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 and they are persuasive. The rejection under U.S.C. 102(a)(1) of Claims 1-24 has been withdrawn. However, upon further consideration, a new ground of rejection is made in view of Yu et al (US 20170352144 A1) under U.S.C. 103. Another rejection under U.S.C. 112(a) has also been made, as essential claimed subject matter introduced by amendment on 09 June 2025 has not been disclosed in the Specification or Drawings. This claimed subject matter should have been rejected in the original office action mailed 28 July 2025. A rejection is now included below.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1-24 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding Claim 1, the claim recites: “A method for determining a registration error of a structure on a mask for use in semiconductor lithography, comprising: - generating an image of at least one region of the mask… wherein the image is an aerial image generated by a mask inspection microscope or an electron microscope.” It is noted this claim language was not part of the original set of claims, but was introduced by amendment on 09 June 2025. However, there is no disclosure of generating any image with a mask inspection microscope and therefore this claim should be rejected as new matter. The only description of a microscope occurs in the Background, paragraphs 2-3 “The production of photomasks which can meet these requirements is extremely complex, susceptible to errors and hence expensive. For determining the registration error, mask inspection microscopes, electron microscopes or position determining devices are used.” There is a description of an “electron micrograph” in Specification paragraph 0030 which would perhaps inherently disclose an image being generated by an electron microscope, as an electron micrograph would be the specific output of such a device. However, no mention of any image being generated or taken by a mask inspection microscope occurs. The claim contains new subject matter and should be rejected under U.S.C. 112(a).
Claims 2-24 are rejected for depending upon Claim 1 above.
Claim Rejections - 35 USC § 103
Claims 1-24 are rejected under 35 U.S.C. 103 as being unpatentable over Tel et al (US Publication No. 20210149312 A1) in view of Yu et al (US 20170352144 A1).
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.
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 [projected] mask (Examiner’s Note: See Rejection of Claim 1 under U.S.C. 112(a) where the Specification and Drawings are silent to such details as to what stage in the lithographic processes the mask is attempting to be imaged. The state of the art points to many possible embodiments which occur during stages of the lithographic processes which might also read generating an image of at least one region of the mask. For semiconductors as an example there is a process when the mask is projected onto the substrate creating an image of a region of a photomask which might also read as generating an image of at least one region of the mask which Tel describes in the below embodiments. 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).
However Tel fails to disclose “generating an image of at least one region of the mask”. Instead, Yu discloses generating an image of at least one region of the mask (Note “mask” Specification paragraph 0035 where the mask is inspected with a mask inspection tool which specifically includes scanning the surface of the mask to provide locations, shapes and sizes of the mask. Noting the mask inspection tool is described as an optical inspection tool or microscope) The motivation is provided in the next paragraph where the ability to repair these detected mask defects is described (See Specification paragraph 0036, Note “EUV mask” and “mask repair tool). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Tel in view of Yu.
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
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.
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/ALEXANDER JOHN RODGERS/Examiner, Art Unit 2661
/JOHN VILLECCO/Supervisory Patent Examiner, Art Unit 2661
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