Evidence map›Paper›PMID 38793491›Full record

ArticleMaterials (Basel, Switzerland)2024

Artificial Neuron Based on the Bloch-Point Domain Wall in Ferromagnetic Nanowires.

Carlos Sánchez, Diego Caso, Farkhad G Aliev

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2024. 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

3 authors.

Carlos SánchezDepartamento de Física de la Materia Condensada C03, Universidad Autónoma de Madrid, 28049 Madrid, Spain.ORCID 0009-0007-4013-1899
Diego CasoDepartamento de Física de la Materia Condensada C03, Universidad Autónoma de Madrid, 28049 Madrid, Spain.ORCID 0000-0003-3273-1863
Farkhad G AlievDepartamento de Física de la Materia Condensada C03, Universidad Autónoma de Madrid, 28049 Madrid, Spain.ORCID 0000-0002-1682-3306

Funding

Spanish Ministry of Science and Innovation PID2021-124585NB-C32 and 130196B-C22Spanish Ministry of Science and Innovation through the María de Maeztu Programme for Units of Excellence in R&D CEX 2023-001316-M
6 · The paper itself

Abstract

Nanomagnetism and spintronics are currently active areas of research, with one of the main goals being the creation of low-energy-consuming magnetic memories based on nanomagnet switching. These types of devices could also be implemented in neuromorphic computing by crafting artificial neurons (ANs) that emulate the characteristics of biological neurons through the implementation of neuron models such as the widely used leaky integrate-and-fire (LIF) with a refractory period. In this study, we have carried out numerical simulations of a 120 nm diameter, 250 nm length ferromagnetic nanowire (NW) with the aim of exploring the design of an artificial neuron based on the creation and destruction of a Bloch-point domain wall. To replicate signal integration, we applied pulsed trains of spin currents to the opposite faces of the ferromagnetic NW. These pulsed currents (previously studied only in the continuous form) are responsible for inducing transitions between the stable single vortex (SV) state and the metastable Bloch point domain wall (BP-DW) state. To ensure the system exhibits leak and refractory properties, the NW was placed in a homogeneous magnetic field of the order of mT in the axial direction. The suggested configuration fulfills the requirements and characteristics of a biological neuron, potentially leading to the future creation of artificial neural networks (ANNs) based on reversible changes in the topology of magnetic NWs.

Indexed as

artificial neuronbloch pointsnanowire

Identifiers

PMID38793491
PMCPMC11123237

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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.