SMART SELECTION AND/OR WEIGHTING OF PARAMETERS FOR LITHOGRAPHIC PROCESS SIMULATION

• US 20110113390A1
• Filed: 11/09/2009
• Published: 05/12/2011
• Est. Priority Date: 07/07/2008
• Status: Active Grant

• Current Assignee: Fel Du, Henying Feng, Martin Snajdr, Wenjin Shao, Yu Cao
• Original Assignee: ASML Netherlands BV (ASML Holding NV)
• Inventors: Snajdr, Martin, CAO, Yu, Du, Fel, Shao, Wenjin, Feng, Henying
• Granted Patent: US 10,025,198 B2
• Time in Patent Office: Days
• US Class Current: 716/55
• CPC Class Codes: G03F 7/705 Modelling or simulating from physical phenomena up to complete wafer processes or whole workflow in wafer productions
• CPC Class Codes: G03F 7/70666 Aerial image, i.e. measuring the image of the patterned exposure light at the image plane of the projection system

Abstract

The present invention generally relates to simulating a lithographic process, and more particularly to methods for smart selection and smart weighting when selecting parameters and/or kernels used in aerial image computation. According to one aspect, advantages in simulation throughput and/or accuracy can be achieved by selecting TCC kernels more intelligently, allowing highly accurate aerial images to be simulated using a relatively fewer number of TCC kernels than in the state of the art. In other words, the present invention allows for aerial images to be simulated with the same or better accuracy using much less simulation throughput than required in the prior art, all else being equal.

Claims

1. A method comprising:

identifying a model for simulating a lithographic process, the model being expressed as a mathematical series with a plurality of terms, which when combined with a mathematical representation a mask, generates a result that simulates performance of the lithographic process using the mask;

identifying characteristics of a desired mask layout;

selecting a subset of the plurality terms of the model based on the identified characteristics the desired mask layout; and

using the model with only the selected subset of the plurality of terms to simulate the performance of the lithographic process.

2. A method according to claim 1, wherein the selecting step includes:

preparing a smart mask that comprises a mathematical representation of the desired mask layout based on the identified characteristics;

for each of the plurality of terms, calculating an aerial image intensity contribution of the each term in response to the smart mask; and

selecting the subset of the plurality of terms based on the respective calculated aerial intensity contributions.

3. A method according to claim 1, wherein the selecting step includes:

preparing a smart mask that comprises a mathematical representation of the desired mask layout based on the identified characteristics;

forming a new set of terms corresponding to the plurality of terms, wherein the new set of terms are weighted by the smart mask; and

selecting the subset of the plurality of terms based on the corresponding new terms.

4. A method according to claim 1, wherein the selecting step includes:

preparing a smart mask that comprises a mathematical representation of the desired mask layout based on the identified characteristics;

for each of the plurality of terms, calculating a value using the smart mask; and

ranking the plurality of terms based on the calculated value.

5. A method according to claim 1, wherein each of the plurality of terms have an associated magnitude, the method further comprising selecting a second subset of the plurality of terms based on the associated magnitudes, and using the selected second subset in addition to the selected subset to simulate the performance of the lithographic process.

6. A method according to claim 1, wherein the plurality of terms represent a perturbation between the lithographic process and a different lithographic processes.

7. A method according to claim 1, wherein the model expression is formed according to Hopkins theory.

8. A method according to claim 1, wherein the plurality of terms comprise Transmission Cross Coefficients (TCCs).

9. A computer program product comprising a computer-readable medium having instructions recorded therein, which when executed by a computer, cause the computer to perform a method comprising:

identifying a model for simulating a lithographic process, the model being expressed as a mathematical series with a plurality of terms, which when combined with a mathematical representation a mask, generates a result that simulates performance of the lithographic process using the mask;

identifying characteristics of a desired mask layout;

selecting a subset of the plurality terms of the model based on the identified characteristics the desired mask layout; and

using the model with only the selected subset of the plurality of terms to simulate the performance of the lithographic process.

10. A computer program product according to claim 9, wherein the selecting step includes:

preparing a smart mask that comprises a mathematical representation of the desired mask layout based on the identified characteristics;

for each of the plurality of terms, calculating an aerial image intensity contribution of the each term in response to the smart mask; and

selecting the subset of the plurality of terms based on the respective calculated aerial intensity contributions.

11. A computer program product according to claim 9, wherein the selecting step includes:

preparing a smart mask that comprises a mathematical representation of the desired mask layout based on the identified characteristics;

forming a new set of terms corresponding to the plurality of terms, wherein the new set of terms are weighted by the smart mask; and

selecting the subset of the plurality of terms based on the corresponding new terms.

12. A computer program product according to claim 9, wherein the selecting step includes:

preparing a smart mask that comprises a mathematical representation of the desired mask layout based on the identified characteristics;

for each of the plurality of terms, calculating a value using the smart mask; and

ranking the plurality of terms based on the calculated value.

13. A computer program product according to claim 9, wherein each of the plurality of terms have an associated magnitude, the method further comprising selecting a second subset of the plurality of terms based on the associated magnitudes, and using the selected second subset in addition to the selected subset to simulate the performance of the lithographic process.

14. A computer program product according to claim 9, wherein the plurality of terms represent a perturbation between two different lithographic processes.

15. A computer program product according to claim 9, wherein the model expression is formed according to Hopkins theory.

16. A computer program product according to claim 9, wherein the plurality of terms comprise Transmission Cross Coefficients (TCCs).