Pore REconstruction and Segmentation (PORES) method for improved porosity quantification of nanoporous materials
Autor: | Kees Joost Batenburg, Sara Bals, C.J. Van Oers, G. Van Eyndhoven, Mert Kurttepeli, Pegie Cool, Jan Sijbers |
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Přispěvatelé: | Scientific Computing |
Rok vydání: | 2015 |
Předmět: |
Computer science
Nanotechnology Nanoporous material 02 engineering and technology Iterative reconstruction 01 natural sciences 010309 optics Segmentation 0103 physical sciences Porosity Instrumentation Pixel Nanoporous business.industry Physics Reconstruction algorithm Pattern recognition Pore size distribution 021001 nanoscience & nanotechnology Full sample Atomic and Molecular Physics and Optics Electronic Optical and Magnetic Materials Chemistry Electron tomography Artificial intelligence Reconstruction 0210 nano-technology business |
Zdroj: | Ultramicroscopy Ultramicroscopy, 148, 10-19 |
ISSN: | 0304-3991 |
Popis: | 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. |
Databáze: | OpenAIRE |
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