Evidence map›Paper›PMID 36984011›Full record

ArticleMaterials (Basel, Switzerland)2023

First-Order Reversal Curves of Sets of Bistable Magnetostrictive Microwires.

Ana María Cabanas, Rafael Pérez Del Real, David Laroze, Manuel Vázquez

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

4 authors.

Ana María CabanasDepartamento de Física, FACI Universidad de Tarapacá, Arica 1010069, Chile.ORCID 0000-0003-2800-150X
Rafael Pérez Del RealInstituto de Ciencia de Materiales, CSIC, 28049 Madrid, Spain.ORCID 0000-0003-1374-8037
David LarozeInstituto de Alta Investigación, CEDENNA, Universidad de Tarapacá, Casilla 7D, Arica 1010069, Chile.ORCID 0000-0002-6487-8096
Manuel VázquezInstituto de Ciencia de Materiales, CSIC, 28049 Madrid, Spain.ORCID 0000-0001-5591-0157

Funding

Agencia Nacional de Investigación y Desarrollo AFB220001Agencia Nacional de Investigación y Desarrollo SA77210039University of Tarapacá UTA-Project 4722-22.
6 · The paper itself

Abstract

Amorphous microwires have attracted substantial attention in the past decade because of their useful technological applications. Their bistable magnetic response is determined by positive or negative magnetostriction, respectively. First-order reversal curves (FORC) are a powerful tool for analyzing the magnetization reversal processes of many-body ferromagnetic systems that are essential for a deeper understanding of those applications. After theoretical considerations about magnetostatic interactions among microwires, this work introduces a systematic experimental study and analysis of the FORC diagrams for magnetostrictive microwires exhibiting an individually bistable hysteresis loop, from a single microwire to sets of an increasing number of coupled microwires, the latter considered as an intermediate case to the standard many-body problem. We performed the study for sets of quasi-identical and different hysteretic microwires where we obtained the coercivity Hc and interaction Hu fields. In the cases with relevant magnetostatic interactions, FORC analysis supplies deeper information than standard hysteresis loops since the intrinsic fluctuations of the switching field generate a complex response. For sets of microwires with very different coercivity, the coercivity distributions of the individual microwires characterize the FORC diagram.

Indexed as

FORC analysismagnetic bistabilitymagnetic microwiresmagnetostatic interactions

Identifiers

PMID36984011
PMCPMC10058406

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Registered trials

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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.