone and long-term operation. This work provides, for the first time, a novel small-scale magnetic stimulation system that requires up to 50-fold lower electric current excitations than required by relevant biomagnetic technology recently proposed. Computational models were developed to analyse the magnetic stimuli distributions and densities delivered to cellular tissues during in vitro experiments, such that the feasibility of this novel stimulator can be firstly evaluated on cell culture tests. The results demonstrate that this new stimulative technology is able to deliver osteogenic stimuli (0.1-7 mT range) by current excitations in the 0.06-4.3 mA range. Moreover, it allows coil designs with heights lower than 1 mm without significant loss of magnetic stimuli capability. Finally, suitable core diameters and stimulator-stimulator distances allow to define heterogeneity or quasi-homogeneity stimuli distributions. These results support the design of high-sophisticated biomagnetic devices for a wide range of therapeutic applications.

Device optimization plays a paramount role in current research on magnetic refrigeration. Solid state refrigerants have been characterized and numerical simulations assume a critical relevance in the development of magnetocaloric technology to have alternatives to vapour-compression systems whose operating elements have high global warming potential. Experimental studies have shown that the thermal properties of several magnetocaloric materials considerably change around their Curie temperatures ($T_C$) and that this temperature dependency should not be dismissed. Current numerical research does not fully predict the complete thermal response of such materials, due to inaccuracies from neglecting the impact of combining both thermal conductivity (k) and specific heat ($C_p$) dependence on temperature. In this study, a simple unidimensional model includes $k\left(T\right)$ and $C_p\left(T\right)$ functions as input parameters, highlighting the relevance of considering temperature dependent thermophysical properties’ inputs when simulating the magnetic refrigerant’s heat transfer processes. The obtained results evidence that neglecting the temperature dependence of the magnetocaloric material thermophysical properties, namely its thermal conductivity and its specific heat, affects its temperature response, what may strongly affect the results after a succession of (hundreds or thousands) cycles.