Evidence map›Paper›PMID 37244978›Full record

ArticleScientific reports2023

Proposing magnetoimpedance effect for neuromorphic computing.

Loghman Jamilpanah, Alessandro Chiolerio, Marco Crepaldi, Andrew Adamatzky, Majid Mohseni

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Loghman JamilpanahDepartment of Physics, Shahid Beheshti University, Evin, Tehran, 19839, Iran. loghmanjamilpanah@gmail.com.
Alessandro ChiolerioBioinspired Soft Robotics, Center for Converging Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16165, Genoa, Italy.
Marco CrepaldiElectronic Design Laboratory, Center for Human Technologies, Istituto Italiano di Tecnologia, Via Enrico Melen 83, 16152, Genoa, Italy.
Andrew AdamatzkyUnconventional Computing Laboratory, University of the West of England, Coldharbour Lane, Bristol, BS16 1QY, UK.
Majid MohseniDepartment of Physics, Shahid Beheshti University, Evin, Tehran, 19839, Iran. m-mohseni@sbu.ac.ir.

Funding

European Commission FET-Open Challenging Current Thinking project "A new cOlloidal cybernetic system towards 2030 (COgITOR)" 964388Iran National Science Foundation 99002503
6 · The paper itself

Abstract

Oscillation 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.

Identifiers

PMID37244978
PMCPMC10224953

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.