SBIR-STTR Award

The global photovoltaic industry is expanding rapidly (up to 40% growth in recent years) to meet growing renewable energy demands, due to dramatically increasing prices of fossil energy sources. Crystalline silicon (c-Si) is a dominant segment in the solar cell market, contributing to over 90% of the solar power module production. One of the current technological problems in the production of c-Si solar cells is the identification and removal mechanical defects (such as cracks and high residual stress), which lead to loss of wafer/cell integrity and ultimately to breakage. This problem is increased further as a result of a cost driven strategy to reduce wafer thickness down to 100 microns while concurrently increasing wafer size up to 210 mm. This project will develop a Resonance Ultrasonic Vibrations (RUV) system for the quick and non-destructive assessment of mechanical defects in full-size c-Si solar cells. The RUV method will be based on the variation of resonance peak characteristics (resonance frequency, bandwidth, and amplitude) that result from physical variations in the wafers and cells caused by cracks. Simple criteria will be developed and used for wafer rejection from the solar cell lines. In Phase I: (1) the sensitivity limits of the RUV method will be established in terms of crack length, location, and geometry; (2) an algorithm will be developed to separate the effect of residual stress from that of periphery cracks on the RUV frequency curve; and (3) stable “24/7” data acquisition and analyses will be demonstrated with a speed capability that matches the 2 seconds per wafer throughput on state-of-the-art automatic production lines.

Commercial Applications and Other Benefits as described by the awardee:
A real-time, in-line, automatic process control tool for the identification and rejection of unstable solar cells (due to periphery cracks and high levels of residual stress) from production lines should be of interest to both solar cell producers and automatic cell line equipment vendors. Market penetration for RUV is currently favored by the high demand for this type of in-line testing and the limitations of competing techniques

Wafer breakage in automated solar cell production lines is a major technical problem and a barrier to further cost reductions in silicon solar module manufacturing. The fragility of silicon wafers is attributed to peripheral and bulk millimeter-length cracks. However, no commercial systems address the critical need for in-line inspection of these cracks. This project will validate the applicability of the Resonance Ultrasonic Vibrations system as a real-time, in-line, manufacturing quality control tool for the fast detection of mechanically unstable silicon solar cells caused by cracks. Phase I confirmed that the Resonance Ultrasonic Vibrations method produced a high 91% crack rejection rate and that the system was capable of matching the 2.0 seconds-per-wafer throughput rate of state-of-the-art solar cell production lines. Phase II is designed to move the technology from the laboratory level to commercial demonstration by developing a system prototype. Specifically, Phase II will (1) specify optimal configurations of the in-line system’s component hardware and software; (2) develop and justify a system prototype that meets the major specifications for high throughput, high level of stability, reproducibility of data acquisition and analysis, and high sensitivity with respect to crack length and crack location; (3) design a system platform that allows easy integration within and adaptation to various solar cell production lines; and (4) develop a testing protocol.

Commercial Applications and Other Benefits as described by the awardee:
The silicon-based solar industry, with crystalline silicon as a dominant segment, shows outstanding performance, with approximately 25% yearly growth during recent years. The Resonance Ultrasonic Vibration system should provide a critical quality control tool for this industry, thereby improving productivity, increasing the reliability of products, and reducing manufacturing costs