Metrology data correction using image quality metric

Patent metadata

Field	Value
Publication number	US-12189307-B2
Application number	US-201917268863-A
Country	US
Kind code	B2
Filing date	Aug 14, 2019
Priority date	Aug 17, 2018
Publication date	Jan 7, 2025
Grant date	Jan 7, 2025

Abstract

A method for correcting metrology data of a patterning process. The method includes obtaining (i) metrology data of a substrate subjected to the patterning process and (ii) a quality metric (e.g., a focus index) that quantifies a quality of the metrology data of the substrate; establishing a correlation between the quality metric and the metrology data; and determining a correction to the metrology data based on the correlation between the quality metric and the metrology data.

First claim

What is claimed is:

1. A method for correcting metrology data of a patterning process, the method comprising:
obtaining (i) metrology data of a substrate subjected to the patterning process and (ii) an image quality metric that quantifies how well a metrology tool has been able to produce an image from which the metrology data is measured or otherwise obtained;
establishing, via a hardware computing system, a correlation between the image quality metric and the metrology data; and
determining, via the computing system, a correction to the metrology data based on the correlation between the image quality metric and the metrology data.

2. The method of claim 1 , wherein determining the correction comprises determining a corrected value of the metrology data based on a correction model.

3. The method of claim 2 , wherein the corrected value is determined based on a slope of the correlation between the image quality metric and the metrology data, and a difference between a maximum value of the image quality metric across the substrate and a value of the image quality metric at a point of interest on the substrate.

4. The method of claim 1 , wherein the image quality metric is a focus index of an image of the substrate captured via the metrology tool.

5. The method of claim 4 , wherein the focus index is determined based on a local phase coherence map that reveals a phase relationship, in a vicinity of a feature location on the substrate, between neighbouring wavelet coefficients in a scale-space.

6. The method of claim 4 , wherein the focus index is determined based on a sample selected from the image that has a relatively higher gradient compared to other locations on the image.

7. The method of claim 6 , wherein the sample is an area of the image that has a relatively high gradient compared to remaining areas of the image.

8. The method of claim 1 , wherein the image quality metric is independent of variations in a dose used in the patterning process.

9. The method of claim 1 , wherein the metrology data comprises an image of a printed substrate, or a parameter of the patterning process.

10. The method of claim 1 , wherein the metrology data comprises a parameter of the patterning process and the parameter of the patterning process is a critical dimension, an edge placement error, or an overlay.

11. The method of claim 1 , further comprising generating a map of a parameter of the patterning process based on the correction applied to the metrology data.

12. The method of claim 11 , wherein the map is a dose map, a focus map, a critical dimension (CD) map, an overlay map, or an edge placement error map.

13. The method of claim 1 , wherein the metrology data is a scanning electron microscope image, or an e-beam image.

14. The method of claim 1 , further comprising training a correction model based on the correlation between the image quality metric and the metrology data, wherein the correction model is configured to determine real-time corrections to metrology data collected during the patterning process.

15. A computer program product comprising a non-transitory computer readable medium having instructions therein, the instructions, when executed by a computer system, configured to cause the computer system to at least:
obtain (i) metrology data of a substrate subjected to a patterning process and (ii) an image quality metric that quantifies how well a metrology tool has been able to produce an image from which the metrology data is measured or otherwise obtained;
establish a correlation between the image quality metric and the metrology data; and
determine a correction to the metrology data based on the correlation between the image quality metric and the metrology data.

16. The computer program product of claim 15 , wherein the instructions configured to cause the computer system to determine the correction are further configured to cause the computer system to determine the correction based on a slope of the correlation between the image quality metric and the metrology data, and a difference between a maximum value of the image quality metric across the substrate and a value of the image quality metric at a point of interest on the substrate.

17. The computer program product of claim 15 , wherein the image quality metric is a focus index of an image of the substrate captured via the metrology tool.

18. The computer program product of claim 15 , wherein the image quality metric is independent of variations in a dose used in the patterning process.

19. The computer program product of claim 15 , wherein the instructions are further configured to cause the computer system to generate a map of a parameter of the patterning process based on the correction applied to the metrology data.

20. The computer program product of claim 15 , wherein the instructions are further configured to cause the computer system to train a correction model based on the correlation between the image quality metric and the metrology data, wherein the correction model is configured to determine real-time corrections to metrology data collected during the patterning process.

Assignees

• Asml Netherlands Bv

Inventors

• Wang Fuming
• Hunsche Stefan
• Fang Wei

Classifications

• G06F18/214

  Generating training patterns; Bootstrap methods, e.g. bagging or boosting · CPC title

• H01J37/28

  with scanning beams {(H01J37/268, H01J37/292, H01J37/2955 take precedence)} · CPC title

• G06T2207/30168

  Image quality inspection · CPC title

• G06T2207/30148

  Semiconductor; IC; Wafer · CPC title

• G06T2207/20081

  Training; Learning · CPC title