We describe a high throughput methodology for evaluation of moisture barrier performance of thin films based on the change in optical density of AI/glass substrates during exposure to high temperature/humidity conditions. This approach has enabled a comparative analysis of hundreds of single and multilayer barrier films and has provided predictive models to identify key input variables that affect moisture barrier performance as well as candidates for protection of thin film solar cells. The data is also utilized to identify different degradation modes that can be correlated with film attributes. The methodology has proved to be valuable in other aspects of thin film lifetime studies, such as the evaluation of transparent conductive oxide material properties as window layers in solar cell applications.
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