Dye sensitized solar cells (DSSC) are an attractive alternative to silicon-based solar cells due to the prospect of high energy conversion efficiency and low production cost.  However, their efficiencies remain low with the best all dyes exhibiting efficiencies of around 11%.  One of the parameters controlling the efficiency of the solar cell is the open circuit voltage (Voc).  Voc, a function of the band gap, should depend on the chemical structure of the dye molecule used.  Here, a quantitative structure-property relationship (QSPR) analysis of Voc and 209 thiophene derivatives [training: 149 molecules and validation: 60 molecules] was carried out using the Neural Network algorithm in Mathematica 8 with the feed forward routine.   Initial results indicate the model underestimates the extreme Voc values.  However, the created database is the most complete set of solar cell dye molecules compiled and will be of great benefit for future studies.

Analyzing a dye sensitized solar cell database to identify quantitative structure property relationships to improve overall dye performance

243rd National Meeting (2012)

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