Methods and system for lithography process window simulation

• US 20090157360A1
• Filed: 12/05/2008
• Published: 06/18/2009
• Est. Priority Date: 12/05/2007
• Status: Active Grant

• Current Assignee: ASML Netherlands BV (ASML Holding NV)
• Original Assignee: ASML Netherlands BV (ASML Holding NV)
• Inventors: Feng, Hanying, Ye, Jun, Cao, Yu
• Granted Patent: US 8,200,468 B2
• Time in Patent Office: Days
• US Class Current: 703/2
• 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 7/70991 Connection with other apparatus, e.g. multiple exposure stations, particular arrangement of exposure apparatus and pre-exposure and/or post-exposure apparatus; Shared apparatus, e.g. having shared radiation source, shared mask or workpiece stage, shared base-plate; Utilities, e.g. cable, pipe or wireless arrangements for data, power, fluids or vacuum
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30

Abstract

A method of efficient simulating imaging performance of a lithographic process utilized to image a target design having a plurality of features. The method includes the steps of determining a function for generating a simulated image, where the function accounts for process variations associated with the lithographic process; and generating the simulated image utilizing the function, where the simulated image represents the imaging result of the target design for the lithographic process. In one given embodiment, the function for simulating the aerial images with focus and dose (exposure) variation is defined as:

I(x,f,1+ε)=I₀(x)+[ε·I₀(x)+(1+ε)·a(x)·(f−f₀)+(1+ε)·b(x)·(f−f₀)²]

where I_O represents image intensity at nominal focus and exposure, f_O represents nominal focus, f and ε represents an actual focus-exposure level at which the simulated image is calculated, and parameter “a” and “b” represent first order and second order derivative images with respect to focus change.

Claims

1. A method of simulating imaging performance of a lithographic process utilized to image a target design having a plurality of features, said method comprising:

determining a function for generating a simulated image, said function accounting for process window variations associated with said lithographic process; and

generating said simulated image utilizing said function;

said simulated image representing the imaging result of said target design for said lithographic process.

2. The method of simulating imaging performance of a lithographic process according to claim 1, wherein said function includes a polynomial function of the process window variations, and said process window variations include variations in at least one of focus and exposure dose.

3. The method of simulating imaging performance of a lithographic process according to claim 2, wherein said process window variations further include variations in optical settings including at least one of numerical aperture and sigma.

4. The method of simulating imaging performance of a lithographic process according to claim 2, wherein said function is defined as:

I(x,f,1+ε

)=I₀(x)+[ε

·

I₀(x)+(1+ε

)·

a(x)·

(f−

f₀)+(1+ε

)·

b(x)·

(f−

f₀)²]

where I_O represents image intensity at nominal focus and exposure, f_O represents nominal focus, f and ε

represents an actual focus-exposure level at which the simulated image is calculated, and parameter “

a” and

“

b”

represent first order and second order derivative images with respect to focus change.

5. The method of simulating imaging performance of a lithographic process according to claim 2, wherein said function is defined as:

I(x,f,1+ε

)=I₀(x)+[ε

·

I₀(x)+(1+ε

)·

a(x)·

(f−

f₀)+(1+ε

)·

b(x)·

(f−

f₀)²]

where I_O represents image intensity at nominal focus and exposure, f_O represents nominal focus, f and ε

represents an actual focus-exposure level at which the simulated image is calculated, and parameter “

a” and

“

b”

represent best fit of a series of aerial images at different focuses.

6. The method of simulating imaging performance of a lithographic process according to claim 2, wherein said function is defined as:

I(x,f,1+ε

)=I₀(x)+[ε

·

I₀(x)+(1+ε

)·

a(x)·

(f−

f₀)+(1+ε

)·

b(x)·

(f−

f₀)²]

where I_O represents image intensity at nominal focus and exposure, f_O represents nominal focus, f and ε

represents an actual focus-exposure level at which the simulated image is calculated, and parameter “

a” and

“

b”

represent the aerial images computed from TCCs A and B which are linear combinations of a series of TCCs at different focuses.

7. The method of simulating imaging performance of a lithographic process according to claim 2, wherein said function is defined as:

I(x,f,1+ε

)=I₀(x)+[ε

·

I₀(x)+(1+ε

)·

a(x)·

(f−

f₀)+(1+ε

)·

b(x)·

(f−

f₀)²]

where I_O represents image intensity at nominal focus and exposure, f_O represents nominal focus, f and ε

represents an actual focus-exposure level at which the simulated image is calculated, and parameter “

a” and

“

b”

represent the aerial images computed from TCCs A and B which are first order and second order derivative TCCs with respect to focus change.

8. The method of simulating imaging performance of a lithographic process according to claim 1, wherein said simulated image corresponds to a resist image.

9. The method of simulating imaging performance of a lithographic process according to claim 8, wherein said function for simulating said resist image with focus and dose variation is defined as:

R=R₀+ε

·

P{I₀}+(1+ε

)·

(f−

f₀)·

P{a}+(1+ε

)·

(f−

f₀)²·

P{b}

where R_O represents image intensity at nominal focus and exposure, I_O represents nominal aerial image, f and ε

represents an actual focus-exposure level at which the simulated image is calculated, parameter “

a” and

“

b”

represent first order and second order derivative aerial images with respect to focus change, P{ } denotes the functional action of applying a filter as a resist model.

10. The method of estimating feature edge shift or critical dimension (CD) change due to process window parameter variation of a lithographic process, said method comprising the steps of:

determining a function for generating a simulated image, said function accounting for process window variations associated with said lithographic process;

generating said simulated image utilizing said function;

said simulated image representing the imaging result of said target design for said lithographic process; and

estimating said feature edge shift or CD change by analyzing said simulated image.

11. The method of estimating feature edge shift or CD change due to process window parameter variation of a lithographic process according to claim 10, wherein said function accounts for variations in focus and dose variation, said function being defined as:

12. A computer program product having a computer readable medium bearing a computer program for simulating imaging performance of a lithographic process utilized to image a target design having a plurality of features, the computer program, when executed, causing a computer to perform the steps of:

determining a function for generating a simulated image, said function accounting for process variations associated with said lithographic process; and

generating said simulated image utilizing said function;

said simulated image representing the imaging result of said target design for said lithographic process.

13. The computer program product of claim 12, wherein said function includes a polynomial function of the process window variations, and said process window variations include variations in at least one of focus and exposure dose.

14. The computer program product of claim 13, wherein said process window variations further include variations in optical settings including at least one of numerical aperture and sigma.

15. The computer program product according to claim 12, wherein said function for simulating aerial images with focus and dose (exposure) variation is defined as:

I(x,f,1+ε

)=I₀(x)+[ε

·

I₀(x)+(1+ε

)·

a(x)·

(f−

f₀)+(1+ε

)·

b(x)·

(f−

f₀)²]

where I_O represents image intensity at nominal focus and exposure, f_O represents nominal focus, f and ε

represents an actual focus-exposure level at which the simulated image is calculated, and parameter “

a” and

“

b”

represent first order and second order derivative images with respect to focus change.

16. The computer program product according to claim 12, wherein said function for simulating aerial images with focus and dose (exposure) variation is defined as:

I(x,f,1+ε

)=I₀(x)+[ε

·

I₀(x)+(1+ε

)·

a(x)·

(f−

f₀)+(1+ε

)·

b(x)·

(f−

f₀)²]

where I_O represents image intensity at nominal focus and exposure, f_O represents nominal focus, f and ε

represents an actual focus-exposure level at which the simulated image is calculated, and parameter “

a” and

“

b”

represent best fit of a series of aerial images at different focuses.

17. The computer program product according to claim 12, wherein said function for simulating aerial images with focus and dose (exposure) variation is defined as:

I(x,f,1+ε

)=I₀(x)+[ε

·

I₀(x)+(1+ε

)·

a(x)·

(f−

f₀)+(1+ε

)·

b(x)·

(f−

f₀)²]

where I_O represents image intensity at nominal focus and exposure, f_O represents nominal focus, f and ε

represents an actual focus-exposure level at which the simulated image is calculated, and parameter “

a” and

“

b”

represent the aerial images computed from TCCs A and B which are linear combinations of a series of TCCs at different focuses.

18. The computer program product according to claim 12, wherein said function for simulating aerial images with focus and dose (exposure) variation is defined as:

I(x,f,1+ε

)=I₀(x)+[ε

·

I₀(x)+(1+ε

)·

a(x)·

(f−

f₀)+(1+ε

)·

b(x)·

(f−

f₀)²]

where I_O represents image intensity at nominal focus and exposure, f_O represents nominal focus, f and ε

represents an actual focus-exposure level at which the simulated image is calculated, and parameter “

a” and

“

b”

represent the aerial images computed from TCCs A and B which are first order and second order derivative TCCs with respect to focus change.

19. The computer program product according to claim 15, wherein said simulated image corresponds to a resist image.

20. The computer program product according to claim 19, wherein said function for simulating said resist image with focus and dose variation is defined as:

R=R₀+ε

·

P{I₀}+(1+ε

)·

(f−

f₀)·

P{a}+(1+ε

)·

(f−

f₀)²·

P{b}

where R_O represents image intensity at nominal focus and exposure, I_O represents nominal aerial image, f and ε

represents an actual focus-exposure level at which the simulated image is calculated, parameter “

a” and

“

b”

represent first order and second order derivative aerial images with respect to focus change, P{ } denotes the functional action of applying a filter as a resist model.

21. The computer program product having a computer readable medium bearing a computer program for estimating feature edge shift or critical dimension (CD) change due to process window parameter variation of a lithographic process, the computer program, when executed, causing a computer to perform the steps of:

determining a function for generating a simulated image, said function accounting for process window variations associated with said lithographic process;

generating said simulated image utilizing said function;

said simulated image representing the imaging result of said target design for said lithographic process; and

estimating said feature edge shift or CD change by analyzing said simulated image.

22. The computer program product according to claim 21, wherein said function accounts for variations in focus and dose variation, said function being defined as: