Evidence map›Paper›PMID 32792603›Full record

ArticleScientific reports2020

Equilibrium properties of assembly of interacting superparamagnetic nanoparticles.

N A Usov, O N Serebryakova

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. 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
0.9field-weighted citation impact, top 30% of its field
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, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Room Temperature Magnetic Memory Effect in Nanodiamond/γ-FeNanomaterials (Basel, Switzerland) · 2021
    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

2 authors at 1 institution in 1 country.

N A UsovNational University of Science and Technology "MISiS", Moscow, 119049, Russia. usov@obninsk.ru.
O N SerebryakovaPushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation, Russian Academy of Sciences, IZMIRAN, Troitsk, Moscow, 108480, Russia.
Institute of Terrestrial Magnetism Ionosphere and Radio Wave Propagation · RU

Funding

Ministry of Higher Education and Science of Russian Federation K-2019-012
6 · The paper itself

Abstract

The stochastic Landau-Lifshitz equation is used to investigate the relaxation process and equilibrium magnetization of interacting assembly of superparamagnetic nanoparticles (SPMNPs) uniformly distributed in a nonmagnetic matrix. For weakly interacting assembly, the equilibrium magnetization is shown to deviate significantly from the Langevin law at moderate and large magnetic fields under the influence of their magnetic anisotropies. For dense assemblies with noticeable influence of the magneto-dipole interaction, a significant dependence of the initial susceptibility on the assembly density is revealed. The difference between the initial susceptibility and the corresponding Langevin susceptibility can serve as an indication of appreciable influence of the magneto-dipole interaction on the assembly properties. A new self-consistent approach is developed to explain the effect of mutual magneto-dipole interaction on the behavior of dense assembly of SPMNPs. The probability densities of the components of random magnetic field acting on magnetic NPs are calculated at thermodynamic equilibrium. The self-consistent probability densities of these components are found to be close to Gaussian distribution. A decreasing equilibrium assembly magnetization as a function of its density can be explained as a disorienting effect of the random magnetic field on the NPs magnetic moments.

Identifiers

PMID32792603
PMCPMC7426820
OpenAlexW3013999997

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.