Prosecution Insights
Last updated: April 19, 2026
Application No. 17/742,733

METHOD FOR DETERMINING A REGISTRATION ERROR

Final Rejection §102§Other
Filed
May 12, 2022
Examiner
RODGERS, ALEXANDER JOHN
Art Unit
2661
Tech Center
2600 — Communications
Assignee
Carl Zeiss Smt GmbH
OA Round
4 (Final)
70%
Grant Probability
Favorable
5-6
OA Rounds
3y 2m
To Grant
77%
With Interview

Examiner Intelligence

Grants 70% — above average
70%
Career Allow Rate
23 granted / 33 resolved
+7.7% vs TC avg
Moderate +7% lift
Without
With
+7.0%
Interview Lift
resolved cases with interview
Typical timeline
3y 2m
Avg Prosecution
12 currently pending
Career history
45
Total Applications
across all art units

Statute-Specific Performance

§101
10.1%
-29.9% vs TC avg
§103
43.4%
+3.4% vs TC avg
§102
26.0%
-14.0% vs TC avg
§112
19.8%
-20.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 33 resolved cases

Office Action

§102 §Other
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 . Response to Arguments Applicant's arguments and amendment filed 09 June 2025 with respect to rejection under U.S.C. 102(a)(1) of Claims 1-24 have been fully considered but are not persuasive. Regarding Claim 1, applicant states: “Tel does not disclose ‘generating an image of at least one region of the mask, ... determining at least one measuring contour in the image…wherein the image is an aerial image generated by a mask inspection microscope or an electron microscope’”. Before diving into Tel, it should be noted the interpretation of the claims which follows the broadest interpretation of the claim language in light of the specification. The claim reads “generating an image of at least one region of a mask” and “wherein the image is an aerial image generated by a mask inspection microscope or an electron microscope”. Therefore, the interpretation taken of this claim language reads only generating an image of some region of a mask. Not of taking an image of the mask itself (to which it must be noted there is also no strict mention of taking an image of a mask with a microscope in applicant specification, but rather only that edge detection is used to detect structures and that the microscopes listed are used for determining the registration error. The closest paragraph is in the Background, Specification paragraph 0003). Therefore, the generation of any images containing regions of masks and not strictly the capturing of images of the mask itself would read on instances of the mask such as images of the mask printed on a substrate as well as being in the form of a design layout (See Tel Specification paragraph 0098) or patterning device or any device which contains a region of the mask and need not necessarily include the mask or reticle itself. Therefore, a broader interpretation of the claims has been taken throughout the course of examination in all actions up to this point to include images of mask regions which might include images constituting patterning device, design layout, and reticle (See Tel Specification paragraph 0098 describing the interchangeable use of these terms) or images of those patterns as they are projected onto surfaces such as substrates as the claim language specifically states “generating an image of at least one region of the mask” and at no point described a literal picture taken of a mask or reticle being taken, but rather speaks to generating images of regions of a mask. Further, there is an interchangeable uses of the aerial and resist images shown throughout Tel (See Specification paragraph 0043, 0048, 0053, 0054, 0055, 0062) which has also been now more thoroughly described in the rejection below for improved clarity in conjunction with the design layout/patterning device/mask term interpretations. Finally, the resist image being a projection of regions of the mask itself is an image of the regions of the mask, or in other words, the resist image is an image of regions of the mask itself carved into the substrate (See Specification paragraph 0080 also describing the coupling of these different images how this resist image can be simulated from the aerial image which in turn is simulated from the mask or design layout itself). 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)(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. Claims 1-24 are rejected under 35 U.S.C. 102a(1) as being anticipated by Tel et al (US Publication No. 20210149312 A1). Regarding Claim 1, Tel discloses A method for determining a registration error (Reference “edge placement error” or “EPE”, see Specification paragraph 0011 and Specification paragraph 0089 where an image-related metric EPE is defined as an edge placement error. See Figure 29 showing a general method flow which will be referenced) of a structure on a mask for use in semiconductor lithography (Reference “lithography” and “patterning device”, see Specification paragraph 0089 further describing this edge placement error in relation to how “stochastic variations affect lithography” in relation to an actual edge and an error which includes a patterning device or mask. See Figure 29 step 2901 describing a layout onto the substrate using a lithographic apparatus. Also see paragraph 0098 describing the interchangeable nature of mask, patterning device, design layout, and reticle) , comprising: - generating an image of at least one region of the mask (Reference “patterning device” and “mask”, see Specification paragraph 0186 where imaging setup of the patterning device or mask is described allowing beams to “focus on portion C of the substrate W”. See Figures 28 as an example generated image and Figure 29 steps 2901 describing the imaging of a portion of a design layout onto a substrate. Also see paragraph 0098 describing the interchangeable nature of mask, patterning device, design layout, and reticle. The resist image being a projection of regions of the mask itself is an image of the regions of the mask, or in other words, the resist image is an image of regions of the mask itself carved into the substrate). - determining at least one measuring contour in the image (Reference “contour”, see Specification paragraph 0011 where a contour is described and a target contour is described. Further See Figure 29 Step 2905 describing the calculation of image related metrics from a contour from the image), and - matching the forms of a design contour and the measuring contour to one another (Reference “contour”, see Specification paragraph 0204 where the contours are matched to one another and it is noted the difference in curved target contour vs rectangular actual manufactured contour described and shown in Figures 27A-D. See the stacking of contours which is the matching performed and shows the contours used in calculations). while at the same time registering the two contours to one another (Reference “contour”, see Specification paragraph 0205 where the aforementioned image related metrics are calculated between these same contours of feature—from an image—and a corresponding target contour. Which in regard to metrics or errors measured such as Edge Placement Error read as registering the two contours to one another. Also note Figure 29 showing steps 2905 and 2907 where metrics and parameters determined from these images), wherein the matching and registering comprises optimizing a set of parameters (Reference “cost function” and “parameters”, see Specification paragraph 0078 describing the process as optimizing a cost function by finding a set of parameters where the cost function can be a root mean square of characteristics or evaluation points. This Cost function is further described in Specification paragraph 0110) comprising at least one form parameter and at least one registration parameter (Examiner’s Note, see application Figure 0002 showing registration parameter Rotation as well as Specification page 5 row 20-25 describing these registration parameters. Similarly note Bias when referring to form parameters described in page 6 rows 5-15. Returning to Tel et al, Reference “parameter”, See Specification paragraph 0110 where possible registration parameters of the cost function include image rotation. Further note the parameter bias which as noted above would be a form parameter), wherein the image is an aerial image generated by a mask inspection microscope or an electron microscope (Reference “aerial image”, see Specification paragraph 0079 further describing the aerial image as being a radiation intensity distribution which is transferred into a resist image. Also see paragraphs 0043 0048 and 0053 which show the above measurements and stochastic variations described above taken in either the resist or aerial image. See Specification paragraph 0043, 0048, 0053, 0054, 0055, 0062 which show the interchangeable uses of these aerial and resist images. See Figure 28 showing an example aerial view while specifics of the electron microscope described later as Reference “SEM”, see Specification paragraph 0240 where the images described above may be obtained with a scanning electron microscope. Also note the definition of mask in paragraph 0069 classifying this microscope as a mask inspection microscope as it inspects the structures of a substrate in lithographic process). Regarding Claim 2, Tel discloses The method of Claim 1 wherein the registering comprises minimizing the mean of lateral distances between the two contours in the image plane (Reference “cost function” and “EPE”, see Specification paragraph 0110 as noted above where the EPE is listed as a possible parameter used in the cost function and further note in Specification paragraph 0089 where the EPE or edge placement error is a difference between average location and intended location. Further note optimization of the EPE terms described in paragraph 0114 where edge locations are described as being with respect to the x direction from the aerial image as previously described and the smaller EPE which is added to the cost function). Regarding Claim 3, Tel discloses The method of Claim 1 wherein the matching and registering of the contours is brought about by a modification of the design contour (Reference “design layout, see Specification paragraph 0118 where the optimization of the cost function includes design layout as characteristic or parameter input to cost function described above) and wherein the set of parameter being optimized is for the design contour (Reference “design variables”, see Specification paragraph 0118 where the design layout which is one of the design variables able to optimized until convergence is met in the cost function). Regarding Claim 4, Tel discloses The method of Claim 1 wherein the matching and the registering of the contours is brought about by a modification of the measuring contour and wherein the set of parameter being optimized is for the measuring contour (Reference “feature contour”, see Specification paragraph 0218 where relations between feature contours and target or design contours are described and the relations of them can be controlled by the set of parameters. Further note in Specification paragraph 0206 where specifically how a contour is created can be altered by the user or programmatically found and this is further described with respect to its relevant controllable parameters described in Specification paragraph 0207 that affect the contours of the feature). Regarding Claim 5, Tel discloses The method of Claim 1 wherein lateral distances between the measuring contour and the design contour are used as a measure of quality to iteratively optimize the set of parameters (Reference “EPE”, see rejection of Claim 2 above where the edge placement error is used to optimize the cost function. Further note the preferred metric or measure of quality is Edge Placement Error as an overall representation of differences between the feature measured and target contour. Further note in Specification paragraph 0118 as described above the cost function further uses a threshold to determine how many iterations are required to perform this optimization). Regarding Claim 6, Tel discloses The method of Claim 5 wherein the iterative optimization comprises a multidimensional Newton method (Reference “multi-variable” and “Gauss-Newton”, see Specification paragraph 0124 where the optimization process is a Gauss Newton Algorithm. This algorithm is further described in paragraph 0125 where the algorithm is descried as having multiple input variable algorithm which reads as multi-dimensional further these variables are of different domains, measurement types or directions from a series of multiple aerial images or layouts and are multidimensional in that regard as well). Regarding Claim 7, Tel discloses The method of Claim 5 wherein the mean value of all the lateral distances is used as the measure of quality made in the iterative optimization (Reference “EPE”, see Specification paragraph 0205 as noted previously where EPE is used as measure of quality for overall representation of the differences between the contours. Further note Specification paragraph 0112 describing the summation of all lengths measured as error in EPE and the ability to sum all of these due to their nature as a length to reach the EPE calculated and describing further alternatives to calculating this EPE). Regarding Claim 8, Tel discloses The method of Claim 1 wherein the optimizing is performed separately for individual subregions of the image (Reference “optimization” and “divided”, see Specification paragraph 0142 and 0143 where the optimization process is described and where in this process the illumination, which is one of design variables input to cost function, is divided into pixel groups which read as subregions of an image). Regarding Claim 9, Tel discloses The method of Claim 1 wherein certain regions of the image are not used for the optimizing (Reference “filter”, see Specification paragraph 0075 where radiation presumably from the electron microscope mentioned in rejection of Claim 1 is filtered to remove undiffracted radiation from unaddressed areas which reflect undiffracted radiation. Also note in Specification paragraph 0087 where only certain locations, the locations of edges for example, are actually used when determining metrics such as critical dimension or edge placement error.). Regarding Claim 10, Tel discloses The method of Claim 1 wherein the regions that are not used for the optimizing are regions in which defects have been detected (Reference “undiffracted”, see Specification paragraph 0075 where the areas removed or filtered are areas where undiffracted radiation is being reflected to the apparatus and these are the areas that removed as having defect detected in image). Regarding Claim 11, Tel discloses The method of Claim 1 wherein an alternating modification of the one or more form parameters and a calculation of a mean of lateral distances between the contours is performed (Reference “cost function”, see Specification paragraph 0118 as described previously where biases or EPEs describing estimated or mean lateral distances between contours are described as parameters for optimization in the cost function. Also noting the form parameter previously described as a bias in rejection of Claim 1). Regarding Claim 12, Tel discloses The method of Claim 2 wherein the matching and registering of the contours is brought about by a modification of the design contour (Reference “design layout, see Specification paragraph 0118 where the optimization of the cost function includes design layout as characteristic or parameter input to cost function described above. Note this is the same cost function as referenced in Claim 2) and wherein the set of parameter being optimized is for the design contour (Reference “design variables”, see Specification paragraph 0118 where the design layout which is one of the design variables able to optimized until convergence is met in the cost function. Note this is the same cost function as referenced in Claim 2). Regarding Claim 13, Tel discloses The method of Claim 2 wherein the matching and the registering of the contours is brought about by a modification of the measuring contour and wherein the set of parameter being optimized is for the measuring contour (Reference “feature contour”, see Specification paragraph 0218 where relations between feature contours and target or design contours are described and the relations of them can be controlled by the set of parameters. Further note in Specification paragraph 0206 where specifically how a contour is created can be altered by the user or programmatically found and this is further described with respect to its relevant controllable parameters described in Specification paragraph 0207 that affect the contours of the feature. Note this is the same set of parameters describing the cost function referenced in Claim 2) Regarding Claim 14, Tel discloses The method of Claim 2 wherein lateral distances between the measuring contour and the design contour are used as a measure of quality to iteratively optimize the set of parameters (Reference “EPE”, see rejection of Claim 2 above where the edge placement error is used to optimize the cost function. Further note the preferred metric or measure of quality is Edge Placement Error as an overall representation of differences between the feature measured and target contour. Further note in Specification paragraph 0118 as described above the cost function further uses a threshold to determine how many iterations are required to perform this optimization. This is the same cost function referenced in Claim 2). Regarding Claim 15, Tel discloses The method of Claim 2 wherein the optimizing is performed separately for individual subregions of the image (Reference “optimization” and “divided”, see Specification paragraph 0142 and 0143 where the optimization process is described and where in this process the illumination, which is one of design variables input to cost function, is divided into pixel groups which read as subregions of an image. Note this is the same cost function referenced in rejection of claim 2). Regarding Claim 16, Tel discloses The method of Claim 2 wherein certain regions of the image are not used for the optimizing (Reference “filter”, see Specification paragraph 0075 where radiation presumably from the electron microscope mentioned in rejection of Claim 1 is filtered to remove undiffracted radiation from unaddressed areas which reflect undiffracted radiation. Also note in Specification paragraph 0087 where only certain locations, the locations of edges for example, are actually used when determining metrics such as critical dimension or edge placement error. Note these are the metrics and parameters used in the cost function described in Claim 2, specifically edge placement error). Regarding Claim 17, Tel discloses The method of Claim 2 wherein an alternating modification of the one or more form parameters and a calculation of a mean of lateral distances between the contours is performed (Reference “cost function”, see Specification paragraph 0118 as described previously where biases or EPEs describing estimated or mean lateral distances between contours are described as parameters for optimization in the cost function. Also noting the form parameter previously described as a bias in rejection of Claim 1 and the cost function is the same as previously described in rejection of Claim 2). Regarding Claim 18, Tel discloses The method of Claim 3 wherein the matching and the registration of the contours is brought about by a modification of the measuring contour and wherein the set of parameter being optimized is for the measuring contour (Reference “feature contour”, see Specification paragraph 0218 where relations between feature contours and target or design contours are described and the relations of them can be controlled by the set of parameters. Further note in Specification paragraph 0206 where specifically how a contour is created can be altered by the user or programmatically found and this is further described with respect to its relevant controllable parameters described in Specification paragraph 0207 that affect the contours of the feature. Note this set of parameters and cost function is the same cost function referenced in rejection of Claim 3 as these can be controlled simultaneously by the same cost function). Regarding Claim 19, Tel discloses The method of Claim 3 wherein lateral distances between the measuring contour and the design contour are used as a measure of quality of the matching(Reference “EPE”, see rejection of Claim 2 above where the edge placement error is used to optimize the cost function. Further note the preferred metric or measure of quality is Edge Placement Error as an overall representation of differences between the feature measured and target contour. Further note in Specification paragraph 0118 as described above the cost function further uses a threshold to determine how many iterations are required to perform this optimization. Note this is the same cost function as described in rejection of Claim 3). Regarding Claim 20, Tel discloses The method of Claim 3 wherein the optimizing is performed separately for individual subregions of the image (Reference “optimization” and “divided”, see Specification paragraph 0142 and 0143 where the optimization process is described and where in this process the illumination, which is one of design variables input to cost function as described in rejection of Claim 3, is divided into pixel groups which read as subregions of an image). Regarding Claim 21, Tel discloses The method of Claim 1, wherein the image is generated by the electron microscope (Reference “SEM”, see Specification paragraph 0240 where the images described above may be obtained with a scanning electron microscope. Also note the definition of mask in paragraph 0069 classifying this microscope as a mask inspection microscope as it inspects the structures of a substrate in lithographic process). Regarding Claim 22, Tel discloses The method of claim 1, wherein the at least one form parameter comprises at least one of sigma, thresh, and bias, and wherein the at least one registration parameter comprises at least one of translation X, translation Y, scale, and rotation. (Examiner’s Note, see application Figure 0002 showing registration parameter Rotation as well as Specification page 5 row 20-25 describing these registration parameters: translation X Y, scale and rotation all appear to align with typical definitions in the art and were evaluated as such. However when referring to form parameters note sigma and thresh both require some context without giving an overly broad reading of the claims which is described in page 6 rows 5-1 where they are, respectively, a width and a function value of a Gaussian filter. Reference “parameter”, See Specification paragraph 0110 where possible registration parameters of the cost function include image rotation. Also see Specification paragraph 0256 describing translation, magnification, and rotation as parameters for the cost function covering respective translation scale and rotation limitations. Further note in Specification paragraph 0110 the parameter bias which as noted above would be a form parameter. Finally the widths and function values described as sigma and thresh are taught in Specification paragraph 0125 where the Gauss-Newton algorithm linearizes in a vicinity or width and then calculates said values or thresh as described by applicant). Regarding Claim 23, Tel discloses The method of claim 1, wherein the image is generated by the mask inspection microscope. (Reference “mask” and note the definition of mask in paragraph 0069 which therefore classifies this microscope as described in Claim 1 as a mask inspection microscope as it inspects the structures of a substrate in lithographic process). Regarding Claim 24, Tel discloses The method of claim 1, wherein the registration error is determined based on the matching and registering (Reference “EPE”, see Specification paragraph 0110 where the edge placement error is based on the contours matched and registered to each other). Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEXANDER JOHN RODGERS whose telephone number is (703)756-1993. The examiner can normally be reached 5:30AM to 2:30PM ET. 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, John Villecco can be reached on (571) 272-7319. 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. /ALEXANDER JOHN RODGERS/Examiner, Art Unit 2661 /JOHN VILLECCO/Supervisory Patent Examiner, Art Unit 2661
Read full office action

Prosecution Timeline

May 12, 2022
Application Filed
Jul 12, 2024
Non-Final Rejection — §102, §Other
Nov 12, 2024
Response Filed
Feb 01, 2025
Final Rejection — §102, §Other
Jun 09, 2025
Request for Continued Examination
Jun 17, 2025
Response after Non-Final Action
Jul 23, 2025
Non-Final Rejection — §102, §Other
Oct 10, 2025
Response Filed
Feb 21, 2026
Final Rejection — §102, §Other (current)

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

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Prosecution Projections

5-6
Expected OA Rounds
70%
Grant Probability
77%
With Interview (+7.0%)
3y 2m
Median Time to Grant
High
PTA Risk
Based on 33 resolved cases by this examiner. Grant probability derived from career allow rate.

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