Optimization of STEM-HAADF Electron Tomography Reconstructions by Parameter Selection in Compressed Sensing Total Variation Minimization-Based Algorithms. Muñoz-Ocaña, J.; Bouziane, A.; Sakina, F.; Baker, R.; Hungría, A.; Calvino, J.; Rodríguez-Chía, A.; and López-Haro, M. Particle and Particle Systems Characterization, 2020. cited By 0
Optimization of STEM-HAADF Electron Tomography Reconstructions by Parameter Selection in Compressed Sensing Total Variation Minimization-Based Algorithms [link]Paper  doi  abstract   bibtex   
A novel procedure to optimize the 3D morphological characterization of nanomaterials by means of high angle annular dark field scanning-transmission electron tomography is reported and is successfully applied to the analysis of a metal- and halogen-free ordered mesoporous carbon material. The new method is based on a selection of the two parameters (μ and β) which are key in the reconstruction of tomographic series by means of total variation minimization (TVM). The parameter-selected TVM reconstructions obtained using this approach clearly reveal the porous structure of the carbon-based material as consisting of a network of parallel, straight channels of ≈6 nm diameter ordered in a honeycomb-type arrangement. Such an unusual structure cannot be retrieved from a TVM 3D reconstruction using default reconstruction values. Moreover, segmentation and further quantification of the optimized 3D tomographic reconstruction provide values for different textural parameters, such as pore size distribution and specific pore volume that match very closely with those determined by macroscopic physisorption techniques. The approach developed can be extended to other reconstruction models in which the final result is influenced by parameter choice. © 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
@ARTICLE{Munoz-Ocana2020,
author={Muñoz-Ocaña, J.M. and Bouziane, A. and Sakina, F. and Baker, R.T. and Hungría, A.B. and Calvino, J.J. and Rodríguez-Chía, A.M. and López-Haro, M.},
title={Optimization of STEM-HAADF Electron Tomography Reconstructions by Parameter Selection in Compressed Sensing Total Variation Minimization-Based Algorithms},
journal={Particle and Particle Systems Characterization},
year={2020},
volume={37},
number={6},
doi={10.1002/ppsc.202000070},
art_number={2000070},
note={cited By 0},
url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084796113&doi=10.1002%2fppsc.202000070&partnerID=40&md5=675be99a81e65e130d7156f5f5f648e0},
abstract={A novel procedure to optimize the 3D morphological characterization of nanomaterials by means of high angle annular dark field scanning-transmission electron tomography is reported and is successfully applied to the analysis of a metal- and halogen-free ordered mesoporous carbon material. The new method is based on a selection of the two parameters (μ and β) which are key in the reconstruction of tomographic series by means of total variation minimization (TVM). The parameter-selected TVM reconstructions obtained using this approach clearly reveal the porous structure of the carbon-based material as consisting of a network of parallel, straight channels of ≈6 nm diameter ordered in a honeycomb-type arrangement. Such an unusual structure cannot be retrieved from a TVM 3D reconstruction using default reconstruction values. Moreover, segmentation and further quantification of the optimized 3D tomographic reconstruction provide values for different textural parameters, such as pore size distribution and specific pore volume that match very closely with those determined by macroscopic physisorption techniques. The approach developed can be extended to other reconstruction models in which the final result is influenced by parameter choice. © 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim},
keywords={Carbon;  Electric impedance tomography;  Image denoising;  Pore size, 3D tomographic reconstruction;  Carbon based materials;  High-angle annular dark fields;  Morphological characterization;  Ordered mesoporous carbon;  Parameter selection;  Total variation minimization;  Transmission electron, Image reconstruction},
document_type={Article},
source={Scopus},
}
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