PV (Crystalline Silicon and Thin Film) Manufacturing Diagnostics

Photovoltaic (PV) technology is predicted to have a very substantial impact on the nation¿s wealth and economy in the 21st century. For very-large-scale PV cells, the high standards for production demand a reduction in labor costs and in-line automated methods to monitor and diagnose the production process. This project will develop a high-throughput, in-line, automated diagnostic system that will provide the needed speed and functionality to permit fast, accurate, and automated mapping of the uniformity, composition, and stress of the coating on a PV cell. In Phase I, a hyperspectral imaging setup was designed, assembled, and tested. Necessary software and data processing algorithms were selected and implemented. The feasibility of the approach was demonstrated by testing the assembled system with an organic solar cell. Phase II will involve the development of a mid-IR spectropolarimetric imaging system, capable of fast and accurate characterization of solar cells with structured surfaces. By the end of Phase II, a new high-throughput, in-line PV manufacturing diagnostic system will be completed. Commercial Applications and Other Benefits as described by the awardee: The technology should yield a number of products, ranging from completely automated systems for in-line diagnostics on large PV manufacturing lines to relatively simple and inexpensive table­top systems for thin film R&D. The installation of such systems should lead to significant yield improvement and cost reduction of solar cells, resulting in reduced cost for solar energy with an attendant reduction in the use of fossil fuels.