Lithography performance of contact holes: I. Optimization of pattern fidelity using MPG and MPG-II

Weaver, Suzanne; Lu, Maiying; Chabala, J. M.; Ton, Dinh; Sauer, Charles A.; Mack, Chris A.

doi:10.1117/12.392054

Cited by 2 publications

(1 citation statement)

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“…But it is difficult to evaluate how the mask corner rounding affects the pattern fidelity. It is well known that when contact hole wafer dimensions are less than about λ/NA (where λ is the imaging wavelength and NA is the objective lens numerical aperture), the nominally square holes print as circles on the wafer due to the diffraction limits of the imaging tool [1] . Based on this observation, we can not judge how much distortion of the pattern on wafer is directly affected by the amount of the mask corner rounding.…”

Section: Introductionmentioning

confidence: 99%

Improvement of Contact OPC Model Accuracy by Using Corner Chopping

Huang

Zhang

et al. 2013

ECS Trans.

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An accurate OPC (Optical Proximity Correction) model with good extrapolating capability plays an important role in achieving the accurate OPC. OPC model usually consists of physical part and empirical part which correspond to optical and resist models respectively. The optical physics has a solid theoretical foundation to follow, this part is very critical to the model accuracy and extrapolation capability. The closer the parameters (illumination, geometrical shape on real masks, etc) to real conditions are fed into optical part, the more accurate the model will be. For contact layer, the corner rounding of patterns on the real mask leads to significant deviations from original post OPC patterns. This deviation can no longer be ignored in both OPC model set up and OPC run at 32nm node and beyond. In this paper we employed a corner chopping technique to emulate the real mask shape and used it to calibrate the contact OPC model. We compared the model fitting error and extrapolate capability. The results showed the improvements in both OPC model accuracy and its extrapolation capability are significant.

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Section: Introductionmentioning

confidence: 99%