Graduation Year


Document Type




Degree Granting Department

Chemical Engineering

Major Professor

John Wolan, Ph.D.

Co-Major Professor

Sergei Ostapenko, Ph.D.

Committee Member

Scott Campbell, Ph.D.


Renewable energy, Photovoltaic, Cracks detection, Acoustic, Standard deviation


The solar energy, or photovoltaic (PV) industry, driven by economic competition with traditional fossil energy sources, strives to produce solar panels of the highest conversion efficiency and best reliability at the lowest production cost. Solar cells based on crystalline silicon are currently the dominant commercial PV technology by a large margin, and they are likely to remain dominant for at least one decade. The problem of improvement mechanical stability of silicon wafers and finished solar cell is one of the most critical for entire PV industry. Mechanical defects in wafer and cells in the form of periphery or internal cracks can be initiated at various steps of the manufacturing process and becomes the trigger for the fracture. There are a limited number of characterization methods for crack detection but only a few of those are able to satisfy PV industry needs in sensitivity of the crack detection incorporated with the analysis time. The most promising are a Resonance Ultrasonic Vibrations (RUV) technique and Photoluminescence (PL) imaging.

The RUV method was further developed in this thesis project for fast non-destructive crack detection in full-size silicon wafers and solar cells. The RUV methodology relies on deviations of the resonance frequency response curve measured on a wafer with peripheral or bulk millimeter-length crack when it is compared with identical non-cracked wafers. It was observed that statistical variations of the RUV parameters on a similarly processed silicon wafers/cells with the same geometry lead to false positive events reducing accuracy of the RUV method. A new statistical approach using three independent RUV crack detection criteria was developed and applied to resolve this issue. This approach was validated experimentally. Crack detection using RUV technique was applied to a set of production-grade Cz-Si wafers and finished solar cells from the Isofoton's S.A. (Spain) production line. Cracked solar cells rejected by the RUV method using the statistical approach were imaged with room temperature PL mapping and independently controlled with Scanning Acoustic Microscopy (SAM). A comparison of three independent techniques for crack detection, RUV, PL and SAM, was performed on selected samples. A high accuracy and selectivity of the RUV method to identify mm-size cracks in wafers and cells was confirmed.