Systematic Prediction of Dyes for Dye Sensitized Solar Cells: Data-mining via Molecular Charge-Transfer Algorithms

Graph theoretical algorithms and classification tests are combined with data-mining tools to present successful predictions of high-performance dyes for dye-sensitized solar cells (DSCs). The construction of molecular charge-transfer algorithms is described, featuring recursive depth-first, back-tracking, graph traversal algorithms with classification test formalisms. These algorithms are employed to search through a representative set of organic chemical space (120,000 chemical molecules) to identify compounds that have the required structural attributes to act as high-performance dyes for DSCs. The first results of these predictions are validated by comparison of the predicted structural motifs to existing well-known dyes that are currently in use for DSC device application. Three chemical motifs are shown to form the chemical back-bone of three popular dyes, thereby validating the predictions. Further work is described which includes the DSC fabrication and testing of the new classes of unknown dye; this pertains to the ultimate goal of systematic design of new dyes for DSC device application.