Visible to the public Characterization of dynamic nonlinear effects in MTJ-based magnetic sensors

TitleCharacterization of dynamic nonlinear effects in MTJ-based magnetic sensors
Publication TypeConference Paper
Year of Publication2017
AuthorsAuerbach, E., Leder, N., Gider, S., Suess, D., Arthaber, H.
Conference Name2017 Integrated Nonlinear Microwave and Millimetre-wave Circuits Workshop (INMMiC)
PublisherIEEE
ISBN Number978-1-5090-5862-4
Keywordscomposability, dynamic nonlinear effects, ferromagnetic resonance (FMR), Frequency measurement, Harmonic analysis, Junctions, magnetic materials, magnetic read sensors, Magnetic resonance, magnetic sensor nonlinear properties, magnetic sensors, magnetic tunnel junction, magnetic tunnel junction (MTJ), Magnetic tunneling, magnetic tunnelling, magnetisation, Magnetization, measurement techniques, memory effects, Metrics, MTJ-based magnetic sensors, Nonlinear dynamical systems, oscillating behaviors, pubcrawl, Resiliency, two-tone measurement technique, two-tone measurements
Abstract

The MgO-based magnetic tunnel junction (MTJ) is the basis of modern hard disk drives' magnetic read sensors. Within its operating bandwidth, the sensor's performance is significantly affected by nonlinear and oscillating behavior arising from the MTJ's magnetization dynamics at microwave frequencies. Static I-V curve measurements are commonly used to characterize sensor's nonlinear effects. Unfortunately, these do not sufficiently capture the MTJ's magnetization dynamics. In this paper, we demonstrate the use of the two-tone measurement technique for full treatment of the sensor's nonlinear effects in conjunction with dynamic ones. This approach is new in the field of magnetism and magnetic materials, and it has its challenges due to the nature of the device. Nevertheless, the experimental results demonstrate how the two-tone measurement technique can be used to characterize magnetic sensor nonlinear properties.

URLhttp://ieeexplore.ieee.org/document/7927309/
DOI10.1109/INMMIC.2017.7927309
Citation Keyauerbach_characterization_2017