Methods and systems for parameter-sensitive and orthogonal gauge design for lithography calibration

• US 8,930,172 B2
• Filed: 11/10/2009
• Issued: 01/06/2015
• Est. Priority Date: 11/10/2008
• Status: Active Grant

• Current Assignee: ASML Netherlands BV (ASML Holding NV)
• Original Assignee: ASML Netherlands BV (ASML Holding NV)
• Inventors: Ye, Jun, Cao, Yu, Feng, Hanying, Shao, Wenjin
• Primary Examiner(s): Craig, Dwin M
• Application Number:
  US13/128,630
• Publication Number:
  US 20110224956A1
• Time in Patent Office: 1,883 Days
• Field of Search: 703/6, 356/4.02
• US Class Current: 703/6
• CPC Class Codes: G03F 1/44 Testing or measuring features, e.g. grid patterns, focus monitors, sawtooth scales or notched scales
• CPC Class Codes: G03F 1/62 Pellicles, e.g. pellicle assemblies, e.g. having membrane on support frame; Preparation thereof
• CPC Class Codes: G03F 1/68 Preparation processes not covered by groups G03F1/20 - G03F1/50
• CPC Class Codes: G03F 7/70433 Layout for increasing efficiency or for compensating imaging errors, e.g. layout of exposure fields for reducing focus errors; Use of mask features for increasing efficiency or for compensating imaging errors
• CPC Class Codes: G03F 7/705 Modelling or simulating from physical phenomena up to complete wafer processes or whole workflow in wafer productions
• CPC Class Codes: G06F 17/10 Complex mathematical operations function generation by table look-up G06F1/03; evaluation of elementary functions by calculation G06F7/544
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30

Abstract

Methods according to the present invention provide computationally efficient techniques for designing gauge patterns for calibrating a model for use in a simulation process, and which minimize degeneracy between model parameters, and thus maximize pattern coverage for parameter calibration. More specifically, the present invention relates to methods of designing gauge patterns that achieve complete coverage of parameter variations with minimum number of gauges and corresponding measurements in the calibration of a lithographic process utilized to image a target design having a plurality of features. According to some aspects, a method according to the invention includes transforming the space of model parametric space (based on CD sensitivity or Delta TCCs), then iteratively identifying the direction that is most orthogonal to existing gauges'"'"' CD sensitivities in this new space, and determining most sensitive line width/pitch combination with optimal assist feature placement which leads to most sensitive CD changes along that direction in model parametric space.

Claims

1. A computer-implemented method for designing test gauges for calibrating a simulation model of an optical lithographic process, the method comprising:

identifying a first parameter of the simulation model;

computing one or more of a width and a spacing of features in a pattern that optimizes a metric associated with the parameter; and

designing one or more test gauges that include the pattern, wherein the identified parameter is chosen as an axis in building a model parametric space within a sensitivity space from which a target number of test gauges are selected;

wherein the identifying and computing steps are performed using a computer.

2. A method according to claim 1, further comprising:

computing one or more assisting features for arrangement in the pattern that further optimizes the metric.

3. A method according to claim 2, wherein the step of computing the one or more assisting features includes computing a guidance map for placement of the assisting features in the pattern.

4. A method according to claim 2, wherein the step of computing the one or more assisting features includes applying manufacturability constraints to a size and spacing of the assisting features.

5. A method according to claim 1, wherein the metric is a sensitivity to a critical dimension in an aerial image resulting from the computed pattern.

6. A method according to claim 5, wherein the computing step includes:

determining a perturbed value of the identified parameter;

using the perturbed value to compute a delta operator; and

using the delta operator to compute the aerial image.

7. A method according to claim 6, wherein the delta operator comprises transmission cross coefficients.

8. The method of claim 1, wherein the method further comprises:

repeating the steps of identifying, computing and designing for different parameters of the simulation model to build different respective model parametric spaces within the same sensitivity space from which the target number of test gauges is selected.

9. The method of claim 8, wherein while building the different respective model parametric spaces within the sensitivity space, only one parameter is varied while additional different parameters of the simulation model are kept constant.

10. The method of claim 8, wherein for N identified parameters of the simulation model, the target number of test gauges is N*(N−

1).

11. A computer-implemented method for designing test gauges for calibrating a simulation model of an optical lithographic process, the method comprising:

identifying at least two different parameters of the simulation model; and

designing test gauges for calibrating the parameters of the simulation model, including at least one first test gauge that maximizes sensitivity to a first change with respect to the parameters, and at least one second test gauge that maximizes sensitivity to a second change with respect to the parameters, wherein the second change exhibits substantial orthogonality to the first change, wherein for a target number of test gauges, an enclosed volume in a sensitivity space is maximized;

wherein the identifying and computing steps are performed using a computer.

12. A method according to claim 11, wherein the designing step includes:

designing a pair of test gauges that maximize a pair-wise sensitivity between a first and a second one of the parameters.

13. A method according to claim 11, wherein the designing step includes:

building a model parametric space in the sensitivity space based on the identified parameters;

identifying a direction in the model parametric space; and

designing one or more test gauges that maximize a sensitivity to changes in parameters associated with the identified direction.

14. A method according to claim 13, wherein the designing step further includes:

identifying a direction associated with an actual sensitivity of the designed test gauges;

removing that direction from the model parametric space; and

iteratively identifying a new direction, designing test gauges that maximize sensitivity in the new direction, identifying the direction associated with the actual sensitivities, and removing that direction from the model parametric space.

15. A method according to claim 13, wherein the step of building the model parametric space includes:

identifying a pattern set; and

calculating sensitivities of the identified model parameters to the patterns in the pattern set.

16. A method according to claim 13, wherein the step of building the model parametric space includes:

calculating a set of perturbations associated with respective ones of the identified model parameters; and

decomposing the set of perturbations to form a hyperspace.

17. A method according to claim 16, wherein the perturbations are characterized by differences in transmission cross coefficients (TCCs) from a nominal simulation model.

18. A method according to claim 17, wherein the step of designing one or more test gauges includes determining a most sensitive line width/pitch combination of patterns comprising the test gauges.

19. A method according to claim 18, wherein the step of designing one or more test gauges further includes determining an optimal assist feature placement relative to the patterns.

20. A method according to claim 11, wherein sensitivity is characterized in connection with predicted and actual critical dimensions of features printed using the lithographic process.

21. A computer program product comprising a non-transitory computer readable medium having recorded therein a set of instructions, which when executed by a computer, perform a method for designing test gauges for calibrating a simulation model of an optical lithographic process, the method comprising:

identifying at least two different parameters of the simulation model;

designing test gauges for calibrating the parameters of the simulation model, including at least one first test gauge that maximizes sensitivity to a first change with respect to the parameters, and at least one second test gauge that maximizes sensitivity to a second change with respect to the parameters, wherein the second change exhibits substantial orthogonality to the first change, wherein for a target number of test gauges, an enclosed volume in a sensitivity space is maximized.

22. A computer program product according to claim 21, wherein the designing step includes:

designing a pair of test gauges that maximize a pair-wise sensitivity between a first and a second one of the parameters.

23. A computer program product according to claim 21, wherein the designing step includes:

building a model parametric space within the sensitivity space based on the identified parameters;

identifying a direction in the model parametric space; and

designing one or more test gauges that maximize a sensitivity to changes in parameters associated with the identified direction.

24. A computer program product according to claim 23, wherein the designing step further includes:

identifying a direction associated with an actual sensitivity of the designed test gauges;

removing that direction from the model parametric space; and

iteratively identifying a new direction, designing test gauges that maximize sensitivity in the new direction, identifying the direction associated with the actual sensitivities, and removing that direction from the model parametric space.

25. A computer program product according to claim 23, wherein the step of building the model parametric space includes:

identifying a pattern set; and

calculating sensitivities of the identified model parameters to the patterns in the pattern set.

26. A computer program product according to claim 23, wherein the step of building the model parametric space includes:

calculating a set of perturbations associated with respective ones of the identified model parameters; and

decomposing the set of perturbations to form a hyperspace.

27. A computer program product according to claim 26, wherein the perturbations are characterized by differences in transmission cross coefficients (TCCs) from a nominal simulation model.