IP Library › Granted Patent US 11,556,052
Granted Patent B2
US 11,556,052 · App. 17/089,190 · Granted Jan 17, 2023

Using mask fabrication models in correction of lithographic masks

Inventors: Lawrence S. Melvin, III (Hillsboro, OR); Kevin J. Hooker (Austin, TX)
Assignee: Synopsys, Inc.
G03F1/20G03F1/36G03F7/705G03F7/70441G03F7/70625H01L21/0337
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Quick Facts
Patent No.
US 11,556,052
App. No.
17/089,190
Granted
Jan 17, 2023
Kind
B2
Abstract

A lithography process is described by a design for a lithographic mask and a description of the lithography configuration, which may include the lithography source, collection/illumination optics, projection optics, resist, and/or subsequent fabrication steps. The actual lithography process uses a lithographic mask fabricated from the mask design, which may be different than the nominal mask design. A mask fabrication model models the process for fabricating the lithographic mask from the mask design. Typically, this is an electron-beam (e-beam) process, which includes e-beam exposure of resist on a mask blank, processing of the exposed resist to form patterned resist, and etching of the mask blank with the patterned resist. The mask fabrication model, usually in conjunction with other process models, is used to estimate a result of the lithography process. Mask correction is then applied to the mask design based on the simulation result.

Claims (35)

1. A method comprising:

accessing a lithographic mask design for use with a mask fabrication process and a lithography process, wherein the mask fabrication process fabricates a lithographic mask from the lithographic mask design, and the lithography process uses the fabricated lithographic mask to fabricate structures on a wafer;

estimating by a processor a result of the lithography process; wherein the result comprises at least one or more of an aerial image, a printed wafer pattern, and a metric for one or more of the aerial image and the printed wafer pattern; and

estimating the result comprises:

using a mask fabrication model for the mask fabrication process to estimate a printed mask pattern for the lithographic mask fabricated from the lithographic mask design; and

estimating the result of the lithography process using the printed mask pattern that was estimated using the mask fabrication model as input to one or more additional process models of the lithography process; and

applying a mask correction to the lithographic mask design based on the estimated result.

2. The method of claim 1 wherein the lithographic mask is fabricated using an electron-beam process; and the mask fabrication model accounts for electron-beam exposure of resist on a mask blank, processing of the exposed resist to form patterned resist, and etching of the mask blank with the patterned resist.

3. The method of claim 1 wherein the lithographic mask is fabricated using an electron-beam process; and the mask fabrication model accounts for at least one of back scattered electrons, long range etch effects, etch bias, and micro loading in the process for fabricating the lithographic mask.

4. The method of claim 1 wherein the lithographic mask design consists of rectilinear shapes and the printed mask pattern comprises curved shapes.

5. The method of claim 1 wherein the mask fabrication model is based on regression against empirical data, and at least one of the additional process models is based on a separate regression against different empirical data.

6. The method of claim 1 wherein the mask fabrication model is applied at one scale to estimate the printed mask pattern, and the estimated printed mask pattern is demagnified to a smaller scale for use as input to the one or more additional process models.

7. The method of claim 1 wherein the method is repeated for multiple iterations, and the mask fabrication model is applied at every iteration.

8. The method of claim 1 wherein the mask fabrication model is based on Gaussian kernels.

9. The method of claim 1 wherein estimating the result of the lithography process is further based on a mask error correction of the lithographic mask design arising from the mask fabrication.

10. The method of claim 1 wherein the mask correction comprises at least one of optical proximity correction, sub-resolution assist features, phase shifting masks, and inverse lithography techniques.

11. A system comprising:

a memory storing instructions and a lithographic mask design for use with a mask fabrication process and a lithography process, wherein the mask fabrication process fabricates a lithographic mask from the lithographic mask design, and the lithography process uses the fabricated lithographic mask to fabricate structures on a wafer; and

a processor, coupled with the memory and to execute the instructions, the instructions when executed cause the processor to:

estimate a result of the lithography process; wherein the result comprises at least one or more of an aerial image, a printed wafer pattern, and a metric for one or more of the aerial image and the printed wafer pattern; and estimating the result comprises:

using a mask fabrication model for the mask fabrication process to estimate a printed mask pattern for the lithographic mask fabricated from the lithographic mask design; and

estimating the result of the lithography process using the printed mask pattern that was estimated using the mask fabrication model as input to the one or more additional process models of the lithography process; and

apply a mask correction to the lithographic mask design based on the estimated result.

12. The system of claim 11 wherein the lithography process operates at an extreme ultraviolet (EUV) wavelength range and at a technology node with feature sizes of approximately 20 nm or smaller.

13. The system of claim 11 wherein the lithographic mask design is for an entire integrated circuit die.

14. The system of claim 11 wherein the mask fabrication model is based on regression against empirical data, and at least one of the additional process models is based on a separate regression against different empirical data.

15. The system of claim 11 wherein the mask correction comprises at least one of optical proximity correction, sub-resolution assist features, phase shifting masks, and inverse lithography techniques.

16. A non-transitory computer readable medium comprising stored instructions, which when executed by a processor, cause the processor to:

access a lithographic mask design for use with a mask fabrication process and a lithography process, wherein the mask fabrication process fabricates a lithographic mask from the lithographic mask design, and the lithography process uses the fabricated lithographic mask to fabricate structures on a wafer;

estimate a result of the lithography process; wherein the result comprises at least one or more of an aerial image, a printed wafer pattern, and a metric for one or more of the aerial image and the printed wafer pattern; and estimating the result comprises:

using a mask fabrication model for the mask fabrication process to estimate a printed mask pattern for the lithographic mask fabricated from the lithographic mask design; and

estimating the result of the lithography process using the printed mask pattern that was estimated using the mask fabrication model as input to one or more additional process models; and

apply a mask correction to the lithographic mask design based on the estimated result.

17. The non-transitory computer readable medium of claim 16 wherein the mask fabrication model is applied at one scale to estimate the printed mask pattern, and the estimated printed mask pattern is demagnified to a smaller scale for use as input to the one or more additional process models.

18. The non-transitory computer readable medium of claim 16 wherein the mask fabrication model is based on Gaussian kernels.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 4, 2020
From: MELVIN, LAWRENCE S, III; HOOKER, KEVIN J.
To: SYNOPSYS, INC.
Reel/Frame 054274/0203 →
Continuity (3)
Continuation PCTUS2020058609 · Nov 2, 2020
Provisional Application 62930134 · Nov 4, 2019
Related Publication 20210132486A1 · May 6, 2021
Cited By (1)
US 12,541,154