Abstract
Background: Over the last four decades, tremendous growth has been witnessed in the field of electrically conducting polymers. A great deal of theoretical and empirical efforts have been made to achieve multifunctional conducting polymeric structures. However, the major challenge in this field is achieving the minimum band gap value which governs various electronic and optoelectronic properties of the structure.
Objective: Artificial optimization viz., metaheuristic algorithms have been clubbed with the polymer problem to investigate the electronic properties of copolymers.
Method: Band structures of different homopolymers obtained from ab-initio Hartree-Fock crystal orbital method have been used as input to obtain the electronic properties of copolymers using genetic algorithm, ant colony optimization and particle swarm optimization.
Result: Nature-based computing methods employed for tailoring intrinsically conducting copolymers correspond to optimal electronic properties.
Conclusion: This computational cloning approach provides a cost-effective and potent passage for taking forward optimized theoretical solutions to synthetic environment.
Keywords: Ant algorithm, artificial intelligence, conducting polymers, copolymerization, electronic properties, genetic algorithm, in-silico optimization, particle swarm optimization.
Graphical Abstract
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