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Computer vision methods for the study of spinodal decomposition in polymer blends
Author(s) -
Gur Y. S.,
Malone M. F.,
Bhatia Q. S.,
Reynolds G.,
Karasz F. E.,
Hanson A. R.,
Riseman E. M.
Publication year - 1989
Publication title -
polymer engineering and science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.503
H-Index - 111
eISSN - 1548-2634
pISSN - 0032-3888
DOI - 10.1002/pen.760292004
Subject(s) - spinodal decomposition , materials science , spinodal , polymer blend , polystyrene , polymer , microstructure , phase (matter) , binary number , thermodynamics , composite material , mathematics , physics , copolymer , organic chemistry , chemistry , arithmetic
We demonstrate the use of computer vision techniques and optical microscopy to follow the kinetics and microstructure during spinodal decomposition of a polymer blend. Among other features, the mean of the population of the local maxima of the gradients in each image is computed; this global feature is shown to co‐develop with the phase separation of the blend. An algorithm is presented which employs the gradient magnitude technique to analyze optical images of spinodally decomposing polymer blends. This algorithm has been used to extract the Cahn‐Hilliard spinodal growth rates for a binary blend of polystyrene with poly(vinyl methyl ether). We show that the spinodal temperature can be found from the temperature dependence of this growth rate. We also show how additional shape features such as compactness might be used to study, the same binary blend.