Assaf Anderson

The high open-circuit potential (Voc) achieved by perovskite solar cells (PSCs) is one of the keys to their success. The Voc analysis is essential to understand their working mechanisms. A large number of CH3NH3PbI3−xClx PSCs were fabricated on single large-area substrates and their Voc dependencies on illumination intensity, I0, were measured showing three distinctive regions. Similar results obtained in Al2O3 based PSCs relate the effect to the compact TiO2 rather than the mesoporous oxide. We propose that two working mechanisms control the Voc in PSCs. The rise of Voc at low I0 is determined by the employed semiconductor n-type contact (TiO2 or MgO coated TiO2). In contrast, at I0 close to AM1.5G, the employed oxide does not affect the achieved voltage. Thus, a change of regime from an oxide-dominated EFn (as in the dye sensitized solar cells) to an EFn, directly determined by the CH3NH3PbI3−xClx absorber is suggested.

ABSTRACT Growth in energy demands, coupled with the need for clean energy, are likely to make solar cells an important part of future energy resources. In particular, cells entirely made of metal oxides (MOs) have the potential to provide clean and affordable energy if their power conversion efficiencies are improved. Such improvements require the development of new MOs which could benefit from combining combinatorial material sciences for producing solar cells libraries with data mining tools to direct synthesis efforts. In this work we developed a data mining workflow and applied it to the analysis of two recently reported solar cell libraries based on Titanium and Copper oxides. Our results demonstrate that QSAR models with good prediction statistics for multiple solar cells properties could be developed and that these models highlight important factors affecting these properties in accord with experimental findings. The resulting models are therefore suitable for designing better solar cells.