OPTIMIZATION OF SOURCE, MASK AND PROJECTION OPTICS

• US 20150074622A1
• Filed: 11/17/2014
• Published: 03/12/2015
• Est. Priority Date: 11/10/2010
• Status: Active Grant

• Current Assignee: ASML Netherlands BV (ASML Holding NV)
• Original Assignee: ASML Netherlands BV (ASML Holding NV)
• Inventors: Feng, Hanying, Cao, Yu, Ye, Jun
• Granted Patent: US 9,619,603 B2
• Time in Patent Office: Days
• US Class Current: 716/54
• CPC Class Codes: G03F 1/70 Adapting basic layout or design of masks to lithographic process requirements, e.g., second iteration correction of mask patterns for imaging
• CPC Class Codes: G03F 7/70125 Use of illumination settings tailored to particular mask patterns details of setting means G03F7/70091
• CPC Class Codes: G03F 7/70258 Projection system adjustments, e.g. adjustments during exposure or alignment during assembly of projection system
• CPC Class Codes: G03F 7/70441 Optical proximity correction [OPC]
• 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 2111/04 Constraint-based CAD
• CPC Class Codes: G06F 2111/06 Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
• CPC Class Codes: G06F 2111/08 Probabilistic or stochastic CAD
• CPC Class Codes: G06F 2119/18 Manufacturability analysis or optimisation for manufacturability
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06F 30/39 Circuit design at the physical level physical level design for reconfigurable circuits G06F30/347

Abstract

Embodiments of the present invention provide methods for optimizing a lithographic projection apparatus including optimizing projection optics therein, and preferably including optimizing a source, a mask, and the projection optics. The projection optics is sometimes broadly referred to as “lens”, and therefore the joint optimization process may be termed source mask lens optimization (SMLO). SMLO is desirable over existing source mask optimization process (SMO), partially because including the projection optics in the optimization can lead to a larger process window by introducing a plurality of adjustable characteristics of the projection optics. The projection optics can be used to shape wavefront in the lithographic projection apparatus, enabling aberration control of the overall imaging process. According to the embodiments herein, the optimization can be accelerated by iteratively using linear fitting algorithm or using Taylor series expansion using partial derivatives of transmission cross coefficients (TCCs).

Claims

1. A computer-implemented method for improving a simulation of a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic projection apparatus comprising data representing an illumination source and projection optics, the method comprising:

formulating a multi-variable cost function comprising projection-optics-related design variables that affect characteristics of the lithographic process; and

reconfiguring, using the computer, the characteristics of the lithographic process by adjusting the projection-optics-related design variables, until a termination condition for the multi-variable cost function is satisfied.

2. The method of claim 1, wherein the improvement of the simulation includes iteratively minimizing the cost function by calculating linear fitting coefficients within predefined relatively small neighborhoods around a starting point in each iteration.

3. The method of claim 2, wherein the cost function is minimized by a method selected from a group consisting of the Gauss-Newton algorithm, the Levenberg-Marquardt algorithm, the gradient descent algorithm, simulated annealing, and the genetic algorithm.

4. The method of claim 1, wherein the cost function is minimized by solving polynomials, including higher-order polynomials of the design variables.

5. The method of claim 4, wherein the cost function is expanded in terms of fitting constant coefficients.

6. The method of claim 5, wherein the fitting constant coefficients are computed from coefficients from polynomial expansion of transmission cross coefficients (TCCs).

7. The method of claim 6, wherein the fitting coefficients from polynomial expansion of transmission cross coefficients (TCCs) are computed from impulse response of the design variables.

8. The method of claim 6, comprising computing partial derivatives of the transmission cross coefficients.

9. The method of claim 8, wherein the partial derivatives of the transmission cross coefficients are computed from impulse response of the design variables.

10. The method of claim 1, wherein the portion of the design layout comprises data representing one or more of the following:

an entire design layout, a clip, a section of a design layout that is known to have one or more critical features, a section of the design layout where a hot spot or a warm spot has been identified from a full-chip simulation, and a section of the design layout where one or more critical features have been identified by a pattern selection method.

11. The method of claim 1, wherein the termination condition includes one or more of:

minimization of the cost function;

maximization of the cost function;

reaching a preset number of iterations;

reaching a value of the cost function equal to or beyond a preset threshold value;

reaching a predefined computation time; and

, reaching a value of the cost function within an acceptable error limit.

12. The method of claim 1, wherein one or more of the design variables are characteristics of the illumination source, and/or one or more of the design variables are characteristics of the design layout.

13. The method of claim 1, wherein the iterative reconfiguration step is performed without constraints or with constraints dictating the range of at least some of the design variables.

14. The method of claim 13, wherein at least some of the design variables are under constraints representing physical restrictions in a hardware implementation of the lithographic projection apparatus.

15. The method of claim 14, wherein the constraints include one or more of:

tuning ranges, rules governing mask manufacturability, and interdependence between the design variables.

16. The method of claim 1, wherein the cost function is a function of one or more of the following lithographic metrics:

edge placement error, critical dimension, resist contour distance, worst defect size, and best focus shift.

17. The method of claim 1, wherein the method comprises, prior to performing the steps of the improvement process, selecting a subset of target patterns that characteristically represents features of the portion of the design layout.

18. The method of claim 1, wherein optimization of various design variables are performed simultaneously until the termination condition is satisfied.

19. The method of claim 1, wherein optimization of various design variables are performed alternatively, keeping at least some of the design variables fixed while the other design variables are optimized, and, repeating the alternative optimization process until the termination condition is satisfied.

20. The method of claim 1, wherein the cost function comprises characteristics of a resist image or an aerial image.

21. The method of claim 1, wherein the cost function is minimized by solving a quadratic programming problem.

22. The method of claim 1, wherein the cost function is a function of only the design variables that are characteristics of the projection optics, while the other design variables are assigned predefined values.

23. A computer program product comprising a computer readable medium having instructions recorded thereon, the instructions when executed by a computer implementing the method of claim 1.