HOPV12 - Blogs

4 th Hybrid and Organic Photovoltaic Conference -Uppsala 2012 175
C57 - Materials Discovery of Dyes for Dye-Sensitized Solar Cells: Prediction,
Validation and Rationalisation
Jacqueline Cole a,b
a, Cavendish Laboratory, University of Cambridge, Cavendish Laboratory, J J Thomson Av, Cambridge, CB3 0HE, GB
b, Department of Chemistry, University of New Brunswick, P. O. Box 4400, Fredericton, E3B 5A3, Canada
This paper illustrates a range of methods that are being employed in order to systematically
discover new classes of dyes for dye-sensitized solar-cell (DSC) applications. The importance of
engaging in the full 'life-cycle' of materials prediction, experimental validation and DSC
performance rationalisation, in order to afford success in this materials discovery program, is
illustrated by several case studies.
Large-scale data-mining methods which are able to predict new chemical dyes are
presented together with results from subsequent DSC performance testing. Such experimental
validation is complemented with quantitative structure-property relationship (QSPR) methods
that have a dual function:- to help to rationalise the experimental results and to provide new
design rules that are then fed back into the materials prediction aspect of this work. The 'lifecycle'
of the materials discovery process then repeats via this feedback-loop creating a
continuous 'design-to-device' operational program.
An overview of the prediction methods includes a demonstration of how large-scale
quantum-chemical calculations can reveal new classes of dyes [1,2]. The benefit of mining the
data from these results in concert with a database of optical spectra is discussed. The
importance of complementary calculations that match the band-gap of electrolyte to dye are
described as well as considerations of other selection criteria. A few case studies that show the
DSC performance tests of new dyes generated from these predictions are presented.
QSPR methods are then presented which employ a priori knowledge from successful classes of
dyes in order to generate new design rules that, in turn, afford more superior classes of dyes.
Several applications of QSPR are illustrated whereby new design rules for DSC dyes are realised
from associated empirical models [3] and statistical correlation [4].
The paper concludes with an outlook on future developments in materials discovery in the
context of this field of research.
References
[1] Cole, J. M "Systematic prediction of dyes for dye-sensitized solar cells: data-mining via molecular charge-transfer
algorithms". Complex Systems, 20, 141-149 (2012).
[2] Cole, J. M. "Large-scale chemical data-mining predicts high-performance dyes for dye-sensitized solar cells", J.
Am. Chem. Soc. (in preparation).
[3] Liu, X.; Cole, J. M.; Waddell, P. G.; Lin, T. C.; Radia, J. Zeidler, A. "Molecular origins of optoelectronic properties in
coumarin dyes: toward designer solar cell and laser applications", J. Phys. Chem. A 116, 727-737 (2012).
[4] Low, K. S.; Cole, J. M.; Zhou, X.; Yufa, N. "Rationalising the molecular origins of Ru and Fe-based dyes for dyesensitized
solar cells", Acta Crystallographica B (submitted).
© SEFIN 2012