Publication
Microlithography 1994
Conference paper

Application of the Aerial Image Measurement System (AIMSTM) to the Analysis of Binary Mask Imaging and Resolution Enhancement Techniques

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Abstract

The newly developed Aerial Image Measurement System (AIMSTM∗) was used to quantify the lithographic benefits of several resolution enhancement techniques as compared to standard binary mask imaging. This system, a microscope based stepper emulator, permits rapid characterization of mask images from both binary and phase shifted mask (PSM) patterns at multiple focal planes. The resultant images are captured digitally with a CCD camera and analyzed using an exposure-defocus tree technique to quantify the depthof- focus as a function of exposure latitude. Mask types analyzed included binary, attenuated PSM, and alternating PSM, combined with standard (0.54 partial coherence), annular (0.6/0.4, 0.4/0.2), and quadrupole illumination . The lithographic benefits of these resolution enhancement techniques depend on the accuracy of the mask fabrication, which makes quantification of any errors essential. The AIMS is used to extract both phase and transmission errors from captured aerial images of all the masks evaluated. Measurements of feature types typically encountered in devices: line-space arrays, bright and dark isolated lines, and contacts were performed on images ranging from O.25-O.5Otm Efforts focused on: the enhancement of isolated bright features with attenuated phase shifting, alternating PSM benefits on nested features, and effects of offaxis illumination designs on both nested and isolated lines typically found in random logic applications. Finally, AIMS results are compared to wafer electrical linewidth data. A 0.5 numerical aperture (NA) DUV stepper was used with a partial coherence of 0.6 combined with IBM APEX-E resist process. Collected data were analyzed using techniques identical to the AIMS analysis, allowing for a high level of consistency. Comparative data focused on binary mask imaging for the verification of the AIMS results. Trends associated with feature sizes and types are discussed.