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Progress in Photovoltaics Research and Applications
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Progress in Photovoltaics Research and Applications
Article . 2018 . Peer-reviewed
License: Wiley Online Library User Agreement
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Evaluating and predicting molecular mechanisms of adhesive degradation during field and accelerated aging of photovoltaic modules

Authors: Nick Bosco; orcid bw Jared Tracy;
Jared Tracy
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Jared Tracy; orcid Dagmar R. D'hooge;
Dagmar R. D'hooge
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Dagmar R. D'hooge in OpenAIRE
Dagmar R. D'hooge; Reinhold H. Dauskardt; Chris Delgado;

Evaluating and predicting molecular mechanisms of adhesive degradation during field and accelerated aging of photovoltaic modules

Abstract

AbstractExtending photovoltaic (PV) module lifetimes beyond 30 years is a goal of significant priority. A challenge that must first be addressed, however, is the development of a predictive reliability model that captures the synergy of terrestrial stressors on module degradation, particularly at encapsulant interfaces. Using a metrology designed specifically for PV modules, a comprehensive study of the widely used ethylene vinyl acetate encapsulant was performed in which encapsulant adhesion was evaluated as a function of environmental stressors (UV exposure, temperature, and humidity) for modules aged both under accelerated lab and internationally located field conditions for months to nearly 3 decades. Mechanical and chemical characterization methods are combined with fundamental polymer reaction engineering to unravel the degradation processes active at the molecular scale that lead to encapsulant delamination. An analytical and modular model framework is put forward enabling the prediction of long‐term PV module durability, starting from fundamental principles at the molecular level and explicitly accounting for bond rupture events in the bulk encapsulant and at the encapsulant interfaces. Successful parameter tuning to adhesion data indicates a dominant occurrence of deacetylation,β‐scission, and hydrolytic depolymerization, respectively. The model contributes to the longstanding challenge of predicting module lifetimes in any geographic location while minimizing time‐consuming and costly aging studies.

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