English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/75851
Share/Impact:
Statistics
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

Title

Digital image processing of nanometer-size metal particles on amorphous substrates

AuthorsSoria, Federico ; Artal, Pablo; Bescós, J.; Heinemann, K.
Issue Date1988
PublisherElsevier
CitationUltramicroscopy 24: 19-25 (1988)
AbstractThe task of differentiating very small metal aggregates supported on amorphous films from the phase contrast image features inherently stemming from the support is extremely difficult in the nanometer particle size range. Digital image processing was employed to overcome some of the ambiguities in evaluating such micrographs. The processing steps included: (a) shading correction and contrast enhancement by adaptive filtering, (b) noise reduction by median filtering, and (c) noise cleaning by adaptive filtering and thresholding. It was demonstrated that such processing allowed positive particle detection and a limited degree of statistical size analysis even for micrographs where by bare eye examination the distribution between particles and erroneous substrate features would seem highly ambiguous. The smallest size class detected for Pd/C samples peaks at 0.8 nm. We found this size class in various samples prepared under different evaporation conditions and conclude that these particles consist of >a magic number> of 13 atoms and have cubo-octahedral or icosahedral crystal structure. © 1988.
URIhttp://hdl.handle.net/10261/75851
DOI10.1016/0304-3991(88)90323-3
Identifiersdoi: 10.1016/0304-3991(88)90323-3
issn: 0304-3991
Appears in Collections:(CFMAC-IO) Artículos
(ICMM) Artículos
Files in This Item:
File Description SizeFormat 
accesoRestringido.pdf15,38 kBAdobe PDFThumbnail
View/Open
Show full item record
Review this work
 

Related articles:


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.