Solar cell performance prediction using advanced analysis methods on optical images of as-cut wafers

A quantitative evaluation of the material quality of as-cut wafers with respect to the corresponding solar cell performance is the basis for a reliable quality control. A number of techniques have been recently developed with most of them using photoluminescence (PL) images as a starting point for the application of various image processing methods. In this work, a new empirical approach is demonstrated that relies on the analysis of optical images. We investigate both optical and PL-images of as-cut wafers using advanced image processing algorithms and compare their predictive power when applied to as-cut wafers. While the optical images of as-cut wafers are much easier acquired, our results show that they nevertheless can be used for a quantitative rating that correlates with the electrical properties of the processed cells.