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Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements
Quantifying chemical compositions around nanovoids is a fundamental task for research and development of various materials. Atom probe tomography (APT) and scanning transmission electron microscopy (STEM) are currently the most suitable tools because of their ability to probe materials at the nanosc...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7039975/ https://www.ncbi.nlm.nih.gov/pubmed/32094330 http://dx.doi.org/10.1038/s41467-020-14832-w |
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author | Wang, Xing Hatzoglou, Constantinos Sneed, Brian Fan, Zhe Guo, Wei Jin, Ke Chen, Di Bei, Hongbin Wang, Yongqiang Weber, William J. Zhang, Yanwen Gault, Baptiste More, Karren L. Vurpillot, Francois Poplawsky, Jonathan D. |
author_facet | Wang, Xing Hatzoglou, Constantinos Sneed, Brian Fan, Zhe Guo, Wei Jin, Ke Chen, Di Bei, Hongbin Wang, Yongqiang Weber, William J. Zhang, Yanwen Gault, Baptiste More, Karren L. Vurpillot, Francois Poplawsky, Jonathan D. |
author_sort | Wang, Xing |
collection | PubMed |
description | Quantifying chemical compositions around nanovoids is a fundamental task for research and development of various materials. Atom probe tomography (APT) and scanning transmission electron microscopy (STEM) are currently the most suitable tools because of their ability to probe materials at the nanoscale. Both techniques have limitations, particularly APT, because of insufficient understanding of void imaging. Here, we employ a correlative APT and STEM approach to investigate the APT imaging process and reveal that voids can lead to either an increase or a decrease in local atomic densities in the APT reconstruction. Simulated APT experiments demonstrate the local density variations near voids are controlled by the unique ring structures as voids open and the different evaporation fields of the surrounding atoms. We provide a general approach for quantifying chemical segregations near voids within an APT dataset, in which the composition can be directly determined with a higher accuracy than STEM-based techniques. |
format | Online Article Text |
id | pubmed-7039975 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70399752020-03-04 Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements Wang, Xing Hatzoglou, Constantinos Sneed, Brian Fan, Zhe Guo, Wei Jin, Ke Chen, Di Bei, Hongbin Wang, Yongqiang Weber, William J. Zhang, Yanwen Gault, Baptiste More, Karren L. Vurpillot, Francois Poplawsky, Jonathan D. Nat Commun Article Quantifying chemical compositions around nanovoids is a fundamental task for research and development of various materials. Atom probe tomography (APT) and scanning transmission electron microscopy (STEM) are currently the most suitable tools because of their ability to probe materials at the nanoscale. Both techniques have limitations, particularly APT, because of insufficient understanding of void imaging. Here, we employ a correlative APT and STEM approach to investigate the APT imaging process and reveal that voids can lead to either an increase or a decrease in local atomic densities in the APT reconstruction. Simulated APT experiments demonstrate the local density variations near voids are controlled by the unique ring structures as voids open and the different evaporation fields of the surrounding atoms. We provide a general approach for quantifying chemical segregations near voids within an APT dataset, in which the composition can be directly determined with a higher accuracy than STEM-based techniques. Nature Publishing Group UK 2020-02-24 /pmc/articles/PMC7039975/ /pubmed/32094330 http://dx.doi.org/10.1038/s41467-020-14832-w Text en © This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Wang, Xing Hatzoglou, Constantinos Sneed, Brian Fan, Zhe Guo, Wei Jin, Ke Chen, Di Bei, Hongbin Wang, Yongqiang Weber, William J. Zhang, Yanwen Gault, Baptiste More, Karren L. Vurpillot, Francois Poplawsky, Jonathan D. Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements |
title | Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements |
title_full | Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements |
title_fullStr | Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements |
title_full_unstemmed | Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements |
title_short | Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements |
title_sort | interpreting nanovoids in atom probe tomography data for accurate local compositional measurements |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7039975/ https://www.ncbi.nlm.nih.gov/pubmed/32094330 http://dx.doi.org/10.1038/s41467-020-14832-w |
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