Computer-implemented methods for detecting and/or sorting defects in a design pattern of a reticle

• US 20060291714A1
• Filed: 12/07/2004
• Published: 12/28/2006
• Est. Priority Date: 12/07/2004
• Status: Active Grant

• Current Assignee: Kla-Tencor Technologies Corporation (KLA Corporation)
• Original Assignee: Kla-Tencor Technologies Corporation (KLA Corporation)
• Inventors: Kulkarni, Ashok, Gao, Lisheng, Kowalski, Michal, Randall, David, Wu, Kenong, Ynzunza, Ramon, Tribble, Ariel, Peterson, Ingrid B., Nafisi, Kourosh
• Granted Patent: US 7,729,529 B2
• Time in Patent Office: Days
• US Class Current: 382/149
• CPC Class Codes: G01N 2021/95676 Masks, reticles, shadow masks
• CPC Class Codes: G01N 21/95607 using a comparative method
• CPC Class Codes: G03F 1/84 Inspecting
• CPC Class Codes: G03F 7/7065 Defects, e.g. optical inspection of patterned layer for defects
• 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

Various computer-implemented methods are provided. One method for sorting defects in a design pattern of a reticle includes searching for defects of interest in inspection data using priority information associated with individual defects in combination with one or more characteristics of a region proximate the individual defects. The priority information corresponds to modulation levels associated with the individual defects. The inspection data is generated by comparing images of the reticle generated for different values of a lithographic variable. The images include at least one reference image and at least one modulated image. A composite reference image can be generated from two or more reference images. The method also includes assigning one or more identifiers to the defects of interest. The identifier(s) may include, for example, a defect classification and/or an indicator identifying if the defects of interest are to be used for further processing.

Claims

1. A computer-implemented method for sorting defects in a design pattern of a reticle, comprising:

searching for defects of interest in inspection data using priority information and defect attributes associated with individual defects in combination with one or more characteristics of a region proximate the individual defects and one or more characteristics of the individual defects, wherein the inspection data is generated by comparing images of the reticle generated for different values of a lithographic variable, and wherein the images comprise at least one reference image and at least one modulated image; and

assigning one or more identifiers to the defects of interest.

2. The method of claim 1, wherein the priority information is derived from a relationship between the individual defects and their corresponding modulation levels.

3. The method of claim 1, wherein the defect attributes comprise inspection parameter information, simple defect information comprising location, size and intensity magnitude, and a relationship among individual defects.

4. The method of claim 1, further comprising filtering the individual defects based on the priority information and the defect attributes.

5. The method of claim 4, wherein criteria for the filtering can be selected by a user.

6. The method of claim 1, wherein the one or more characteristics of the region proximate the individual defects and on the individual defects are derived from the at least one reference image and the at least one modulated image, respectively.

7. The method of claim 1, wherein the one or more characteristics of the region proximate the individual defects are selected by a user.

8. The method of claim 1, further comprising grouping the defects of interest based on the one or more characteristics of the region proximate the individual defects.

9. The method of claim 8, further comprising analyzing one or more characteristics of the region proximate one or more of the individual defects in the group to determine if the group is an irrelevant defect group.

10. The method of claim 1, further comprising grouping the defects of interest based on the one or more characteristics of the region proximate the individual defects in combination with the one or more characteristics of the defects of interest.

11. The method of claim 10, further comprising refining the grouping of the defects of interest based on similarity of the individual defects to a selected defect in the population based on the one or more characteristics of the region proximate the individual defects or the individual defects themselves.

12. The method of claim 1, wherein the one or more identifiers comprise a defect classification.

13. The method of claim 1, wherein the one or more identifiers comprise an indicator identifying if the defects of interest are to be selected for future processing.

14. The method of claim 1, wherein the one or more identifiers comprise an indicator identifying if the defects of interest are to be selected for future processing, and wherein said assigning the one or more identifiers is performed through a sampling algorithm preformed automatically based on the priority information and the defect classification.

15. The method of claim 1, further comprising comparing the defects of interest to inspection data generated by design rule checking performed on design pattern data of the reticle to determine if the defects of interest correlate to design rule checking defects.

16. The method of claim 15, further comprising removing from the defects of interest the defects that do not correlate with results of the design rule checking.

17. The method of claim 1, wherein the one or more characteristics of the region comprise one or more characteristics of the region extracted from a GDS or aerial image.

18. The method of claim 1, wherein the one or more characteristics of the region comprise one or more characteristics of the region determined from a high resolution image.

19. A computer-implemented method for detecting defects in a design pattern of a reticle, comprising:

acquiring images of the reticle for different values of a lithographic variable, wherein the images comprise two or more reference images obtained at nominal values and one or more modulated images;

generating a composite reference image from the two or more reference images;

comparing at least two of the images, wherein the at least two of the images comprise the composite reference image; and

determining if a defect is present in the design pattern using results of said comparing.

20. The method of claim 19, wherein if the defect is determined to be present, the method further comprises assigning the defect to a group based on one or more characteristics of a region proximate the defect.

21. The method of claim 20, wherein the one or more characteristics of the region comprise one or more characteristics of the design pattern in the region of at least one of the two or more reference images.

22. The method of claim 20, wherein the one or more characteristics of the region comprise one or more characteristics of the region in the at least two of the images used for said comparing.

23. The method of claim 20, wherein the one or more characteristics of the region comprise one or more characteristics of the region extracted from a GDS or aerial image.

24. The method of claim 20, wherein the one or more characteristics of the region comprise one or more characteristics of the region determined from a high resolution image.

25. The method of claim 20, further comprising analyzing the one or more characteristics of the region of one or more defects in the group to determine if the group is an irrelevant defect group.

26. The method of claim 20, further comprising analyzing one or more characteristics of one or more defects in the group to determine if the group indicates a failure in the design pattern.

27. The method of claim 19, wherein the images further comprise images of an entire swath of dies printed on a wafer using the reticle, and wherein the at least two of the images used for said comparing further comprise the images of all of the dies in the entire swath.

28. The method of claim 27, wherein modulated dies in the entire swath are printed using the same value of the lithographic variable, which is different than the value of the lithographic variable at which reference dies are printed in the entire swath.

29. The method of claim 27, wherein modulated dies in the entire swath are printed using the different values of the lithographic variable, and wherein reference dies in the entire swath are printed using an additional different value of the lithographic value.

30. The method of claim 19, wherein a user with knowledge of a layout of dies printed on a wafer selects which of the at least two of the images used for said comparing.

31. The method of claim 19, wherein said acquiring comprises acquiring images of the design pattern printed on a wafer using the reticle.

32. A computer-implemented method for detecting defects in a design pattern of a reticle, comprising:

acquiring images of an entire swath of dies printed on a wafer using the reticle, wherein at least two of the dies are printed at different values of a lithographic variable;

subsequent to said acquiring, comparing at least two of the images; and

determining if a defect is present in the design pattern using results of said comparing.

33. The method of claim 32, wherein the dies comprise modulated dies and at least one reference die, and wherein a number of the modulated dies in the entire swath is greater than or equal to a number of the at least one reference die in the entire swath.

34. The method of claim 32, wherein the dies comprise two or more reference dies, wherein the method further comprises generating a composite reference image from the images of the two or more reference dies, and wherein one of the at least two of the images used for said comparing comprises the composite reference image.

35. The method of claim 32, wherein the dies comprise modulated dies and at least one reference die, and wherein the modulated dies are printed at values of the lithographic variable that are the same for each of the modulated dies but different than the value of the lithographic variable at which the at least one reference die is printed.

36. The method of claim 32, wherein the dies comprise modulated dies and at least one reference die, and wherein the modulated dies are printed at values of the lithographic variable that are different for each of the modulated dies and different than the value of the lithographic variable at which the at least one reference die is printed.

37. A computer-implemented method for detecting and sorting defects in a design pattern of a reticle, comprising:

acquiring images of the reticle for different values of a lithographic variable;

comparing at least two of the images;

determining if pixel differences in the at least two of the images follow a typical or atypical trend over the different values of the lithographic variable.

38. The method of claim 37, wherein the atypical trend indicates a potentially relevant defect location.

39. The method of claim 37, wherein the images comprise images of modulated dies printed at the different values of the lithographic variable and images of reference dies printed using an additional different value of the lithographic variable.

40. The method of claim 37, wherein said acquiring comprises acquiring images of the design pattern printed on a wafer using the reticle.