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

• US 20080183446A1
• Filed: 11/08/2007
• Published: 07/31/2008
• Est. Priority Date: 11/08/2006
• Status: Active Grant

• Current Assignee: ASML Netherlands BV (ASML Holding NV)
• Original Assignee: ASML Masktools B.V. (ASML Holding NV)
• Inventors: Hansen, Steve
• Granted Patent: US 8,050,898 B2
• Time in Patent Office: Days
• US Class Current: 703/2
• 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 of generating a model for simulating the imaging performance of an optical imaging system;

said method comprising the steps of;

defining said optical imaging system and a process to be utilized by said optical imaging system;

defining a first model representing the imaging performance of said optical imaging system and said process and calibrating said model, said first model generating values corresponding to a developed image dimension and a latent image slope; and

defining a second model for estimating a line width roughness of a feature to be imaged, said second model utilizing said latent image slope values to estimate said line width roughness.

2. A method of generating a model for simulation the imaging performance of an optical imaging system according to claim 1, wherein said second model is calibrated by comparing experimental imaging data to simulated imaging data generated by said first model, and selecting values for parameters contained in said second model such that said second model generates line width roughness estimates which correspond to the line width roughness data of the experimental data with a predefined error tolerance.

18. A method of generating a model for simulation the imaging performance of an optical imaging system according to claim 1, wherein said latent image slope is determined at the edge of said feature.

3. A method of generating a model for simulation the imaging performance of an optical imaging system according to claim 3, where said second model is defined as:

LWR=a·

(LI_slope)^b+c, where a, b and c correspond to said parameters.

4. A method of simulating the imaging performance of an optical imaging system;

said method comprising the steps of;

defining said optical imaging system and a process to be utilized by said optical imaging system;

defining a first model representing the imaging performance of said optical imaging system and said process and calibrating said model, said first model generating values corresponding to a developed image dimension and a latent image slope; and

defining a second model for estimating a line width roughness of a feature to be imaged, said second model utilizing said latent image slope values to estimate said line width roughness.

5. A method of simulating the imaging performance of an optical imaging system according to claim 4, wherein said second model is calibrated by comparing experimental imaging data to simulated imaging data generated by said first model, and selecting values for parameters contained in said second model such that said second model generates line width roughness estimates which correspond to the line width roughness data of the experimental data with a predefined error tolerance.

6. A method of simulating the imaging performance of an optical imaging system according to claim 5, where said second model is defined as:

LWR=a·

(LI_slope)^b+c, where a, b and c correspond to said parameters.

19. A method of simulating the imaging performance of an optical imaging system according to claim 4, wherein said latent image slope is determined at the edge of said feature.

7. A computer readable medium bearing a computer program for generating a model for simulating the imaging performance of an optical imaging system, the computer program, when executed, causing a computer to perform the steps of:

defining said optical imaging system and a process to be utilized by said optical imaging system;

defining a first model representing the imaging performance of said optical imaging system and said process and calibrating said model, said first model generating values corresponding to a developed image dimension and a latent image slope; and

defining a second model for estimating a line width roughness of a feature to be imaged, said second model utilizing said latent image slope values to estimate said line width roughness.

8. The computer readable medium according to claim 7, wherein said second model is calibrated by comparing experimental imaging data to simulated imaging data generated by said first model, and selecting values for parameters contained in said second model such that said second model generates line width roughness estimates which correspond to the line width roughness data of the experimental data with a predefined error tolerance.

9. The computer readable medium according to claim 8, where said second model is defined as:

LWR=a·

(L_slope)^b+c, where a, b and c correspond to said parameters.

20. The computer readable medium according to claim 7, wherein said latent image slope is determined at the edge of said feature.

10. A method of generating a model for simulating the imaging performance of an optical imaging system;

said method comprising the steps of;

defining said optical imaging system and a process to be utilized by said optical imaging system;

defining a first model representing the imaging performance of said optical imaging system and said process and calibrating said model, said first model generating values corresponding to a developed image dimension and a latent image slope; and

defining a second model for estimating a pattern failure regarding a feature to be imaged, said second model utilizing said latent image slope values to define parameters which estimate when pattern failure of a given feature will occur.

11. A method of generating a model for simulation the imaging performance of an optical imaging system according to claim 10, wherein said second model is calibrated by comparing experimental imaging data to simulated imaging data generated by said first model, and selecting values for parameters contained in said second model such that said parameters indicate whether pattern failure will occur for a given feature based on the parameter values associated with said given feature.

12. A method of generating a model for simulation the imaging performance of an optical imaging system according to claim 11, where said parameters include:

CD_min, LI_{slope min}, and C_ct,

wherein CD_min is the minimum allowable critical dimension for the given process, LI_slopemin is the minimum allowable contrast for the given process; and

Cct is a cross-term for indicating a failure condition when both CD_min, LI_{slope min} are above but approximate the minimum acceptable values.

13. A method of generating a model for simulation the imaging performance of an optical imaging system according to claim 12, wherein said parameters further include:

Space_min and LI_{slope min2},

where Space_min corresponds to the minimal space requirement between features, and LI_{slope min2} corresponds to the latent image value associated with the minimal space requirements between features.

21. A method of generating a model for simulation the imaging performance of an optical imaging system according to claim 10, wherein said latent image slope is determined at the edge of said feature.

14. A method of simulating the imaging performance of an optical imaging system;

said method comprising the steps of;

defining said optical imaging system and a process to be utilized by said optical imaging system;

defining a first model representing the imaging performance of said optical imaging system and said process and calibrating said model, said first model generating values corresponding to a developed image dimension and a latent image slope; and

defining a second model for estimating a pattern failure regarding a feature to be imaged, said second model utilizing said latent image slope values to define parameters which estimate when pattern failure of a given feature will occur.

15. A method of simulating the imaging performance of an optical imaging system according to claim 14, wherein said second model is calibrated by comparing experimental imaging data to simulated imaging data generated by said first model, and selecting values for parameters contained in said second model such that said parameters indicate whether pattern failure will occur for a given feature based on the parameter values associated with said given feature.

16. A method of simulating the imaging performance of an optical imaging system according to claim 15, where said parameters include:

CD_min, LI_{slope min}, and C_ct,

wherein CD_min is the minimum allowable critical dimension for the given process, LI_slopemin is the minimum allowable contrast for the given process; and

C_ct is a cross-term for indicating a failure condition when both CD_min, LI_{slope min} are above but approximate the minimum acceptable values.

17. A method of simulating the imaging performance of an optical imaging system according to claim 16, wherein said parameters further include:

Space_min and LI_{slope min2},

where Space_min corresponds to the minimal space requirement between features, and LI_{slope min2} corresponds to the latent image value associated with the minimal space requirements between features.

22. A method of simulating the imaging performance of an optical imaging system according to claim 14, wherein said latent image slope is determined at the edge of said feature.