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http://hdl.handle.net/1942/38702Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | De Wael, Annelies | - |
| dc.contributor.author | De Backer , Annick | - |
| dc.contributor.author | Yu, Chu-Ping | - |
| dc.contributor.author | Sentuerk, Duygu Gizem | - |
| dc.contributor.author | Lobato, Ivan | - |
| dc.contributor.author | FAES, Christel | - |
| dc.contributor.author | Van Aert, Sandra | - |
| dc.date.accessioned | 2022-10-06T07:47:23Z | - |
| dc.date.available | 2022-10-06T07:47:23Z | - |
| dc.date.issued | 2022 | - |
| dc.date.submitted | 2022-10-04T15:07:49Z | - |
| dc.identifier.citation | MICROSCOPY AND MICROANALYSIS, | - |
| dc.identifier.uri | http://hdl.handle.net/1942/38702 | - |
| dc.description.abstract | A decade ago, a statistics-based method was introduced to count the number of atoms from annular dark-field scanning transmission electron microscopy (ADF STEM) images. In the past years, this method was successfully applied to nanocrystals of arbitrary shape, size, and composition (and its high accuracy and precision has been demonstrated). However, the counting results obtained from this statistical framework are so far presented without a visualization of the actual uncertainty about this estimate. In this paper, we present three approaches that can be used to represent counting results together with their statistical error, and discuss which approach is most suited for further use based on simulations and an experimental ADF STEM image. | - |
| dc.description.sponsorship | This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 770887 and No. 823717 ESTEEM3). The authors acknowledge financial support from the Research Foundation Flanders (FWO, Belgium) through grants to A.D.w. and A.D.B. and projects G.0502.18N, G.0267.18N, and EOS 30489208. S.V.A. acknowledges TOP BOF funding from the University of Antwerp. The authors are grateful to L.M. Liz-Marzán (CIC biomaGUNE and Ikerbasque) for providing the samples. | - |
| dc.language.iso | en | - |
| dc.publisher | CAMBRIDGE UNIV PRESS | - |
| dc.rights | The Author(s), 2022. Published by Cambridge University Press on behalf of the Microscopy Society of America. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. | - |
| dc.subject.other | model averaging | - |
| dc.subject.other | quantitative electron microscopy | - |
| dc.subject.other | scanning transmission electron microscopy | - |
| dc.subject.other | statistical parameter estimation theory | - |
| dc.subject.other | statistical uncertainty | - |
| dc.title | Three Approaches for Representing the Statistical Uncertainty on Atom-Counting Results in Quantitative ADF STEM | - |
| dc.type | Journal Contribution | - |
| local.bibliographicCitation.jcat | A1 | - |
| dc.description.notes | Van Aert, S (corresponding author), Univ Antwerp, EMAT, Antwerp, Belgium.; Van Aert, S (corresponding author), Univ Antwerp, NANOlab Ctr Excellence, Antwerp, Belgium. | - |
| dc.description.notes | sandra.vanaert@uantwerpen.be | - |
| local.publisher.place | 32 AVENUE OF THE AMERICAS, NEW YORK, NY 10013-2473 USA | - |
| local.type.refereed | Refereed | - |
| local.type.specified | Article | - |
| local.bibliographicCitation.status | Early view | - |
| dc.identifier.doi | 10.1017/S1431927622012284 | - |
| dc.identifier.pmid | 36117265 | - |
| dc.identifier.isi | 000854930500001 | - |
| dc.contributor.orcid | De Backer, Annick/0000-0002-8592-4776; Yu, Chu-Ping/0000-0003-1563-5095; | - |
| dc.contributor.orcid | FAES, Christel/0000-0002-1878-9869; Lobato Hoyos, Ivan | - |
| dc.contributor.orcid | Pedro/0000-0003-4088-6398; De wael, Annelies/0000-0003-1356-2777; | - |
| dc.contributor.orcid | Senturk, Duygu Gizem/0000-0002-0205-8156 | - |
| local.provider.type | wosris | - |
| local.description.affiliation | [De Wael, Annelies; De Backer, Annick; Yu, Chu-Ping; Sentuerk, Duygu Gizem; Lobato, Ivan; Van Aert, Sandra] Univ Antwerp, EMAT, Antwerp, Belgium. | - |
| local.description.affiliation | [De Wael, Annelies; De Backer, Annick; Yu, Chu-Ping; Sentuerk, Duygu Gizem; Lobato, Ivan; Van Aert, Sandra] Univ Antwerp, NANOlab Ctr Excellence, Antwerp, Belgium. | - |
| local.description.affiliation | [Faes, Christel] Hasselt Univ, Data Sci Inst, I BioStat, Hasselt, Belgium. | - |
| local.uhasselt.international | no | - |
| item.contributor | De Wael, Annelies | - |
| item.contributor | De Backer , Annick | - |
| item.contributor | Yu, Chu-Ping | - |
| item.contributor | Sentuerk, Duygu Gizem | - |
| item.contributor | Lobato, Ivan | - |
| item.contributor | FAES, Christel | - |
| item.contributor | Van Aert, Sandra | - |
| item.accessRights | Open Access | - |
| item.fulltext | With Fulltext | - |
| item.fullcitation | De Wael, Annelies; De Backer , Annick; Yu, Chu-Ping; Sentuerk, Duygu Gizem; Lobato, Ivan; FAES, Christel & Van Aert, Sandra (2022) Three Approaches for Representing the Statistical Uncertainty on Atom-Counting Results in Quantitative ADF STEM. In: MICROSCOPY AND MICROANALYSIS,. | - |
| item.validation | ecoom 2023 | - |
| crisitem.journal.issn | 1431-9276 | - |
| crisitem.journal.eissn | 1435-8115 | - |
| Appears in Collections: | Research publications | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| S1431927622012284jra 1..9.pdf | Published version | 1.06 MB | Adobe PDF | View/Open |
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