Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/35339
Title: | Predictive coalescence modeling of particles from different polymers: application to PVDF and PMMA pair | Authors: | Aid, Sara Eddhahak, Anissa Ortega, Zaida Froelich, Daniel Tcharkhtchi, Abbas |
UNESCO Clasification: | 3313 Tecnología e ingeniería mecánicas | Issue Date: | 2017 | Journal: | Journal of Materials Science | Abstract: | This paper aims to study the coalescence phenomenon of two different polymers PVDF and PMMA. The paper is divided in two parts: the first part is devoted to the experimental work, and the second one focuses on the modeling of the coalescence phenomenon. The first step was a physicochemical and rheological characterization. Then, the coalescence tests have been performed on droplets derived from PVDF and PMMA polymers using a polarized light optical microscope combined with a hot stage. The effect of several significant parameters like temperature and particle size was investigated. The second part of this study is focused on the modeling of the coalescence phenomenon based on the well-known Bellehumeur model. The latter has been commonly used to describe the coalescence phenomenon between identical grains. The novelty of the present work consists in the extension of the coalescence model to wider describe the coalescence phenomenon between grains of different polymers. In addition, probabilistic analysis was performed in order to investigate the effect of the parameters governing the coalescence model, namely the viscosity, the surface tension and the relaxation time. The results have shown a good compromise between the experimental results and the predictive generalized Bellehumeur model. | URI: | http://hdl.handle.net/10553/35339 | ISSN: | 0022-2461 | DOI: | 10.1007/s10853-017-1302-4 | Source: | Journal of Materials Science[ISSN 0022-2461],v. 52, p. 11725-11736 |
Appears in Collections: | Artículos |
SCOPUSTM
Citations
11
checked on Dec 15, 2024
WEB OF SCIENCETM
Citations
10
checked on Dec 15, 2024
Page view(s)
82
checked on Oct 19, 2024
Google ScholarTM
Check
Altmetric
Share
Export metadata
Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.