Title
Pore REconstruction and Segmentation (PORES) method for improved porosity quantification of nanoporous materials
Author
Faculty/Department
Faculty of Sciences. Chemistry
Faculty of Sciences. Physics
Publication type
article
Publication
Amsterdam ,
Subject
Physics
Chemistry
Source (journal)
Ultramicroscopy. - Amsterdam
Volume/pages
148(2015) , p. 10-19
ISSN
0304-3991
ISI
000345973000002
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Electron tomography is currently a versatile tool to investigate the connection between the structure and properties of nanomaterials. However, a quantitative interpretation of electron tomography results is still far from straightforward. Especially accurate quantification of pore-space is hampered by artifacts introduced in all steps of the processing chain, i.e., acquisition, reconstruction, segmentation and quantification. Furthermore, most common approaches require subjective manual user input. In this paper, the PORES algorithm POre REconstruction and Segmentation is introduced; it is a tailor-made, integral approach, for the reconstruction, segmentation, and quantification of porous nanomaterials. The PORES processing chain starts by calculating a reconstruction with a nanoporous-specific reconstruction algorithm: the Simultaneous Update of Pore Pixels by iterative REconstruction and Simple Segmentation algorithm (SUPPRESS). It classifies the interior region to the pores during reconstruction, while reconstructing the remaining region by reducing the error with respect to the acquired electron microscopy data. The SUPPRESS reconstruction can be directly plugged into the remaining processing chain of the PORES algorithm, resulting in accurate individual pore quantification and full sample pore statistics. The proposed approach was extensively validated on both simulated and experimental data, indicating its ability to generate accurate statistics of nanoporous materials.
E-info
https://repository.uantwerpen.be/docman/iruaauth/1882b7/2218263.pdf
Full text (open access)
https://repository.uantwerpen.be/docman/irua/01b4ec/8370.pdf
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