MULTI-MODEL METROLOGY

• US 20160322267A1
• Filed: 07/07/2016
• Published: 11/03/2016
• Est. Priority Date: 08/23/2013
• Status: Abandoned Application

• Current Assignee: KLA-Tencor Corporation (KLA Corporation)
• Original Assignee: KLA-Tencor Corporation (KLA Corporation)
• Inventors: Kim, In-Kyo, Li, Xin, Poslavsky, Leonid, Lee, Liequan, Cao, Meng, Yoo, Sungchul, Shchegrov, Andrei V., Park, Sangbong
• Application Number:
  US15/204,461
• Publication Number:
  US 20160322267A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G03F 7/70616 Monitoring the printed patterns
• 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
• CPC Class Codes: H01L 21/67288 Monitoring of warpage, curvature, damage, defects or the like
• CPC Class Codes: H01L 22/12 for structural parameters, e.g. thickness, line width, refractive index, temperature, warp, bond strength, defects, optical inspection, electrical measurement of structural dimensions, metallurgic measurement of diffusions electrical measurement of diffusions H01L22/14
• CPC Class Codes: H01L 22/20 Sequence of activities consisting of a plurality of measurements, corrections, marking or sorting steps

Abstract

Disclosed are apparatus and methods for characterizing a plurality of structures of interest on a semiconductor wafer. A plurality of models having varying combinations of floating and fixed critical parameters and corresponding simulated spectra is generated. Each model is generated to determine one or more critical parameters for unknown structures based on spectra collected from such unknown structures. It is determined which one of the models best correlates with each critical parameter based on reference data that includes a plurality of known values for each of a plurality of critical parameters and corresponding known spectra. For spectra obtained from an unknown structure using a metrology tool, different ones of the models are selected and used to determine different ones of the critical parameters of the unknown structure based on determining which one of the models best correlates with each critical parameter based on the reference data.

Claims

1. A method of characterizing a plurality of structures of interest on a sample, the method comprising:

generating a plurality of models that are different from each other in that they have different combinations of floating and fixed critical parameters for outputting simulated spectra, wherein the models are generated as final models to determine different one or more critical parameters for unknown structures based on spectra collected from such unknown structures;

after generating the models and without generating another model, determining which one of the models best correlates with each critical parameter based on reference data that includes a plurality of known values for each of a plurality of critical parameters and corresponding known spectra; and

for spectra measured from an unknown structure using a metrology tool, selecting and using different ones of the models to determine different ones of the critical parameters of the unknown structure based on determining which one of the models best correlates with each critical parameter based on the reference data.

2. The method of claim 1, wherein the models have different sets of one or more critical parameters that are fixed and different sets of one or more critical parameters that are floating.

3. The method of claim 1, wherein each of the models has a low degree of freedom and is configured to provide a different subset of the critical parameters of the unknown structure.

4. The method of claim 1, wherein at least one of the models is configured to utilize a same geometric model with a plurality of different constraint conditions that correspond to a plurality of sub-models or utilize different geometric models that correspond to a plurality of sub-models.

5. The method of claim 1, wherein at least a first one of the models is configured to send a selected critical parameter to a second one of the models using a transform function.

6. The method of claim 1, wherein the spectra from the known structure and the unknown structure, is acquired using one or more of the following:

spectroscopic ellipsometry, Mueller matrix spectroscopic ellipsometry, spectroscopic reflectometry, spectroscopic scatterometry, beam profile reflectometry, beam profile ellipsometry, a single wavelength, a single discrete wavelength range, or multiple discrete wavelength ranges.

7. The method of claim 1, wherein each of the models is generated using a rigorous wave coupling analysis technique.

8. The method of claim 1, wherein the critical parameters include a middle critical dimension (MCD), top CD (TCD), bottom CD (BCD), height (HT) and side wall angle (SWA).

9. The method of claim 1, wherein a first one of the models is selected and used to determine a first one of the critical parameters and a second one of the models is selected and used to determine a second one of the critical parameters, wherein the first model has a higher correlation for determining the first critical parameter than the second model, and wherein the second model has a higher correlation for determining the second critical parameter than the first model.

10. The method of claim 1, wherein selecting and using different models includes selecting between a plurality of sub-models of a first model based on execution of the first model meeting a condition, wherein each sub-model is configured for determining a same set of critical parameters.

11. The method of claim 1, wherein each sub-model has different sets of fixed and floating critical parameters and the first model is initially executed with all its critical parameters floating.

12. The method of claim 1, wherein selecting and using different models includes selecting between a plurality of sub-models of a first model and the first model based on execution of the first model meeting a condition, wherein each sub-model is configured for determining a different subset of a base set of critical parameters and the first model is configured for determining the base set of critical parameters.

13. The method of claim 1, wherein selecting and using different models is further based on an expected critical dimension range.

14. The method of claim 1, wherein different models are also selected and used for different subsystems of the metrology tool.

15. A semiconductor metrology tool, comprising:

an illuminator for generating illumination;

illumination optics for directing the illumination towards an unknown structure;

collection optics for directing a plurality of spectra from the unknown structure to a sensor;

the sensor for acquiring the plurality of spectra signals from the unknown structure; and

a processor and memory configured for performing the following operations;

generating a plurality of models that are different from each other in that they have different combinations of floating and fixed critical parameters for outputting simulated spectra, wherein the models are generated as final models to determine different one or more critical parameters for unknown structures based on spectra collected from such unknown structures; and

after generating the models and without generating another model, determining which one of the models best correlates with each critical parameter based on reference data that includes a plurality of known values for each of a plurality of critical parameters and corresponding known spectra.

16. The metrology tool of claim 15, wherein at least one of the models is configured to utilize a same geometric model with a plurality of different constraint conditions that correspond to a plurality of sub-models or utilize different geometric models that correspond to a plurality of sub-models.

17. The metrology tool of claim 15, wherein at least a first one of the models is configured to send a selected critical parameter to a second one of the models using a transform function.

18. The metrology tool of claim 15, wherein the spectra from the known structure and the unknown structure is acquired using one or more of the following:

spectroscopic ellipsometry, Mueller matrix spectroscopic ellipsometry, spectroscopic reflectometry, spectroscopic scatterometry, beam profile reflectometry, beam profile ellipsometry, a single wavelength, a single discrete wavelength range, or multiple discrete wavelength ranges.

19. The metrology tool of claim 15, wherein the critical parameters include a middle critical dimension (MCD), top CD (TCD), bottom CD (BCD), and side wall angle (SWA).

20. The metrology tool of claim 15, wherein a first one of the models is selected and used to determine a first one of the critical parameters and a second one of the models is selected and used to determine a second one of the critical parameters, wherein the first model has a higher correlation for determining the first critical parameter than the second model, and wherein the second model has a higher correlation for determining the second critical parameter than the first model.

21. The metrology tool of claim 15, wherein selecting and using different models includes selecting between a plurality of sub-models of a first model based on execution of the first model meeting a condition, wherein each sub-model is configured for determining a same set of critical parameters.

22. The metrology tool of claim 15, wherein each sub-model has different sets of fixed and floating critical parameters and the first model is initially executed with all its critical parameters floating.

23. The metrology tool of claim 15, wherein selecting and using different models includes selecting between a plurality of sub-models of a first model and the first model based on execution of the first model meeting a condition, wherein each sub-model is configured for determining a different subset of a base set of critical parameters and the first model is configured for determining the base set of critical parameters.

24. The metrology tool of claim 15, wherein selecting and using different models is further based on an expected critical dimension range.

25. The metrology tool of claim 15, wherein different models are also selected and used for different subsystems of the metrology tool.