ABSTRACT
52Electrically conducting polymers have attracted a great deal of attention ever since their discovery. There have been enormous experimental and theoretical efforts in the area because of the versatile properties of these materials which combine the high conductivity of pure metals while being corrosion resistant, light in weight, and easy to process. These features make them one of the most widely applicable classes of materials. Their applications include super capacitors, electronic devices, organic light-emitting diodes, optical devices, smart windows, sensors, batteries, solar cells, artificial muscles, memory devices, nanoswitches, and many more. The chemical structures of these organic conjugated polymers can be manipulated in several ways to obtain properties as desired. In order to “tailor-make” these polymers and obtain desired properties out of them, it is very important to first understand the relationship 54between the chemical structure of the polymer and its properties. Efforts are thus being made to make these materials intrinsically conducting and more processable.
When it comes to designing a polymer, there can be enormous ways in which the homopolymer units may be arranged to form a polymeric chain. As a result, the task of synthesizing a polymeric chain with desired properties becomes very cumbersome. To simplify this problem, we have endeavored to the use of a computational method of optimization for designing of low bandgap polymers, known as the genetic algorithm (GA). GA has proved to be a very versatile technique for theoretical designing of low bandgap polymers which possess high level of delocalization.
