A chemoinformatic approach to the screening of small organic molecules and ruthenium sensitizers for solar cells applications.
Sara Tortorella a
a Università degli studi di Perugia; Dipartimento di Chimica, Via Elce di sotto, 8, Perugia, 6100, Italy
International Conference on Hybrid and Organic Photovoltaics
Proceedings of 6th International Conference on Hybrid and Organic Photovoltaics (HOPV14)
Ecublens, Switzerland, 2014 May 11th - 14th
Organizers: Michael Graetzel and Mohammad Nazeeruddin
Poster, Sara Tortorella, 233
Publication date: 1st March 2014

The increasing interest in solar energy market has led to the development of photovoltaic technology towards three generations of solar cells, already commercialized but still under investigation to achieve better performance. Third generation solar cells are the most attractive ones, bacause they are both cheaper than and potentially as efficient as the previous generation solar cells. They can be organic solar cells, made of polymers or small organic molecules with specific opto-electronic properties, or dye-sensitized solar cells, using an organometallic dye, TiO2 and an electrolyte solution.

To date, whether we decide to investigate the properties of a small molecules or a dye, we face the traditional trial and error approach: we think about a suitable compound, we synthesise it, we characterize it, we test the solar cells made of it and, finally and hopefully, we elucidate structure-electronic properties relationships that will be used in the next study.

An innovative approach could be to extend the molecular modelling and drug design techniques to the above-mentioned research field, with the aim of replacing the traditional trial and error approach with a rational design-based virtual screening of possible candidates.Considering the statistical and chemometric techniques that play a crucial role in determining structure-property relationships[i], the important point is to find relevant molecular descriptors to describe our target molecules. We have found that combining semiempirically calculated descriptors (Homo, Lumo, bandgap, UV-Vis spectrum) and selected GRID/MIF-3D and 2D descriptors also used in drug design[ii], different models  predicting structure-property (open circuit voltage, current intensity or power conversion efficiency) relationships can be built and used both to plan new experiments and to predict new compounds photovoltaic performance. This approach, starting from the building of a database of already tested candidates used to train the model, was extended to both small molecule semiconductors for organic photovoltaic solar cells and heteroleptic Ruthenium complexes for dye-sensitized solar cells and interesting results were obtained. In particular, we were able to find the descriptors that more contribute to enhance the performance investigated, thus finding directives for the design of potentially high-performing candidates.

In the early stage of this project, we demonstrated that molecular modelling methods can be succesfully extended also to the field of material science as an alternative to the traditional expensive and time-consuming approach.


PLS model for the PCE built with known small molecules for organic photovoltaic and able to extimate the performance of new candidates.
[i] Geladi, P.; Kovalski, B. R. Partial Least-Square Regression: a tutorial. Analytica Chimica Acta 1986, 185, 1-17. [ii] Cruciani, G.; Crivori, P.; Carrupt, P. A.; Testa, B. Molecular Fields in Quantitative Structure-Permeation Relationships: the VolSurf Approach. J. Mol. Struct. 2000, THEOCHEM 503, 17-30.
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