MODEL BUILDING AND ANALYSIS ENGINE FOR COMBINED X-RAY AND OPTICAL METROLOGY

• US 20140019097A1
• Filed: 07/03/2013
• Published: 01/16/2014
• Est. Priority Date: 07/10/2012
• Status: Active Grant

• Current Assignee: KLA-Tencor Corporation (KLA Corporation)
• Original Assignee: KLA-Tencor Corporation (KLA Corporation)
• Inventors: Bakeman, Michael S., Shchegrov, Andrei V., Zhao, Qiang, Tan, Zhengquan
• Granted Patent: US 10,013,518 B2
• Time in Patent Office: Days
• US Class Current: 703/1
• CPC Class Codes: G03F 1/70 Adapting basic layout or design of masks to lithographic process requirements, e.g., second iteration correction of mask patterns for imaging
• CPC Class Codes: G03F 7/70608 Monitoring the unpatterned workpiece, e.g. measuring thickness, reflectivity or effects of immersion liquid on resist
• CPC Class Codes: G03F 7/70625 Dimensions, e.g. line width, critical dimension [CD], profile, sidewall angle or edge roughness
• CPC Class Codes: G06F 30/39 Circuit design at the physical level physical level design for reconfigurable circuits G06F30/347

Abstract

Structural parameters of a specimen are determined by fitting models of the response of the specimen to measurements collected by different measurement techniques in a combined analysis. Models of the response of the specimen to at least two different measurement technologies share at least one common geometric parameter. In some embodiments, a model building and analysis engine performs x-ray and optical analyses wherein at least one common parameter is coupled during the analysis. The fitting of the response models to measured data can be done sequentially, in parallel, or by a combination of sequential and parallel analyses. In a further aspect, the structure of the response models is altered based on the quality of the fit between the models and the corresponding measurement data. For example, a geometric model of the specimen is restructured based on the fit between the response models and corresponding measurement data.

Claims

1. A model building and analysis engine comprising:

a geometric model building module configured to generate a geometric model of a structure of a specimen;

an optical response function building module configured to generate an optical response model of a response of the structure of the specimen to incident optical radiation based at least in part on the geometric model;

an x-ray response function building module configured to generate an x-ray response model of a response of the structure of the specimen to incident x-ray radiation based at least in part on the geometric model, wherein both the optical response model and the x-ray response model include at least one common geometric parameter from the geometric model; and

a fitting analysis module configured to;

receive a first amount of measurement data indicative of an amount of optical radiation detected from the specimen in response to an optical illumination beam incident on the specimen;

receive a second amount of measurement data indicative of an amount of x-ray radiation detected from the specimen in response to an x-ray illumination beam incident on the specimen;

determine at least one specimen parameter value based on a fitting of the optical response model with the first amount of measurement data and a fitting of the x-ray response model to the second amount of measurement data; and

output the at least one specimen parameter value for storage in a memory.

2. The model building and analysis engine of claim 1, wherein a value of the at least one common geometric parameter is determined based on the fitting of the x-ray response model to the second amount of measurement data and the determined value is treated as a constant in the fitting of the optical response model with the first amount of measurement data to determine the at least one specimen parameter value.

3. The model building and analysis engine of claim 1, wherein the at least one common geometric parameter is treated as a global parameter in a parallel fitting analysis including both the fitting of the optical response model with the first amount of measurement data and the fitting of the x-ray response model to the second amount of measurement data.

4. The model building and analysis engine of claim 2, wherein the fitting of the optical response model with the first amount of measurement data involves minimizing a cost function.

5. The model building and analysis engine of claim 3, wherein the parallel fitting analysis involves minimizing a combined cost function.

6. The model building and analysis engine of claim 1, wherein the fitting analysis module is further configured to:

determine a residual value of a cost function associated with the fitting of the first amount of measurement data with the optical response model and the fitting of the second amount of measurement data with the x-ray response model;

determine if the residual value exceeds a predetermined threshold value;

restructure the geometric model of the structure of the specimen if the residual value exceeds the predetermined threshold value; and

store the geometric model of the structure of the specimen if the residual value does not exceed the predetermined threshold value.

7. The model building and analysis engine of claim 1, wherein the optical response model and the x-ray response model share all of the geometric parameters of the geometric model.

8. The model building and analysis engine of claim 1, wherein the at least one common geometric parameter is any of a line edge roughness, line width roughness, pore size, pore density, side wall angle, profile, film thickness, critical dimension, and pitch.

9. The model building and analysis engine of claim 1, wherein the model building and analysis engine is a computing system of a combined x-ray/optical metrology tool.

10. The model building and analysis engine of claim 9, wherein the combined x-ray/optical metrology tool comprises:

a liquid metal based x-ray illumination system including a liquid metal x-ray illumination source and x-ray illumination optics configured to shape and direct an incident x-ray beam to an inspection area of a specimen;

an x-ray detector configured to detect the amount of x-ray radiation from the specimen in response to the incident x-ray beam;

an optical illumination system including an optical illumination source and optical illumination optics configured to shape and direct an incident optical illumination beam to the inspection area of the specimen simultaneous with the incident x-ray beam, wherein the incident optical illumination beam and the incident x-ray beam spatially overlap at the inspection area of the specimen; and

an optical detector configured to detect the amount of optical radiation from the specimen in response to the incident optical illumination beam.

11. A method comprising:

generating a geometric model of a structure of a specimen;

generating an optical response model and an x-ray response model based at least in part on the geometric model, wherein both the optical response model and the x-ray response model include at least one common geometric parameter from the geometric model;

receiving a first amount of measurement data based on an amount of optical radiation detected from the specimen in response to an optical illumination beam incident on the specimen;

receiving a second amount of measurement data based on an amount of x-ray radiation detected from the specimen in response to an x-ray illumination beam incident on the specimen;

determining at least one specimen parameter value based on a fitting analysis of the first amount of measurement data with the optical response model and a fitting analysis of the second amount of measurement data with the x-ray response model; and

storing the at least one specimen parameter value.

12. The method of claim 11, further comprising:

determining a value of the at least one common geometric parameter based on the fitting analysis of the second amount of measurement data, and wherein the determined value of the at least one common geometric parameter is treated as a constant in the fitting analysis of the first amount of measurement data.

13. The method of claim 11, further comprising:

determining a value of the at least one common geometric parameter based on a parallel fitting analysis of the first amount of measurement data with the optical response model and the second amount of measurement data with the x-ray response model.

14. The method of claim 11, further comprising:

determining a residual value of a cost function associated with the fitting analysis of the first amount of measurement data with the optical response model and the fitting analysis of the second amount of measurement data with the x-ray response model;

determining if the residual value exceeds a predetermined threshold value;

restructuring the geometric model of the structure of the specimen if the residual value exceeds the predetermined threshold value; and

storing the geometric model of the structure of the specimen if the residual value does not exceed the predetermined threshold value.

15. The method of claim 11, wherein the at least one common geometric parameter is any of a line edge roughness, line width roughness, pore size, pore density, side wall angle, profile, film thickness, critical dimension, and pitch.

16. The method of claim 13, wherein the parallel fitting analysis involves minimizing a combined cost function.

17. A non-transitory, computer-readable medium, comprising:

code for causing a computer to generate a geometric model of a structure of a specimen;

code for causing the computer to generate an optical response model and an x-ray response model based at least in part on the geometric model, wherein both the optical response model and the x-ray response model include at least one common geometric parameter from the geometric model;

code for causing the computer to receive a first amount of measurement data based on an amount of optical radiation detected from the specimen in response to an optical illumination beam incident on the specimen;

code for causing the computer to receive a second amount of measurement data based on an amount of x-ray radiation detected from the specimen in response to an x-ray illumination beam incident on the specimen;

code for causing the computer to determine at least one specimen parameter value based on a fitting analysis of the first amount of measurement data with the optical response model and a fitting analysis of the second amount of measurement data with the x-ray response model; and

code for causing the computer to store the at least one specimen parameter value.

18. The non-transitory, computer-readable medium of claim 17, further comprising:

code for causing the computer to determine a value of the at least one common geometric parameter based on the fitting analysis of the second amount of measurement data, and wherein the determined value of the at least one common geometric parameter is treated as a constant in the fitting analysis of the first amount of measurement data.

19. The non-transitory, computer-readable medium of claim 17, further comprising:

code for causing the computer to determine a value of the at least one common geometric parameter based on a parallel fitting analysis of the first amount of measurement data with the optical response model and the second amount of measurement data with the x-ray response model.

20. The non-transitory, computer-readable medium of claim 17, further comprising:

code for causing the computer to determine a residual value of a cost function associated with the fitting analysis of the first amount of measurement data with the optical response model and the fitting analysis of the second amount of measurement data with the x-ray response model;

code for causing the computer to determine if the residual value exceeds a predetermined threshold value;

code for causing the computer to restructure the geometric model of the structure of the specimen if the residual value exceeds the predetermined threshold value; and

code for causing the computer to store the geometric model of the structure of the specimen if the residual value does not exceed the predetermined threshold value.