Author:
Jamilpanah Loghman,Chiolerio Alessandro,Crepaldi Marco,Adamatzky Andrew,Mohseni Majid
Abstract
AbstractOscillation of physical parameters in materials can result in a peak signal in the frequency spectrum of the voltage measured from the materials. This spectrum and its amplitude/frequency tunability, through the application of bias voltage or current, can be used to perform neuron-like cognitive tasks. Magnetic materials, after achieving broad distribution for data storage applications in classical Von Neumann computer architectures, are under intense investigation for their neuromorphic computing capabilities. A recent successful demonstration regards magnetisation oscillation in magnetic thin films by spin transfer or spin orbit torques accompanied by magnetoresistance (MR) effect that can give a voltage peak in the frequency spectrum of voltage with bias current dependence of both peak frequency and amplitude. Here we use classical magnetoimpedance (MI) effect in a magnetic wire to produce such a peak and manipulate its frequency and amplitude by means of the bias voltage. We applied a noise signal to a magnetic wire with high magnetic permeability and owing to the frequency dependence of the magnetic permeability we got frequency dependent impedance with a peak at the maximum permeability. Frequency dependence of the MI effect results in different changes in the voltage amplitude at each frequency when a bias voltage is applied and therefore a shift in the peak position and amplitude can be obtained. The presented method and material provide optimal features in structural simplicity, low-frequency operation (tens of MHz-order) and high robustness at different environmental conditions. Our universal approach can be applied to any system with frequency dependent bias responses.
Funder
European Commission FET-Open Challenging Current Thinking project “A new cOlloidal cybernetic system towards 2030 (COgITOR)”
Iran National Science Foundation
Publisher
Springer Science and Business Media LLC
Cited by
1 articles.
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1. Numerical Modeling of the Magnetoimpedance effect from Micromagnetism;2024 IEEE International Magnetic Conference - Short papers (INTERMAG Short papers);2024-05-05