Parameter estimation and modeling of hydrogenated amorphous silicon

• Main Author: Kim, Ji Cheol
• Format: Dissertation
• Language: English
• Published: ProQuest Dissertations & Theses 01-01-1996
• Subjects: Condensation; Condensed matter physics; Electrical engineering; Materials science
• ISBN: 9780591344400; 0591344408

The use of hydrogenated amorphous silicon material (a-Si:H) in devices such as solar cells, active thin film transistor liquid crystal display panels, various sensors, etc. requires an accurate model of the material characteristics and their dependence on light intensity and light soaking over a broad temperature range. Through the use of nonlinear parameter estimation techniques, a gap state model and recombination parameters have been developed from temperature dependent photoconductivity data. These data include the effects of light intensity variation and light soaking. This model provides better agreement between the model and experimental results on a-Si:H than conventional models especially in lower temperature regions. The results of this study are especially beneficial for use in various a-Si device simulations since it represents an accurate model of material performance over a broad temperature range $(125\sp\circ K{-}415\sp\circ K).$ A computer program has been developed, which applies nonlinear parameter estimation techniques to the mathematical description of temperature dependent photoconductivity, for the parametric estimation of an a-Si:H gap state model and recombination parameters. This program produces a plausible model of a-Si deduced from the photoconductivity data. The light effects of soaking and the illumination intensity dependency of the temperature dependent photoconductivity have been analyzed using the charge distribution and the recombination in the localized states of a-Si:H. The charge distribution and recombination are computed using the parameter sets obtained by applying nonlinear regression technique to experimental data for the temperature dependent photoconductivity. Simulated photoconductivity based on a positive correlation energy defect model has been compared with simulated photoconductivity obtained from a negative correlation energy defect model.