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Data Science Helps to Understand Degradation Mechanisms in Solar Panels

Teams of researchers from Case Western Reserve University in Cleveland, Ohio (US), and Gebze Technical University in Turkey have used data science to determine and predict the effects of exposure to weather and other conditions on different samples of polyethylene-terephthalate (PET). A deeper understanding of the degradation mechanisms in such solar materials could help researchers to design better photovoltaic devices with extended lifetimes. 

Different responses of the material were measured on all samples as materials were exposed to accelerated weathering. “This means that we had a larger data set to develop predictive models,” says study leader Laura Bruckman, assistant professor in the Department of Materials Science and Engineering at Case Western Reserve University. “Having multiple samples of the same material shows the variation of the same material as it gets more and more exposure.”

Newfound knowledge

“We showed that having multiple samples of the same material undergoing the same exposure had a large variation in the haze response,” says Bruckman, speaking on what novel knowledge they gleaned from the study. “The change in the yellowness of the material was very consistent among the samples through time.” She explains that multiple combined stress conditions induce multiple degradation mechanisms that are difficult to differentiate and model accurately with traditional statistical methods. “And applied statistical approaches in this study, combining materials science and data analytics, helped model these multiple degradation mechanisms.”

Impact on future generations of photovoltaics

Bruckman confirms that the conclusions from this study could in future help to design better solar cells and panels, with extended lifetimes. “These findings allow scientists to predict the response of a PET in the solar panel's backsheet, which is critical to both lifetime prediction and safety from electrical hazards.”

Bruckman notes that she was surprised they were able to demonstrate a statistically informed data science approach that is not commonly used. “Most studies of this sort are observational and not focused on predicting behavior,” she says.


For Bruckman and her colleagues, the next step beyond prediction will be to infer the mechanisms that are responsible for this degradation. “This will help us guide the development of longer-lived solar panels,” she projects.

Results of the study are summarized in the article “Predictive models of poly(ethylene-terephthalate) film degradation under multi-factor accelerated weathering exposures,” published in the journal PLOS ONE.

Written by Sandra Henderson, Research Editor, Solar Novus Today

Labels: Case Western Reserve University,Gebze Technical University,polyethylene-terephthalate,solar panel degradation,Professor Laura Bruckman

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