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dc.contributor.author
Lotito, Valeria
dc.contributor.author
Zambelli, Tomaso
dc.date.accessioned
2020-09-29T07:36:44Z
dc.date.available
2020-09-27T02:46:41Z
dc.date.available
2020-09-29T07:36:44Z
dc.date.issued
2020-10
dc.identifier.issn
0001-8686
dc.identifier.issn
1873-3727
dc.identifier.other
10.1016/j.cis.2020.102252
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/442891
dc.description.abstract
Characterization of the morphology, identification of patterns and quantification of order encountered in colloidal assemblies is essential for several reasons. First of all, it is useful to compare different self-assembly methods and assess the influence of different process parameters on the final colloidal pattern. In addition, casting light on the structures formed by colloidal particles can help to get better insight into colloidal interactions and understand phase transitions. Finally, the growing interest in colloidal assemblies in materials science for practical applications going from optoelectronics to biosensing imposes a thorough characterization of the morphology of colloidal assemblies because of the intimate relationship between morphology and physical properties (e.g. optical and mechanical) of a material. Several image analysis techniques developed to investigate images (acquired via scanning electron microscopy, digital video microscopy and other imaging methods) provide variegated and complementary information on the colloidal structures under scrutiny. However, understanding how to use such image analysis tools to get information on the characteristics of the colloidal assemblies may represent a non-trivial task, because it requires the combination of approaches drawn from diverse disciplines such as image processing, computational geometry and computational topology and their application to a primarily physico-chemical process. Moreover, the lack of a systematic description of such analysis tools makes it difficult to select the ones more suitable for the features of the colloidal assembly under examination. In this review we provide a methodical and extensive description of real-space image analysis tools by explaining their principles and their application to the investigation of two-dimensional colloidal assemblies with different morphological characteristics.
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.subject
Colloidal self-assembly
en_US
dc.subject
Colloidal pattern analysis
en_US
dc.subject
Colloidal image analysis
en_US
dc.subject
Colloidal pattern identification
en_US
dc.subject
Colloidal morphology analysis
en_US
dc.subject
Colloidal order analysis
en_US
dc.title
Pattern detection in colloidal assembly: A mosaic of analysis techniques
en_US
dc.type
Review Article
dc.date.published
2020-09-05
ethz.journal.title
Advances in Colloid and Interface Science
ethz.journal.volume
284
en_US
ethz.journal.abbreviated
Adv. colloid interface sci. (Print)
ethz.pages.start
102252
en_US
ethz.size
58 p.
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Amsterdam
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2020-09-27T02:46:47Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2020-09-29T07:36:57Z
ethz.rosetta.lastUpdated
2020-09-29T07:36:57Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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