Computational atomistic blueprinting of novel conducting copolymers using particle swarm optimization

Area of Science:

• Materials Science
• Computational Chemistry
• Polymer Chemistry

Background:

• Heterocyclic polymers like those based on thiophene, pyrrole, and furan are promising for electronic applications.
• Understanding their electronic structures and conduction properties is crucial for material design.

Purpose of the Study:

• To design novel binary and ternary copolymers using thiophene, pyrrole, and furan skeletons.
• To comparatively study the electronic structures and conduction properties of these copolymers and their benzene-substituted analogues.

Main Methods:

• Employed a metaheuristic approach: particle swarm optimization coupled with negative factor counting and inverse iteration.
• Utilized ab-initio Hartree-Fock crystal orbital calculations to derive band structure results.

Main Results:

• Benzene substitution on the polymer backbone decreased the band gap due to increased quinoid contributions, enhancing intrinsic conductivity.
• Highest Occupied Molecular Orbital (HOMO) energies were found to have a more decisive influence than Lowest Unoccupied Molecular Orbital (LUMO) energies on copolymer composition.
• Density of states analysis verified trends in electronic properties.

Conclusions:

• The study provides a potent route for molecular engineering of sustainable and efficient electronic materials.
• Results can streamline synthetic efforts for developing advanced functional polymers.