Prosecution Insights
Last updated: April 19, 2026
Application No. 18/714,728

SYSTEMS AND METHODS FOR OPTIMIZING LITHOGRAPHIC DESIGN VARIABLES USING IMAGE-BASED FAILURE RATE MODEL

Non-Final OA §102
Filed
May 30, 2024
Examiner
KIM, PETER B
Art Unit
2882
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
ASML Netherlands B.V.
OA Round
1 (Non-Final)
83%
Grant Probability
Favorable
1-2
OA Rounds
2y 8m
To Grant
92%
With Interview

Examiner Intelligence

Grants 83% — above average
83%
Career Allow Rate
776 granted / 938 resolved
+14.7% vs TC avg
Moderate +9% lift
Without
With
+9.1%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
34 currently pending
Career history
972
Total Applications
across all art units

Statute-Specific Performance

§101
2.2%
-37.8% vs TC avg
§103
41.2%
+1.2% vs TC avg
§102
24.3%
-15.7% vs TC avg
§112
19.0%
-21.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 938 resolved cases

Office Action

§102
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claim Rejections - 35 USC § 102 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claim(s) 1, 2, 5-7 and 17-31 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hansen (WO 2020/094389 in IDS). Regarding claim 1, Hansen discloses a method (Fig. 6, para 0008, 0009) for determining a value of a design variable of a lithographic process based on a predicted failure rate for printing a target pattern on a substrate using a lithographic apparatus (Fig. 1, para 00109-00111), the method comprising: obtaining an image corresponding to a target pattern to be printed on a substrate using a lithographic apparatus, wherein the image is generated based on a set of values of design variables of the lithographic apparatus or a lithographic process (Fig. 6, para 00125, 00128, the failure model can take and image and dose values and predict a failure rate, image obtained from simulation of the patterning process); determining image properties, the image properties representative of a pattern printed on the substrate, the pattern corresponding to the target pattern (Fig. 6, para 00128-00130, an image intensity value obtained from the simulation of lithographic models data); predicting, by a hardware computer system (Fig. 30, computer system, para 00255), a failure rate in printing the pattern on the substrate based on the image properties (Fig. 6, para 00131, using processor applying the values of dose and intensity to predict a value of a pattern failure); and determining a specified value of a specified design variable based on the failure rate, the specified value to be used in the lithographic process to print the target pattern on the substrate (Fig. 6, para 00146, using the predicted value of failure for adjusting a parameter of patterning process). Regarding claim 17, Hansen discloses a non-transitory computer readable medium having instructions therein (para 00040, 00252), the instructions, when executed by a computer system, configured to cause the computer system to at least: obtain an image corresponding to a target pattern to be printed on a substrate using a lithographic apparatus, wherein the image is generated based on a set of values of design variables of the lithographic apparatus or a lithographic process (Fig. 6, para 00125, 00128, the failure model can take and image and dose values and predict a failure rate, image obtained from simulation of the patterning process); determine image properties, the image properties representative of a pattern printed on the substrate, the pattern corresponding to the target pattern (Fig. 6, para 00128-00130, an image intensity value obtained from the simulation of lithographic models data); predict a failure rate in printing the pattern on the substrate based on the image properties (Fig. 6, para 00131, using processor applying the values of dose and intensity to predict a value of a pattern failure); and determine a specified value of a specified design variable based on the failure rate, the specified value to be used in the lithographic process to print the target pattern on the substrate (Fig. 6, para 00146, using the predicted value of failure for adjusting a parameter of patterning process). Regarding claims 2 and 18, Hansen discloses wherein the instructions configured to cause the computer system to determine a specified value are further configured to cause the computer system (para 00040, 00252) to determine a value of the specified design variable for which a predicted failure rate satisfies a failure rate condition (Fig. 20, para 00192, for each dose-focus values, maximum failure rate of the multiple failure modes is selected to generate the combined failure process window). Regarding claim 19, Hansen discloses wherein the instructions configured to cause the computer system (para 00040, 00252) to determine a specified value are further configured to cause the computer system to determine the value for which a throughput value satisfies a throughput condition (para 00206, cost function represent suitable characteristics such as throughput). Regarding claim 20, Hansen discloses wherein the instructions configured to cause the computer system (para 00040, 00252) to determine, based on the failure rate, at least one selected from: a mask bias value, a pupil shape, a target critical dimension value, a dose value, and/or a focus value (Fig. 20, para 00192). Regarding claims 5 and 21, Hansen discloses wherein the instructions configured to cause the computer system (para 00040, 00252) to predict the failure rate are further configured to cause the computer system to: obtain (a) a set of images of a specified pattern to be printed on a specified substrate, wherein each image of the set of images is generated based on different sets of values of the design variables (para 00125-0127), and (b) measured failure rates, wherein each failure rate corresponds to a set of values of the different sets of values of the design variables and correlate the measured failure rates with image properties of the set of images to predict the failure rate, wherein the image corresponding to the target pattern is an aerial image, a resist image, an etch image, or a mask image (para 00127-0131, 00135-00137, 00192). Regarding claims 6 and 22, Hansen discloses wherein the instructions configured to cause the computer system (para 00040, 00252) to determine the image properties are further configured to cause the computer system to extract, by a lithographic model, at least one selected from: (a) a product of peak intensity and dose (para 00128, image intensity value is a peak image intensity), (b) a product of intensity integral and dose (para 00128, the image intensity value that is used as a multiplier of the dose), and/or (c) image log slope from the aerial image (para 00133, 00136). Regarding claims 7 and 23, Hansen discloses wherein the instructions configured to cause the computer system (para 00040, 00252) to obtain the image are further configured to cause the computer system to: provide a first set of values of the design variables as input to a lithographic model, wherein the lithographic model is configured to generate aerial images of patterns to be printed on the substrate; and generate, by the lithographic model, a first aerial image based on the first set of values (para 00144, Fig. 9C). Regarding claim 24, Hansen discloses wherein the lithographic model is configured to generate the aerial image by: obtaining of mean critical dimension measurements of a specified pattern for different sets of values of the design variables (para 00142, 00144, CD); and training of the lithographic model to generate a specified aerial image of the specified pattern for each set of values of the different sets of values of the design variables (para 00125, 00127, 00135, 00153, aerial image). Regarding claim 25, Hansen discloses wherein the instructions configured to cause the computer system to determine a specified value are further configured to cause the computer system (para 00040, 00252) to determine, based on the failure rate, an illumination variable of an illumination and/or a mask variable of a mask pattern in an illumination-mask optimization process (para 00200-00206, illumination source can also be optimized, source-mask optimization SMO). Regarding claim 26, Hansen discloses wherein the instructions configured to cause the computer system to determine the illumination variable and/or the mask variable are further configured to cause the computer system to: compute a cost function to determine, based on the failure rate, the illumination variable and/or the mask variable; and determine the illumination variable and/or the mask variable by minimization of the cost function (para 00202-00206, 00210). Regarding claim 27, Hansen discloses wherein the instructions configured to cause the computer system (para 0040, 00252) to compute the cost function are further configured to cause the computer system to: compute a gradient of the cost function for the illumination variable and/or the mask variable (para 00216, 00222); and determining the illumination variable and/or the mask variable by minimization of the gradient of the cost function (para 00215, 00216, 00222). Regarding claim 28, Hansen discloses wherein the instructions configured to cause the computer system to compute the cost function are further configured to cause the computer system to: compute a gradient of the failure rate for an aerial image associated with the target pattern (para 000190); and determine the illumination variable and/or the mask variable by minimization of the gradient of the failure rate (para 000190, 00216, 00222). Regarding claim 29, Hansen discloses wherein the design variables include a critical dimension of the target pattern printed on the substrate (para 00142, 00144, 00206, 00243), a mask bias, or a mask type (para 00208). Regarding claim 30, Hansen discloses wherein the design variables include a pupil of an illumination within the lithographic apparatus (para 00210), a dose of the illumination (para 00126, 00127, 00130), or a focus associated with radiation from the illumination (para 00144, 00146). Regarding claim 31, Hansen discloses wherein the instructions configured to cause the computer system to determine a specified value are further configured to cause the computer system to determine at least one selected from: a mask bias value, a pupil shape, a target critical dimension value, a dose value, and/or a focus value (para 00126, 00142, 00144, 00146), for which a lithographic metric satisfies a specified condition and a throughput value satisfies a throughput condition, wherein the lithographic metric includes one or more selected from: a depth of focus, an exposure latitude, a local critical dimension uniformity, and/or the failure rate (para 00202-00210). Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Kooiman et al. (2022/0342316) discloses determining failure rate based on characteristic values of feature from an image from simulation (para 0228, 0321). Any inquiry concerning this communication or earlier communications from the examiner should be directed to PETER B KIM whose telephone number is (571)272-2120. The examiner can normally be reached M-F 8:00 AM - 4:00 PM. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Toan Ton can be reached at (571) 272-2303. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /PETER B KIM/Primary Examiner, Art Unit 2882 January 5, 2026
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Prosecution Timeline

May 30, 2024
Application Filed
Jan 05, 2026
Non-Final Rejection — §102 (current)

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Prosecution Projections

1-2
Expected OA Rounds
83%
Grant Probability
92%
With Interview (+9.1%)
2y 8m
Median Time to Grant
Low
PTA Risk
Based on 938 resolved cases by this examiner. Grant probability derived from career allow rate.

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