IEICE TRANSACTIONS on Fundamentals
A Fast Mask Manufacturability and Process Variation Aware OPC Algorithm with Exploiting a Novel Intensity Estimation Model
Summary :
With being pushed into sub-16nm regime, advanced technology nodes printing in optical micro-lithography relies heavily on aggressive Optical Proximity Correction (OPC) in the foreseeable future. Although acceptable pattern fidelity is utilized under process variations, mask design time and mask manufacturability form crucial parameters whose tackling in the OPC recipe is highly demanded by the industry. In this paper, we propose an intensity based OPC algorithm to find a highly manufacturable mask solution for a target pattern with acceptable pattern fidelity under process variations within a short computation time. This is achieved through utilizing a fast intensity estimation model in which intensity is numerically correlated with local mask density and kernel type to estimate the intensity in a short time and with acceptable estimation accuracy. This estimated intensity is used to guide feature shifting, alignment, and concatenation following linearly interpolated variational intensity error model to achieve high mask manufacturability with preserving acceptable pattern fidelity under process variations. Experimental results show the effectiveness of our proposed algorithm on the public benchmarks.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E99-A No.12 pp.2363-2374
- Publication Date
- 2016/12/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E99.A.2363
- Type of Manuscript
- Special Section PAPER (Special Section on VLSI Design and CAD Algorithms)
- Category
Authors
Ahmed AWAD
Tokyo Institute of Technology
Atsushi TAKAHASHI
Tokyo Institute of Technology
Chikaaki KODAMA
Toshiba Corporation
Keyword
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Ahmed AWAD, Atsushi TAKAHASHI, Chikaaki KODAMA, "A Fast Mask Manufacturability and Process Variation Aware OPC Algorithm with Exploiting a Novel Intensity Estimation Model" in IEICE TRANSACTIONS on Fundamentals,
vol. E99-A, no. 12, pp. 2363-2374, December 2016, doi: 10.1587/transfun.E99.A.2363.
Abstract: With being pushed into sub-16nm regime, advanced technology nodes printing in optical micro-lithography relies heavily on aggressive Optical Proximity Correction (OPC) in the foreseeable future. Although acceptable pattern fidelity is utilized under process variations, mask design time and mask manufacturability form crucial parameters whose tackling in the OPC recipe is highly demanded by the industry. In this paper, we propose an intensity based OPC algorithm to find a highly manufacturable mask solution for a target pattern with acceptable pattern fidelity under process variations within a short computation time. This is achieved through utilizing a fast intensity estimation model in which intensity is numerically correlated with local mask density and kernel type to estimate the intensity in a short time and with acceptable estimation accuracy. This estimated intensity is used to guide feature shifting, alignment, and concatenation following linearly interpolated variational intensity error model to achieve high mask manufacturability with preserving acceptable pattern fidelity under process variations. Experimental results show the effectiveness of our proposed algorithm on the public benchmarks.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E99.A.2363/_p
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@ARTICLE{e99-a_12_2363,
author={Ahmed AWAD, Atsushi TAKAHASHI, Chikaaki KODAMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Fast Mask Manufacturability and Process Variation Aware OPC Algorithm with Exploiting a Novel Intensity Estimation Model},
year={2016},
volume={E99-A},
number={12},
pages={2363-2374},
abstract={With being pushed into sub-16nm regime, advanced technology nodes printing in optical micro-lithography relies heavily on aggressive Optical Proximity Correction (OPC) in the foreseeable future. Although acceptable pattern fidelity is utilized under process variations, mask design time and mask manufacturability form crucial parameters whose tackling in the OPC recipe is highly demanded by the industry. In this paper, we propose an intensity based OPC algorithm to find a highly manufacturable mask solution for a target pattern with acceptable pattern fidelity under process variations within a short computation time. This is achieved through utilizing a fast intensity estimation model in which intensity is numerically correlated with local mask density and kernel type to estimate the intensity in a short time and with acceptable estimation accuracy. This estimated intensity is used to guide feature shifting, alignment, and concatenation following linearly interpolated variational intensity error model to achieve high mask manufacturability with preserving acceptable pattern fidelity under process variations. Experimental results show the effectiveness of our proposed algorithm on the public benchmarks.},
keywords={},
doi={10.1587/transfun.E99.A.2363},
ISSN={1745-1337},
month={December},}
Copy
TY - JOUR
TI - A Fast Mask Manufacturability and Process Variation Aware OPC Algorithm with Exploiting a Novel Intensity Estimation Model
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2363
EP - 2374
AU - Ahmed AWAD
AU - Atsushi TAKAHASHI
AU - Chikaaki KODAMA
PY - 2016
DO - 10.1587/transfun.E99.A.2363
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E99-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2016
AB - With being pushed into sub-16nm regime, advanced technology nodes printing in optical micro-lithography relies heavily on aggressive Optical Proximity Correction (OPC) in the foreseeable future. Although acceptable pattern fidelity is utilized under process variations, mask design time and mask manufacturability form crucial parameters whose tackling in the OPC recipe is highly demanded by the industry. In this paper, we propose an intensity based OPC algorithm to find a highly manufacturable mask solution for a target pattern with acceptable pattern fidelity under process variations within a short computation time. This is achieved through utilizing a fast intensity estimation model in which intensity is numerically correlated with local mask density and kernel type to estimate the intensity in a short time and with acceptable estimation accuracy. This estimated intensity is used to guide feature shifting, alignment, and concatenation following linearly interpolated variational intensity error model to achieve high mask manufacturability with preserving acceptable pattern fidelity under process variations. Experimental results show the effectiveness of our proposed algorithm on the public benchmarks.
ER -
English
