Two threshold resist models for optical proximity correction

Huang, Wen‐Shih; Lin, Chia-Hui; Kuo, C. C.; Huang, Chung-Ping; Lin, Jyh-Ching; Chen, Jeng-Horng; Liu, Ru-Gun; Ku, Y.H.; Lin, B. N.

doi:10.1117/12.544252

Cited by 26 publications

(12 citation statements)

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“…Some photoresist models employ a Constant Threshold Resist (CTR) [22], where the developed resist profile can then be described by a sigmoid transformation of the aerial image, [8,9] that is,…”

Section: Methodsmentioning

confidence: 99%

Choosing objective functions for inverse lithography patterning

2011

SPIE Proceedings

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Inverse lithography which generates model-based patterns theoretically has superior patterning fidelity comparing to conventional rule-based technique. Cost functions are the determinant of performance inverse lithography that is also an optimization problem. However, the design and know-how of cost functions have rarely been discussed. In this paper, we investigate the impacts of various cost functions and their superposition for inverse lithography patterning exploiting a steepest descent algorithm. We research the most generally used objective functions, which are the resist and aerial images, and also deliver a derivation for the aerial image contrast. We then discuss the pattern fidelity and final mask characteristics for simple layouts with a single isolated contact and two nested contacts. Moreover, the convergences which are expressed by edge-placement error (EPE) and contrast versus iteration numbers rapidly attain to steady sate in most hybrid cost functions. All in all, we conclude that a cost function composed of a dominant resist-image component and a minor aerial-image or image-contrast component can carry out a good mask correction and contour targets when using inverse lithography patterning.

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Section: Methodsmentioning

confidence: 99%

Choosing objective functions for inverse lithography patterning

2011

SPIE Proceedings

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“…Generally, the constant threshold resist (CTR) model is used to approximate the photoresist effect [22]. However, for numerical considerations, the sigmoid function is often employed to replace the CTR model due to its differentiability [23][24][25][26].…”

Section: Lithography Vectorial Imaging Modelmentioning

confidence: 99%

Robust hybrid source and mask optimization to lithography source blur and flare

Han

et al. 2015

Appl. Opt.

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As a promising resolution enhancement technique, a set of pixelated source and mask optimization (SMO) methods has been introduced to further improve the lithography at 45 nm node and beyond. Recently, some papers studied the impact of the scanner errors on SMO, and the results revealed that the source blur and flare seriously impact on the lithography performance of the optimal source and mask resulting from SMO. However, current SMO methods did not propose an effective method to compensate for the impact of these nonideal factors of the actual scanners. To overcome this drawback, this paper focuses on developing a robust hybrid SMO (HSMO) method where the sensitivities of the aerial image to source blur and flare are introduced into the cost function. Simulation results are compared with traditional SMO to demonstrate the benefit of the proposed source blur-flare-aware HSMO method in pattern fidelity and process window.

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“…[2] In this work, dense simulation is utilized to numerically compute the intensity from Eq. (1) at full 2D grid at once [10], based on discrete-time Fourier transforms [3].…”

Section: Optical Modelmentioning

confidence: 99%

“…They are used to describe the behavior of complex chemical interactions and reactions. Two kinds of resist model have been proposed including CTRM and VTRM [10]. CTRM means the area with optical intensity above a certain threshold value will be developed.…”

Section: Introductionmentioning

confidence: 99%

Design of automatic controllers for model-based OPC with optimal resist threshold determination for improving correction convergence

Tsai

et al. 2008

Optical Microlithography XXI

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Model-based Optical Proximity Correction (MBOPC) has become one of the most important resolution enhancement technologies (RETs), which can effectively improve the image fidelity and process robustness. MBOPC is performed by iteratively shifting the polygon edges of mask patterns until convergence requirements are achieved. In this paper, we specifically discuss the design of feedback controllers to improve MBOPC convergence. Effective controller design rules are derived from the OPC results of several circuit layouts. Meanwhile, resist models also significantly affect MBOPC convergence. Two kinds of resist model have been proposed for MBOPC such as constant threshold resist model (CTRM) and variable threshold resist model (VTRM). We propose a novel CTRM, called pattern-based optimal threshold determination (PBOTD). By normalized mean square error (NMSE) formulation, appropriate threshold values with minimum NMSE can be determined to improve image fidelity, and effectively decrease iterations required. The effectiveness of applying both optimized controller and PBOTD is demonstrated on a 90-nm SRAM cell.

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Two threshold resist models for optical proximity correction

Cited by 26 publications

References 0 publications

Choosing objective functions for inverse lithography patterning

Choosing objective functions for inverse lithography patterning

Robust hybrid source and mask optimization to lithography source blur and flare

Design of automatic controllers for model-based OPC with optimal resist threshold determination for improving correction convergence

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