Method for characterizing a manufacturing process of semiconductor devices

Patent metadata

Field	Value
Publication number	US-11860548-B2
Application number	US-202017425355-A
Country	US
Kind code	B2
Filing date	Feb 6, 2020
Priority date	Feb 20, 2019
Publication date	Jan 2, 2024
Grant date	Jan 2, 2024

Abstract

A method of determining a characteristic of one or more processes for manufacturing features on a substrate, the method including: obtaining image data of a plurality of features on a least part of at least one region on a substrate; using the image data to obtain measured data of one or more dimensions of each of at least some of the plurality of features; determining a statistical parameter that is dependent on the variation of the measured data of one or more dimensions of each of at least some of the plurality of features; determining a probability of defective manufacture of features in dependence on a determined number of defective features in the image data; and determining the characteristic of the one or more processes to have the probability of defective manufacture of features and the statistical parameter.

First claim

What is claimed is:

1. A method comprising:
obtaining image data of a plurality of features on at least part of at least one region on a substrate;
using the image data to obtain one or more dimensions of at least some features out of the plurality of features;
determining a value of a statistical parameter based on a value of variation of the one or more dimensions and a mean value of the one or more dimensions;
obtaining a probability of defective manufacture of features in dependence on a determined number of defective features in the image data; and
determining, using a hardware computer, a characteristic of one or more processes for manufacturing features on a substrate by deriving a relation between the probability of defective manufacture of features and the value of the statistical parameter.

2. The method of claim 1 , wherein the image data is obtained from a plurality of regions on the substrate.

3. The method of claim 2 , further comprising:
determining, for each of the plurality of regions, a value of a local statistical parameter that is dependent on the variation of the one or more dimensions of a plurality of features in the respective region; and
determining the value of the statistical parameter in dependence on values of the local statistical parameter.

4. The method of claim 3 , wherein the value of the local statistical parameter of each region is dependent on local critical dimension uniformity of features in the region.

5. The method of claim 1 , further comprising determining a defect probability relationship that indicates a relationship between determined probabilities of defective manufacture of features and values of respective statistical parameters,
wherein determining the defect probability relationship comprises generating a plurality of characteristics for one or more processes performed in the manufacturing of features on the substrate, wherein each of the plurality characteristics is generated by performing the method under different conditions of the one or more processes.

6. The method of claim 5 , wherein the defect probability relationship is determined by generating a plurality of characteristics at each of a plurality of dose settings of a process and at each of a plurality of focus settings of a process.

7. The method of claim 5 , further comprising:
determining, for each of a plurality of photoresists, a defect probability relationship and one or more process windows in dependence on the defect probability relationship; and
selecting a photoresist for use in the process of manufacturing features in dependence on the determined one or more process windows.

8. The method of claim 1 , wherein the determined defective features in the image data comprise missing features when a feature should be present and merged at least two features when the at least two features should be separated from each other.

9. The method of claim 1 , further comprising adjusting, based on the determined characteristic, one or more apparatuses or materials used in the one or more processes for manufacturing features on a substrate.

10. A non-transitory computer-readable medium comprising instructions therein that, when executed by a processor system, are configured to cause the processor system to at least:
obtain image data of a plurality of features on at least part of at least one region on a substrate;
use the image data to obtain one or more dimensions of at least some features out of the plurality of features;
determine a value of a statistical parameter based on a value of variation of the one or more dimensions and a mean value of the one or more dimensions;
obtain a probability of defective manufacture of features in dependence on a determined number of defective features in the image data; and
determine a characteristic of one or more processes for manufacturing features on a substrate by deriving a relation between the probability of defective manufacture of features and the value of the statistical parameter.

11. The non-transitory computer-readable medium of claim 10 , wherein the instructions are further configured to cause the processor system to:
determine, for each of a plurality of photoresists, a defect probability relationship and one or more process windows in dependence on the defect probability relationship; and
select a photoresist for use in the process of manufacturing features in dependence on the determined one or more process windows.

12. The non-transitory computer-readable medium of claim 10 , wherein the image data is obtained from a plurality of regions on the substrate.

13. The non-transitory computer-readable medium of claim 12 , wherein the instructions are further configured to cause the processor system to:
determine, for each of the plurality of regions, a value of a local statistical parameter that is dependent on the variation of the one or more dimensions of a plurality of features in the respective region; and
determine the value of the statistical parameter in dependence on values of the local statistical parameter.

14. The non-transitory computer-readable medium of claim 13 , wherein the value of the local statistical parameter of each region is dependent on local critical dimension uniformity of features in the region.

15. The non-transitory computer-readable medium of claim 10 , wherein the instructions are further configured to cause the processor system to determine a defect probability relationship that indicates a relationship between determined probabilities of defective manufacture of features and values of respective statistical parameters, wherein the statistical parameters and the determined probabilities of defective manufacture of features are obtained for different conditions of the one or more processes.

16. The non-transitory computer-readable medium of claim 15 , wherein the defect probability relationship is determined at each of a plurality of dose settings of a process and at each of a plurality of focus settings of a process.

17. The non-transitory computer-readable medium of claim 10 , wherein the instructions are further configured to cause the processor system to output a signal to cause or enable adjustment, based on the determined characteristic, of one or more apparatuses or materials used in the one or more processes for manufacturing features on a substrate.

18. A non-transitory computer-readable medium comprising instructions therein that, when executed by a processor system, are configured to cause the processor system to at least:
determine a characteristic of one or more processes for manufacturing features on a substrate by deriving a relation between a probability of defective manufacture of features and a value of a statistical parameter, the statistical parameter based on a value of variation of one or more dimensions of one or more features on at least part of at least one region on a substrate and on a mean value of the one or more dimensions;
output a signal to cause or enable adjustment, based on the determined characteristic, of one or more apparatuses or materials used in the one or more processes for manufacturing features on a substrate.

19. The non-transitory computer-readable medium of claim 18 , wherein the instructions are further configured to cause the processor system to:
use image data to obtain the one or more dimensions of the one or more features; and
obtain the probability of defective manufacture of features in dependence on a determined number of defective features in the image data.

Assignees

• Asml Netherlands Bv

Inventors

• Tel Wim Tjibbo
• Dillen Hermanus Adrianus
• Kea Marc Jurian
• Maslow Mark John
• Thuijs Koen
• Engblom Peter David
• Huijgen Ralph Timotheus
• Slotboom Daan Maurits
• Mulkens Johannes Catharinus Hubertus

Classifications

• G03F7/706837

  Data analysis, e.g. filtering, weighting, flyer removal, fingerprints or root cause analysis · CPC title

• G03F7/705 Primary

  Modelling or simulating from physical phenomena up to complete wafer processes or whole workflow in wafer productions · CPC title

• G03F7/7065

  Defects, e.g. optical inspection of patterned layer for defects · CPC title

• G03F7/70525

  Controlling normal operating mode, e.g. matching different apparatus, remote control or prediction of failure · CPC title

• G03F7/70658

  Electrical testing · CPC title