Visualization Based Data Mining for Comparison Between Two Solar Cell Libraries.

Material informatics may provide meaningful insights and powerful predictions for the development of new and efficient Metal Oxide (MO) based solar cells. The main objective of this paper is to establish the usefulness of data reduction and visualization methods for analyzing data sets emerging from multiple all-MOs solar cell libraries. For this purpose, two libraries, TiO |Co O and TiO |Co O |MoO , differing only by the presence of a MoO layer in the latter were analyzed with Principal Component Analysis and Self-Organizing Maps. Both analyses suggest that the addition of the MoO layer to the TiO |Co O library has affected the overall photovoltaic (PV) activity profile of the solar cells making the two libraries clearly distinguishable from one another. Furthermore, while MoO had an overall favorable effect on PV parameters, a sub-population of cells was identified which were either indifferent to its presence or even demonstrated a reduction in several parameters.