Method and apparatus for determining an optical model that models the effects of optical proximity correction

• US 20080235651A1
• Filed: 03/21/2007
• Published: 09/25/2008
• Est. Priority Date: 03/21/2007
• Status: Active Grant

• Current Assignee: Synopsys Incorporated
• Original Assignee: Synopsys Incorporated
• Inventors: Li, Jianliang, Melvin, Lawrence S., Yan, Qilang
• Granted Patent: US 7,788,630 B2
• Time in Patent Office: Days
• US Class Current: 716/21
• CPC Class Codes: G03F 1/36 Masks having proximity correction features; Preparation thereof, e.g. optical proximity correction [OPC] design processes

Abstract

One embodiment provides a system that can enable a designer to determine the effects of subsequent processes at design time. During operation, the system may receive a test layout and an optical model that models an optical system, but which does not model the effects of subsequent processes, such as optical proximity correction (OPC). The system may generate a first dataset using the test layout and the optical model. Next, the system may apply OPC to the test layout, and generate a second dataset using the corrected test layout and the optical model. The system may then use the first dataset and the second dataset to adjust the optical model to obtain a second optical model that models the effects of subsequent processes.

Claims

1. A method for determining an optical model that models effects of optical proximity correction, the method comprising:

receiving a first optical model which is represented using kernels;

receiving a test layout;

determining a first dataset by convolving the kernels with the test layout at sampling points in the test layout;

applying optical proximity correction to the test layout to obtain a corrected test layout;

determining a second dataset by convolving the kernels with the corrected test layout at the sampling points in the corrected test layout; and

determining a second optical model using the first dataset and the second dataset.

2. The method of claim 1,

wherein the first optical model models effects of a photolithography process, but does not model effects of optical proximity correction;

and

wherein the second optical model models effects of the photolithography process and optical proximity correction.

3. The method of claim 2, comprising:

receiving a first layout to which optical proximity correction has not been applied; and

determining a contour using the first layout and the second optical model, wherein the contour predicts a pattern that would be generated if the first layout is corrected using optical proximity correction and then printed using the photolithography process.

4. The method of claim 3, wherein determining a contour includes:

determining a set of values by convolving the second optical model with the first layout at a set of evaluation points in the first layout; and

comparing the set of values with a threshold.

5. The method of claim 1, wherein the second optical model is represented as a summation of weighted kernels, wherein the kernels are weighted using kernel coefficients, and wherein the method comprises storing the kernel coefficients in a computer-readable storage-medium.

6. The method of claim 1, wherein determining the second optical model includes determining matrix A so that M_OPC^T{circle around (×

)}U≈

M₀^T{circle around (×

)}UA, where M₀^T is a transpose of the test layout'"'"'s transmission function, M_OPC^T is a transpose of the corrected test layout'"'"'s transmission function, and U is the first optical model.

7. The method of claim 6,

wherein the first dataset includes values M_0,i^T{circle around (×

)}K_j, which represents the convolution of the transpose of the test layout'"'"'s transmission function, M₀^T, with kernel K_j at sample point i;

wherein the second dataset includes values M_OPC,i^T{circle around (×

)}K_j, which represents the convolution of the transpose of the corrected test layout'"'"'s transmission function, M_OPC^T, with kernel K_j at sample point i; and

wherein determining matrix A includes fitting the first dataset and the second dataset using a least squares fitting technique.

8. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for determining an optical model that models effects of optical proximity correction, the method comprising:

receiving a first optical model which is represented using kernels;

receiving a test layout;

determining a first dataset by convolving the kernels with the test layout at sampling points in the test layout;

applying optical proximity correction to the test layout to obtain a corrected test layout;

determining a second dataset by convolving the kernels with the corrected test layout at the sampling points in the corrected test layout; and

determining a second optical model using the first dataset and the second dataset.

9. The computer-readable storage medium of claim 8,

wherein the first optical model models effects of a photolithography process, but does not model effects of optical proximity correction;

and

wherein the second optical model models effects of the photolithography process and optical proximity correction.

10. The computer-readable storage medium of claim 9, comprising:

receiving a first layout to which optical proximity correction has not been applied; and

determining a contour using the first layout and the second optical model, wherein the contour predicts a pattern that would be generated if the first layout is corrected using optical proximity correction and then printed using the photolithography process.

11. The computer-readable storage medium of claim 10, wherein determining a contour includes:

determining a set of values by convolving the second optical model with the first layout at a set of evaluation points in the first layout; and

comparing the set of values with a threshold.

12. The computer-readable storage medium of claim 8, wherein the second optical model is represented as a summation of weighted kernels, wherein the kernels are weighted using kernel coefficients, and wherein the method comprises storing the kernel coefficients in a second computer-readable storage-medium.

13. The computer-readable storage medium of claim 8, wherein determining the second optical model includes determining matrix A so that M_OPC^T{circle around (×

)}U≈

M₀^T{circle around (×

)}UA, where M₀^T is a transpose of the test layout'"'"'s transmission function, M_OPC^T is a transpose of the corrected test layout'"'"'s transmission function, and U is the first optical model.

14. The computer-readable storage medium of claim 13,

wherein the first dataset includes values M_0,i^{T {circle around (×}

)}K_j, which represents the convolution of the transpose of the test layout'"'"'s transmission function, M₀^T with kernel K_j at sample point i;

wherein the second dataset includes values M_OPC,i^T{circle around (×

)}K_j, which represents the convolution of the transpose of the corrected test layout'"'"'s transmission function, M_OPC^T, with kernel K_j at sample point i; and

wherein determining matrix A includes fitting the first dataset and the second dataset using a least squares fitting technique.

15. An apparatus for determining an optical model that models effects of optical proximity correction, the apparatus comprising:

a first receiving mechanism configured to receive a first optical model which is represented using kernels;

a second receiving mechanism configured to receive a test layout;

a first determining mechanism configured to determine a first dataset by convolving the kernels with the test layout at sampling points in the test layout;

an applying mechanism configured to apply optical proximity correction to the test layout to obtain a corrected test layout;

a second determining mechanism configured to determine a second dataset by convolving the kernels with the corrected test layout at the sampling points in the corrected test layout; and

a third determining mechanism configured to determine a second optical model using the first dataset and the second dataset.

16. The apparatus of claim 15,

wherein the first optical model models effects of a photolithography process, but does not model the effects of optical proximity correction;

and

wherein the second optical model models effects of the photolithography process and optical proximity correction.

17. The apparatus of claim 16, comprising:

a third receiving mechanism configured to receive a first layout to which optical proximity correction has not been applied; and

a fourth determining mechanism configured to determine a contour using the first layout and the second optical model, wherein the contour predicts a pattern that would be generated if the first layout is corrected using optical proximity correction and then printed using the photolithography process.

18. The apparatus of claim 17, wherein the fourth determining mechanism is configured to:

determine a set of values by convolving the second optical model with the first layout at a set of evaluation points in the first layout; and

compare the set of values with a threshold.

19. The apparatus of claim 15, wherein the second optical model is represented as a summation of weighted kernels, wherein the kernels are weighted using kernel coefficients, and wherein the apparatus is configured to store the kernel coefficients in a computer-readable storage-medium.

20. The apparatus of claim 15, wherein the third determining mechanism is configured to determine matrix A so that M_OPC^T{circle around (×

)}U≈

M₀^T{circle around (×

)}UA, where M₀^T is a transpose of the test layout'"'"'s transmission function, M_OPC^T is a transpose of the corrected test layout'"'"'s transmission function, and U is the first optical model.