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Author |
Craig, T.M.; Kadu, A.A.; Batenburg, K.J.; Bals, S. |
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Title |
Real-time tilt undersampling optimization during electron tomography of beam sensitive samples using golden ratio scanning and RECAST3D |
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A1 Journal article |
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Year |
2023 |
Publication |
Nanoscale |
Abbreviated Journal |
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Volume |
15 |
Issue |
11 |
Pages |
5391-5402 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
Electron tomography is a widely used technique for 3D structural analysis of nanomaterials, but it can cause damage to samples due to high electron doses and long exposure times. To minimize such damage, researchers often reduce beam exposure by acquiring fewer projections through tilt undersampling. However, this approach can also introduce reconstruction artifacts due to insufficient sampling. Therefore, it is important to determine the optimal number of projections that minimizes both beam exposure and undersampling artifacts for accurate reconstructions of beam-sensitive samples. Current methods for determining this optimal number of projections involve acquiring and post-processing multiple reconstructions with different numbers of projections, which can be time-consuming and requires multiple samples due to sample damage. To improve this process, we propose a protocol that combines golden ratio scanning and quasi-3D reconstruction to estimate the optimal number of projections in real-time during a single acquisition. This protocol was validated using simulated and realistic nanoparticles, and was successfully applied to reconstruct two beam-sensitive metal–organic framework complexes. |
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Wos |
000937908900001 |
Publication Date |
2023-02-13 |
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Edition |
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ISSN |
2040-3364 |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
6.7 |
Times cited |
1 |
Open Access  |
OpenAccess |
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Notes |
H2020 European Research Council, 815128 ; H2020 Marie Skłodowska-Curie Actions, 860942 ; |
Approved |
Most recent IF: 6.7; 2023 IF: 7.367 |
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Call Number |
EMAT @ emat @c:irua:195235 |
Serial |
7260 |
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Author |
Skorikov, A.; Batenburg, K.J.; Bals, S. |
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Title |
Analysis of 3D elemental distribution in nanomaterials : towards higher throughput and dose efficiency |
Type |
A1 Journal article |
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Year |
2023 |
Publication |
Journal of microscopy |
Abbreviated Journal |
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Volume |
289 |
Issue |
3 |
Pages |
157-163 |
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Keywords |
A1 Journal article; Electron microscopy for materials research (EMAT) |
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Abstract |
Many advanced nanomaterials rely on carefully designed morphology and elemental distribution to achieve their functionalities. Among the few experimental techniques that can directly visualise the 3D elemental distribution on the nanoscale are approaches based on electron tomography in combination with energy-dispersive X-ray spectroscopy (EDXS) and electron energy loss spectroscopy (EELS). Unfortunately, these highly informative methods are severely limited by the fundamentally low signal-to-noise ratio, which makes long experimental times and high electron irradiation doses necessary to obtain reliable 3D reconstructions. Addressing these limitations has been the major research question for the development of these techniques in recent years. This short review outlines the latest progress on the methods to reduce experimental time and electron irradiation dose requirements for 3D elemental distribution analysis and gives an outlook on the development of this field in the near future. |
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Wos |
000910532600001 |
Publication Date |
2022-12-26 |
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ISSN |
0022-2720 |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
2 |
Times cited |
2 |
Open Access |
OpenAccess |
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Notes |
ERC Consolidator Grant, Grant/Award Number: 815128 |
Approved |
Most recent IF: 2; 2023 IF: 1.692 |
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Call Number |
UA @ admin @ c:irua:193428 |
Serial |
7281 |
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Author |
Kavak, S.; Kadu, A.A.; Claes, N.; Sánchez-Iglesias, A.; Liz-Marzán, L.M.; Batenburg, K.J.; Bals, S. |
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Title |
Quantitative 3D Investigation of Nanoparticle Assemblies by Volumetric Segmentation of Electron Tomography Data Sets |
Type |
A1 Journal Article |
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Year |
2023 |
Publication |
The journal of physical chemistry: C : nanomaterials and interfaces |
Abbreviated Journal |
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Volume |
127 |
Issue |
20 |
Pages |
9725-9734 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
Morphological characterization of nanoparticle assemblies and hybrid nanomaterials is critical in determining their structure-property relationships as well as in the development of structures with desired properties. Electron tomography has become a widely utilized technique for the three-dimensional characterization of nanoparticle assemblies. However, the extraction of quantitative morphological parameters from the reconstructed volume can be a complex and labor-intensive task. In this study, we aim to overcome this challenge by automating the volumetric segmentation process applied to three-dimensional reconstructions of nanoparticle assemblies. The key to enabling automated characterization is to assess the performance of different volumetric segmentation methods in accurately extracting predefined quantitative descriptors for morphological characterization. In our methodology, we compare the quantitative descriptors obtained through manual segmentation with those obtained through automated segmentation methods, to evaluate their accuracy and effectiveness. To show generality, our study focuses on the characterization of assemblies of CdSe/CdS quantum dots, gold nanospheres and CdSe/CdS encapsulated in polymeric micelles, and silica-coated gold nanorods decorated with both CdSe/CdS or PbS quantum dots. We use two unsupervised segmentation algorithms: the watershed transform and the spherical Hough transform. Our results demonstrate that the choice of automated segmentation method is crucial for accurately extracting the predefined quantitative descriptors. Specifically, the spherical Hough transform exhibits superior performance in accurately extracting quantitative descriptors, such as particle size and interparticle distance, thereby allowing for an objective, efficient, and reliable volumetric segmentation of complex nanoparticle assemblies. |
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Wos |
000991752700001 |
Publication Date |
2023-05-25 |
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Edition |
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ISSN |
1932-7447 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
3.7 |
Times cited |
2 |
Open Access |
OpenAccess |
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Notes |
Fonds Wetenschappelijk Onderzoek, 1181122N ; Horizon 2020 Framework Programme, 861950 ; H2020 European Research Council, 815128 ; |
Approved |
Most recent IF: 3.7; 2023 IF: 4.536 |
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Call Number |
EMAT @ emat @c:irua:196971 |
Serial |
8793 |
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