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 Amendment
The amendment filed February 3, 2026 has been entered. Claims 1-20 remain pending in the instant application.
Response to Arguments
Applicant’s arguments, filed February 3, 2026, regarding rejections under 35 U.S.C 101 have been fully considered, but they are not persuasive.
Applicant first argues that the claims provide a practical application to any recited judicial exception. Specifically, Applicant points to the recited limitations in Claim 1 of a cross sectional profile of a substrate, a first set […] associated with a first region, a second set […] associated with a second region, and generating a piecewise functional fit as describing a “data configuration [that] corresponds to the physical structure of the substrate feature,” and the limitations “enable a practical application of accurately characterizing the cross-sectional profile of a substrate feature” (e.g., remarks; page 11, paragraphs 2 and 3). Applicant further argues that this practical application solves a specific technical problem with a specific technical solution.
Regarding Applicant’s argument that the claims recite a practical application, the argued application of “accurately characterizing the cross-sectional profile of a substrate feature” is itself a mathematical concept or mental process and is thus not a practical application. The analogous limitation of generating a piecewise functional fit, as recited in the claims, describes the mathematical concept of constructing a piecewise function. The other identified limitations merely link the judicial exception to a general field of use or technological environment. For instance, the claims do not provide a specific structure or method for generating the data beyond merely reciting that the data is indicative of measurements or associated with a region. Given it’s broadest reasonable interpretation, the data could be of a structure that is not exclusive to characterizing a cross sectional profile of a substrate.
Regarding Applicant’s argument that the claims solve a specific technical problem, i.e., the claims provide an improvement to a technology, the Examiner notes that “the judicial exception alone cannot provide the improvement,” see MPEP § 2106.05(a) referenced by MPEP § 2106.04(d)(1). While the improvement can be provided by one or more additional element(s) in combination with the judicial exception(s), the additional elements of Claim 1 merely recite generic computer components as instructions to apply the abstract idea(s) on a computer, insignificant extra-solution activity, and/or a general field of use and technological environment, see MPEP § 2106.05(f)-(h). The additional elements are merely gathering data generally linked to measurements of a substrate to perform the abstract idea of generating a piecewise function, see MPEP § 2106.05(a)(III); “Examples that the courts have indicated may not be sufficient to show an improvement to technology include […] iii. Gathering and analyzing information using conventional techniques and displaying the result.”
An updated rejection under 35 U.S.C 101, necessitated by Applicant’s amendment, is provided below.
Applicant’s arguments regarding rejections under 35 U.S.C 103 have been considered but are moot because the new ground of rejection, necessitated by Applicant’s amendment, does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) mental processes and/or mathematical concepts without significantly more.
The following is an analysis of independent claim 1 based on the 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG).
Step 1, Statutory Category:
Yes: Claims 1-11 are directed to a method.
Step 2A Prong I, judicial Exception:
The Examiner submits that the foregoing claim limitations constitute mathematical concepts, as the claims cover mathematical relationships, mathematical formulas or equations, or mathematical calculations, given their broadest reasonable interpretation. Abstract ideas are bolded.
Claim 1 recites the limitations:
1. A method, comprising:
generating data indicative of a plurality of measurements of a cross-sectional profile of a substrate, the cross sectional profile comprising a width of a substrate feature as a function of a depth of the substrate feature;
receiving, by a processing device, the data indicative of the plurality of measurements of the cross-sectional profile of a substrate;
separating, by the processing device, the data indicative of the plurality of measurements into a plurality of sets of data, wherein a first set of the plurality of sets is associated with a first region of the cross-sectional profile, and wherein a second set of the plurality of sets is associated with a second region of the cross-sectional profile;
fitting data of the first set to a first function to generate a first fit function, wherein the first function is selected from a library of functions;
fitting data of the second set to a second function to generate a second fit function, wherein the second function is selected from the library of functions, and wherein the second function is different from the first function; and
generating a piecewise functional fit of the cross-sectional profile of the substrate, wherein the piecewise functional fit comprises the first fit function and the second fit function.
The limitations fitting data […] to generate a first fit function, fitting data […] to generate a second fit function and generating a piecewise functional fit are abstract ideas because they are directed to mathematical relationships, mathematical formulas or equations, or mathematical calculations.
Step 2A Prong II, Integration into a Practical Application:
Claim 1 recites the following additional claim limitations outside the abstract idea which only present general fields of use, mere instructions to apply an exception, and/or insignificant extra-solution activity:
generating data indicative of a plurality of measurements (insignificant extra-solution activity of data gathering, see MPEP § 2106.05(g)).
of a cross-sectional profile of a substrate, the cross sectional profile comprising a width of a substrate feature as a function of a depth of the substrate feature (general field of use and/or technological environment, see MPEP § 2106.05(h)).
receiving, by a processing device, the data indicative of a plurality of measurements of the cross-sectional profile of a substrate (insignificant extra-solution activity of data gathering, see MPEP § 2106.05(g)).
separating, by the processing device, the data indicative of the plurality of measurements into a plurality of sets of data (insignificant extra-solution activity of data gathering, see MPEP § 2106.05(g)).
wherein a first set of the plurality of sets is associated with a first cross-sectional region of the profile, and wherein a second set of the plurality of sets is associated with a second cross-sectional region of the profile (general field of use and/or technological environment, see MPEP § 2106.05(h)).
wherein the first function is selected from a library of functions (general field of use and/or technological environment, see MPEP § 2106.05(h)).
wherein the second function is selected from the library of functions (general field of use and/or technological environment, see MPEP § 2106.05(h)).
ADDITIONAL ELEMENTS:
Claim 1 recites the following additional elements:
“Processing device” is a high level recitation of generic computer components, computer elements used as a tool, and represents mere instructions to apply the abstract idea on a computer as in MPEP § 2106.05(f). Therefore, the additional element does not integrate the recited abstract ideas into a practical application.
Step 2B, Significantly More:
When considered individually or in combination, the additional limitations and elements of claim 1 do not amount to significantly more than the judicial exceptions for the same reasons above as to why the additional limitations do not integrate the abstract idea into a practical application.
The additional element “processing device” reciting generic computer components as mere instructions to apply on a computer per MPEP § 2106.05(f) is carried over and does not provide significantly more than the abstract idea. The examiner also notes that the specification does not define the structures of the additional elements in any way that could be used to integrate the abstract idea into a practical application.
The additional limitations identified as mere instructions to apply an exception, insignificant extra-solution activity, or general field of use above are carried over and also do not provide significantly more than the abstract idea. See MPEP § 2106.04(d) referencing MPEP § 2106.05(f), MPEP § 2106.05(g), and MPEP § 2106.05(h).
The insignificant extra solution activity of generating data, receiving […] data and separating […] the data is considered to be further well understood, routine and conventional, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
Considering the claim limitations in combination and the claims as a whole does not change this conclusion, and Claim 1 is ineligible under 35 U.S.C 101.
Regarding Claim 2, the claim recites The method of claim 1, wherein generating the piecewise functional fit of the cross-sectional profile comprises: applying one or more constraints to data points associated with a boundary between the first region and the second region; this limitation is considered to constitute additional mathematical concepts under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III).
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations are considered to constitute additional mathematical concepts under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, Claim 2 is ineligible under 35 U.S.C 101.
Regarding Claim 3, the claim recites The method of claim 2, wherein the constraints are selected from a group comprising: continuity of the piecewise functional fit across the boundary; continuity of a first derivative of the piecewise functional fit across the boundary; and continuity of a second derivative of the piecewise functional fit across boundary; this limitation is considered to constitute additional mathematical concepts under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III).
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations are considered to constitute additional mathematical concepts under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, Claim 3 is ineligible under 35 U.S.C 101.
Regarding Claim 4, the claim recites The method of claim 1, wherein the library of functions comprises at least one of zeroth-order polynomials; first-order polynomials; second-order polynomials; exponential functions; or logarithmic functions; this limitation is considered to constitute additional mathematical concepts under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III).
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations are considered to constitute additional mathematical concepts under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, Claim 4 is ineligible under 35 U.S.C 101.
Regarding Claim 5, the claim recites The method of claim 1, wherein the plurality of measurements of the cross-sectional profile of the substrate are associated with a simulated substrate; this limitation is considered to merely link the judicial exception to a particular field of use and/or technological environment under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(h).
and wherein generating the simulated substrate comprises: providing one or more simulation inputs to a physics-based model; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
receiving, from the physics-based model, data indicative of the simulated substrate; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
and extracting, from the data indicative of the simulated substrate, the plurality of measurements of the cross-sectional profile of the substrate; this limitation is considered to constitute additional mental processes and/or mathematical concepts under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). A user can perform the mental evaluation of calculating measurements from the simulation data. A user may use pen and paper to convert the data.
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations are considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, Claim 5 is ineligible under 35 U.S.C 101.
Regarding Claim 6, the claim recites The method of claim 1, wherein the plurality of measurements of the cross-sectional profile of the substrate are associated with a simulated substrate; this limitation is considered to merely link the judicial exception to a particular field of use and/or technological environment under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(h).
wherein generating the simulated substrate comprises: providing one or more machine learning inputs to a machine learning model; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
receiving, from the machine learning model, data indicative of geometry of the simulated substrate; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
and extracting, from the data indicative of geometry of the simulated substrate, the plurality of measurements of the cross-sectional profile of the substrate; this limitation is considered to constitute additional mental processes and/or mathematical concepts under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). A user can perform the mental evaluation of calculating measurements from the simulation data. A user may use pen and paper to convert the data.
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations are considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, Claim 6 is ineligible under 35 U.S.C 101.
Regarding Claim 7, the claim recites The method of claim 1, wherein the substrate comprises a semiconductor memory device; this limitation is considered to merely link the judicial exception to a particular field of use and/or technological environment under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(h).
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, Claim 7 is ineligible under 35 U.S.C 101.
Regarding Claim 8, the claim recites The method of claim 1, further comprising: receiving a plurality of piecewise functional fits; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
wherein the plurality of piecewise functional fits are associated with a plurality of cross-sectional profiles of a plurality of substrates; this limitation is considered to merely link the judicial exception to a particular field of use and/or technological environment under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(h).
providing the plurality of piecewise functional fits and the piecewise functional fit to a machine learning model; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
and receiving, from the machine learning model, data indicative of clustering of fit parameters of the plurality of piecewise functional fits and the piecewise functional fit; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, Claim 8 is ineligible under 35 U.S.C 101.
Regarding Claim 9, the claim recites The method of claim 1 further comprising: receiving a user selection of the first function; and receiving a user selection of the second function; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory. […] i. Recording a customer’s order.”
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, Claim 9 is ineligible under 35 U.S.C 101.
Regarding Claim 10, the claim recites The method of claim 1, further comprising: selecting, by the processing device, the first function from the library of functions; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
and selecting, by the processing device, the second function from the library of functions; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, Claim 10 is ineligible under 35 U.S.C 101.
Regarding Claim 11, the claim recites The method of claim 1, further comprising: providing, to a model, one or more input conditions associated with generating the substrate; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
providing, to the model, the piecewise functional fit; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
receiving, from the model, an indication of an effect of a first input condition of the one or more input conditions on a first parameter of the piecewise functional fit; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] iv. Storing and retrieving information in memory.”
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, Claim 11 is ineligible under 35 U.S.C 101.
Regarding Claims 12, 13, 14, 15, and 16, the claims recite substantially similar limitations to Claims 1, 2, 4, 7, and 11, respectively, and the claims are ineligible under 35 U.S.C 101 for the same reasons. The additional elements non-transitory machine readable storage medium and instructions recite mere instructions to apply the abstract idea on a computer as in MPEP § 2106.05(f) and thus do not integrate the judicial exceptions into a practical application or recite significantly more.
Regarding Claims 17, 18, 19, and 20, the claims recite substantially similar limitations to Claims 1, 2, 3, and 10, respectively, and the claims are ineligible under 35 U.S.C 101 for the same reasons. The additional elements system and memory recite mere instructions to apply the abstract idea on a computer as in MPEP § 2106.05(f) and thus do not integrate the judicial exceptions into a practical application or recite significantly more.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-4, 7, 9, 10, 12-15, and 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Matova et al. (U.S. Pub. No. 2021/0271171 A1), hereinafter Matova, in view of Hench et al. (U.S. Pub. No. 2022/0252395 A1, filed February 1, 2022), hereinafter Hench.
Regarding Claim 1, Matova teaches A method, comprising […] receiving, by a processing device, the data indicative of the plurality of measurements of the cross-sectional profile of a substrate (“The computer system CL may obtain 500 one or more values of the parameter for at least two sub-regions of the plurality of sub-regions position in a region. The computer system CL may obtain a plurality of parameter values. In exemplary arrangements, the computer system CL may obtain the values from another apparatus, such as the metrology tool MT. The metrology tool may have undertaken a plurality of measurements of the parameter across the region of the substrate and these measurements may form the values of the parameter obtained by the computer system CL.”) (e.g., paragraph [0055]).
separating, by the processing device, the data indicative of the plurality of measurements into a plurality of sets of data (“The computer system CL may divide 502 the region of the substrate into sub-regions,” wherein the parameters associated with a sub-region is interpreted as a set of data.) (e.g., paragraph [0056]).
wherein a first set of the plurality of sets is associated with a first region of the cross-sectional profile and wherein a second set of the plurality of sets is associated with a second region of the cross-sectional profile (“The computer system CL may obtain at least one value of the parameter for each sub-region in the region and in some arrangements may obtain a plurality of values of the parameter for one or more of the sub-regions.”) (e.g., paragraph [0075]).
fitting data of the first set to a first function to generate a first fit function (“The computer system CL may estimate the parameter in every sub-region of the region by evaluating the function for at least one position in each sub-region [...] The function used by the computer system CL to estimate a parameter may be a piecewise polynomial spline, or specifically may comprise NURBS, wherein a sub-region of the region corresponds to a single polynomial.” Evaluating a function for a first sub-region is interpreted as fitting data to a function, wherein the evaluated function is a first fit function.) (e.g., paragraphs [0076] and [0078]).
wherein the first function is selected from a library of functions (“The computer system CL may estimate the parameter at a position in the region by evaluation of a function, the function comprising piecewise defined base functions […] Computer program instructions may also be stored in a computer-readable medium that can direct a computer or other programmable data processing apparatus to function in a particular manner.” The computer readable medium is used to store the defined base functions, wherein the defined base functions stored in memory are a library of functions.) (e.g., paragraphs [0061] and [0100]).
fitting data of the second set to a second function to generate a second fit function (“The computer system CL may estimate the parameter in every sub-region of the region by evaluating the function for at least one position in each sub-region [...] The function used by the computer system CL to estimate a parameter may be a piecewise polynomial spline, or specifically may comprise NURBS, wherein a sub-region of the region corresponds to a single polynomial.” Evaluating a function for a second sub-region is interpreted as fitting data to a function, wherein the evaluated function is a first fit function.) (e.g., paragraphs [0076] and [0078]).
wherein the second function is selected from the library of functions (“The computer system CL may estimate the parameter at a position in the region by evaluation of a function, the function comprising piecewise defined base functions […] Computer program instructions may also be stored in a computer-readable medium that can direct a computer or other programmable data processing apparatus to function in a particular manner.” The computer readable medium is used to store the defined base functions, wherein the defined base functions stored in memory are a library of functions.) (e.g., paragraphs [0061] and [0100]).
and wherein the second function is different from the first function (“Using a NURBS fit to estimate the parameter makes it possible to have faces of the piecewise function to have different shapes and sizes.”) (e.g., paragraph [0083]).
and generating a piecewise functional fit of the cross-sectional profile of the substrate, wherein the piecewise functional fit comprises the first fit function and the second fit function (“The function comprises piecewise defined base functions, or specifically may comprise splines or NURBS, wherein each single base function is defined across a subregion of the region, also referred to as face or section, within the piecewise base function description, that is to say, the piecewise division into faces of the function evaluated across position in the region corresponds to the division of the region into sub-regions.” The evaluated function is interpreted as a generated piecewise functional fit of the profile substrate, wherein the faces of the function are the first and second fit functions.) (e.g., paragraph [0062]).
However, Matova does not appear to specifically teach generating data indicative of a plurality of measurements of a cross-sectional profile of a substrate, the cross sectional profile comprising a width of a substrate feature as a function of a depth of the substrate feature;
On the other hand, Hench, which relates similarly as a method for characterizing shapes of semiconductor structures, does teach generating data indicative of a plurality of measurements of a cross-sectional profile of a substrate, the cross sectional profile comprising a width of a substrate feature as a function of a depth of the substrate feature(“In general, the independent parameters of a geometric model describing an in-plane hole shape are expressed as functions of depth through the structure. In this manner, the geometric model captures the real variation of the in-plane shape of processed semiconductor devices as a function of depth […] In some embodiments, the measurement model is an electromagnetic model ( e.g., a Born Wave Model) of the measurement that generates images representative of the scattering from the target under measurement […] the modelled images may also be parameterized by structural parameters of the measured high aspect ratio structure (e.g., height, diameter at different heights […] etc.).”) (e.g., paragraphs [0033] and [0078]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the Applicant's claimed invention to combine Matova with Hench. The claimed invention is considered to be merely combining prior art elements according to known methods to yield predictable results, see MPEP § 2143(I)(A). Matova teaches a method for fitting piecewise functions to a substrate profile. However, Matova does not appear to specifically teach generating measurement data of a cross sectional profile, wherein a width of a feature is a function of depth. On the other hand, Hench, which relates similarly as a method for characterizing shapes of semiconductor structures, does teach generating measurement data wherein a hole diameter is a function of height. The only difference between the claimed invention and the prior art is a lack of actual combination of the measurement model of Hench with the piecewise fitting of Matova into a single prior art reference. Furthermore, Matova discloses the use of a metrology tool MT to provide input to the computer system CL (e.g., Matova; paragraph [0051]), wherein the computer system CL performs the piecewise fitting; one of ordinary skill in the art could have merely used the measurement model of Hench as the source of metrology input to the computer system of Matova. In combination, each element merely performs the same function as it does separately, and one of ordinary skill in the art would have recognized the results of the combination as predictable. Therefore, it would have been obvious to a person of ordinary skill in the art to combine Matova with Hench in order to provide metrology data that captures the feature width as a function of depth as in Hench.
Regarding Claim 2, Matova in view of Hench teaches The method of claim 1. Matova further teaches wherein generating the piecewise functional fit of the cross-sectional profile comprises: applying one or more constraints to data points associated with a boundary between the first region and the second region (“Continuity for piecewise defined functions, for example NURBS, may be defined as above for portions of the function within a face of the piecewise function, for example by not having breaks in the function within a single piece, and may further require that the function output value on a boundary between adjacent faces is the same for each piecewise function describing a position on that boundary.” Defining continuity between pieces of the piecewise function is interpreted as applying one or more constraints at the boundary between a first and second region.) (e.g., paragraph [0081]).
Regarding Claim 3, Matova in view of Hench teaches The method of claim 2. Matova further teaches wherein the constraints are selected from a group comprising: continuity of the piecewise functional fit across the boundary (“A property of NURBS is that the piecewise polynomials can be defined so that they are continuous between faces. This continuity may be geometric continuity, that is to say, the transition from one face to an adjacent face is smooth, without breaks in the function output.”) (e.g., paragraph [0081]).
continuity of a first derivative of the piecewise functional fit across the boundary (“In the case where the function describes a two-dimensional structure, a surface, a function may be considered to be smooth if it has no breaks in the surface. In case of a mathematical function, smoothness in a region can also be defined by its differentiability, that is to say whether a derivative of the function exists at all points of the function in that region.”) (e.g., paragraph [0081]).
and continuity of a second derivative of the piecewise functional fit across boundary (“The derivative of a function may in itself be a differentiable function, as may one or more further resulting derivatives of that function. The amount of times a function is differentiable is an indication of the level of continuity, or smoothness, of the original function.”) (e.g., paragraph [0081]).
Regarding Claim 4, Matova in view of Hench teaches The method of claim 1. Matova further teaches wherein the library of functions comprises at least one of zeroth-order polynomials; first-order polynomials; second-order polynomials; exponential functions; or logarithmic functions (“A piecewise polynomial function comprises a plurality of polynomials, wherein each polynomial has an order, which may be the highest degree of a term in the polynomial with a non-zero coefficient when the polynomial is written in its expanded form. The order of the polynomial determines the nature and complexity of the function. A piecewise polynomial function may comprise polynomials of different orders, or each polynomial in the piecewise polynomial function may have the same order.”) (e.g., paragraph [0079]).
Regarding Claim 7, Matova in view of Hench teaches The method of claim 1. Matova further teaches wherein the substrate comprises a semiconductor memory device (Figure 4 discloses a semiconductor wafer used according to the method of Matova, wherein the wafer is a substrate that may be used for memory devices.) (e.g., figures 4(a) and 4(b).
Regarding Claim 9, Matova in view of Hench teaches The method of claim 1. Matova further teaches further comprising: receiving a user selection of the first function; and receiving a user selection of the second function s (“The computer system CL may estimate the parameter at a position in the region by evaluation of a function, the function comprising piecewise defined base functions.” The defined base functions are interpreted as being defined by a user.) (e.g., paragraph [0061]).
Regarding Claim 10, Matova in view of Hench teaches The method of claim 1. Matova further teaches further comprising: selecting, by the processing device, the first function from the library of functions; and selecting, by the processing device, the second function from the library of functions (“The computer system CL may estimate the parameter at a position in the region by evaluation of a function, the function comprising piecewise defined base functions.” The computer system CL is interpreted as selecting the appropriate base functions, wherein the base functions form a library of functions.) (e.g., paragraph [0061]).
Regarding Claim 12, Matova teaches A non-transitory machine readable storage medium storing instructions which, when executed, cause a processing device to perform operations (“Computer program instructions may also be stored in a computer-readable medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture including instructions which implement the functions/ acts specified in the block diagrams and/or flowchart block or blocks.”) (e.g., paragraph [0100]).
The remaining limitations of Claim 11 are substantially similar to Claim 1, and the claim is rejected under 35 U.S.C 103 for the same reasons.
Regarding Claims 13, 14, and 15, the claims recite substantially similar limitations to Claims 2, 4, and 7, respectively, and the claims are rejected under 35 U.S.C 103 for the same reasons.
Regarding Claim 17, Matova teaches A system, comprising memory and a processing device coupled to the memory, wherein the processing device is configured (“An apparatus comprising: a memory having computer program code; and a processor configured to execute the computer program code.) (e.g., Claim 13).
The remaining limitations of Claim 17 are substantially similar to Claim 1, and the claim is rejected under 35 U.S.C 103 for the same reasons.
Regarding Claims 18, 19, and 20, the claims recite substantially similar limitations to Claims 2, 3, and 10, respectively, and the claims are rejected under 35 U.S.C 103 for the same reasons.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Matova in view of Hench, further in view of Werkman et al. (U.S. Pub. No. 2021/0405544 A1), hereinafter Werkman.
Regarding Claim 5, Matova in view of Hench teaches The method of claim 1. However, neither Matova nor Hench appear to specifically teach wherein the plurality of measurements of the cross-sectional profile of the substrate are associated with a simulated substrate, and wherein generating the simulated substrate comprises: providing one or more simulation inputs to a physics-based model; receiving, from the physics-based model, data indicative of the simulated substrate; and extracting, from the data indicative of the simulated substrate, the plurality of measurements of the cross-sectional profile of the substrate.
On the other hand, Werkman, which relates similarly to semiconductor manufacturing, does teach wherein the plurality of measurements of the cross-sectional profile of the substrate are associated with a simulated substrate (“to properly train the AI network, an extensive training data set is required. For various reasons (e.g., metrology effort required and/or confidentiality issues), obtaining sufficient training data is difficult [...] As such, a method for modifying a training data set configured for training of a model will now be described. The method may comprise obtaining a first data set comprising context and/or metrology data associated with a semiconductor manufacturing process and modifying the first data set by introducing variability based on a characteristic of the semiconductor manufacturing process, to obtain said training data set. Alternatively, no first data set is used and the training data comprises entirely synthetic data based on a characteristic of the semiconductor manufacturing process. In this way, a training data set is obtained which is a synthetic or hybrid (semi-synthetic) data set.” The synthetic data is interpreted as measurements associated with a simulation.) (e.g., paragraphs [0063] and [0064]).
and wherein generating the simulated substrate comprises: providing one or more simulation inputs to a physics-based model (“The synthetic data can be generated from initial measured data based on certain behavioral properties which are known and/or expected to occur [...] The behavioral properties can be based on engineering knowledge (known situations known to be possible and for which a proper response is known) and on an existing customer data set.” The initial measured data are interpreted as simulation inputs. A model utilizing known and expected behavior properties based on engineering knowledge is interpreted as a physics-based model.) (e.g., paragraphs [0065] and [0066]).
receiving, from the physics-based model, data indicative of the simulated substrate (“Using one or both of known behavioral properties and any actual metrology results, synthetic data can be produced.”) (e.g., paragraph [0073]).
and extracting, from the data indicative of the simulated substrate, the plurality of measurements of the cross-sectional profile of the substrate (“Therefore, for example, synthetic metrology data for different noise levels could be generated, as could synthetic metrology data describing a parameter subject to a different level of reticle heating or a different lens aberration effect with respect to the actual measurements performed.” The synthetic metrology data is interpreted as measurements of the profile of the substrate.) (e.g., paragraph [0074]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the Applicant's claimed invention to combine the modified reference of Matova in view of Hench with Werkman. The claimed invention is considered to be merely combining prior art elements according to known methods to yield predictable results, see MPEP § 2143(I)(A). Matova teaches a method for fitting piecewise functions to a substrate profile. However, Matova does not appear to specifically teach obtaining metrology data for the substrate from a simulation of the substrate. On the other hand, Werkman does teach a method for generating synthetic metrology data for a substrate. The only difference between the claimed invention and the prior art is a lack of actual combination of the synthetic metrology generation of Werkman and the piecewise fitting of Matova into a single prior art reference. Furthermore, Matova discloses the use of a metrology tool MT to provide input to the computer system CL (e.g., Matova; paragraph [0051]), wherein the computer system CL performs the piecewise fitting; one of ordinary skill in the art could have merely used the output of the synthetic metrology method of Werkman as the input to the computer system of Matova. In combination, the synthetic metrology method of Werkman and the piecewise fitting of Matova merely perform the same functions as they do separately, and one of ordinary skill in the art would have recognized the results of the combination as predictable. Therefore, it would have been obvious to a person of ordinary skill in the art to combine the modified reference of Matova in view of Hench with Werkman in order to use the larger synthetic/hybrid dataset of Werkman with the method of Matova.
Claim(s) 6, 11, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Matova in view of Hench, further in view of David (U.S. Pub. No. 2017/0109646 A1), hereinafter David.
Regarding Claim 6, Matova in view of Hench teaches The method of claim 1. However, neither Matova nor Hench appear to specifically teach wherein the plurality of measurements of the cross-sectional profile of the substrate are associated with a simulated substrate, wherein generating the simulated substrate comprises: providing one or more machine learning inputs to a machine learning model; receiving, from the machine learning model, data indicative of geometry of the simulated substrate; and extracting, from the data indicative of geometry of the simulated substrate, the plurality of measurements of the cross-sectional profile of the substrate.
On the other hand, David, which relates similarly to semiconductor manufacturing, does teach wherein the plurality of measurements of the cross-sectional profile of the substrate are associated with a simulated substrate (“In another example, virtual metrology can use machine learning algorithms to predict metrology metrics such as film thickness and critical dimensions (CD) without having to take actual measurements, in real-time.”) (e.g., paragraph [0046]).
wherein generating the simulated substrate comprises: providing one or more machine learning inputs to a machine learning model (“The input data can be upstream metrology measurements, or data from process equipment (such as temperatures and run times).”) (e.g., paragraph [0046]).
receiving, from the machine learning model, data indicative of geometry of the simulated substrate (“In another example, virtual metrology can use machine learning algorithms to predict metrology metrics such as film thickness and critical dimensions (CD) without having to take actual measurements, in real-time.” Film thickness and critical dimensions are interpreted as data indicative of geometry.) (e.g., paragraph [0046]).
and extracting, from the data indicative of geometry of the simulated substrate, the plurality of measurements of the cross-sectional profile of the substrate (“Based on sensor data from production equipment and actual metrology values of sampled wafers to train the algorithm, virtual metrology can predict metrology values for all wafers.”) (e.g., paragraph [0046]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the Applicant's claimed invention to combine the modified reference of Matova in view of Hench with David. The claimed invention is considered to be merely combining prior art elements according to known methods to yield predictable results, see MPEP § 2143(I)(A). Matova teaches a method for fitting piecewise functions to a substrate profile. However, Matova does not appear to specifically teach obtaining metrology data for the substrate from a simulation of the substrate. On the other hand, David does teach a method for generating virtual metrology data for a substrate. The only difference between the claimed invention and the prior art is a lack of actual combination of the virtual metrology generation of David and the piecewise fitting of Matova into a single prior art reference. Furthermore, Matova discloses the use of a metrology tool MT to provide input to the computer system CL (e.g., Matova; paragraph [0051]), wherein the computer system CL performs the piecewise fitting; one of ordinary skill in the art could have merely used the output of the virtual metrology method of David as the input to the computer system of Matova. In combination, the virtual metrology method of David and the piecewise fitting of Matova merely perform the same functions as they do separately, and one of ordinary skill in the art would have recognized the results of the combination as predictable. Therefore, it would have been obvious to a person of ordinary skill in the art to combine the modified reference of Matova in view of Hench with David in order to have metrology data without requiring actual measurements.
Regarding Claim 11, Matova in view of Hench teaches The method of claim 1. However, neither Matova nor Hench appear to specifically teach the method further comprising: providing, to a model, one or more input conditions associated with generating the substrate; providing, to the model, the piecewise functional fit; receiving, from the model, an indication of an effect of a first input condition of the one or more input conditions on a first parameter of the piecewise functional fit.
On the other hand, David, which relates similarly to semiconductor manufacturing, does teach a method further comprising: providing, to a model, one or more input conditions associated with generating the substrate (“receiving input data from a plurality of metrology measurements and at least one upstream process step for at least one targeted process parameter of the individual process step;” A model is interpreted as receiving the input data, wherein the input data comprises input conditions.) (e.g., Claim 1).
providing, to the model, the piecewise functional fit (“receiving input data from a plurality of metrology measurements and at least one upstream process step for at least one targeted process parameter of the individual process step;” A model is interpreted as receiving the input data, wherein the input data comprises a piecewise functional fit from Matova.) (e.g., Claim 1).
receiving, from the model, an indication of an effect of a first input condition of the one or more input conditions on a first parameter of the piecewise functional fit (“evaluating the multi-variate relationship of the input data for the targeted process parameter to form an initial prediction as to whether a final semiconductor product formed by the semiconductor process will pass or fail;” Evaluating the multi-variate relationship of the input data to a process passing or failing is interpreted as providing an indication of an effect of input conditions, wherein the variables in the multi-variate relationship comprise the input conditions.) (e.g., Claim 1).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the Applicant's claimed invention to combine the modified reference of Matova in view of Hench with David. The claimed invention is considered to be merely combining prior art elements according to known methods to yield predictable results, see MPEP § 2143(I)(A). Matova teaches a method for fitting piecewise functions to a substrate profile. However, Matova does not appear to specifically teach using the piecewise function to indicate an effect of input conditions on parameters of the functional fit. On the other hand, David does teach a method for evaluating the effect of input conditions on a semiconductor process. The only difference between the claimed invention and the prior art is a lack of actual combination of the virtual metrology generation of David and the piecewise fitting of Matova into a single prior art reference. As both Matova and David relate to semiconductor manufacturing, one of ordinary skill in the art could have merely used the output of the virtual metrology method of David as the input to the computer system of Matova. In combination, the virtual metrology method of David and the piecewise fitting of Matova merely perform the same functions as they do separately, and one of ordinary skill in the art would have recognized the results of the combination as predictable. Therefore, it would have been obvious to a person of ordinary skill in the art to combine the modified reference of Matova in view of Hench with David in order to determine the effect of metrology data on the piecewise fitting of Matova.
Regarding Claim 16, the claim recites substantially similar limitations to Claim 11, and the claim is rejected under 35 U.S.C 103 for the same reasons.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Matova in view of Hench, further in view of Mossavat et al. (U.S. Pub. No. 2016/0325504 A1), hereinafter Mossavat.
Regarding Claim 8, Matova in view of Hench teaches The method of claim 1. Matova further teaches wherein the plurality of piecewise functional fits are associated with a plurality of cross-sectional profiles of a plurality of substrates (“The computer system CL may obtain at least one value of the parameter for each sub-region in the region and in some arrangements may obtain a plurality of values of the parameter for one or more of the sub-regions.”) (e.g., paragraph [0075]).
However, neither Matova nor Hench appear to specifically teach the method further comprising: receiving a plurality of piecewise functional fits […] providing the plurality of piecewise functional fits and the piecewise functional fit to a machine learning model; and receiving, from the machine learning model, data indicative of clustering of fit parameters of the plurality of piecewise functional fits and the piecewise functional fit.
On the other hand, Mossavat, which relates to metrology for lithographic systems, does teach a method further comprising: receiving a plurality of piecewise functional fits (“Input data 710 comprises the inspection data element set, obtained from, for example, measurements of all target structures on a wafer, a subset of these target structures or measurements of target structures over multiple wafers, e.g., a lot. The input data also comprises a profile ( e.g., a CD profile) for performing a reconstruction of the target structures and (optionally) a value for the number of clusters which the inspection data is to be divided into.”) (e.g., paragraph [0112]).
providing the plurality of piecewise functional fits and the piecewise functional fit to a machine learning model (“At step 720, the inspection data elements are clustered, and cluster representatives identified, using one of the methods already described.” Mossavat previously discloses that “It is therefore proposed to perform an unsupervised clustering or machine learning algorithm to partition the inspection data into clusters in such a way that inspection data elements within a cluster are more similar than the inspection data elements in other clusters.”) (e.g., paragraphs [0092] and [0113]).
and receiving, from the machine learning model, data indicative of clustering of fit parameters of the plurality of piecewise functional fits and the piecewise functional fit (“At step 720, the inspection data elements are clustered, and cluster representatives identified, using one of the methods already described.”) (e.g., paragraph [0113]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the Applicant's claimed invention to combine the modified reference of Matova in view of Hench with Mossavat. The claimed invention is considered to be merely combining prior art elements according to known methods to yield predictable results, see MPEP § 2143(I)(A). Matova teaches a method for fitting piecewise functions to a substrate profile. However, Matova does not appear to specifically teach clustering fit parameters of the piecewise functional fits. On the other hand, Mossavat does teach a method for clustering parameters of the piecewise fit. The only difference between the claimed invention and the prior art is a lack of actual combination of the clustering method of Mossavat and the piecewise fitting of Matova into a single prior art reference. As both Matova and Mossavat relate to semiconductor manufacturing, one of ordinary skill in the art could have merely used the piecewise function output of Matova as the input to the clustering method of Mossavat. In combination, the clustering method of Mossavat and the piecewise fitting of Matova merely perform the same functions as they do separately, and one of ordinary skill in the art would have recognized the results of the combination as predictable. Therefore, it would have been obvious to a person of ordinary skill in the art to combine the modified reference of Matova in view of Hench with Mossavat in order to group similar fit parameters.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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.
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/K.H.T./ Examiner, Art Unit 2189
/REHANA PERVEEN/ Supervisory Patent Examiner, Art Unit 2189
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