AUTOMATIC SELECTION OF SAMPLE VALUES FOR OPTICAL METROLOGY

• US 20150142395A1
• Filed: 11/15/2014
• Published: 05/21/2015
• Est. Priority Date: 11/15/2013
• Status: Active Grant

• Current Assignee: KLA-Tencor Corporation (KLA Corporation)
• Original Assignee: Inkyo Kim
• Inventors: Cao, Meng, Poslavsky, Leonid, Lee, Lie-Quan, Kim, Inkyo
• Granted Patent: US 10,895,810 B2
• Time in Patent Office: Days
• US Class Current: 703/1
• CPC Class Codes: G01B 11/02 for measuring length, width or thickness G01B11/08 takes precedence
• CPC Class Codes: G01B 11/0625 with measurement of absorption or reflection
• CPC Class Codes: G01B 11/0641 with measurement of polarization
• CPC Class Codes: G01B 11/24 for measuring contours or curvatures
• CPC Class Codes: G01B 2210/56 Measuring geometric parameters of semiconductor structures, e.g. profile, critical dimensions or trench depth
• CPC Class Codes: G01N 2021/213 Spectrometric ellipsometry
• CPC Class Codes: G01N 21/211 Ellipsometry optical thickness measurement G01B11/06
• CPC Class Codes: G03F 7/70625 Dimensions, e.g. line width, critical dimension [CD], profile, sidewall angle or edge roughness

Abstract

Embodiments include automatic selection of sample values for optical metrology. An embodiment of a method includes providing a library parameter space for modeling of a diffracting structure using an optical metrology system; automatically determining by a processing unit a reduced sampling set from the library parameter space, wherein the reduced space is based on one or both of the following recommending a sampling shape based on an expected sample space usage, or recommending a sampling filter based on correlation between two or more parameters of the library parameter space; and generating a library for the optical metrology system using the reduced sampling set.

Claims

1. A method comprising:

providing a library parameter space for modeling of a diffracting structure using an optical metrology system;

automatically determining by a processing unit a reduced sampling set from the library parameter space, wherein the reduced space is based on one or both of the following;

recommending a sampling shape based on an expected sample space usage, or

recommending a sampling filter based on correlation between two or more parameters of the library parameter space; and

generating a library for the optical metrology system using the reduced sampling set.

2. The method of claim 1, further comprising determining a physical characteristic of the diffracting structure with the library.

3. The method of claim 1, wherein recommending a sampling shape includes evaluation of a plurality of possible sampling shapes to determine a best fit for the expected sample space use.

4. The method of claim 1, wherein the expected sample space use is based at least in part upon prior knowledge of a customer'"'"'s region of interest.

5. The method of claim 1, wherein recommending a sampling filter includes identifying correlations between parameters and comparing such correlations.

6. The method of claim 5, wherein recommending a sampling filter further includes processing the correlated parameters using one or more algorithms.

7. The method of claim 6, wherein the sampling filter includes a region defined by a certain slope and a certain width.

8. The method of claim 7, wherein the one or more algorithms include a least squares fitting to determine the slope of the region of the sample filter.

9. The method of claim 6, wherein the processing of the correlated parameters is based at least in part on prior knowledge of parameter correlation.

10. The method of claim 1, wherein the optical metrology system includes one or more of a spectroscopic or angle-resolved ellipsometer or spectroscopic or angle-resolved reflectometer.

11. An optical metrology system comprising:

a memory storage for storage of an optical metrology library for the system; and

a processing unit to generate the library, the processing unit to;

provide a library parameter space for modeling of a diffracting structure using the system,

automatically determine by a processing unit a reduced sampling set from the library parameter space, wherein the reduced space is based on one or both of the following;

a recommendation of a sampling shape based on an expected sample space usage, or

a recommendation of a sampling filter based on correlation between two or more parameters of the library parameter space, and

generate a library for the optical metrology system using the reduced sampling set.

12. The system of claim 11, wherein the system includes one or more of a spectroscopic or angle-resolved ellipsometer or spectroscopic or angle-resolved reflectometer.

13. The system of claim 11, wherein the system is further to determine a physical characteristic of the diffracting structure with the library.

14. The system of claim 11, wherein the memory storage further includes a plurality of possible sampling shapes;

and

wherein the recommendation of a sampling shape includes an evaluation of the plurality of possible sampling shapes to determine a best fit for the expected sample space use.

15. The system of claim 11, wherein the expected sample space use is based at least in part upon prior knowledge of a customer'"'"'s region of interest.

16. The system of claim 11, wherein the recommendation of a sampling filter includes the processing unit identifying correlations between parameters and comparing such correlations.

17. The system of claim 16, wherein the recommendation of a sampling filter further includes the processing unit processing the correlated parameters using one or more algorithms.

18. The system of claim 17, wherein the sampling filter includes a region defined by a certain slope and a certain width.

19. The system of claim 18, wherein the one or more algorithms include a least squares fitting to determine the slope of the region of the sample filter.

20. The system of claim 17, wherein the processing of the correlated parameters is based at least in part on prior knowledge of parameter correlation.

21. A non-transitory computer-readable storage medium having stored thereon data representing sequences of instructions that, when executed by a processor, cause the processor to perform operations comprising:

providing a library parameter space for modeling of a diffracting structure using an optical metrology system;

automatically determining by a processing unit a reduced sampling set from the library parameter space, wherein the reduced space is based on one or both of the following;

recommending a sampling shape based on an expected sample space usage, or

recommending a sampling filter based on correlation between two or more parameters of the library parameter space; and

generating a library for the optical metrology system using the reduced sampling set.

22. The medium of claim 21, further comprising instructions that, when executed by the processor, cause the processor to perform operations comprising:

determining a physical characteristic of the diffracting structure with the library.

23. The medium of claim 21, wherein recommending a sampling shape includes evaluation of a plurality of possible sampling shapes to determine a best fit for the expected sample space use.

24. The medium of claim 21, wherein the expected sample space use is based at least in part upon prior knowledge of a customer'"'"'s region of interest.

25. The medium of claim 21, wherein recommending a sampling filter includes processing identifying correlations between parameters and comparing such correlations.

26. The method of claim 25, wherein recommending a sampling filter further includes processing the correlated parameters using one or more algorithms.

27. The medium of claim 26, wherein the sampling filter includes a region defined by a certain slope and a certain width.

28. The medium of claim 27, wherein the one or more algorithms include a least squares fitting to determine the slope of the region of the sample filter.

29. The medium of claim 26, wherein the processing the correlated parameters is based at least in part on prior knowledge of parameter correlation.