Prosecution Insights
Last updated: August 17, 2026
Application No. 18/841,698

AI-INTEGRATED SYSTEMS, METHODS, AND COMPUTER-READABLE MEDIA FOR CHARACTERIZING MICROSPHERIC MATERIAL

Non-Final OA §102§103§112
Filed
Aug 27, 2024
Priority
Mar 08, 2022 — provisional 63/269,034 +2 more
Examiner
DANG, DUY M
Art Unit
Tech Center
Assignee
BASF SE
OA Round
1 (Non-Final)
91%
Grant Probability
Favorable
1-2
OA Rounds
7m
Est. Remaining
97%
With Interview

Examiner Intelligence

Grants 91% — above average
91%
Career Allowance Rate
792 granted / 869 resolved
+31.1% vs TC avg
Moderate +6% lift
Without
With
+6.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 7m
Avg Prosecution
27 currently pending
Career history
890
Total Applications
across all art units

Statute-Specific Performance

§101
24.3%
-15.7% vs TC avg
§103
17.4%
-22.6% vs TC avg
§102
23.3%
-16.7% vs TC avg
§112
17.7%
-22.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 869 resolved cases

Office Action

§102 §103 §112
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 . Applicant’s preliminary amendment filed on August 27, 2024 has been entered and made of record. Currently, claims 1-3, 7-8, 10, 13-14, 17, 23, 26-28, 31, 33-34, 39, 41-42, and 45-48 are pending. Claim Interpretation Claims 1-3, 7-8, 10, 13-14, 17, 23, 26-28, 31, 33-34, 39, and 41-42 are not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because they are all method claims. Claims 45-46 are is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the recitations of “processor” provide sufficient structure to perform all claimed limitations. Claims 47-48 are not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because each of these claims is an article of manufacture claim. Claim Rejections - 35 USC § 102 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of the appropriate paragraphs of pre-AIA 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. (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. Claim(s) 1, 8, 10, 13-14, 26-27, 31, 33, 41-42, and 45-48 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Scheidegger et al. (U.S. Pat. App. Pub. No. 20220180497A1, referred as Scheidegger hereinafter). Regarding claim 1 as a representative claim, Scheidegger teaches a method for characterizing microspheric materials comprising: acquiring tiled image data representative of microscopic images of a microspheric material, spectroscopic images of a microspheric material, or a combination of microscopic and spectroscopic images of a microspheric material (see figure 2 and para. [0044] – [0046] (image 202 comprises a plurality of image tiles); figure 3 and para. [0047] (tiles); para. [0059] (identified object in an image tile is the material defect wherein the material is, for example, rebar which is metal and comprises iron; thus, the rebar, for example, corresponds to the so-called microspheric material; this interpretation, in view of BRI, is consistent with applicant’s spec. paras. [0082], for example)); stitching the tiled image data into a composite image (see fig. 5 and para. [0051] (mering tiles 502 and 504 to form tile 510, for example)) classifying, by a trained machine-learning model, one or more regions of the composite image (see paras. [0002] and [0016] (machine learning (i.e., deep learning, RCNN) is used for image classification, detection and segmentation), [0041] (identifying and classifying defect), [0060] (using CNN for object detection and classification)); and characterizing, by the trained machine-learning model, one or more classified regions of the composite image according to at least one of the following properties: composition, composition-specific size distribution, crystalline phase, degree of crystallinity, or crystallite-specific size distribution (see para. [0059] (material defect or surface such as rebar corrosion, crack, rust, spalling, algae)). The advanced statements as applied to claim 1 above are incorporated hereinafter. Regarding claim 8, Scheidegger further teaches wherein the tiled image data is two- or three-dimensional image data (see fig. 5 (2D image tiles 502 and 504, for example); fig. 2 and paras. [0044] – [0046] (24 image tiles included in image 206, each image tile is a rectangular, thus a 2D)). Regarding claim 10, Scheidegger further teaches wherein the tiled image data is acquired in a partially automated process, or a fully automated process, or an unsupervised process (see paras. [0003] (automated defect detection), [0054] (present invention is fully automated) and [0063] (system 600 comprises a processor communicatively couple to a memory 602 storing instructions for causing the system to receive then generate image tiles from the received image; this process is performed by system 600 so it is an automated process partially, fully or unsupervised)). Regarding claim 13, Scheidegger further teaches wherein the tiled image data is acquired by grid segmentation in a row-column pattern (see fig. 2 and paras. [0044] – [0046] (24 image tiles included in image 206, for example)). Regarding claim 14, Scheidegger further teaches wherein the tiled image data comprises partially overlapping image tiles (see fig. 5, tiles 510 and 512). Regarding claim 26, Scheidegger further teaches wherein the one or more regions of the composite image are classified as corresponding to at least one of a particle, an intra-particle pore, or an interparticle void (see para. [0059] (material defect or surface such as rebar corrosion, crack, rust, spalling, algae)). Regarding claim 27, Scheidegger further teaches wherein the one or more regions of the composite image are classified as corresponding to at least one of clay, alumina, or pores (see para. [0059] (material defect or surface such as rebar corrosion, crack, rust, spalling, algae)). Regarding claim 31, Scheidegger further teaches wherein the particle-classified regions are further classified as comprising at least one of potassium, cesium, calcium, barium, strontium, copper, yttrium, phosphorus, sulfur, selenium, fluorine, chlorine, bromine, iodine, lanthanum, cerium, aluminum, silicon, sodium, carbon, oxygen, iron, vanadium, or nickel (see para. [0059] (identified object in an image tile is the material defect wherein the material is, for example, rebar which is metal and comprises iron; thus, the rebar, for example, corresponds to the so-called microspheric material; this interpretation, in view of BRI, is consistent with applicant’s spec. paras. [0082], for example)). Regarding claim 33, Scheidegger further teaches wherein the microspheric material is nodulated (see para. [0059] (material defect or surface such as rebar corrosion, crack, rust, spalling, algae)). Regarding claim 41, Scheidegger further teaches wherein the machine-learning model is trained to distinguish particles, intra-particle pores, and inter-particle voids using manually-annotated image data as a ground truth reference (see paras. [0002] and [0016] (machine learning (i.e., deep learning, RCNN) is used for image classification, detection and segmentation), [0041] (identifying and classifying defect), [0055] (annotated training patterns), [0059] (material defect or surface such as rebar corrosion, crack, rust, spalling, algae), and [0060] (using CNN for object detection and classification)). Regarding claim 42, Scheidegger further teaches wherein the machine-learning model comprises a convolutional neural network or a recurrent neural network. (see paras. [0002] and [0016] (machine learning (i.e., deep learning, RCNN) is used for image classification, detection and segmentation) and [0060] (using CNN for object detection and classification)). Regarding claim 45, it is noted that claim recites similar claim limitations called for in the counterpart claim 1. Thus, the advanced statements as applied to claim 1 are incorporated hereinafter. Scheidegger further teaches at least one processor (see abstract (one or more processors), paras. [0004] (one or more processors), [0063] (processor), and [0068] (one or more processors)). Regarding claim 46, it is noted that claim recites similar claim limitations called for in claim 45. Thus, claim 46 is rejected for same reasons as applied to claim 45 above. Regarding claim 47, it is noted that claim recites similar claim limitations called for in the counterpart claim 45. Thus, the advanced statements as applied to claim 45 are incorporated hereinafter. Scheidegger further teaches a non-transitory computer-readable medium having instructions encoded thereon and at least one processor (see abstract (one or more processors), paras. [0004] (one or more processors), [0063] (processor), 0068] (one or more processors) and [0074] (medium having computer readable program instructions thereon for causing a processor to carry out the prevent invention)). Regarding claim 48, it is noted that claim recites similar claim limitations called for in claim 47. Thus, claim 48 is rejected for same reasons as applied to claim 47 above. Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 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. Claim(s) 2-3, 7, 17, 23, 28, 34, and 39 is/are rejected under 35 U.S.C. 103 as being unpatentable over Scheidegger. The advanced statements as applied to claims 1, 8, 10, 13-14, 26-27, 31, 33, 41-42, and 45-48 are incorporated hereinafter. Regarding claim 2, Scheidegger does not teach claim limitation “wherein the tiled image data is obtained by scanning electron microscopy (SEM) and/or by transmission electron spectroscopy (TEM)”. However, such claim limitation is well known in the art (Official Notice). The motivation for doing so is to obtain more information about the object being detected/inspected because SEM and/or TEM uses electron to generate image. Therefore, before the effective filing date of the instant claim invention, it would have been obvious to incorporate such claim limitation in combination with Scheidegger for that reasons. Regarding claim 3, Scheidegger does not teach claim limitation “wherein the tiled image data is obtained by cross-sectional scanning electron microscopy or by backscatter electron scanning electron microscopy (BSE-SEM)”. However, such claim limitation is well known in the art (Official Notice). The motivation for doing so is to obtain more information about the object being detected/inspected because SEM and/or BSE-SEM uses electron to generate image. Therefore, before the effective filing date of the instant claim invention, it would have been obvious to incorporate such claim limitation in combination with Scheidegger for that reasons. Regarding claim 7, Scheidegger does not teach claim limitation “wherein the tiled image data is obtained by energy dispersive X-ray spectroscopy (EDX)”. However, such claim limitation is well known in the art (Official Notice). The motivation for doing so is to obtain more information about the object being detected/inspected because EDX uses electron to generate image. Also, it is non-destructive and simple to use. Therefore, before the effective filing date of the instant claim invention, it would have been obvious to incorporate such claim limitation in combination with Scheidegger for that reasons. Regarding claim 17, Scheidegger does not teach claim limitation “wherein the tiled image data is acquired at a magnification between the range of l00X and 6,000X or at a magnification between the range of 20,000X and 500,000X”. However, such claim limitation is well known in the art (Official Notice). The motivation for doing so is to obtain more information about the object being detected/inspected so that it would improve the detection and/or inspection. Therefore, before the effective filing date of the instant claim invention, it would have been obvious to incorporate such claim limitation in combination with Scheidegger for that reasons. Regarding claim 23, Scheidegger does not teach claim limitation “wherein the tiled image data includes microscopic images and spectroscopic images obtained at substantially the same magnification and/or obtained at substantially the same field of view”. However, such claim limitation is well known in the art (Official Notice). The motivation for doing so is to obtain the same images so that it would improve the detection and/or inspection. Therefore, before the effective filing date of the instant claim invention, it would have been obvious to incorporate such claim limitation in combination with Scheidegger for that reasons. Regarding claim 28, Scheidegger does not teach claim limitation “wherein the microspheric material comprises at least one clay-based silica-alumina or alumina, the alumina optionally comprising at least one of gibbsite, flash-calcined gibbsite, bayerite, or boehmite”. However, such claim limitation is well known in the art (Official Notice). The motivation for doing so is to allow other type of material to be detected/inspected so that it would improve the detection and/or inspection. Therefore, before the effective filing date of the instant claim invention, it would have been obvious to incorporate such claim limitation in combination with Scheidegger for that reasons. Regarding claim 34, Scheidegger does not teach claim limitation “wherein the microspheric material is a fluid catalytic cracking (FCC) catalyst”. However, such claim limitation is well known in the art (Official Notice). The motivation for doing so is to allow other type of material to be detected/inspected so that it would improve the detection and/or inspection. Therefore, before the effective filing date of the instant claim invention, it would have been obvious to incorporate such claim limitation in combination with Scheidegger for that reasons. Regarding claim 39, Scheidegger does not teach claim limitation “wherein the microspheric material is embedded in an epoxy resin prior to imaging”. However, such claim limitation is well known in the art (Official Notice). The motivation for doing so is to protect the material being inspected/detected from destructive/damage. Therefore, before the effective filing date of the instant claim invention, it would have been obvious to incorporate such claim limitation in combination with Scheidegger for that reasons. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Morishita et al. (U.S. Pat. App. Pub. No. 2014/0361167 A1) teaches SEM (para. [0051]) and backscrattered electron (para. [0045]). Any inquiry concerning this communication or earlier communications from the examiner should be directed to DUY M DANG whose telephone number is (571)272-7389. The examiner can normally be reached Monday to Friday from 7:00AM to 3:00PM. 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, Amandeep Saini can be reached at 571-272-3382. 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. /DUY M DANG/Primary Examiner, Art Unit 2662
Read full office action

Prosecution Timeline

Aug 27, 2024
Application Filed
Jul 14, 2026
Non-Final Rejection mailed — §102, §103, §112 (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

1-2
Expected OA Rounds
91%
Grant Probability
97%
With Interview (+6.3%)
2y 7m (~7m remaining)
Median Time to Grant
Low
PTA Risk
Based on 869 resolved cases by this examiner. Grant probability derived from career allowance rate.

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