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Noise-dependent bias in quantitative STEM-EMCD experiments revealed by bootstrapping
Stockholm University, Faculty of Science, Department of Materials and Environmental Chemistry (MMK). Uppsala University, Sweden; Forschungszentrum Jülich, Germany.ORCID iD: 0000-0002-8262-5893
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Number of Authors: 72024 (English)In: Ultramicroscopy, ISSN 0304-3991, E-ISSN 1879-2723, Vol. 257, article id 113891Article in journal (Refereed) Published
Abstract [en]

Electron magnetic circular dichroism (EMCD) is a powerful technique for estimating element-specific magnetic moments of materials on nanoscale with the potential to reach atomic resolution in transmission electron microscopes. However, the fundamentally weak EMCD signal strength complicates quantification of magnetic moments, as this requires very high precision, especially in the denominator of the sum rules. Here, we employ a statistical resampling technique known as bootstrapping to an experimental EMCD dataset to produce an empirical estimate of the noise-dependent error distribution resulting from application of EMCD sum rules to bcc iron in a 3-beam orientation. We observe clear experimental evidence that noisy EMCD signals preferentially bias the estimation of magnetic moments, further supporting this with error distributions produced by Monte-Carlo simulations. Finally, we propose guidelines for the recognition and minimization of this bias in the estimation of magnetic moments.

Place, publisher, year, edition, pages
2024. Vol. 257, article id 113891
Keywords [en]
Electron magnetic circular dichroism, Electron energy loss spectroscopy, Scanning, Transmission electron microscopy, Bootstrapping, Noise dependent bias, Error analysis
National Category
Other Materials Engineering
Identifiers
URN: urn:nbn:se:su:diva-225757DOI: 10.1016/j.ultramic.2023.113891ISI: 001132754500001PubMedID: 38043363Scopus ID: 2-s2.0-85178597506OAI: oai:DiVA.org:su-225757DiVA, id: diva2:1830457
Available from: 2024-01-23 Created: 2024-01-23 Last updated: 2024-01-30Bibliographically approved

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Ali, HasanTai, Cheuk-WaiThersleff, Thomas

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