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Conjugated organic molecules represent an important area of materialschemistry for both fundamental scientific exploration and technologicalapplications. Using a genetic algorithm to computationally screen up to ~25-50million molecules for organic photovoltaic properties, we find that our methodsfind top monomers 6,000-8,000 times faster than brute force search. By testingmultiple runs and establishing convergence criteria, we show the computationalscaling with search space size, common molecular motifs, and discuss thereliability to choose the same molecules independent of initial data set size.We outline remaining areas of difficulty in growing to larger search spaces,potential solutions, and filtering criteria for potential organic photovoltaicmaterials. Efficient genetic algorithm searches promise to address a wide rangeof property-driven inverse design problems in chemistry.

Rapid Computational Optimization of Molecular Properties using Genetic  Algorithms: Searching Across Millions of Compounds for Organic Photovoltaic  Materials