Real Time Spectroscopic Ellipsometry Studies of Thin Film Materials and Structures for Photovoltaic Applications
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Spectroscopic ellipsometry (SE) is a powerful tool to characterize multilayered thin films, providing structural parameters and materials optical properties over a wide spectral range. Further analyses of these optical properties can provide additional information of interest on the physical and chemical properties of materials. In situ real time SE (RTSE) combines high surface sensitivity with fast data acquisition and non-destructive probing, thus lends unique insights into the dynamics of film growth. RTSE have been applied to investigate the growth process and material properties for major thin film photovoltaic technologies, including cadmium telluride (CdTe) and hydrogenated silicon (Si:H). The growth rate, nucleation behavior, evolution of surface roughness, and development of void structures in magnetron sputtering of CdTe and CdS show strong variations with deposition temperature and Ar pressure. The complex dielectric functions ε of CdTe and CdS films also sensitively depend on preparation conditions. In-depth analyses of ε provide consistent estimates of temperature, excited carrier mean free path, group speeds of excited carriers, and intrinsic stress in the films. Thus, SE has the potential to monitor not only film thickness, but also materials properties on a solar cell production line. Major SE analyses results are compared with other characterization techniques, including atomic force microscopy and X-ray diffraction. RTSE has been applied to establish deposition phase diagrams that describe very high frequency plasma enhanced chemical vapor depositions for Si:H thin films on various substrates. Close correlations between RTSE results and solar cell performance have been observed. For advanced instrumentation, significant generalizations from previous studies have been achieved for the study of a dual rotating compensator ellipsometer system. Computer software was developed to verify the generalized approach, to simulate the operations of such a system under non-ideal conditions, and to predict the best hardware design, experimental configuration, and data reduction strategies.