Statistical methods for linking material composition to recombination losses in optoelectronic devices.

In light of the accumulation of characterization measurement data in the industrial production of solar cell devices, the investigation of a large amount of samples by statistical means lends itself to be a useful tool to gain further insights into how the data correlate with performance parameters. However, due to the multicollinearity among high-dimensional input parameters of compositional data, revealing the underlying patterns may prove to be a difficult endeavor. In this work, we present statistics consisting of 280 thin-film solar cell samples based on Cu(In, Ga)(S, Se)2 absorber layers whose depth-resolved composition was assessed by glow-discharge optical emission spectroscopy (GDOES).