PATTERN DENSITY BASED PREDICTION FOR DEEP REACTIVE ION ETCH (DRIE)

A quantitative model capturing Deep Reactive Ion Etch (DRIE) pattern density effects is presented. Our previous work has explored the causes of wafer-level variation and demonstrated dielevel interactions resulting from pattern density and reactant species consumption [1]. Several reports have focused on experimental evidence and modeling of feature-level (aspect ratio) dependencies [2]. In contrast, in this work we contribute a computationally efficient and effective modeling approach that focuses on layout pattern density-induced nonuniformity in DRIE. This is a key component in an integrated model combining wafer-, die-, and feature-level DRIE dependencies to predict etch depth for an input layout and a characterized etch tool and process. A microscale engine turbopump layout is used to demonstrate the model, which was calibrated to fit across-die variation within 1% and intra-die variation to within 0.1% (normalized RMS error).