Method, program product and apparatus for predicting line width roughness and resist pattern failure and the use thereof in a lithography simulation process

• US 10,386,730 B2
• Filed: 09/23/2011
• Issued: 08/20/2019
• Est. Priority Date: 11/08/2006
• Status: Active Grant

• Current Assignee: ASML Netherlands BV (ASML Holding NV)
• Original Assignee: ASML Netherlands BV (ASML Holding NV)
• Inventors: Hansen, Steve
• Primary Examiner(s): Jones, Hugh M
• Application Number:
  US13/244,191
• Publication Number:
  US 20120109607A1
• Time in Patent Office: 2,888 Days
• Field of Search: 703 6
• 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 7/70625 Dimensions, e.g. line width, critical dimension [CD], profile, sidewall angle or edge roughness
• CPC Class Codes: G03F 7/70675 Latent image, i.e. measuring the image of the exposed resist prior to development

Abstract

A method of generating a model for simulating the imaging performance of an optical imaging system. The method includes the steps of defining the optical imaging system and a process to be utilized by the optical imaging system; defining a first model representing the imaging performance of the optical imaging system and the process, and calibrating the model, where the first model generates values corresponding to a latent image slope. The method further includes the step of defining a second model for estimating a line width roughness of a feature to be imaged, where the second model utilizes the latent image slope values to estimate the line width roughness.

Claims

1. A method comprising:

obtaining a first model representing an imaging performance of a physical optical imaging system configured to produce a pattern in or on a radiation-sensitive substrate and a physical manufacturing process utilizing the optical imaging system to produce the pattern in or on the substrate;

simulating, by a hardware computer system, at least the imaging performance using the first model, the simulating generating values corresponding to a latent image slope;

defining a second model for estimating a pattern failure value that is other than or in addition to a line roughness value, regarding a feature to be imaged, the defining the second model utilizing the values corresponding to the latent image slope generated by the first model to define parameters which estimate occurrence of pattern failure of a given feature imaged using the process, the first model and/or second model defined based on measurement results of the optical imaging system or on measurement results of an output from the process; and

configuring the process and/or optical imaging system based on data generated using an estimated pattern failure determined using the second model and/or communicating data generated based on an estimated pattern failure determined using the second model to a physical apparatus in order to create or modify a physical configuration of the optical imaging system and/or the process.

2. The method of claim 1, wherein the second model is defined by comparing measured imaging data to simulated imaging data generated by the first model, and selecting values for parameters contained in the second model such that the parameters indicate, when evaluated, whether pattern failure will occur for the given feature based on parameter values associated with the given feature.

3. The method of claim 2, wherein the parameters of the second model include a parameter corresponding to a minimum allowable critical dimension for the given process, a parameter corresponding to a minimum allowable contrast for the given process, and a cross-term for indicating a failure condition when both the critical dimension and the contrast are above but approximate the minimum allowable values.

4. The method of claim 3, wherein the parameters of the second model further include a parameter corresponding to a minimal space requirement between features, and a parameter corresponding to a latent image slope value associated with the minimal space requirement between features.

5. The method of claim 1, wherein the latent image slope is determined at the edge of the feature.

6. A method comprising:

obtaining a first model representing an imaging performance of a physical optical imaging system configured to produce a pattern in or on a radiation-sensitive substrate and a physical manufacturing process utilizing the optical imaging system to produce the pattern in or on the substrate;

simulating, by a hardware computer system, at least the imaging performance using the first model, the simulating generating values corresponding to a latent image parameter;

defining a second model for predicting a pattern failure value that is other than or in addition to a line roughness value, regarding a feature to be imaged, the defining the second model utilizing the values corresponding to the latent image parameter generated by the first model to define parameters which predict pattern failure of a given feature imaged using the process, the first model and/or second model defined based on measurement results of the optical imaging system or on measurement results of an output from the process; and

configuring the process and/or optical imaging system based on a predicted pattern failure determined using the second model and/or communicating data generated based on a predicted pattern failure determined using the second model to a physical apparatus in order to create or modify a physical configuration of the optical imaging system and/or the process.

7. The method of claim 6, wherein the second model is defined by comparing measured imaging data to simulated imaging data generated by the first model, and selecting values for parameters contained in the second model such that the parameters indicate, when evaluated, whether pattern failure is predicted to occur for the given feature based on parameter values associated with the given feature.

8. The method of claim 7, wherein the parameters of the second model include a parameter corresponding to a minimum allowable critical dimension for the given process, a parameter corresponding to a minimum allowable contrast for the given process, and a cross-term for indicating a failure condition when both the critical dimension and the contrast are above but approximate the minimum allowable values.

9. The method of claim 8, wherein the parameters of the second model further include a parameter corresponding to a minimal space requirement between features, and a parameter corresponding to a latent image parameter value associated with the minimal space requirement between features.

10. The method of claim 6, wherein the latent image parameter is determined at the edge of the feature.

11. The method of claim 6, further comprising defining a line width roughness model by selecting values for parameters in the line width roughness model such that the line width roughness model generates line width roughness estimates from the simulated latent image parameter values, which correspond to measured line width roughness data within a predefined error tolerance.

12. A non-transitory computer readable storage medium having instructions stored thereon which, when executed by a hardware computer system, cause the hardware computer system to at least:

obtain a first model representing an imaging performance of a physical optical imaging system configured to produce a pattern in or on a radiation-sensitive substrate and a physical manufacturing process utilizing the optical imaging system to produce the pattern in or on the substrate;

simulate at least the imaging performance using the first model, the simulation generating values corresponding to a latent image parameter;

define a second model for predicting a pattern failure value that is other than or in addition to a line roughness value, regarding a feature to be imaged, definition of the second model utilizing the values corresponding to the latent image parameter generated by the first model to define parameters which predict pattern failure of a given feature imaged using the process, the first model and/or second model defined based on measurement results of the optical imaging system or on measurement results of an output from the process; and

configure the process and/or optical imaging system based on data generated using a predicted pattern failure determined using the second model and/or communicate data generated based on a predicted pattern failure determined using the second model to a physical apparatus in order to create or modify a physical configuration of the optical imaging system and/or the process.

13. The non-transitory computer readable storage medium of claim 12, wherein the second model is defined by comparing experimental imaging data to simulated imaging data generated by the first model, and the instructions are further configured to cause the hardware computer system to implement selection of values for parameters contained in the second model such that the parameters indicate, when evaluated, whether pattern failure is predicted to occur for the given feature based on parameter values associated with the given feature.

14. The non-transitory computer readable storage medium of claim 12, wherein the parameters of the second model include a parameter corresponding to a minimum allowable critical dimension for the given process, a parameter corresponding to a minimum allowable contrast for the given process, and a cross-term for indicating a failure condition when both the critical dimension and the contrast are above but approximate the minimum allowable values.

15. The non-transitory computer readable storage medium of claim 14, wherein the parameters of the second model further include a parameter corresponding to a minimal space requirement between features, and a parameter corresponding to a latent image parameter value associated with the minimal space requirement between features.

16. The non-transitory computer readable storage medium of claim 12, wherein the latent image parameter is determined at the edge of the feature.

17. The non-transitory computer readable storage medium of claim 12, wherein the instructions are further configured to cause the hardware computer system to implement definition of a line width roughness model by selecting values for parameters in the line width roughness model such that the line width roughness model generates line width roughness estimates from the simulated latent image parameter values, which correspond to measured line width roughness data within a predefined error tolerance.

18. A method comprising:

obtaining a model for estimating a pattern failure regarding a feature to be imaged by a physical optical imaging system configured to produce a pattern in or on a radiation-sensitive substrate as part of a physical manufacturing process utilizing the optical imaging system to produce the pattern in or on the substrate, the model comprising parameters to estimate occurrence of pattern failure of a given feature imaged using the process, the parameters of the model including a parameter representing a minimum allowable critical dimension for the given process and a parameter representing a minimum allowable contrast for the given process;

determining, by a hardware computer system, an estimate of a pattern failure of the optical imaging system and/or the process using the model; and

configuring the process and/or optical imaging system based on data generated using the estimate of the pattern failure and/or communicating data generated based on the estimate of the pattern failure to a physical apparatus in order to create or modify a physical configuration of the optical imaging system and/or the process.

19. The method of claim 18, wherein the parameters of the model further comprise a cross-term for indicating a failure condition when both the critical dimension and the contrast are above but approximate the minimum allowable values.

20. The method of claim 19, wherein the parameters of the model further include a parameter corresponding to a minimal space requirement between features and a parameter correspond to a latent image parameter value associated with the minimal space requirement between features.

21. A non-transitory computer readable storage medium having instructions stored thereon which, when executed by a hardware computer system, cause the hardware computer system to at least:

obtain a model for estimating a pattern failure regarding a feature to be imaged by a physical optical imaging system configured to produce a pattern in or on a radiation-sensitive substrate as part of a physical manufacturing process utilizing the optical imaging system to produce the pattern in or on the substrate, the model comprising parameters to estimate occurrence of pattern failure of a given feature imaged using the process, the parameters of the model including a parameter representing a minimum allowable critical dimension for the given process and a parameter representing a minimum allowable contrast for the given process;

determine an estimate of a pattern failure of the optical imaging system and/or the process using the model; and

configure the process and/or optical imaging system based on data generated using the estimate of the pattern failure and/or communicate data generated based on the estimate of the pattern failure to a physical apparatus in order to create or modify a physical configuration of the optical imaging system and/or the process.

22. The non-transitory computer readable storage medium of claim 21, wherein the parameters of the model further comprise a cross-term for indicating a failure condition when both the critical dimension and the contrast are above but approximate the minimum allowable values.

23. The non-transitory computer readable storage medium of claim 22, wherein the parameters of the model further include a parameter corresponding to a minimal space requirement between features and a parameter correspond to a latent image parameter value associated with the minimal space requirement between features.