Model-based process simulation systems and methods

• US 8,806,387 B2
• Filed: 05/29/2009
• Issued: 08/12/2014
• Est. Priority Date: 06/03/2008
• Status: Active Grant

• Current Assignee: ASML Netherlands BV (ASML Holding NV)
• Original Assignee: ASML Netherlands BV (ASML Holding NV)
• Inventors: Cao, Yu, Shao, Wenjin, Goossens, Ronaldus Johannes Gijsbertus, Ye, Jun, Koonmen, James Patrick
• Primary Examiner(s): NGUYEN, NHA T
• Application Number:
  US12/475,095
• Publication Number:
  US 20090300573A1
• Time in Patent Office: 1,901 Days
• Field of Search: 716 50- 56, 430/5, 430/30
• US Class Current: 716/51
• CPC Class Codes: B29C 64/386 Data acquisition or data processing for additive manufacturing
• CPC Class Codes: G03F 7/70091 Illumination settings, i.e. intensity distribution in the pupil plane or angular distribution in the field plane; On-axis or off-axis settings, e.g. annular, dipole or quadrupole settings; Partial coherence control, i.e. sigma or numerical aperture [NA]
• CPC Class Codes: G03F 7/70458 Mix-and-match, i.e. multiple exposures of the same area using a similar type of exposure apparatus, e.g. multiple exposures using a UV apparatus
• 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: G03F 7/70516 Calibration of components of the microlithographic apparatus, e.g. light sources, addressable masks or detectors
• CPC Class Codes: G03F 7/70525 Controlling normal operating mode, e.g. matching different apparatus, remote control or prediction of failure
• CPC Class Codes: G06F 2113/18 Chip packaging
• 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
• CPC Class Codes: G06F 30/398 Design verification or optimisation, e.g. using design rule check [DRC], layout versus schematics [LVS] or finite element methods [FEM] optical proximity correction [OPC] design processes G03F1/36

Abstract

Systems and methods for process simulation are described. The methods may use a reference model identifying sensitivity of a reference scanner to a set of tunable parameters. Chip fabrication from a chip design may be simulated using the reference model, wherein the chip design is expressed as one or more masks. An iterative retuning and simulation process may be used to optimize critical dimension in the simulated chip and to obtain convergence of the simulated chip with an expected chip. Additionally, a designer may be provided with a set of results from which an updated chip design is created.

Claims

1. A method for simulating contours produced by a lithographic process for a design, wherein the method is implemented by a computer, the method comprising:

maintaining a differential model that defines differences in imaging results obtained when using a second lithographic process from imaging results obtained when using a different first lithographic process, wherein the differences in imaging results are attributable to differences in lithographic process parameters between the second lithographic process and the different first lithographic process; and

generating, using the computer and the differential model, a predicted difference in simulated wafer contours for the second lithographic process, wherein the predicted difference is a difference between simulated wafer contours respectively produced by the first and second lithographic processes for the design.

2. The method of claim 1, wherein the differences in lithographic process parameters correspond to one or more of mask differences, resist differences, track differences, etch differences and scanner differences.

3. The method of claim 2, wherein the scanner differences include differences associated with one or more of optics, mechanics, control and device-specific laser drift.

4. The method of claim 1, wherein the simulated wafer contours correspond to wafer contours in resist.

5. The method of claim 1, wherein the simulated wafer contours correspond to wafer contours after etch.

6. The method of claim 1, wherein the simulated wafer contours include contours generated by lithographic processes mutually distinguishable by at least one different lithographic process parameter.

7. The method of claim 1, wherein the differential model characterizes differences in the different first and second lithographic processes associated with different first and second scanners.

8. The method of claim 7, further comprising deriving a model of one of the two scanners using the differential model and a model of the other scanner.

9. The method of claim 8, wherein the model of the other scanner is one of an OPC model and an OPC verification model.

10. The method of claim 1, wherein differences described by the differential model include tunable and non-tunable parameters.

11. The method of claim 1, further comprising:

combining the predicted difference with simulated wafer contours produced by the first lithographic process to obtain simulated wafer contours produced by the second lithographic process for the design.

12. A method for calibrating a lithographic model, wherein the method is implemented by a computer, the method comprising:

performing a plurality of simulations of a lithographic process, wherein for each simulation, tunable settings of a process model are changed;

comparing simulated contours produced by the simulations with measured contours produced under corresponding changes in the lithographic process to identify differences between the simulated contours and the measured contours; and

calibrating, using the computer, parameters of the process model using a cost function based on the identified differences,

wherein the process model describes differences in imaging results when using a second set of tunable settings of the lithographic process, wherein the differences in imaging results are attributable to differences in lithographic process parameters between the second set of tunable settings of the lithographic process and a different first set of tunable settings of the lithographic process.

13. The method of claim 12, wherein the process model is a sensitivity model that describes differences in imaging results attributable to differences in apparatus settings for a lithographic apparatus.

14. A method for calibrating a lithographic model, wherein the method is implemented by a computer, the method comprising:

performing simulations of a lithographic process for a plurality of scanners, wherein a differential model characterizes scanner related differences in the lithographic process;

identifying differences between simulated contours produced by the simulations and corresponding measured contours obtained from the plurality of scanners under the simulated conditions; and

optimizing, using the computer, parameters of the differential model based on the identified differences,

wherein the differential model describes differences in imaging results when using a second one of the scanners, wherein the differences in imaging results are attributable to differences in lithographic process parameters between the second scanner and a different first one of the scanners.

15. The method of claim 14, wherein the step of optimizing includes adjusting tunable and non-tunable scanner parameters until differences in the simulated contours match corresponding differences in the measured contours.

16. The method of claim 14, wherein the plurality of scanners comprise scanners made by a single vendor and belonging to a same model type.

17. The method of claim 14, wherein the first scanner comprises a reference scanner, and wherein the differential model can be used to generate a predicted difference in simulated wafer contours for the second scanner, wherein the predicted difference is a difference between simulated wafer contours respectively produced by the first and second scanners for a same design.

18. The method of claim 14, further comprising:

performing simulations of a second lithographic process for the plurality of scanners, wherein a second differential model characterizes scanner related differences in the second lithographic process;

identifying differences between simulated contours produced by the simulations and corresponding measured contours obtained from the plurality of scanners under the simulated conditions; and

optimizing, using the computer, parameters of the second differential model based on the identified differences,

wherein the second differential model describes differences in imaging results when using a third one of the scanners, wherein the differences in imaging results are attributable to differences in lithographic process parameters between the third scanner and the different first scanner.