Impact of measured pupil illumination fill distribution on lithography simulation and OPC models

Bodendorf, C.; Schlief, Ralph E.; Ziebold, Ralf

doi:10.1117/12.535575

Cited by 17 publications

(25 citation statements)

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“…It is well known that many process factors can impact proximity behavior, such as illumination (NA/sigma), focus, PEB bake, acid diffusion, quencher diffusion, resist contrast, flare, etc [3,4]. Some of them can be mitigated by changing process parameters, but others are intrinsic and cannot be changed at will.…”

Section: Simulation Studymentioning

confidence: 98%

Proximity matching for 193 nm scanner using scatterometry

Zhou¹,

Yu²,

Lo³

et al. 2005

Optical Microlithography XVIII

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In this paper, we evaluate several approaches for proximity matching on a 193nm scanner system such as image contrast tuning, illumination tuning and photoresist tuning. Both experimental and simulation studies are carried out to reveal the differences between approaches. We find that it is very important to determine the root cause of proximity mismatch before attempting proximity matching, and that spectroscopic scatterometry is an excellent tool for OPC tuning.

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Section: Simulation Studymentioning

confidence: 98%

Proximity matching for 193 nm scanner using scatterometry

Zhou¹,

Yu²,

Lo³

et al. 2005

Optical Microlithography XVIII

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“…For simplicity, we restricted our current evaluation to simple assumptions like top hat pupil illumination fill. It is imaginable that a more realistic, smoothened illumination distribution [18,19] might lead to a slightly faster convergence of the SOCS algorithm. Moreover, for the typical usage of the tool for full chip OPC purposes, the interplay between optical and resist model in combination with a fit to empirical data is the finally relevant measure for the success.…”

Section: Evaluation In Terms Of Rms Errorsmentioning

confidence: 98%

Benchmark of numerical versus analytical proximity curve calculations

2006

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For the technology development of microlithography various optical simulation tools are established as a planning and development tool. Depending on the application, various numerical approximation schemes are used to tradeoff accuracy versus speed. Determining the correct numerical setting is often a tricky task as it is a compromise between these two contrary properties. In our study, we compare the numerical accuracy of two optical simulators, Solid-E as a representative for simulators for technology development and Mentor Calibre as design-for-manufacturing and optical proximity correction (OPC) tool. Calibre uses a coherent kernel approximation for performing fast simulations. As a measure for the simulation accuracy, we use the root-mean-square error criterion of a linearity curve compared to an analytical reference simulation.

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“…Partially coherent illumination sources such as circular, annular, c-quad, r-quad, and quasar, have continuous pupil illumination functions unlike the so called top-hat approximation, [1][2][3][4][5] which is piecewise constant and discontinuous. Previously reported techniques 5-10 of measuring the pupil illumination function require specialized hardware that is sometimes not readily available.…”

Section: Introductionmentioning

confidence: 99%

Metrology for stepper illumination pupil profile

Perçin¹

2006

J. Micro/Nanolith. MEMS MOEMS

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A technique for measuring the profile of the illumination in the pupil of a lithography projector is presented. The technique is based on exposing pinhole patterns on a wafer at different dose and defocus settings, and processing the scanning electron microscopy ͑SEM͒ images of the printed pinholes. The latent image intensity at the edges of the resist patterns equals the dose-to-clear. This establishes a multitude of equations, each of which states that the latent image intensity at a particular field location, dose, and defocus is known. The intensity distribution in the pupil of the illuminator is obtained by solving a large system of such equations, subject to the constraint that the intensity distribution is non-negative. An image processing algorithm based on nonlinear diffusion is used for finding coordinates of points on the edges of resist in SEM images. The results of the inversion for 193-nm stepper with 0.55/ 0.85 annular illumination and numerical aperture of 0.75 at five exposure field locations are presented.

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Impact of measured pupil illumination fill distribution on lithography simulation and OPC models

Cited by 17 publications

References 0 publications

Proximity matching for 193 nm scanner using scatterometry

Proximity matching for 193 nm scanner using scatterometry

Benchmark of numerical versus analytical proximity curve calculations

Metrology for stepper illumination pupil profile

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