Image log slope (ILS) optimization
A method to improve a lithographic process of imaging a portion of a design layout onto a substrate using a lithographic projection apparatus, the method including: computing a multi-variable cost function, the multi-variable cost function being a function of a stochastic variation of a characteristic of an aerial image or a resist image, or a function of a variable that is a function of the stochastic variation or that affects the stochastic variation, the stochastic variation being a function of a plurality of design variables that represent characteristics of the lithographic process; and reconfiguring one or more of the characteristics of the lithographic process by adjusting one or more of the design variables until a certain termination condition is satisfied.
1. A method to improve a lithographic process of imaging a portion of a design layout onto a substrate using a lithographic apparatus, the method comprising:
computing, by a hardware computer, a multi-variable cost function, the multi-variable cost function comprising a function expressing a size or edge location characteristic of an aerial image or resist image of the design layout summed with a function pertaining to stochastic variation of a characteristic of the aerial or resist image, the function pertaining to stochastic variation being a function expressing the stochastic variation, or being a function of a variable that is a function of the stochastic variation, or being a function of a variable that affects the stochastic variation, the stochastic variation being a function of a plurality of design variables that represent one or more characteristics of the lithographic process; and
reconfiguring one or more of the characteristics of the lithographic process by adjusting one or more of the design variables until a certain termination condition is satisfied.
2. The method of claim 1 , wherein the stochastic variation comprises line edge roughness, line width roughness, local critical dimension uniformity, or any combination selected from the foregoing.
3. The method of claim 1 , wherein the cost function is a function of one or more of the following: edge placement error, critical dimension, resist contour distance, worst defect size, and/or best focus shift.
4. The method of claim 1 , wherein the function pertaining to stochastic variation is a first term of the multi-variable cost function and a function of at least a change of dose, and the function of the size or edge location characteristic is a second term of the multi-variable cost function and that is a function expressing edge placement error.
5. The method of claim 4 , wherein a weight of the second term has a greater value when an absolute value of the edge placement error is greater than an offset than a value of the weight when the absolute value of the edge placement error is not greater than the offset.
6. The method of claim 1 , wherein the design variables comprise one or more selected from: blurred image log slope (bl_ILS), image log slope (ILS), normalized image log slope (NILS), blurred image intensity, image intensity, global bias, mask anchor bias and/or dose.
7. A method to improve a lithographic process of imaging a portion of a design layout onto a substrate using a lithographic apparatus, the method comprising:
computing, by a hardware computer, a multi-variable cost function, the multi-variable cost function being a function of a size or edge location characteristic of an aerial image or resist image of the design layout, of a stochastic variation of a characteristic of the aerial or resist image, the stochastic variation being a function of a parameter pertaining to image log slope, and of a constant parameter representing a change in dose; and
reconfiguring one or more of the characteristics of the lithographic process by adjusting one or more of the design variables until a certain termination condition is satisfied.
8. The method of claim 7 , wherein the parameter pertaining to image log slope comprises blurred image log slope, image log slope, or normalized image log slope.
9. The method of claim 7 , wherein the cost function comprises a first term corresponding to the size or edge location characteristic summed with a second term corresponding to the stochastic variation and the constant parameter representing a change in dose.
10. The method of claim 9 , wherein a weight of the first term has a greater value when an absolute value of the size or edge location characteristic is greater than an offset than a value of the weight when the absolute value of the size or edge location characteristic is not greater than the offset.
11. A non-transitory computer-readable medium comprising instructions therein that when executed by a computer system are configured to cause the computer system to at least:
computing, by a hardware computer, a multi-variable cost function, the multi-variable cost function being a function of a size or edge location characteristic of an aerial image or resist image of a portion of a design layout for transfer onto a substrate using a lithographic apparatus in a lithographic process, of a stochastic variation of a characteristic of the aerial image or image, the stochastic variation being a function of a parameter pertaining to image log slope, and of a constant parameter representing a change in dose; and
reconfiguring one or more of the characteristics of the lithographic process by adjusting one or more of the design variables until a certain termination condition is satisfied.
12. The computer-readable medium of claim 11 , wherein the parameter pertaining to image log slope comprises blurred image log slope, image log slope, or normalized image log slope.
13. The computer-readable medium of claim 11 , wherein the cost function comprises a first term corresponding to the size or edge location characteristic summed with a second term corresponding to the stochastic variation and the constant parameter representing a change in dose.
14. The computer-readable medium of claim 13 , wherein a weight of the first term has a greater value when an absolute value of the size or edge location characteristic is greater than an offset than a value of the weight when the absolute value of the size or edge location characteristic is not greater than the offset.
15. A non-transitory computer-readable medium comprising instructions therein that when executed by a computer system are configured to cause the computer system to at least:
compute a multi-variable cost function, the multi-variable cost function comprising a function expressing a size or edge location characteristic of an aerial image or resist image of a portion of a design layout for transfer onto a substrate using a lithographic apparatus in a lithographic process summed with a function pertaining to a stochastic variation of a characteristic of the aerial or resist image, the function pertaining to stochastic variation being a function expressing the stochastic variation, or being a function of a variable that is a function of the stochastic variation, or being a function of a variable that affects the stochastic variation, the stochastic variation being a function of a plurality of design variables that represent one or more characteristics of the lithographic process; and
reconfigure one or more of the characteristics of the lithographic process by adjusting one or more of the design variables until a certain termination condition is satisfied.
16. The computer-readable medium of claim 15 , wherein the stochastic variation comprises line edge roughness, line width roughness, local critical dimension uniformity, or any combination selected from the foregoing.
17. The computer-readable medium of claim 15 , wherein the cost function is a function of one or more of the following: edge placement error, critical dimension, resist contour distance, worst defect size, and/or best focus shift.
18. The computer-readable medium of claim 15 , wherein the function pertaining to stochastic variation is a first term of the multi-variable cost function and is a function of at least a change of dose, and the function of the size or edge location characteristic is a second term of the multi-variable cost function and is a function expressing an edge placement error.
19. The computer-readable medium of claim 18 , wherein a weight of the second term has a greater value when an absolute value of the edge placement error is greater than an offset than a value of the weight when the absolute value of the edge placement error is not greater than the offset.
20. The computer-readable medium of claim 15 , wherein the design variables comprise one or more selected from: blurred image log slope (bl_ILS), image log slope (ILS), normalized image log slope (NILS), blurred image intensity, image intensity, global bias, mask anchor bias and/or dose.