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Type: Artigo de periódico
Title: Using artificial intelligence methods to design new conducting polymers
Author: Giro, Ronaldo
Cyrillo, Márcio
Galvão, Douglas Soares
Abstract: In the last years the possibility of creating new conducting polymers exploring the concept of copolymerization (different structural monomeric units) has attracted much attention from experimental and theoretical points of view. Due to the rich carbon reactivity an almost infinite number of new structures is possible and the procedure of trial and error has been the rule. In this work we have used a methodology able of generating new structures with pre-specified properties. It combines the use of negative factor counting (NFC) technique with artificial intelligence methods (genetic algorithms - GAs). We present the results for a case study for poly(phenylenesulfide phenyleneamine) (PPSA), a copolymer formed by combination of homopolymers: polyaniline (PANI) and polyphenylenesulfide (PPS). The methodology was successfully applied to the problem of obtaining binary up to quinternary disordered polymeric alloys with a pre-specific gap value or exhibiting metallic properties. It is completely general and can be in principle adapted to the design of new classes of materials with pre-specified properties.
Subject: genetic algorithms
conducting polymers
poly(phenylene sulfide-phenyleneamine
Editor: ABM, ABC, ABPol
Rights: aberto
Identifier DOI: 10.1590/S1516-14392003000400017
Date Issue: 1-Dec-2003
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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