An Accurate Method for Determining Pattern Collapse Occurrence for Nano-Structures

Abstract

Pattern collapse of nano-structures during the wet cleaning process is one of the main problems which leads to poor device yield. In general, aspect ratio (AR) is often used as the indicator for determining the likelihood of pattern collapse occurrence, because high aspect ratio structures tend to collapse more easily. However, pattern collapse is also influenced by flexural rigidity of the structures, material and shape. Therefore, AR lacks versatility in comparing different structures and material. We propose “γPC ” as the substitute parameter for aspect ratio. In this paper, we demonstrate with experimental data that γPC is more accurate than aspect ratio, and can be used to quantitatively determine the pattern collapse prevention performance of dry technologies.