Edge-based full chip mask topography modeling

• US 8,918,743 B1
• Filed: 08/12/2013
• Issued: 12/23/2014
• Est. Priority Date: 08/12/2013
• Status: Active Grant

• Current Assignee: Synopsys Incorporated
• Original Assignee: Synopsys Incorporated
• Inventors: Yan, Qiliang, Zhang, Hongbo, Croffie, Ebo, Zhang, Lin, Fan, Yongfa, Brooker, Peter, Ren, Qian
• Primary Examiner(s): Memula, Suresh
• Application Number:
  US13/965,111
• Time in Patent Office: 498 Days
• Field of Search: 716/51
• US Class Current: 716/51
• CPC Class Codes: G03F 7/70283 Mask effects on the imaging process
• CPC Class Codes: G03F 7/705 Modelling or simulating from physical phenomena up to complete wafer processes or whole workflow in wafer productions

Abstract

A method and apparatus of a novel full chip edge-based mask three-dimensional (3D) model for performing photolithography simulation is described. The method applies a thin mask model to a mask design layout to create a thin mask transmission. The method generates a thick mask model that has a plurality of edge-based kernels. The method applies the thick mask model to the mask design layout to create a mask 3D residual. The method combines the thin mask transmission and the mask 3D residual to create a mask 3D transmission.

Claims

1. A computer-implemented method of performing mask topography effect modeling on a mask design layout, the method comprising:

applying, using a computing device, a thin mask model to the mask design layout to create a thin mask transmission;

applying a thick mask model to the mask design layout, the thick mask model comprising a plurality of edge-based kernels;

applying a rasterization filter to the plurality of edge-based kernels to generate a plurality of filtered kernels, the applying of the thick mask model comprising applying the plurality of filtered kernels to edges in the mask design layout to produce a mask 3D residual; and

combining the thin mask transmission and the mask 3D residual to create a mask 3D transmission, wherein the mask topography effect modeling on the mask design layout is used to create an improved optical mask for creating an integrated circuit.

2. The method of claim 1, wherein the plurality of edge-based kernels are for transverse electric (TE) polarization and transverse magnetic (TM) polarization.

3. The method of claim 1 further comprising generating the thick mask model.

4. The method of claim 3, wherein the generating of the thick mask model further comprises:

receiving a mask topography structure;

performing a rigorous simulation to simulate a near-field;

generating a reference mask 3D residual by subtracting a thin mask electric field from the near-field; and

deriving the plurality of edge-based kernels by decomposing the reference mask 3D residual.

5. The method of claim 4, wherein half-plane is used as a primitive in the reference mask 3D residual.

6. The method of claim 1, wherein the rasterization filter preserves high fidelity within an optical bandwidth, attenuates frequencies beyond a mirror point, and has a small spatial-domain ambit and angular symmetry.

7. The method of claim 1, wherein the applying of the plurality of filtered kernels to edges comprises:

for each point on the edges, applying the plurality of filtered kernels to generate disturbance waves emitted by the point; and

superposing the disturbance waves emitted by all points on the edges to produce the mask 3D residual.

8. The method of claim 1, wherein the applying of the thick mask model comprises applying the plurality of edge-based kernels to edges in the mask design layout to produce the mask 3D residual.

9. The method of claim 8, wherein one of the edges is an all-angle edge and the applying of the plurality of edge-based kernels to the all-angle edge further comprises:

decomposing an incident electric field of the all-angle edge into a TE polarization component and a TM polarization component;

applying corresponding edge-based kernels from the plurality of edge-based kernels to the TE polarization component and the TM polarization component to produce a mask 3D correction for the TE polarization component and a mask 3D correction for the TM polarization component; and

combining the mask 3D correction for the TE polarization component and the mask 3D correction for the TM polarization component to form the mask 3D residual.

10. The method of claim 8, wherein the applying of the thick mask model further comprises generating a record that defines a set of relevant edges for each region in the mask design layout, and the applying of the plurality of edge-based kernels to edges further comprises, for each region in the mask design layout, applying the plurality of edge-based kernels only to the set of edges relevant to the region by checking the record, wherein an edge and a region is related when a point on the edge is within a pre-determined distance from the region.

11. A data processing system for performing mask topography effect modeling on a mask design layout, the data processing system comprising:

means for applying a thin mask model to the mask design layout to create a thin mask transmission;

means for applying a thick mask model comprising a plurality of edge-based kernels to the mask design layout;

means for applying a rasterization filter to the plurality of edge-based kernels to generate a plurality of filtered kernels, wherein the applying of the thick mask model comprises applying the plurality of filtered kernels to edges in the mask design layout to produce a mask three-dimensional (3D) residual; and

means for combining the thin mask transmission and the mask 3D residual to create a mask 3D transmission, wherein the mask topography effect modeling on the mask design layout is used to create an improved optical mask for creating an integrated circuit.

12. The data processing system of claim 11 further comprising:

means for receiving a lookup table containing scaling parameters for edge coupling effects, each scaling parameter is indexed by associated geometry information,

wherein the means for applying the thick mask model further comprises means for updating the plurality of edge-based kernels with the scaling parameters from the lookup table.

13. The data processing system of claim 12 further comprising means for generating the lookup table, wherein the means for generating the lookup table further comprises:

means for collecting a plurality of near-field data for a plurality of periodic structures through rigorous simulation, different periodic structures have different feature width and space combinations;

for each combination of feature width and space, means for calculating a set of scaling parameters by performing linear regression based on the plurality of filtered kernels and the near-field data related to a periodic structure corresponding to the combination of feature width and space; and

means for storing the calculated scaling parameters into the lookup table.

14. The data processing system of claim 13, wherein the set of scaling parameters includes scaling factors for transverse electric (TE) polarization and transverse magnetic (TM) polarization.

15. The data processing system of claim 12, wherein the means for updating the plurality of edge-based kernels further comprises:

means for determining edge segments and adjacent feature width and space for each edge segment;

for each edge segment, means for determining a set of scaling parameters corresponding to the feature width and space combination for the edge segment by looking up the lookup table;

for each edge segment, means for updating the plurality of edge-based kernels by applying the set of scaling parameters determined for the edge segment; and

for each edge segment, means for applying the plurality of updated kernels to reflect edge coupling effect.

16. The data processing system of claim 15, wherein the means for determining the adjacent feature width and space for each edge segment comprises means for performing a vertical scan and a horizontal scan using a scanline algorithm.

17. A computer program product stored as program code on a non-transitory computer-readable medium, the program code executable by at least one processor for performing mask topography effect modeling on a mask design layout, the computer program product comprising a computer readable program code comprising instructions for:

applying a thin mask model to the mask design layout to create a thin mask transmission;

applying a thick mask model comprising a plurality of edge-based kernels to the mask design layout;

applying a rasterization filter to the plurality of edge-based kernels to generate a plurality of filtered kernels, wherein the applying of the thick mask model comprises applying the plurality of filtered kernels to edges in the mask design layout to produce a mask three-dimensional (3D) residual; and

combining the thin mask transmission and the mask 3D residual to create a mask 3D transmission, wherein the mask topography effect modeling on the mask design layout is used to create an improved optical mask for creating an integrated circuit.

18. The computer program product of claim 17, wherein the computer readable program code further comprises instructions for receiving a set of scaling parameters for off-axis illumination (OAI) effective masks,

wherein the instructions for applying the thick mask model comprise instructions for updating the plurality of edge-based kernels with the set of scaling parameters.

19. The computer program product of claim 18, wherein the computer readable program code further comprises instructions for generating the thick mask model, wherein the instructions for generating the thick mask model further comprises instructions for:

receiving a mask topography structure;

performing a rigorous simulation to simulate a near-field;

generating a reference mask 3D residual by subtracting a thin mask electric field from the near-field; and

deriving the plurality of edge-based kernels by decomposing the reference mask 3D residual.

20. The computer program product of claim 18, wherein the computer readable program code further comprises instructions for computing the set of scaling parameters for the OAI effective masks.

21. The computer program product of claim 20, wherein the instructions for computing the set of scaling parameters comprises instructions for:

determining a reference critical dimension (CD) of the OAI effective mask;

receiving the set of scaling parameters with initially assigned values;

determining a CD of the OAI effective mask based on a result of the mask rasterization, wherein the mask rasterization is performed by applying the set of scaling parameters to corresponding kernels;

determining whether a difference between the CD and the reference CD is less than a pre-determined CD threshold; and

when the difference is not less than the pre-determined CD threshold, updating the set of scaling parameters.

22. The computer program product of claim 21, wherein the reference CD is determined through rigorous simulation.

23. The computer program product of claim 21, wherein the reference CD is determined through measuring wafer CD.

24. The computer program product of claim 20, wherein the instructions for computing the set of scaling parameters comprises instructions for:

determining a plurality of reference intensity signals for a plurality of sampling points through rigorous simulation;

generating a set of partial electric fields based on the plurality of convolution kernels and a plurality of optics kernels for the plurality of sampling points; and

extracting the set of scaling parameters based on the set of reference intensity signals and the set of partial electric fields by performing a non-linear regression to minimize a function about the set of scaling parameters.

25. The computer program product of claim 24, wherein the plurality of reference intensity signals is determined based on a mask 3D definition and a test pattern definition.