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Proceedings Paper

Multi-layer model vs. single-layer model for N and P doped poly layers in etch bias modeling
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Paper Abstract

In modern photolithography, ever smaller critical dimension (CD) budgets require tighter control over the entire process, demanding more accurate practice of optical proximity correction (OPC). In last decade, the model based OPC (MBOPC) has outpaced the rule based OPC (RBOPC) and become widely adopted in semiconductor industry. During the MBOPC process, the physical models are called to compute the signal values at the evaluation points and the design patterns are perturbed such that the final model contours are as close to the targets as possible. It has been demonstrated that in addition to simulating the optics and resist effects, the physical models must accommodate the pattern distortion due to etch process as well. While the etch process may be lumped with optics and resist processes into one model for the 65nm and above nodes, it can no longer be treated as small perturbations on photolithographic effects for more advanced nodes and it is highly desired to build a physics-based etch model formulations that differ from the conventional convolution-based process models used to simulate the optical and resist effect. Our previous studies proposed a novel non-linear etch modeling object in combination with conventional convolution kernels, which simulates the non-optics and non-resist proximity effect successfully. This study examines further the non-linear etch modeling method by checking the different behaviors of N and p doped layers which physically have different etching rates and should be represented differently in etch modeling. The experimental results indicate that the fitting accuracy is significantly improved when the data points are split into N and P groups and calibrated separately. The N and P layer etch models are used in staged MBOPCs and the results are compared with single-layer model as well.

Paper Details

Date Published: 24 September 2010
PDF: 9 pages
Proc. SPIE 7823, Photomask Technology 2010, 78233V (24 September 2010); doi: 10.1117/12.866040
Show Author Affiliations
Jianliang Li, Synopsys, Inc. (United States)
Ezequiel Vidal-Russell, Micron Technology, Inc. (United States)
Daniel Beale, Beale Innovations, Inc. (United States)
Chunqing Wang, Synopsys, Inc. (United States)
Lawrence S. Melvin, Synopsys, Inc. (United States)

Published in SPIE Proceedings Vol. 7823:
Photomask Technology 2010
M. Warren Montgomery; Wilhelm Maurer, Editor(s)

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