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 .
Notice to Applicants
This action is in response to the remarks and amendments filed on 10/31/2025.
Claims 1-20 are pending.
Corrective Actions by Applicant
Claim 8 has been amended.
Response to Arguments
The examiner has fully considered Applicant’s presented arguments.
On page 7 of the remarks, Applicant argues that the amendment to claim 8 overcomes the objection against it. This is persuasive. The objection to claim 8 has been withdrawn.
On pages 7-9 of the remarks, Applicant argues that claims 1-4, 6-13, and 16-20 are directed to eligible subject matter under 35 U.S.C. 101. This is persuasive, particularly regarding Applicant’s arguments of evaluating the claims as a whole and how the claims reflect improvements to the problems discussed in at least paragraphs 0055-0056 of the originally filed specification. All of the 35 U.S.C. 101 rejections have been withdrawn.
On pages 9-11 of the remarks, Applicant argues that Toyoda fails to overcome the deficiencies of Sato regarding independent claims 1 and 17. The examiner respectfully disagrees.
In response to applicant’s arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
As discussed in the non-final office action, Sato discloses obtain a plurality of raw images of a patterned substrate (see figure 11 and paragraph 0148, where a plurality of images will be analyzed to remove abnormal images), determine a raw image quality metric (see figure 11 and paragraph 0148, where quality of raw images is measured by evaluating displacement, contrast, or blur of the images in general); select, based on the raw image quality metric, a sub-set of raw images from the plurality of raw images (see figure 11 and paragraph 0148, where abnormal images are removed, leaving a subset of raw images); and provide the sub-set of raw images for performing measurements associated with the one or more features within an image (paragraph 0151 specifies that this embodiment can be applied to embodiment 4, which paragraphs 0126-0128 specify is directed to measuring dimensions of wafer patterns).
In other words, Sato discloses a system for filtering out abnormal images of patterned substrates to obtain suitable sub-sets of raw images to perform further measurements on. What Sato fails to disclose is the specific method used to determine the image quality metric, i.e., determine a raw image quality metric based on data associated with one or more gauges or one or more contours of one or more features within each image of the plurality of raw images, the raw image quality metric being indicative of a raw image quality (emphasis added via underline).
The examiner acknowledges Applicant’s arguments as to how Toyoda is directed towards analyzing the quality of the physical object itself, rather than the quality of the image per se. However, as discussed below, the examiner argues that the combination of Sato and Toyoda still discloses the limitations of claims 1 and 17.
Whether the intent of a system is to evaluate the quality of the physical item itself or the quality of the image, both of these actions in the context of the present application require the identification of present/missing gauges and/or the quality in which they appear in the images. Regardless of the intent, the performed action is still the same in context of the claimed invention.
For example, claim 4 narrows the quality determination by reciting wherein the instructions configured to determine the raw image quality metric are further configured to cause the one or more processors to: determine whether the gauge data is missing one or more CD gauges for the given raw image of the plurality of images; and responsive to one or more CD gauges being missing, reduce the second value of the raw image quality metric by a specified amount (emphasis added via underline). For example, see paragraph 0085 and figure 5 of the originally filed specification, where an image 502, in which no gauges appear due to a lack of horizontal line features of the substrate in said image, is assigned a lower quality value.
A system that makes such a determination of the presence/absence of gauges, such as Toyoda’s system, could be used either for image quality determinations or object quality determinations. As Sato already evaluates the quality of images of wafer patterns in general (see Sato paragraph 0148, where displacement, contrast, or blur of the images is considered in general), it would have been obvious to one of ordinary skill in the art to extend Toyoda’s image analysis methods to Sato’s image quality evaluation methods by considering gauges and/or contours appearing in said images. Doing so allows for evaluating quality of the features in the image (see Toyoda paragraph 0179).
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 1-2, 9, 12-13, and 17-18 are rejected under 35 U.S.C 103 as being unpatentable over Sato et al. (U.S. Publ. US-2003/0111602-A1) in view of Toyoda et al. (U.S. Publ. US-2009/0202139-A1).
Regarding claim 1, Sato discloses a non-transitory computer-readable medium comprising instructions (see paragraphs 0045-0046) stored therein that, when executed by one or more processors, are configured to the one or more processors to at least:
obtain a plurality of raw images of a patterned substrate (see figure 11 and paragraph 0148, where a plurality of images will be analyzed to remove abnormal images);
determine a raw image quality metric (see figure 11 and paragraph 0148, where quality of raw images is measured by evaluating displacement, contrast, or blur of the images in general);
select, based on the raw image quality metric, a sub-set of raw images from the plurality of raw images (see figure 11 and paragraph 0148, where abnormal images are removed, leaving a subset of raw images);
and provide the sub-set of raw images for performing measurements associated with the one or more features within an image (paragraph 0151 specifies that this embodiment can be applied to embodiment 4, which paragraphs 0126-0128 specify is directed to measuring dimensions of wafer patterns).
Sato fails to disclose determine a raw image quality metric based on data associated with one or more gauges or one or more contours of one or more features within each image of the plurality of raw images, the raw image quality metric being indicative of a raw image quality (emphasis added via underline).
Pertaining to the same field of endeavor, Toyoda discloses determine a raw image quality metric based on data associated with one or more gauges or one or more contours of one or more features within each image of the plurality of raw images, the raw image quality metric being indicative of a raw image quality (see figure 13 and paragraphs 0179-0190, where a feature in an image is compared to a reference feature pattern to determine an evaluation value/image quality; figure 9 and paragraph 0177 specify the format of reference patterns, which the examiner interprets as using gauges to map out the contour).
Sato and Toyoda are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Toyoda into Sato because doing so allows for evaluating quality of the features in the image (see Toyoda paragraph 0179).
Regarding claim 2, Sato fails to disclose the limitations of claim 2.
Pertaining to the same field of endeavor, Toyoda discloses wherein the instructions configured to determine the raw image quality metric are further configured to cause the one or more processors to analyze, based on specified criteria, gauge data associated with gauges of each image of the plurality of raw images (see figure 13 and paragraphs 0179-0190, where the gauges of the reference pattern are used to compare changes in gaps, deformations, or areas of the target and reference patterns).
Sato and Toyoda are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Toyoda into Sato because doing so allows for evaluating quality of the features in the image (see Toyoda paragraph 0179).
Regarding claim 9, Sato fails to disclose the limitations of claim 9.
Pertaining to the same field of endeavor, Toyoda discloses wherein the instructions configured to determine the raw image quality metric are further configured to cause the one or more processors to perform statistical analysis on gauge data of the gauges associated with each raw image to generate the raw image quality metric (see paragraph 0182, where an average/mean or dispersion/variance of gaps between the reference and target patterns can be used as the evaluation value).
Sato and Toyoda are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Toyoda into Sato because measuring gaps between the reference and target patterns provides quality information (see Toyoda paragraph 0200).
Regarding claim 12, Sato fails to disclose the limitations of claim 12.
Pertaining to the same field of endeavor, Toyoda discloses wherein the instructions configured to determine the raw image quality metric are further configured to cause the one or more processors to: obtain a first contour of a feature within an average image of the plurality of raw images associated with a particular pattern (see paragraphs 0160-0163, where the reference pattern can be generated by overlaying/clustering a plurality of raw images to generate a composite image); obtain a second contour of the feature from each of the raw images associated with the particular pattern (see figure 14B and paragraph 0182, where target pattern 1402 is obtained); and determine a distance between the first contour with the second contour (see figure 14B and paragraph 0182, where a gap between the target and reference patterns is measured).
Sato and Toyoda are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Toyoda into Sato because measuring gaps between the reference and target patterns provides quality information (see Toyoda paragraph 0200).
Regarding claim 13, Sato fails to disclose the limitations of claim 13.
Pertaining to the same field of endeavor, Toyoda discloses wherein the average image is obtained by: clustering of the raw images based on a characteristic of the feature; and averaging a cluster of raw images (see paragraphs 0160-0163, where the reference pattern can be generated by overlaying/clustering a plurality of raw images to generate a composite image) within a specified cluster region (see figure 14C, band 1404 and paragraph 0183).
Sato and Toyoda are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Toyoda into Sato because using an averaged reference pattern reduces the influence of small defects from individual images (see Toyoda paragraph 0203).
Regarding claim 17, Sato in view of Toyoda discloses claim 17 as applied to claim 1 above.
Regarding claim 18, Sato in view of Toyoda discloses claim 18 as applied to claim 2 above.
Claims 3-8 and 19-20 are rejected under 35 U.S.C 103 as being unpatentable over Sato et al. (U.S. Publ. US-2003/0111602-A1) in view of Toyoda et al. (U.S. Publ. US-2009/0202139-A1), and further in view of Konishi (U.S. Publ. US-2017/0017862-A1).
Regarding claim 3, Sato in view of Toyoda fails to disclose the limitations of claim 3.
Pertaining to the same field of endeavor, Konishi discloses wherein the instructions configured to analyze gauge data are further configured to cause the one or more processors to: determine whether the gauge data associated with the gauges exists for a given raw image of the plurality of images (see paragraph 0051, where the number of matching feature points that exist is counted; paragraph 0047 specifies that edges and corners can be feature points); responsive to the gauge data not existing, assign a first value to the raw image quality metric (see paragraph 0051, where the match counter n starts at zero, and if no matches exist, would thus output a similarity score of zero, as the similarity score is a proportion of n to the number of feature points in the reference image); and responsive to the gauge data existing, assign a second value to the raw image quality metric different than the first value (see paragraph 0051, where if at least one match exists, the similarity score would be greater than and different to zero; the examiner regards the similarity score as analogous to a quality metric, as both are results of comparing an input image to a reference image to determine similarity to a template).
Sato and Konishi are considered analogous art, as they are both directed to evaluating quality of manufacturing images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Konishi into Sato and Toyoda because doing so allows for accurate recognition with low processing load (see Konishi paragraph 0020).
Regarding claim 4, Sato fails to disclose the limitations of claim 4.
Pertaining to the same field of endeavor, Konishi discloses wherein the instructions configured to determine the raw image quality metric are further configured to cause the one or more processors to: determine whether the gauge data is missing one or more (see paragraph 0051, where the number of matching feature points that exist is counted; paragraph 0047 specifies that edges and corners can be feature points); and responsive to one or more (see paragraph 0051, where the similarity score is proportional to the amount of existing matching features, thus a specific amount being missing would reduce the score by a specific amount).
Sato and Konishi are considered analogous art, as they are both directed to evaluating quality of manufacturing images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Konishi into Sato because doing so allows for accurate recognition with low processing load (see Konishi paragraph 0020).
Sato in view of Konishi fails to further disclose determine whether the gauge data is missing one or more CD gauges for the given raw image of the plurality of images; and responsive to one or more CD gauges being missing, reduce the second value of the raw image quality metric by a specified amount (emphasis added via underline).
Pertaining to the same field of endeavor, Toyoda discloses detecting the presence/absence of CD gauges (see figures 14B, 17, and paragraph 0182, where a gap between the contours of the target pattern and reference pattern is identified and measured; paragraph 00155 of the present specification states that edge-to-edge distance can be considered a CD metric).
Sato and Toyoda are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Toyoda into Sato and Konishi because doing so allows for evaluating quality of the features in the image (see Toyoda paragraph 0179).
Regarding claim 5, Sato in view of Toyoda fails to disclose the limitations of claim 5.
Pertaining to the same field of endeavor, Konishi discloses wherein the specified amount is related to a number of gauge types and a number of repeating patterns (see figure 5 and paragraphs 0045-0048, where different repeated pattern types, each with unique features/gauges are defined and searched for; see paragraph 0051, where the similarity score is proportional to the amount of existing matching features, thus a specific amount being missing would reduce the score by a specific amount).
Sato and Konishi are considered analogous art, as they are both directed to evaluating quality of manufacturing images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Konishi into Sato and Toyoda because doing so allows for accurate recognition with low processing load (see Konishi paragraph 0020).
Regarding claim 6, Sato in view of Konishi fails to disclose the limitations of claim 6.
Pertaining to the same field of endeavor, Toyoda discloses wherein the instructions configured to determine the raw image quality metric are further configured to cause the one or more processors to: cluster the gauge data associated with the gauges of the plurality of raw images, the gauge data being edge placement (EP) gauge data (see paragraphs 0160-0163, where the reference pattern can be generated by overlaying/clustering a plurality of raw images to generate a composite image); and modify, based on the clustering, the second value of the raw image quality metric (see figure 14C and paragraph 0183, where the extent to which the target pattern 1402 exists outside the reference pattern area/cluster 1404 influences the evaluation value; figure 15B and paragraph 0188 specify that gauges existing outside the cluster reduce quality).
Sato and Toyoda are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Toyoda into Sato and Konishi because doing so allows for determining defective images (see Toyoda paragraph 0183).
Regarding claim 7, Sato in view of Konishi fails to disclose the limitations of claim 7.
Pertaining to the same field of endeavor, Toyoda discloses wherein the instructions configured to modify the second value of the raw image quality metric are further configured to cause the one or more processors to: determine whether the EP gauge data of one or more raw images of the plurality of raw images are within a specified cluster region; and responsive to the EP gauge data being within the specified cluster region, modify the second value of the raw image quality metric associated with the one or more raw images (see figure 14C and paragraph 0183, where the extent to which the target pattern 1402 exists outside the reference pattern area/cluster 1404 influences the evaluation value; figure 15B and paragraph 0188 specify that gauges existing outside the cluster reduce quality, implying that gauges existing inside the cluster increase quality).
Sato and Toyoda are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Toyoda into Sato and Konishi because doing so allows for determining defective images (see Toyoda paragraph 0183).
Regarding claim 8, Sato in view of Konishi fails to disclose the limitations of claim 8.
Pertaining to the same field of endeavor, Toyoda discloses wherein the modification of the second value of the raw image quality metric is based on a statistic associated with CD gauge data (see figures 14B, 17, and paragraph 0182, where a gap between the contours of the target pattern and reference pattern is identified and measured), and wherein the instructions configured to modify the second value of the raw image quality metric are further configured to cause the one or more processors to: determine whether the statistic associated with the CD gauge data is outside a statistic threshold (see paragraph 0187, where the gap is analyzed to determine if it is larger than a gap of a non-defective pattern); and responsive to the statistic associated with the CD gauge data being outside the statistic threshold, reduce the second value of the raw image quality metric of the one or more raw images by a specified amount (see paragraph 0187, where a pattern having a large enough gap is considered to have lower quality).
Sato and Toyoda are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Toyoda into Sato and Konishi because measuring gaps between the reference and target patterns provides quality information (see Toyoda paragraph 0200).
Regarding claim 19, Sato in view of Toyoda fails to teach the limitations of claim 19.
Pertaining to the same field of endeavor, Konishi discloses wherein the analyzing comprises: determining whether the gauge data associated with the gauges exists for a given raw image of the plurality of images (see paragraph 0051, where the number of matching feature points that exist is counted; paragraph 0047 specifies that edges and corners can be feature points); and responsive to the gauge data not existing, assigning a first value to the raw image quality metric, the first value being lower than a selection threshold (see paragraph 0051, where the match counter n starts at zero, and if no matches exist, would thus output a similarity score of zero, as the similarity score is a proportion of n to the number of feature points in the reference image; paragraph 0066 specifies that, if multiple reference patterns are used, the one with the highest similarity is selected, thus a similarity score of zero is guaranteed to be less than the selection threshold), or responsive to the gauge data existing, assigning a second value to the raw image quality metric, the second value being relatively higher than the selection threshold (see paragraph 0051, where if at least one match exists, the similarity score would be greater than and different to zero; paragraph 0066 specifies that, if multiple reference patterns are used, the one with the highest similarity is selected, thus only a pattern with at least one match can be higher than the selection threshold).
Sato and Konishi are considered analogous art, as they are both directed to evaluating quality of manufacturing images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Konishi into Sato and Toyoda because doing so allows for accurate recognition with low processing load (see Konishi paragraph 0020).
Regarding claim 20, Sato in view of Toyoda and Konishi anticipates claim 20 as applied to claim 4 above.
Claims 10-11 are rejected under 35 U.S.C 103 as being unpatentable over Sato et al. (U.S. Publ. US-2003/0111602-A1) in view of Toyoda et al. (U.S. Publ. US-2009/0202139-A1), and further in view of Grodt et al. (U.S. Publ. US-2019/0128664-A1).
Regarding claim 10, Sato in view of Toyoda discloses wherein the raw image quality metric indicates a contrast (see Sato figure 11 and paragraph 0148, where quality of raw images is measured by evaluating displacement, contrast, or blur of the images in general).
Sato in view of Toyoda fails to disclose wherein the raw image quality metric indicates a contrast at the gauges associated with each raw image (emphasis added via underline).
Pertaining to the same field of endeavor, Grodt discloses wherein the raw image quality metric indicates a contrast at the gauges associated with each raw image (see figure 1C and paragraph 0025, where an edge profile of a target is first obtained by obtaining light gradients across the inter to outer diameter of the target at different points along the contour; see figure 4 and paragraph 0030, where the average/median contrast for each point is used as an edge profile symmetry metric).
Sato and Grodt are considered analogous art, as they are both directed to evaluating quality of manufacturing images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Grodt into Sato and Toyoda because calculating the edge profile in this manner allows for accurately determining edge symmetry and dimensional deviations (see Grodt paragraph 0015).
Regarding claim 11, Sato in view of Toyoda fails to disclose the limitations of claim 11.
Pertaining to the same field of endeavor, Grodt discloses wherein the raw image quality metric indicates an average of slopes determined at the gauges associated with each raw image (see figure 1C and paragraph 0025, where an edge profile of a target is first obtained by obtaining light gradients across the inter to outer diameter of the target at different points along the contour; see figure 4 and paragraph 0030, where the average/median contrast for each point is used as an edge profile symmetry metric).
Sato and Grodt are considered analogous art, as they are both directed to evaluating quality of manufacturing images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Grodt into Sato and Toyoda because calculating the edge profile in this manner allows for accurately determining edge symmetry and dimensional deviations (see Grodt paragraph 0015).
Claims 14-15 are rejected under 35 U.S.C 103 as being unpatentable over Sato et al. (U.S. Publ. US-2003/0111602-A1) in view of Toyoda et al. (U.S. Publ. US-2009/0202139-A1), and further in view of Chen et al. (U.S. Publ. US-2012/0298862-A1).
Regarding claim 14, Sato in view of Toyoda fails to teach the limitations of claim 14.
Pertaining to the same field of endeavor, Chen discloses wherein the instructions configured to obtain the second contour are further configured to cause the one or more processors to: determine an image property at contour locations associated with the feature within a given raw image; determine whether the image property breaches a threshold (see paragraph 0044, where contrast thresholds are applied to image segments, including contour and corner segments, and defect pixels/blobs are determined from those pixels above the threshold); and responsive to the image property breaching the threshold, extract the second contour of the feature from the given raw image (see paragraphs 0047-0049, where the contours surrounding the defect blobs are extracted and then compared to reference contours).
Sato and Chen are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Chen into Sato and Toyoda because doing so allows for classifying defects into various classes (see Chen paragraph 0048).
Regarding claim 15, Sato in view of Toyoda fails to teach the limitations of claim 15.
Pertaining to the same field of endeavor, Chen discloses wherein the image property is a local edge sharpness or contrast value at a location associated with the feature, or intensity at a contour of the feature (see paragraph 0044, where contrast thresholds are applied to image segments, including contour and corner segments, and defect pixels/blobs are determined from those pixels above the threshold).
Sato and Chen are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Chen into Sato and Toyoda because using contrast allows for ranking of defect severity (see Chen paragraph 0046).
Claim 16 is rejected under 35 U.S.C 103 as being unpatentable over Sato et al. (U.S. Publ. US-2003/0111602-A1) in view of Toyoda et al. (U.S. Publ. US-2009/0202139-A1), and further in view of Kusnadi et al. (U.S. Publ. US-2009/0100389-A1).
Regarding claim 16, Sato in view of Toyoda fails to teach the limitations of claim 16.
Pertaining to the same field of endeavor, Kusnadi discloses wherein the instructions configured to determine the raw image quality metric are further configured to cause the one or more processors to: obtain contours of a feature within each raw image of the plurality of raw images associated with a particular pattern; and determine a matrix of a distance between a contour of each raw image of the plurality of raw images with a contour of each another raw image of the plurality of raw images (see figures 8-9 and paragraph 0037, where the distance between corresponding points on a contour are mapped from a printed feature image and a simulated feature image).
Sato and Kusnadi are considered analogous art, as they are both directed to evaluating quality of semiconductor images. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Kusnadi into Sato and Toyoda because comparing cost functions, such as those of Kusnadi paragraph 0037, is useful for evaluating the accuracy of photolithographic models (see Kusnadi paragraph 0036).
Conclusion
THIS ACTION IS MADE FINAL. 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.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NICHOLAS JOHN HELCO whose telephone number is (703)756-5539. The examiner can normally be reached on Monday-Friday from 9:00 AM to 5:00 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella, can be reached at telephone number 571-272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NICHOLAS JOHN HELCO/Examiner, Art Unit 2667
/MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667