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Distribution functions of magnetic nanoparticles determined by a numerical inversion method

Ten Hoope-Bender, Petra; Balceris, C.; Ludwig, F; Posth, O.; Bogart, L. K.; Szczerba, W.; Castro, A. LU ; Nilsson, L. LU ; Costo, R. and Gavilán, H., et al. (2017) In New Journal of Physics 19(7).
Abstract

In the present study, we applied a regularized inversion method to extract the particle size, magnetic moment and relaxation-time distribution of magnetic nanoparticles from small-angle x-ray scattering (SAXS), DC magnetization (DCM) and AC susceptibility (ACS) measurements. For the measurements the particles were colloidally dispersed in water. At first approximation the particles could be assumed to be spherically shaped and homogeneously magnetized single-domain particles. As model functions for the inversion, we used the particle form factor of a sphere (SAXS), the Langevin function (DCM) and the Debye model (ACS). The extracted distributions exhibited features/peaks that could be distinctly attributed to the individually dispersed... (More)

In the present study, we applied a regularized inversion method to extract the particle size, magnetic moment and relaxation-time distribution of magnetic nanoparticles from small-angle x-ray scattering (SAXS), DC magnetization (DCM) and AC susceptibility (ACS) measurements. For the measurements the particles were colloidally dispersed in water. At first approximation the particles could be assumed to be spherically shaped and homogeneously magnetized single-domain particles. As model functions for the inversion, we used the particle form factor of a sphere (SAXS), the Langevin function (DCM) and the Debye model (ACS). The extracted distributions exhibited features/peaks that could be distinctly attributed to the individually dispersed and non-interacting nanoparticles. Further analysis of these peaks enabled, in combination with a prior characterization of the particle ensemble by electron microscopy and dynamic light scattering, a detailed structural and magnetic characterization of the particles. Additionally, all three extracted distributions featured peaks, which indicated deviations of the scattering (SAXS), magnetization (DCM) or relaxation (ACS) behavior from the one expected for individually dispersed, homogeneously magnetized nanoparticles. These deviations could be mainly attributed to partial agglomeration (SAXS, DCM, ACS), uncorrelated surface spins (DCM) and/or intra-well relaxation processes (ACS). The main advantage of the numerical inversion method is that no ad hoc assumptions regarding the line shape of the extracted distribution functions are required, which enabled the detection of these contributions. We highlighted this by comparing the results with the results obtained by standard model fits, where the functional form of the distributions was a priori assumed to be log-normal shaped.

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published
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keywords
ACsusceptibility, distribution functions, magnetic nanoparticles, magnetization measurements, numerical inversion, SAXS
in
New Journal of Physics
volume
19
issue
7
publisher
IOP Publishing Ltd.
external identifiers
  • scopus:85026846181
ISSN
1367-2630
DOI
10.1088/1367-2630/aa73b4
language
English
LU publication?
yes
id
6c8a6535-504e-4ec7-be3a-0c148d932a55
date added to LUP
2017-08-31 15:28:31
date last changed
2017-08-31 15:28:31
@article{6c8a6535-504e-4ec7-be3a-0c148d932a55,
  abstract     = {<p>In the present study, we applied a regularized inversion method to extract the particle size, magnetic moment and relaxation-time distribution of magnetic nanoparticles from small-angle x-ray scattering (SAXS), DC magnetization (DCM) and AC susceptibility (ACS) measurements. For the measurements the particles were colloidally dispersed in water. At first approximation the particles could be assumed to be spherically shaped and homogeneously magnetized single-domain particles. As model functions for the inversion, we used the particle form factor of a sphere (SAXS), the Langevin function (DCM) and the Debye model (ACS). The extracted distributions exhibited features/peaks that could be distinctly attributed to the individually dispersed and non-interacting nanoparticles. Further analysis of these peaks enabled, in combination with a prior characterization of the particle ensemble by electron microscopy and dynamic light scattering, a detailed structural and magnetic characterization of the particles. Additionally, all three extracted distributions featured peaks, which indicated deviations of the scattering (SAXS), magnetization (DCM) or relaxation (ACS) behavior from the one expected for individually dispersed, homogeneously magnetized nanoparticles. These deviations could be mainly attributed to partial agglomeration (SAXS, DCM, ACS), uncorrelated surface spins (DCM) and/or intra-well relaxation processes (ACS). The main advantage of the numerical inversion method is that no ad hoc assumptions regarding the line shape of the extracted distribution functions are required, which enabled the detection of these contributions. We highlighted this by comparing the results with the results obtained by standard model fits, where the functional form of the distributions was a priori assumed to be log-normal shaped.</p>},
  articleno    = {073012},
  author       = {Ten Hoope-Bender, Petra and Balceris, C. and Ludwig, F and Posth, O. and Bogart, L. K. and Szczerba, W. and Castro, A. and Nilsson, L. and Costo, R. and Gavilán, H. and González-Alonso, D. and Pedro, I. De and Barquin, L. Fernández and Johansson, C.},
  issn         = {1367-2630},
  keyword      = {ACsusceptibility,distribution functions,magnetic nanoparticles,magnetization measurements,numerical inversion,SAXS},
  language     = {eng},
  month        = {07},
  number       = {7},
  publisher    = {IOP Publishing Ltd.},
  series       = {New Journal of Physics},
  title        = {Distribution functions of magnetic nanoparticles determined by a numerical inversion method},
  url          = {http://dx.doi.org/10.1088/1367-2630/aa73b4},
  volume       = {19},
  year         = {2017},
}