Unraveling Nanostructured Spin Textures in Bulk Magnets

Bender, Philipp; Leliaert, Jonathan; Bersweiler, Mathias; Honecker, Dirk; Michels, Andreas

doi:10.1002/smsc.202000003

Cited by 8 publications

(7 citation statements)

References 52 publications

(79 reference statements)

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“…While this is negligible when handling 1D data, it is a huge advantage for 2D data analysis as shown e.g. by Bender et al (2019Bender et al ( , 2021. Regarding an automated data analysis, the KA in particular has great potential as also discussed in the context of other measurement techniques (Karpavic ˇius et al, 2021).…”

Section: Discussion and Summarymentioning

confidence: 99%

“…This is not the case for magnetic neutron scattering due to the anisotropic nature of the dipole-dipole interaction (Mettus & Michels, 2015). However, the derived correlation functions still contain important information that reflects the real-space magnetization over the mesoscale (Bender et al, 2021). Thus, the Fourier transform of reciprocal SANS data is an easy and straightforward approach to obtain model-independent information regarding the chemical and magnetic nanostructure of the sample.…”

Section: Introductionmentioning

confidence: 99%

“…However, this approach is computationally intensive for large data sets. Therefore, two faster numerical approaches were recently introduced to determine the 2D correlation functions from scattering patterns, namely the singular value decomposition (SVD) (Bender et al, 2019) and the iterative Kaczmarz algorithm (KA) (Bender et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust approaches for model-free small-angle scattering data analysis

Bender¹,

Honecker²,

Bersweiler³

et al. 2022

J Appl Cryst

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The small-angle neutron scattering data of nanostructured magnetic samples contain information regarding their chemical and magnetic properties. Often, the first step to access characteristic magnetic and structural length scales is a model-free investigation. However, due to measurement uncertainties and a restricted q range, a direct Fourier transform usually fails and results in ambiguous distributions. To circumvent these problems, different methods have been introduced to derive regularized, more stable correlation functions, with the indirect Fourier transform being the most prominent approach. Here, the indirect Fourier transform is compared with the singular value decomposition and an iterative algorithm. These approaches are used to determine the correlation function from magnetic small-angle neutron scattering data of a powder sample of iron oxide nanoparticles; it is shown that with all three methods, in principle, the same correlation function can be derived. Each method has certain advantages and disadvantages, and thus the recommendation is to combine these three approaches to obtain robust results.

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Section: Discussion and Summarymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robust approaches for model-free small-angle scattering data analysis

Bender¹,

Honecker²,

Bersweiler³

et al. 2022

J Appl Cryst

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“…387 For data fitting, improved tools are developed such as Bayesian approaches for improving model fits of neutron reflectometry 388 and SANS 389 data to increase the predictive power of the fits and maximize the information density. Similar to model-fits also inverse Fourier transforms are usually ill-posed problems, and thus new approaches have been introduced in recent years that improve data analysis either by applying Bayesian analysis to find the most probable solution 390 or by using novel approaches such as the singular value decomposition 132 or fast iterative method to reveal the real-space 2D correlations 391 . In this context, it is safe to assume that also machine learning will massively contribute in upcoming years.…”

Section: Summary and Perspectivesmentioning

confidence: 99%

Using small-angle scattering to guide functional magnetic nanoparticle design

Honecker,

Bersweiler,

Erokhin

et al. 2022

Preprint

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Magnetic nanoparticles offer unique potential for various technological, biomedical, or environmental applications thanks to the size-, shape-and material-dependent tunability of their magnetic properties. To optimize particles for a specific application, it is crucial to interrelate their performance with their structural and magnetic properties. This review presents the advantages of small-angle X-ray and neutron scattering techniques for achieving a detailed multiscale characterization of magnetic nanoparticles and their ensembles in a mesoscopic size range from 1 to a few hundred nanometers with nanometer resolution. Both X-rays and neutrons allow the ensemble-averaged determination of structural properties, such as particle morphology or particle arrangement in multilayers and 3D assemblies. Additionally, the magnetic scattering contributions enable retrieving the internal magnetization profile of the nanoparticles as well as the inter-particle moment correlations caused by interactions within dense assemblies. Most measurements are used to determine the time-averaged ensemble properties, in addition advanced small-angle scattering techniques exist that allow accessing particle and spin dynamics on various timescales. In this review, we focus on conventional small-angle X-ray and neutron scattering (SAXS and SANS), X-ray and neutron reflectometry, gracing-incidence SAXS and SANS, X-ray resonant magnetic scattering, and neutron spin-echo spectroscopy techniques. For each technique, we provide a general overview, present the latest scientific results, and discuss its strengths as well as sample requirements. Finally, we give our perspectives on how future small-angle scattering experiments, especially in combination with micromagnetic simulations, could help to optimize the performance of magnetic nanoparticles for specific applications.

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“…32,40 Additionally, SANS allows one to access the internal magnetisation prole, 41,42 which renders it in general as an ideal technique to characterise complex nanostructured magnetic samples. 43 However, SANS is a highly complex technique which can be only performed at large-scale facilities whose access requires a long proposal application process, making it impractical as a day-to-day characterisation method.…”

Section: Introductionmentioning

confidence: 99%