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“Real-time tilt undersampling optimization during electron tomography of beam sensitive samples using golden ratio scanning and RECAST3D”. Craig TM, Kadu AA, Batenburg KJ, Bals S, Nanoscale 15, 5391 (2023). http://doi.org/10.1039/D2NR07198C
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.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
Impact Factor: 6.7
Times cited: 1
DOI: 10.1039/D2NR07198C
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“Quantitative 3D Investigation of Nanoparticle Assemblies by Volumetric Segmentation of Electron Tomography Data Sets”. Kavak S, Kadu AA, Claes N, Sánchez-Iglesias A, Liz-Marzán LM, Batenburg KJ, Bals S, The journal of physical chemistry: C : nanomaterials and interfaces 127, 9725 (2023). http://doi.org/10.1021/acs.jpcc.3c02017
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.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
Impact Factor: 3.7
Times cited: 2
DOI: 10.1021/acs.jpcc.3c02017
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“The ASTRA Toolbox: A platform for advanced algorithm development in electron tomography”. van Aarle W, Palenstijn WJ, De Beenhouwer J, Altantzis T, Bals S, Batenburg KJ, Sijbers J, Ultramicroscopy 157, 35 (2015). http://doi.org/10.1016/j.ultramic.2015.05.002
Abstract: We present the ASTRA Toolbox as an open platform for 3D image reconstruction in tomography. Most of the software tools that are currently used in electron tomography offer limited flexibility with respect to the geometrical parameters of the acquisition model and the algorithms used for reconstruction. The ASTRA Toolbox provides an extensive set of fast and flexible building blocks that can be used to develop advanced reconstruction algorithms, effectively removing these limitations. We demonstrate this flexibility, the resulting reconstruction quality, and the computational efficiency of this toolbox by a series of experiments, based on experimental dual-axis tilt series.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 562
DOI: 10.1016/j.ultramic.2015.05.002
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