Granted Patent B2

US 12,242,201 · App. 17/276,533 · Granted Mar 4, 2025

Inventors: Youping Zhang (Cupertino, CA); Weixuan Hu (Shenzhen, CN); Fei Yan (Shenzhen, CN); Wei Peng (Shenzhen, CN); Vivek Kumar Jain (Fremont, CA)

Assignee: ASML NETHERLANDS B.V.

G03F7/70525G03F7/70641G03F7/7065G03F7/7085

Abstract

Claims (49)

1. A method comprising:

obtaining (i) a set of hot spots of a patterning process, (ii) measured values of one or more parameters of the patterning process corresponding to the set of hot spots, and (iii) simulated values of the one or more parameters of the patterning process corresponding to the set of hot spots;

determining, via a hardware computer system, a measurement feedback based on the measured values and the simulated values of the one or more parameters of the patterning process; and

determining, via computer simulation using a process model of the patterning process, a ranking of a hot spot within the set of hot spots based on the measurement feedback.

2. The method of claim 1 , wherein the measurement feedback is a bias function determined as a difference between a first function representing the measured values and a second function representing the simulated values.

3. The method of claim 2 , wherein the determining the measurement feedback comprises:

categorizing hot spots within the set of hot spots in one or more categories; and

determining the bias function for a particular category of the hot spot based on the measured values of the one or more parameters of the patterning process and the simulated values of the one or more parameters of the patterning process.

4. The method of claim 3 , wherein at least one category of the one or more categories is based on a pattern type and/or on values of one or more parameters of the patterning process.

5. The method of claim 4 , wherein at least one category of the one or more categories is based on a pattern type and the pattern type is determined based on geometric shapes of the features within the hot spot.

6. The method of claim 4 , wherein at least one category of the one or more categories is based on values of one or more parameters of the patterning process and the one or more parameters of the patterning process include a critical dimension, a dose, and/or a focus.

7. The method of claim 2 , wherein the first function and/or the second function is a mathematical model and/or a look up table.

8. The method of claim 2 , further comprising determining the bias function, the determining the bias function comprising: determining the first function as one fitting the measured values; determining the second function as one corresponding to the process model of the patterning process used to generate the simulated values; and determining the difference between the first function and the second function.

9. The method of claim 1 , wherein the measurement feedback is a maximum value of a difference between the measured values and the simulated values.

10. The method of claim 1 , wherein the measurement feedback is an average value of a difference between the measured values and the simulated values corresponding to a category of the hot spot within the set of the hot spots.

11. The method of claim 1 , wherein the determining the ranking of the hot spot comprises:

determining a category of one or more hot spots of the set of hot spots;

applying a bias function corresponding to the category to generate a biased version of the one or more hot spots; and

determining, via simulation of a ranking algorithm of the process model of the patterning process, the ranking of the biased hot spot.

12. The method of claim 11 , wherein the ranking algorithm includes determining a defect metric corresponding to each hot spot within the set of hot spots, wherein:

the defect metric is evaluated within a focus uncertainty range, and/or

the defect metric is a weighted sum of a difference between a defect size and a threshold defect size at different focus values within a focus uncertainty range.

13. The method of claim 1 , further comprising:

guiding an inspection tool to collect measurement data on a printed substrate according to the ranking of the hot spots; and

determining defects on the printed substrate based on the measurement data.

14. The method of claim 1 , wherein the determining the measurement feedback is an iterative process, an iteration comprising:

obtaining defect data corresponding to the set of hot spots;

determining a correlation between the defect data and hot spot ranking;

evaluating a level of the correlation; and

responsive to the level of correlation breaching a threshold, determining the measurement feedback.

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) a set of hot spots of a patterning process, (ii) measured values of one or more parameters of the patterning process corresponding to the set of hot spots, and (iii) simulated values of the one or more parameters of the patterning process corresponding to the set of hot spots;

determine a measurement feedback based on the measured values and the simulated values of the one or more parameters of the patterning process; and

determine, via computer simulation using a process model of the patterning process, a ranking of a hot spot within the set of hot spots based on the measurement feedback.

16. The computer program product of claim 15 , wherein the measurement feedback is a bias function determined as a difference between a first function representing the measured values and a second function representing the simulated values.

17. The computer program product of claim 16 , wherein the instructions configured to cause the computer system to determine the measurement feedback are further configured to cause the computer system to:

categorize hot spots within the set of hot spots in one or more categories; and

determine the bias function for a particular category of the hot spot based on the measured values of the one or more parameters of the patterning process and the simulated values of the one or more parameters of the patterning process.

18. The computer program product of claim 16 , wherein the instructions are further configured to cause the computer system to determine the bias function, the determination of the bias function comprising: determination of the first function as one fitting the measured values; determination of the second function as one corresponding to the process model of the patterning process used to generate the simulated values; and determination of the difference between the first function and the second function.

19. The computer program product of claim 16 , wherein the instructions configured to cause the computer system to determine the ranking of the hot spot are further configured to cause the computer system to:

determine a category of one or more hot spots of the set of hot spots;

apply a bias function corresponding to the category to generate a biased version of the one or more hot spots; and

determine, via simulation of a ranking algorithm of the process model of the patterning process, the ranking of the biased hot spot.

20. The computer program product of claim 16 , wherein the instructions configured to cause the computer system to determine the measurement feedback are further configured to cause the computer system to do so in an iterative process, an iteration thereof comprising:

obtaining of defect data corresponding to the set of hot spots;

determination of a correlation between the defect data and hot spot ranking;

evaluation of a level of the correlation; and

responsive to the level of correlation breaching a threshold, determination of the measurement feedback.

21. The computer program product of claim 15 , wherein the measurement feedback is a maximum value of a difference between the measured values and the simulated values or an average value of a difference between the measured values and the simulated values corresponding to a category of the hot spot within the set of the hot spots.

Assignments (2)

Continuity (2)

References Cited (31)