This work is now available as an ASAP at J. Phys. Chem. C:
N.M. O'Boyle, C.M. Campbell, G.R. Hutchison.
Computational Design and Selection of Optimal Organic Photovoltaic Materials
J. Phys. Chem. C 2011. In press.
Rather than repeat the abstract here, I'll summarise the general idea. Current solar cells are based on semiconductor technology and are expensive to make both in terms of materials and energy. Organic solar cells, while never going to be as efficient at converting light to electricity, offer the possibility of cheap solar energy due to the ease of manufacture and low cost of materials. In 2006, Scharber et al described how to calculate the efficiency of an organic solar cell based on the electronic structure (i.e. HOMO, LUMO) of the solar cell components, so the question was: could we find organic polymers with the required structure to maximise efficiency?
To cut a long story short, we could. What we did was combine Open Babel/Pybel (for structure generation and forcefield optimisation), Gaussian09 (for ZINDO/S//PM6 calculations), cclib (for extracting the results) and a Python script implementing a genetic algorithm, and out popped molecular wires predicted to be highly efficient. The top candidates were then filtered according to additional criteria et voilà. Overall, over 90,000 polymers were tested - still only a small fraction (about 4%) of what we'd have had to test without the genetic algorithm.
If you're interested in a copy of the paper and don't have access to the journal, get in touch - we can distribute a number of copies through the ACS website.