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|Title:||In-silico engineering of intrinsically conducting copolymers using particle swarm optimization algorithm|
Bakhshi, A K
|Keywords:||Theoretical chemistry;Electrically conducting polymers;Conducting polymers;Copolymers;Electronic properties;Binary particle swarm optimization;Particle swarm optimization|
|Abstract:||A socio-cognitive computational algorithm, viz., particle swarm optimization (PSO) has been adopted along with negative factor counting technique and inverse iteration method (IIM) for investigating the electronic properties of a model binary copolymer, of Type I class of quasi one-dimensional polymeric superlattices. The optimal relative concentrations of the constituent components in the copolymer returned by PSO algorithm correspond to a minimum band gap composition and to one of the highly delocalized configurations. The optimal composition of the conducting copolymer obtained using PSO algorithm is found to be in good agreement with the result obtained from systematic search. An appropriate and reasonable selection of swarm size, topology and convergence parameters are found to make the algorithm diverse and efficient in terms of its exploration and exploitation abilities. Further the PSO algorithm has been found to be more effective and computationally cost efficient in comparison to genetic algorithm for designing novel conducting copolymers.|
|Appears in Collections:||IJC-A Vol.52A(03) [March 2013]|
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