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Designing Conducting Polymers with Genetic Algorithms

  • R. Giro (a1), M. Cyrillo (a1) and D.S. Galvão (a1)
Abstract
Abstract

We have developed a new methodology to design conducting polymers with pre-specified properties using genetic algorithms (GAs). The methodology combines GAs with the Negative Factor Counting (NFC) technique. NFC is a powerful technique to obtain the eigenvalues of large matrices without direct diagonalization.We present the results for a case study of polyanilines, one of the most important families of conducting polymers. The methodology proved to be able of generating automatic solutions for the problem of determining the optimum relative concentration for binary and ternary disordered polyaniline alloys exhibiting metallic properties. The methodology is completely general and can be used to design new classes of materials.

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[5] J. Ladik , M. Seel , P. Otto and A.K. Bakhshi , Chem. Phys. 108, 203 (1986).

[7] D. S. Galvão , D. A. dos Santos , B. Laks , C. P. de Melo , and M. J. Caldas , Phys. Rev. Lett. 63, 786 (1989).

[8] F.C. Lavarda , M.C. dos Santos , D.S. Galvão , and B. Laks , Phys. Rev. Lett. 73, 1267 (1994).

[10] S. Forrest , Science 261, 872 (1993).

[11] A. G. MacDiarmid . J. C. Chiang , A. F. Richter , and A. J. Epstein , Synth. Met. 18, 285 (1987).

[16] P. Dean , Rev. Mod. Phys., 44, 122 (1972).

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MRS Online Proceedings Library (OPL)
  • ISSN: -
  • EISSN: 1946-4274
  • URL: /core/journals/mrs-online-proceedings-library-archive
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