Exciton Hamiltonian of Polymer Chlorosome Nanocomposites

Light harvesting in photosynthesis is a highly efficient process that can be adapted to a wide range of light conditions. Artificial photosynthesis has the potential to eclipse the efficiency of current solar technology by several times. Computational models have been used for years to predict the behavior of natural systems, but the complicated protein environment has made them difficult to analyse. Advances have been made in making synthetic versions of light harvesting organelles, known as polymer chlorosome nanocomposites. These simplified systems allow for easy comparison to computational models. The challenge at hand is to generate and understand them. Known chemical structures were input into Ab Initio computational chemistry software to gather data in the form of excited state energies and transition densities. We will present how we used this data to predict the time evolution of corresponding systems.