Chemical mechanical polishing (CMP) has become the enabling planarization method for shallow trench isolation (STI) of sub 0.25μm technology. CMP is able to reduce topography over longer lateral distances than earlier techniques; however, CMP still suffers from pattern dependencies that result in large variation in the post-polish profile across a chip. In the STI process, insufficient polish will leave residue nitride and cause device failure, while excess dishing and erosion degrade device performance.
Our group has proposed several chip-scale CMP pattern density models , and a methodology using designed dielectric CMP test mask to characterize CMP processes . The methodology has proven helpful in understanding STI CMP; however, it has several limitations as the existing test mask primarily consists of arrays of lines and spaces of large feature size varying from 10 to 100 μm. In this paper, we present a new STI characterization mask, which consists of various rectangular, L-shape, and X-shape structures of feature sizes down to submicron. The mask is designed to study advanced STI CMP processes better, as it is more representative of real STI structures. The small feature size amplifies the effects of edge acceleration and oxide deposition bias, and thus enables us to study their impact better. Experimental data from an STI CMP process is shown to verify the methodology, and these secondary effects are explored. The new mask and data guide ongoing development of improved pattern dependent STI CMP models.