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Knowledge Discovery in Conducting Polymeric Composite Devices: AN Essential Research Towards New Computer/Sensing Information Devices

Published online by Cambridge University Press:  10 February 2011

A. Talaie
Affiliation:
Lab of Polymer Surface Chemistry, Department of Organic Materials Osaka National Research Institute, 1-8-31 Midorigaoka, Ikeda, Osaka 563, Japan ICI Laboratory of Process System Engineering, Chemical Engineering Department The University of Sydney, NSW 2006, Australia
H. Eisazadeh
Affiliation:
Technical College, Babol, PO.BOX 484, IRAN
K. Adachi
Affiliation:
Lab of Polymer Surface Chemistry, Department of Organic Materials Osaka National Research Institute, 1-8-31 Midorigaoka, Ikeda, Osaka 563, Japan
T. Taguchi
Affiliation:
Lab of Polymer Surface Chemistry, Department of Organic Materials Osaka National Research Institute, 1-8-31 Midorigaoka, Ikeda, Osaka 563, Japan
J.A. Romagnoli
Affiliation:
ICI Laboratory of Process System Engineering, Chemical Engineering Department The University of Sydney, NSW 2006, Australia
S. Buniran
Affiliation:
Advanced Polymer group, SIRIM BERHAD, PO BOX 7035, KL, Malaysia
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Abstract

A composite of two conducting polymers, polyaniline and polypyrrole, could result in much improved physical properties with respect to their applications in pH electrodes and conducting paints/coatings. However, the composite has time dependant properties that made the use of dynamic computational algorithms necessary to control its behaviour. We used a sandwich-modified electrode as a pH-sensing electrode, which was integrated with a pre-trained computer for data processing and knowledge discovery. Conducting polypyrrole/polyaniline colloidal composites have been also prepared by deposition of the mixture solution of polypyrrole and polyaniline at negative potentials. Different substrates were dipped in the solution containing the mixture together with an acrylic latex and after drying the adhesive strength and electroactivity of the paint were studied. Several colloidal composite based coatings were investigated. At last a computer facilitated with powerful artificial ncural network based algorithms classified the paints.

Type
Research Article
Copyright
Copyright © Materials Research Society 1999

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References

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