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Proceedings Paper

Assist feature printability prediction by 3-D resist profile reconstruction
Author(s): Xin Zheng; Jensheng Huang; Fook Chin; Aram Kazarian; Chun-Chieh Kuo
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Paper Abstract

Sub-resolution Assist Features (SRAFs) are powerful tools to enhance the focus margin of drawn patterns. SRAFs are placed and sized so they do not print on the wafer, but the larger the SRAF, the more effective it becomes at enhancing through-focus stability. The size and location of an SRAF that will image on a wafer is highly dependent upon neighboring patterns and models of SRAF printability are, at present, unreliable. Model-based SRAF placement has been used to enhance resolution at 20nm node processes and below with stringent requirements that inserted SRAFs will not be imaged on wafer. However, despite widespread SRAF use and hard data as to SRAF effectiveness, it has been very difficult to develop a process model that accurately predicts under what process conditions an SRAF will image on a wafer. More accurate models of SRAF printing should allow model based SRAF placement to be relaxed, resulting in more effective SRAF placement and broader focus margins. One of the first problems with the concept of SRAF printability is the definition of an SRAF printing on a wafer. This is not obvious because two different states of printing exist. The first print state is when a residue is left on a wafer from the SRAF. The first state can be considered printing from the point of view that photoresist is on the wafer and the photoresist may even lift off and cause defects. However, the first state can be considered non-printing because the over etch from the etch process will generally remove the photoresist residual and the material underneath. The second state is when a pattern is formed and etched into the substrate, a state at which the pattern has clearly printed on the wafer. Of course, intermediate states may also be defined. In order to be applicable, an SRAF printability model must be able to predict both printing states. In addition, the model must be able to extrapolate to configurations beyond those used to develop the model in the first place. These model properties may then be used to optimize the printability vs. efficacy of an SRAF either prior to or during an Optical Proximity Correction (OPC) run. The process models that are used during OPC have never been able to reliably predict which SRAFs will print. This appears to be due to the fact that OPC process models are generally created using data that does not include printed subresolution patterns. An enhancement to compact modeling capability to predict Assist Features (AF) printability is developed and discussed. A hypsometric map representing 3-D resist profile was built by applying a first principle approximation to estimate the "energy loss" from the resist top to bottom. Such a 3-D resist profile is an extrapolation of a well calibrated traditional OPC model without any additional information. Assist features are detected at either top of resist (dark field) or bottom of resist (bright field). Such detection can be done by just extracting top or bottom resist models from our 3-D resist model. There is no measurement of assist features needed when we build AF but it can be included if interested but focusing on resist calibration to account for both exposure dosage and focus change sensitivities. This approach significantly increases resist model's capability for predicting printed SRAF accuracy. And we don't need to calibrate an SRAF model in addition to the OPC model. Without increase in computation time, this compact model can draw assist feature contour with real placement and size at any vertical plane. The result is compared and validated with 3-D rigorous modeling as well as SEM images. Since this method does not change any form of compact modeling, it can be integrated into current MBAF solutions without any additional work.

Paper Details

Date Published: 30 June 2012
PDF: 6 pages
Proc. SPIE 8441, Photomask and Next-Generation Lithography Mask Technology XIX, 84410K (30 June 2012); doi: 10.1117/12.964973
Show Author Affiliations
Xin Zheng, Synopsys, Inc. (United States)
Jensheng Huang, Synopsys, Inc. (United States)
Fook Chin, Synopsys, Inc. (United States)
Aram Kazarian, Synopsys, Inc. (United States)
Chun-Chieh Kuo, Synopsys, Inc. (Taiwan)

Published in SPIE Proceedings Vol. 8441:
Photomask and Next-Generation Lithography Mask Technology XIX
Kokoro Kato, Editor(s)

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