Statistical characterization of process-induced plasma damage

During plasma processes, charging damage produces various defects in silicon oxide, thereby deteriorating device performance. Optimizing process-induced charging damage requires a computer model, as well as a quantitative analysis of process parameter effects. In this study, plasma charge damage on threshold voltage of metal-semiconductor field-effect transistors is statistically investigated. This includes the analysis of main and interaction effects of process parameters, as well as the construction of response surface models. Charging damage is characterized by means of a statistical experiment. Four types of statistical regression models are constructed. A model with the largest R-Square (R²) fit of 90.6 is chosen for the response surface analysis. Analysis of the main effects revealed that radio frequency power and gas ratio are the most significant and least significant factors, respectively. Among various interaction terms, only the interaction between radio frequency power and bias is found to be influential. Meanwhile, several conflicting effects are noted as the bias power or gas ratio are varied. An optimized regression model is used to understand parameter effects on plasma charging damage.