Patrick Thornton

Research Interests

Adhesion and Reliability of Photovoltaic Materials

My research focuses primarily on implementing novel techniques to characterize mechanical behavior and failure in advanced materials, specifically those of interest in the photovoltaic (PV) industry. Using simple metrologies based on fundamentals of fracture mechanics, I analyze the interfacial adhesive and cohesive properties in multi-layer materials under stress states and environmental conditions relevant to their real-world applications in the solar industry. Such analyses are critical for assessing a material’s reliability in the field.

PV modules are designed for decades of sustained operation in the field. Over time, however, mechanical/thermomechanical forces, moisture, and ultraviolet radiation degrade the adhesive properties of structural materials that protect the solar cell, ultimately leading to reduced performance. Through collaboration with scientists at SLAC and under the DuraMAT program within the Department of Energy, I am utilizing advanced characterization techniques, including WAXS/SAXS utilizing Stanford Synchrotron Radiation Lightsource, to better understand the fundamental degradation pathways critical for encapsulant failure in solar modules and their interdependencies. Additionally, through collaboration with the National Renewable Energy Laboratory, I am building on the work previously done in our lab by Jared Tracy to develop and test simple and reproducible metrologies for evaluating adhesion in PV encapsulation and backsheet structures, with the overarching objective of identifying key factors to improve reliability while limiting cost. Using these metrologies, I am characterizing adhesive properties of relevant layers of PV modules, in both coupon-level test specimens as well as on decades-old field modules. Furthermore, through collaboration with Prof. Dr. Ir. Dagmar D’hooge from Ghent University in Belgium, we are developing models that can fundamentally characterize the appropriate degradation mechanisms. This will allow for efficient predictive modeling in conjunction with the appropriate, effective use of accelerated tests to verify the viability of future materials solutions.

Awards

• The Rick and Melinda Reed Graduate Fellowship in the School of Engineering (2017)