Only recently, methods for quality control of multicrystalline silicon wafers have been published, which allow the efficiency of solar cells to be predicted precisely from photoluminescence (PL) images taken in the as-cut state. In this letter it is shown that oxygen precipitates, present in standard Czochralski silicon wafers, can cause efficiency losses of more than 4% (absolute) within an industrial solar cell proc- ess. These efficiency losses correlate with ring-like defect structures of reduced intensity in the PL image. In comparison with QSSPC-based lifetime measurements, we introduce a PL-based method of quality control which allows the critical wafers to be identified and sorted out reliably at an early state of production and thus increases yield and average efficiency of production lines

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Luminescence imaging is a very rapid technique for the characterisation of silicon samples. Megapixel luminescence images on silicon bricks, unprocessed wafers, partially processed wafers and fully processed cells can be captured with acquisition times of typically a few seconds or less than one second. A number of specific luminescence imaging applications have been developed over the last three years, allowing quantitative spatial information to be gained about a variety of crucial material and device parameters. This paper reviews some of the intriguing possibilities for inline monitoring in PV production at an early stage of production that result from the above mentioned short measurement times. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Luminescence images of silicon solar cells contain information about local recombination properties and local series resistance. It is difficult to separate the information and interpret single images correctly and quantitatively though, which greatly limits the use of single luminescence images, in particular for the application as an in-production characterization tool. We therefore developed a fast method based on photoluminescence imaging for a spatially resolved coupled determination of the dark saturation current and series resistance (C-DCR)

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We introduce a fast and easy to apply method for determining the local series resistance of standard silicon solar cells. For this method only two electroluminescence images taken at different voltages are needed. From these two images, the local voltage and the local current density through the device can be calculated. Knowing these parameters for each pixel yields the local series resistance. By calculating the cell's dark saturation current from the lower voltage image, the method also works with multicrystal line material. We show images, acquired in only 300 ms and compare them with other luminescence based series resistance images

In this paper we give a mathematical derivation of how luminescence images of silicon solar cells can be calibrated to local junction voltage. We compare two different models to extract spatially resolved physical cell parameters from voltage images. The first model is the terminal connected diode model, where each pixel is regarded as a diode with a certain dark saturation current, which is connected via a series resistance with the terminal. This model is frequently used to evaluate measurement data of several measurement techniques with respect to local series resistance. The second model is the interconnected diode model, where the diode on one pixel is connected with the neighbor diodes via a sheet resistance. For each model parameter at least one image is required for a coupled determination of the parameters. We elaborate how also the voltage calibration can be added as an unknown parameter into the models, and how the resulting system of equations can be solved analytically. Finally the application of the models and the different ways of voltage calibration are compared experimentally

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