Prosecution Insights
Last updated: October 02, 2026
Application No. 19/009,546

ABERRATION IMPACT SYSTEMS, MODELS, AND MANUFACTURING PROCESSES

Non-Final OA §102§103§DOUBLEPATENT
Filed
Jan 03, 2025
Priority
Jun 10, 2020 — provisional 63/037,494 +3 more
Examiner
PERSAUD, DEORAM
Art Unit
Tech Center
Assignee
ASML Holding N.V.
OA Round
1 (Non-Final)
77%
Grant Probability
Favorable
1-2
OA Rounds
1y 0m
Est. Remaining
89%
With Interview

Examiner Intelligence

Grants 77% — above average
77%
Career Allowance Rate
593 granted / 771 resolved
+16.9% vs TC avg
Moderate +12% lift
Without
With
+12.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 9m
Avg Prosecution
24 currently pending
Career history
801
Total Applications
across all art units

Statute-Specific Performance

§101
3.7%
-36.3% vs TC avg
§103
48.0%
+8.0% vs TC avg
§102
31.4%
-8.6% vs TC avg
§112
6.9%
-33.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 771 resolved cases

Office Action

§102 §103 §DOUBLEPATENT
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 . Specification The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification. Double Patenting The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. Claims 1-15 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12,210,291 B2, issued to Peng et al. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of application 19/009546 are directed to the same invention of the claims of US 12, 210,291 B2. In this instance the claims of application 19/009546 are broader than those of US 12, 210,291 B2. As such, the claims of application 19/009546 are met by the claim of US 12, 210,291 B2. Claims 1-15 are met by claims 1-15 of US 12, 210,291 B2 Claim Rejections - 35 USC § 102 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1-5, 8 and 10 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Hsu et al. [WO 2020/002143 A1]. Regarding claim 1, Hsu et al. discloses a non-transitory computer readable medium having instructions therein, the instructions (Fig. 20, paragraphs [0240]-[0246]), when executed by a computer system, configured to cause the computer system to at least: execute a calibrated model configured to receive patterning system aberration data (as shown in Fig. 3, see also paragraphs [0122]-[0125]), the model calibrated with patterning system aberration calibration data and corresponding patterning process impact calibration data (as shown in Fig. 3, see also paragraphs [0122], [0123] and [0126]); and determine, based on the model, new patterning process impact data for the received patterning system aberration data (as shown in Fig. 3, see also paragraphs [0126], [0127] and [0131]), wherein the model comprises a hyperdimensional function configured to correlate the received patterning system aberration data with the new patterning process impact data in a simplified form without calculation of an aerial image representation (as shown in Fig. 3, see also paragraphs [0127]-[0130]). Regarding claims 2 and 4, Hsu et al. discloses wherein the model is calibrated by providing patterning system aberration calibration data to a base model to obtain a prediction of the patterning process impact calibration data, and using the patterning process impact calibration data as feedback to update one or more configurations of the base model, wherein the one or more configurations are updated based on a comparison between the patterning process impact calibration data and the prediction of the patterning process impact calibration data (as shown in Fig. 3, see also paragraphs [0127]-[0131]), wherein the patterning system aberration calibration data are simulated based on associated pupil shapes and layer-specific patterning device designs (paragraph [0194], see also Fig. 14). Regarding claim 3, Hsu et al. discloses wherein the model comprises a linear or quadratic algorithm or a combination thereof (paragraphs [0192] and [0197]). Regarding claim 5, Hsu et al. discloses wherein the new patterning process impact data comprises a cost function for a corresponding patterning system aberration, s(Z), the patterning system aberration defined by the received patterning system aberration data, wherein the cost function s(Z) is indicative of an impact on the patterning process caused by the corresponding patterning system aberration (paragraphs [0135]-[0137]). Regarding claim 8, Hsu et al. discloses wherein the new patterning process impact data from the model is configured to be used to determine a set of patterning process control metrics (Fig. 3, paragraph [0123]), the set of patterning process control metrics configured to be determined by a linear solver (paragraphs [0192] and [0197]). Regarding claim 10, Hsu et al. discloses wherein the set of patterning process control metrics comprises one or more lithography metrics, and wherein the new patterning process impact data is indicative of an impact, by a corresponding patterning system aberration, on one or more selected from: a critical dimension, a pattern placement error, an edge placement error, critical dimension asymmetry, a best focus shift, or a defect count associated with a patterning process (paragraphs [0123], [0135]-[0137], see also Fig. 3). Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 6, 7 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Hsu et al. in view of Akhssay et al. [US 7,262,831 B2]. Regarding claims 6, 7 and 11, Hsu et al. discloses the medium, as applied above. Hsu et al. does not teach wherein the new patterning process impact data from the model is configured to be provided to a second model to enable dynamic in-situ aberration control of a patterning system, wherein the second model is a projection optics correction model, wherein the patterning system comprises a scanner, and wherein dynamic in-situ control of the scanner comprises generating a corrected scanner control parameter recipe for a given scanner aberration to optimize a set of lithography performance metrics, wherein the model is calibrated such that the new patterning process impact data is configured to facilitate enhanced control of an effect from heating of one or more mirrors and/or lenses of the patterning system. However, Akhssay et al. discloses a lithographic projection apparatus that includes a measurement system for measuring changes in projection system aberrations with time, and a predictive control system for predicting variation of projection system aberrations with time on the basis of model parameters and for generating a control signal for compensating a time-varying property of the apparatus wherein the new patterning process impact data from the model is configured to be provided to a second model to enable dynamic in-situ aberration control of a patterning system, wherein the second model is a projection optics correction model, wherein the patterning system comprises a scanner, and wherein dynamic in-situ control of the scanner comprises generating a corrected scanner control parameter recipe for a given scanner aberration to optimize a set of lithography performance metrics, wherein determining the set of patterning process control metrics comprises performing a singular value decomposition on a cost function Hessian (Col. 24 line 33 – Col. 25 line 27, see also Fig. 5). Therefore, it would have been obvious to one of ordinary skill in the art to include a second model for dynamic in-situ aberration control for generating corrected scanner control parameters, as taught by Akhssay et al. in the system of Hsu et al. because such a modification provides adjustments to the projection system of lithographic projection apparatus to compensate for the effect of lens aberrations in such a manner as to correct for predictive errors based on imprecisely known aberrations and to reduce the throughput loss caused by unnecessary alignment step (Col. 7 lines 31-36 of Akhssay et al.). Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Hsu et al. in view of Tsiatmas et al. [EP 3 444 674 A1]. Regarding claim 9, Hsu et al. discloses the medium, as applied above. Hsu et al. does not teach wherein determining the set of patterning process control metrics comprises performing a singular value decomposition on a cost function Hessian. However, Tsiatmas et al. discloses determining the set of patterning process control metrics comprises performing a singular value decomposition on a cost function Hessian (paragraphs [0150]-[0155], see also Fig. 14). Therefore, it would have been obvious to one of ordinary skill in the art to include a step of performing a singular value decomposition on a cost function Hessian as taught by Tsiatmas et al. in the system of Hsu et al. because such a modification provides fine tuning of the processing parameter (paragraph [0155] of Tsiatmas et al.). Claims 12-15 are rejected under 35 U.S.C. 103 as being unpatentable over Hsu et al. in view of Ye et al. [EP 2 028 546 A2]. Regarding claims 12 and 13, Hsu et al. discloses the medium, as applied above. Hsu et al. does not teach wherein the new patterning process impact data from the model is configured to be provided to a cost function to facilitate determination of costs associated with individual patterning process metrics and/or costs associated with individual patterning process variables, and wherein the costs associated with individual patterning process metrics and/or costs associated with individual patterning process variables are configured to be used to facilitate co-optimization of multiple scanners, wherein the model comprises one or more critical feature components configured to model scanner to scanner variation for critical features of a patterning process; and one or more regulation components configured to model generic performance across scanners for non-critical features of the patterning process. However, Ye et al. discloses a model-based tuning method for tuning a lithography system wherein the new patterning process impact data from the model is configured to be provided to a cost function to facilitate determination of costs associated with individual patterning process metrics and/or costs associated with individual patterning process variables, and wherein the costs associated with individual patterning process metrics and/or costs associated with individual patterning process variables are configured to be used to facilitate co-optimization of multiple scanners, wherein the model comprises one or more critical feature components configured to model scanner to scanner variation for critical features of a patterning process; and one or more regulation components configured to model generic performance across scanners for non-critical features of the patterning process (paragraphs [0030]-[0038] and [0044]-[0046], see also Figs. 1 and 2). Therefore, it would have been obvious to one of ordinary skill in the art to include a cost function configured to co-optimize multiple scanners with respect to critical feature components as taught by Ye et al. in the system of Hsu et al. because such a modification provides fine tuning of the processing parameter (paragraphs [0044]-[0046] of Ye et al.). Regarding claim 14, Hsu et al. discloses wherein the cost function comprises two or more selected from: a first component associated with critical features of a patterning process, a second component associated with non-critical features of a patterning process, and/or a third component associated with physical functional limitations of one or more scanners (paragraphs [0135]-[0137], see also Fig. 3). Regarding claim 15, Hsu et al. discloses wherein the co-optimization comprises using lens actuators as variables, and a gradient based non-linear optimizer to co-determine actuator positions for multiple scanners (paragraphs [0216]-[0238], Figs. 18 and 19). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to DEORAM PERSAUD whose telephone number is (571)270-5476. The examiner can normally be reached M-F 8AM-5PM. 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, Minh-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. /DEORAM PERSAUD/Primary Examiner, Art Unit 2882
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Prosecution Timeline

Jan 03, 2025
Application Filed
Aug 31, 2026
Non-Final Rejection mailed — §102, §103, §DOUBLEPATENT (current)

Precedent Cases

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
77%
Grant Probability
89%
With Interview (+12.0%)
2y 9m (~1y 0m remaining)
Median Time to Grant
Low
PTA Risk
Based on 771 resolved cases by this examiner. Grant probability derived from career allowance rate.

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