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High‐temperature annealing, known asTabula Rasa(TR), proves to be an effective method for dissolving oxygen precipitate nuclei inn‐Cz silicon and makes this material resistant to temperature‐induced and process‐induced lifetime degradation.Tabula Rasais especially effective inn‐Cz wafers with oxygen concentration >15 ppma. Vacancies, self‐interstitials, and their aggregates result from TR as a metastable side effect. Temperature‐dependent lifetime spectroscopy reveals that these metastable defects have shallow energy levels ~0.12 eV. Their concentrations strongly depend on the ambient gases during TR because of an offset of the thermal equilibrium between vacancies and self‐interstitials. However, these metastable defects anneal out at typical cell processing temperatures ≥850°C and have little effect on the bulk lifetime of the processed cell structures. Without dissolving built‐in oxygen precipitate nuclei, high‐temperature solar cell processing severely degrades the minority carrier lifetimes to below 0.1 millisecond, while TR‐treatedn‐Cz wafers after the cell processing steps exhibit carrier lifetimes above 2.2 milliseconds.

Spectral differences affect solar cell performance, an effect that is especially visible when comparing different solar cell technologies. To reproduce the impact of varying spectra on solar cell performance in the lab, a unique classification of spectra is needed, which is currently missing in literature. The most commonly used classification, average photon energy (APE), is not unique, and a single APE value may represent various spectra depending on location. In this work, we propose a classification method based on an iterative use of the k‐means clustering algorithm. We call this method RISE (Representative Identification of Spectra and the Environment). We define a set of 18 spectra using RISE and reproduce the spectral impact on energy yield for various solar cell technologies and locations. We explore effects on yield for commercially available solar cell technologies (Si and CdTe) in four locations: Singapore (fully humid equatorial climate), Colorado (cold arid), Brazil (warm, humid, and subtropical), and Denmark (fully humid warm temperature). We then reduce our findings to practice by implementing the spectrum set into an LED current–voltage (IV) tester. We verify our performance predictions using our set of representative spectra to reproduce energy yield differences between Si solar cells and CdTe solar cells with an average error of less than1.5 ± 0.5% as compared to over 5% when using standard testing conditions.