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Surface effects in nanoparticles: application to maghemite -Fe O

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Kachkachi, H., Ezzir, A., Noguès, M., Tronc, E.·2000·The European Physical Journal B

Abstract

Abstract:We present a microscopic model for nanoparticles, of the maghemite-Fe2O3) type, and perform classical Monte Carlo simulations of their magnetic properties. On account of Mössbauer spectroscopy and high-field magnetisation results, we consider a particle as composed of a core and a surface shell of constant thickness. The magnetic state in the particle is described by the anisotropic classical Dirac-Heisenberg model including exchange and dipolar interactions and bulk and surface anisotropy. We consider the case of ellipsoidal (or spherical) particles with free boundaries at the surface. Using a surface shell of constant thickness nm) we vary the particle size and study the effect of surface magnetic disorder on the thermal and spatial behaviors of the net magnetisation of the particle. We study the shift in the surface “critical region” for different surface-to-core ratios of the exchange coupling constants. It is also shown that the profile of the local magnetisation exhibits strong temperature dependence, and that surface anisotropy is responsible for the non saturation of the magnetisation at low temperatures.

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Metadata

Authors
Kachkachi, H., Ezzir, A., Noguès, M., & Tronc, E.
Venue
The European Physical Journal B
Published
2000-04
Volume
14
Issue
4
Pages
681-689
ISSN
  • 1434-6028 (ISSN-L)
  • 1434-6036
OpenAlex
W2315024714
Cited by
158
References
0
FWCI
7.93
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Surface effects in nanoparticles: application to maghemite -Fe O. https://app.cochat.ai/papers/10.1007/s100510051079
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Kachkachi, H., Ezzir, A., Noguès, M., & Tronc, E. (2000). Surface effects in nanoparticles: application to maghemite -Fe O. The European Physical Journal B. https://doi.org/10.1007/s100510051079

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.