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Logic gate and circuit training on randomly dispersed carbon nanotubes

Kotsialos, A.; Massey, M.K.; Qaiser, F.; Zeze, D.A.; Pearson, C.; Petty, M.C.

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A. Kotsialos

M.K. Massey

F. Qaiser

C. Pearson

M.C. Petty


This paper presents results of computations based on threshold logic performed by a thin solid film, following the general principle of evolution in materio. The electrical conductivity is used as the physical property manipulated for evolving Boolean functions. The material used consists of a composite of single-wall carbon nanotubes (SWCNTs) and the polymer poly(methyl methacrylate). The SWCNTs are randomly dispersed in the polymer forming a complex conductive network at the nano-scale. The training is formulated as an optimisation problem with continuous and binary constraints and is subsequently solved by two derivative-free algorithms, the Nelder-Mead (NM) and the Differential Evolution (DE) algorithms. This approach has been used to evolve gates and circuits. The NM fails to converge for all computational tasks, whereas the DE is always successful. The computation tasks considered are simple threshold logic gates and more complicated circuits. The thin film composite is very stable and its behavior remains the same after the optimal solution has been achieved.

Journal Article Type Article
Acceptance Date Jun 2, 2014
Publication Date Sep 1, 2014
Deposit Date Oct 16, 2014
Publicly Available Date Dec 5, 2014
Journal International Journal of Unconventional Computing
Print ISSN 1548-7199
Electronic ISSN 1548-7202
Publisher Old City Publishing
Peer Reviewed Peer Reviewed
Volume 10
Issue 5-6
Pages 473-497
Keywords Evolution in materio, Randomly dispersed carbon nanotubes, Threshold logic circuits, Optimisation.
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