DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1, 3-11, and 13-20 are presented for examination based on the amended claims in the application filed on November 20, 2025. Claims 2 and 12 have been cancelled by the applicant.
Claims 1, 3-11, and 13-20 are rejected under 35 USC § 101 because the claimed invention is directed to judicial exception, an abstract idea, it has not been integrated into practical application.
Claims 1, 3-4, 7-8, 11, 13-14 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over US 2016/0012176 A1 Liu, et al. [herein “Liu”] in view of US 2019/0311083 A1 Feng, et al. [herein “Feng”].
Claims 5-6 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Liu and Feng as applied to claim 1 and 11 above, and further in view of Wong, Alison, Benjamin Pope, Louis Desdoigts, Peter Tuthill, Barnaby Norris, and Chris Betters. "Phase retrieval and design with automatic differentiation: tutorial." JOSA B 38, no. 9 (2021): 2465-2478 [herein “Wong”].
Claims 9-10 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Liu and Feng, as applied to claims 1 and 11 above, and in further view of US 2003/0204326 A1 Opsal, et al. [herein “Opsal”].
This action is made Non-Final.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on November 20, 2025 has been entered.
Response to Amendment
The amendment filed November 20, 2025 has been entered. Claims 1, 3-11, and 13-20 remain pending in the application.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on September 06, 2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claims 1, 3-11, and 13-20 are rejected under 35 USC § 101 because the claimed invention is directed to judicial exception, an abstract idea, it has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception. Examiner has evaluated the claims under the framework provided in the 2019 Patent Eligibility Guidance published in the Federal Register 01/07/2019 and has provided such analysis below.
Step 1:
Claims 1 and 3-10 are directed to non-transitory computer-readable medium and fall within the statutory category of articles of manufacture; and Claims 11 and 13-20 are directed to a method and falls within the statutory category of a process. Therefore, “Are the claims to a process, machine, manufacture or composition of matter?” Yes.
In order to evaluate the Step 2A inquiry “Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?” we must determine, at Step 2A Prong 1, whether the claim recites a law of nature, a natural phenomenon or an abstract idea and further whether the claim recites additional elements that integrate the judicial exception into a practical application.
Step 2A Prong 1:
Claims 1 and 11: The limitations of
“determining an original test design for a test physical device”,
“measuring performance of an instance of the test physical device fabricated by the fabrication system using the original test design to determine an as-fabricated performance metric”,
“determining an as-fabricated design by performing an iterative optimization that includes backpropagating a loss metric through the original test design via a first loss function to determine a structural gradient and updating the original test design based on the structural gradient so that the updated original test design converges to the as-fabricated design, wherein the first loss function is based on differences in a simulated performance metric of the original test design and the as-fabricated performance metric”,
“optimizing a fabrication model using a second loss function based on differences between the original test design and the as-fabricated design”, and
“using the optimized fabrication model to optimize a new design for a new physical device” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, the limitations can be conducted as the following:
a person can mentally create or draw with pen and paper an initial design for a first device,
a person can mentally qualify or draw with pen and paper the performance parameters of a device as metrics,
a person can mentally create or draw with pen and paper an as-fabricated design based on a calculated structural gradient using backpropagating differential gradient formula of the performance differences between of the initial test design and the as-fabricated design to converge the initial test design to the as-fabricated design,
a person can mentally alter or draw with pen and paper the design process that converges the initial test design to the as-fabricated design based on the simulated results and structural parameter differences between the initial test design and fabricated design, and
a person can mentally draw with pen and paper using the updated fabricated design process model from the first device a second initial design for a second device. For example, a fabricated design which would be the physical implementation of the initial design based on processes and manufacturing limitations that are altered to better represent the initial design based on their performance and structural differences, and one can take the improvements from a process used in one design and carry over certain parameters, applications, enhancements, and lessons learned from a previous design into a second design.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, claims 1 and 11: The limitation of “determining an as-fabricated design by performing an iterative optimization that includes backpropagating a loss metric through the original test design via a first loss function to determine a structural gradient and updating the original test design based on the structural gradient so that the updated original test design converges to the as-fabricated design, wherein the first loss function is based on differences in a simulated performance metric of the original test design and the as-fabricated performance metric” and “optimizing a fabrication model using a second loss function based on differences between the original test design and the as-fabricated design”, as drafted, is an operation that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation of mathematical evaluations. For example, calculating a structural gradient to optimize an initial design to converge to an as-fabricated design can be conducted using backpropagating differential gradient formulas (as shown in Para. 78-86) on the performance differences between of the test design and the as-fabricated design. Based on this calculation, the fabrication model can be optimized to better reflect the performance of the as-fabricated design. Secondly, calculating a loss function can be conducted using the mean-squared error equations the difference between the performance of the simulated test and as-fabricated designs (see Para. 68 and 89). Based on this calculation, the test design can be optimized to better reflect the performance of the as-fabricated design.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation of mathematic operation but for the recitation of generic computer components, then it falls within the “Mathematical Operation” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Therefore, yes, claims 1 and 11 recite judicial exceptions. The claims have been identified to recite judicial exceptions, Step 2A Prong 2 will evaluate whether the claims are directed to the judicial exception.
Step 2A Prong 2:
Claims 1 and 11: The judicial exception is not integrated into a practical application. In particular, the claims recite the following additional element: “A non-transitory computer-readable medium having computer-executable instructions stored thereon that, in response to execution by one or more processors of a computing system, cause the computing system to perform actions for deriving a fabrication model for a fabrication system using an inverse design process” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) with the broadest reasonable interpretation, which does not integrate a judicial exception into elements. Further, the following additional element: “transmitting the optimized new design for the new physical device to the fabrication system to cause the fabrication system to fabricate an instance of the new physical device” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) and, alternatively, is merely a recitation of insignificant extra-solution data outputting activity (see MPEP § 2106.05(g)) with the broadest reasonable interpretation, which does not integrate a judicial exception into elements. The insignificant extra-solution activities are further addressed below under step 2B as also being Well-Understood, Routine, and Conventional (WURC).
Therefore, “Do the claims recite additional elements that integrate the judicial exception into a practical application?” No, these additional elements do not integrate the abstract idea into a practical application and they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
After having evaluated the inquires set forth in Steps 2A Prong 1 and 2, it has been concluded that claims 1 and 11 not only recites a judicial exception but that the claim is directed to the judicial exception as the judicial exception has not been integrated into practical application.
Step 2B:
Claims 1 and 11: The claims do not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than generic computing components which do not amount to significantly more than the abstract idea. Further, the insignificant extra-solution data gathering, record update, and data transmission activities are also 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, ii. Performing repetitive calculations, iii. Electronic recordkeeping, iv. Storing and retrieving information in memory”).
Therefore, “Do the claims recite additional elements that amount to significantly more than the judicial exception?” No, these additional elements, alone or in combination, do not amount to significantly more than the judicial exception. Having concluded the analysis within the provided framework, claims 1 and 11 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Regarding claims 3 and 13, they recite an additional element recitation of “transmitting the original test design to the fabrication system for fabrication of the instance of the test physical device” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) and, alternatively, is merely a recitation of insignificant extra-solution data outputting activity (see MPEP § 2106.05(g)) with the broadest reasonable interpretation, which does not integrate a judicial exception into elements. Further, the insignificant extra-solution data gathering, record update, and data transmission activities are also 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" iii. Electronic recordkeeping). Further, this claim does not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fails both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fails Step 2B. Therefore, claims 3 and 13 do not recite patent eligible subject matter under 35 U.S.C. §101.
Regarding claim 4, it recites an additional limitation of “measuring accuracy of the fabrication model by comparing a scanning electron microscope (SEM) image of the instance of the test physical device to the as-fabricated design”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally qualify or draw with a pen and paper the similarities between an SEM image of the test design and the physical design to determine the accuracy of the fabrication model.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Regarding claims 5 and 15, they recite an additional limitation of “wherein optimizing the fabrication model includes using at least one of gradient descent and an Adam optimizer” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation of mathematical evaluations. For example, calculating structural gradients can be conducted using differential gradients formulas (as shown in Para. 78-86) and parameter optimization of the performances based on the structural differences between the test design and the as-fabricated design. Based on this calculation, the fabrication model can be optimized to better reflect the performance of the as-fabricated design to update and optimize the fabrication model.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation of mathematic evaluations but for the recitation of generic computer components, then it falls within the “Mathematical Operation” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 5 and 15, they recite an additional limitation of “wherein optimizing the fabrication model includes using at least one of gradient descent and an Adam optimizer”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally list and alter or draw with pen and paper for the optimization of parameters in the design process based on a calculated structural gradient using backpropagating differential gradient decent formulas of the performance differences between the simulated results and structural parameter differences between the initial design and fabricated design.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 5 and 15, they recite an additional element recitation of “wherein the fabrication model includes a neural network” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) with the broad reasonable interpretation, which does not integrate a judicial exception into elements. Further, these claims do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fail Step 2B as not amounting to significantly more. Therefore, claims 5 and 15 do not recite patent eligible subject matter under 35 U.S.C. §101.
Regarding claims 6 and 16, they recite an additional limitation of “wherein the fabrication model includes a sequence of differentiable operations” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation of mathematical evaluations. For example, calculating the structural gradient can be conducted using differential operation formulas (as shown in Para. 78-86) on the performances based on the structural differences between the test design and the as-fabricated design. Based on this calculation, the fabrication model can be optimized to better reflect the performance of the as-fabricated design.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation of mathematic evaluations but for the recitation of generic computer components, then it falls within the “Mathematical Operation” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 6 and 16, they recite an additional limitation of “wherein the fabrication model includes a sequence of differentiable operations”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally list and alter or draw with pen and paper for the optimization of parameters in the design process based on a calculated structural gradient using backpropagating differential gradient decent formulas of the performance differences between the simulated results and structural parameter differences between the initial design and fabricated design.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 6 and 16, they recite additional element recitations of “wherein optimizing the fabrication model includes using a JAX framework” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) with the broad reasonable interpretation, which does not integrate a judicial exception into elements. Further, these claims do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fail Step 2B as not amounting to significantly more. Therefore, claims 6 and 16 do not recite patent eligible subject matter under 35 U.S.C. §101.
Regarding claims 7 and 17, they recite an additional limitation of “wherein the original test design includes at least one performance goal given an expected input”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally create or draw with pen and paper an initial design for an electrical device that generates an output given a certain input per given specifications.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Regarding claims 8 and 18, they recite additional elements of “wherein determining the original test design includes providing the at least one performance goal given the expected input to an inverse design process to generate the original test design”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally create or draw with pen and paper an initial design for an electrical device using an inverse design process that generates an output based on a certain input per given specifications.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Regarding claims 9 and 19, it recites an additional limitation of “wherein measuring performance of the instance of the test physical device includes measuring performance of the instance of the test physical device within the one or more intended wavelength spectra and outside of the one or more intended wavelength spectra”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally assess or draw with a pen and paper the performance of the physical devices by determining if the frequencies both inside and outside the desire frequency band conform to the desired specification.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 9 and 19, they recite additional element recitations of “wherein the expected input includes one or more intended wavelength spectra for operation of the test physical device” which is merely a field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Further, these claims do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fail Step 2B as not amounting to significantly more. Therefore, claims 9 and 19 do not recite patent eligible subject matter under 35 U.S.C. §101.
Regarding claims 10 and 20, they recite an additional limitation of “wherein measuring performance of the instance of the test physical device includes measuring performance of instances of the plurality of test physical devices fabricated on the single wafer”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, person can mentally assess or draw with a pen and paper the performance of the physical devices on a single wafer by determining if the devices meet their specifications.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 10 and 20, they recite an additional limitation of “wherein determining the original test design for the test physical device includes determining a plurality of test designs for a plurality of test physical devices to be fabricated on a single wafer”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally create or draw with pen and paper an initial design for an electrical device that contains multiple components on a single wafer using an inverse design process that generates an output based on a certain input per given specifications.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Regarding claim 14, it recites an additional limitation of “measuring accuracy of the structural parameters by comparing a scanning electron microscope (SEM) image of the instance of the test physical device to the structural parameters”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally qualify the similarities between an SEM image of the design and the physical design to determine the accuracy of the structural parameters from the fabrication model.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Therefore, having concluded the analysis within the provided framework, claims 1, 3-11, and 13-20 do not recite patent eligible subject matter and are rejected under 35 U.S.C. § 101 because the claimed invention is directed to judicial exception, an abstract idea, that has not been integrated into a practical application. The claims further do not recite significantly more than the judicial exception. Claims 3-10 and 13-20 are also rejected for incorporating the deficiency of their independent claim 1 and 11, respectively.
Claim Rejections - 35 U.S.C. § 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.
Claims 1, 3-4, 7-8, 11, 13-14 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over US 2016/0012176 A1 Liu, et al. [herein “Liu”] in view of US 2019/0311083 A1 Feng, et al. [herein “Feng”].
As per claim 1, Liu teaches “A non-transitory computer-readable medium having computer-executable instructions stored thereon that, in response to execution by one or more processors of a computing system, cause the computing system to perform actions for deriving a fabrication model for a fabrication system using an inverse design process, the actions comprising:” (Para. 85, “Recording the results from an operation or data acquisition, such as for example, recording results at a particular frequency or wavelength is understood to mean and is defined herein as writing output data in a non-transitory manner to a storage element, to a machine-readable storage medium [non-transitory computer-readable medium].” Para. 87, “It is understood that memory used by the microcomputer, including for example instructions for data processing coded as “firmware” can reside in memory physically inside of a microcomputer chip [executing instructions store thereon that, in the response to the execution by a processor].” Para. 19, “the method identifying fabrication design rules of a fabrication process; generating an initial device design by determining, with use of constraints of the fabrication design rules, a plurality of I/O ports and segments along a direction of optical signal propagation, each segment of the plurality of segments characterized by at least one width; and iteratively optimizing a device design starting with the initial device design by: generating a smoothed geometry of the device design with use of at least one of optical proximity correction and device fabrication simulation; simulating a functionality of the device utilizing the smoothed geometry of the device design; and utilizing an optimization algorithm on said widths characterizing said segments [process of deriving a fabrication model].” Para. 20, “simulating a functionality of the device comprises determining at least one figure of merit (FOM), wherein iteratively optimizing the device design comprises evaluating optimization criteria with use of the at least one FOM, and for each iteration of said iteratively optimizing for which optimization criteria has not been met [inverse design process].” Para. 42, “The device has a minimum feature size of 200 nm, and successfully fabricated using 248 nm lithography [a means of fabricating the device, i.e., a fabrication system].” Further see Para. 19-20, 42, and 85-87. The examiner has interpreted following: outputting data in a non-transitory manner to a machine-readable storage medium as a non-transitory computer-readable medium; memory used by the microcomputer, including for example instructions for data processing coded as “firmware” can reside in memory physically inside of a microcomputer chip as executing instructions by a processor of a computing system; the method iteratively optimizing a device design starting with the initial device design as a deriving a fabrication model using an inverse design process; and a fabricating a device using 248 nm lithography as a means of fabricating the device, i.e., a fabrication system.)
Liu also teaches “determining an original test design for a test physical device”. (Para. 69, “an initial design is created [determining an original test design] which uses judiciously chosen input and output (I/0) ports 610 having widths so as to remain within the constraints of the fabrication design rules.” Para 66, “the method described above for use in designing photonic devices [design for a physical test device] will now be described.” Further see Para. 66-69. The examiner has interpreted that creating an initial design for a photonic device as determining an original test design for a test physical device.)
Liu also teaches “measuring performance of an instance of the test physical device fabricated by the fabrication system using the original test design to determine an as-fabricated performance metric”. (Para 36, “We have designed a compact, low-loss... waveguide… and fabricated the device [device fabricated using the original test design] in a 248 nm CMOS line.” Para. 42, “The device has a minimum feature size of 200 nm, and successfully fabricated using 248 nm lithography [a means of fabricating the device, i.e., a fabrication system].” Para. 54, “Light from a tunable laser was coupled into the device under test (DUT) [instance of the test physical device].” Para. 59, “It is difficult to measure sub-0.5 dB insertion loss [measuring performance] from a single device. Therefore, test structures with different numbers of Y-junctions in the loop were used to figure out the insertion loss. The measured peak power [as-fabricated performance metric] as a function of number of Y-junctions in the loop is plotted in FIG. 5A. Further see Para. 42 and 54-59. The examiner has interpreted the measuring insertion loss of the device under test that was designed to be a compact, low-loss waveguide and fabricated successfully using 248 nm lithography by measuring the peak power as measuring performance of an instance of the original test physical device fabricated by the fabrication system to determine an as-fabricated performance metric.)
Liu does not specifically teach “determining an as-fabricated design by performing an iterative optimization that includes backpropagating a loss metric through the original test design via a first loss function to determine a structural gradient and updating the original test design based on the structural gradient so that the updated original test design converges to the as-fabricated design, wherein the first loss function is based on differences in a simulated performance metric of the original test design and the as-fabricated performance metric”, “optimizing a fabrication model using a second loss function based on differences between the original test design and the as-fabricated design”, “using the optimized fabrication model to optimize a new design for the new physical device”, and “transmitting the optimized new design for the new physical device to the fabrication system to cause the fabrication system to fabricate of an instance of the new physical device.”
However, in the same field of endeavor namely modeling and simulating semiconductor systems, Feng teaches “determining an as-fabricated design by performing an iterative optimization that includes backpropagating a loss metric through the original test design via a first loss function to determine a structural gradient and updating the original test design based on the structural gradient so that the updated original test design converges to the as-fabricated design”. (Para. 67, “Examples of such floated process model parameters include vertical etch rate, lateral etch rate, nominal etch depth, etch selectivity, vertical deposition rate, plasma angular dependence of sputter yield, and plasma energy dependence of sputter yield, all for a given material subject to a given semiconductor device fabrication operation” [e.g., structural parameters]. Para. 88, “The computationally predicted result R[λ]calc, and metrology generated result R[λ]exp are compared (e.g., a difference, ratio, or other metric is determined) by a "cost function calculator" 412 to output one or more cost values, e.g., identified in the figure as R[λ]exp - R[λ]calc. This comparison provides cost value(s) that reflect the magnitude of the difference (or agreement) between the predicted/simulation result, e.g., R[λ]calc, and the experimentally determined result, R[λ]exp” [a loss metric, a first loss function]. Para. 89, “Estimator 418 employs a "convergence checker," which is an algorithm for evaluating potential convergence of the floated process model parameter value, α.” Para. 90, “during one or more iterations of the optimization routine, execution of the convergence checker 418 will indicate that the cost values have not reached a required convergence condition” [determining an as-fabricated design by performing an iterative optimization via a first loss function so that the updated original test design converges to the as-fabricated design]. “In such instances, the convergence checker adjusts the current value of α and outputs an adjusted value of α as illustrated at 424. Adjusting α may employ, as understood by those of skill in the art, the current value of α and/or the cost value, as well as, optionally, one or more prior values of α and/or prior values the cost value. A gradient descent technique may be employed for this purpose. The adjusted α is then re-input, as illustrated at 426” [that includes backpropagating a loss metric through the original test design via a first loss function to determine a structural gradient and updating the original test design based on the structural gradient]. Further see Para. 67 and 88-90. The examiner has interpreted that executing a optimization routine for multiple iterations that adjusts a floated process model parameter such as nominal etch depth using a gradient descent technique to make a cost value that determines a metric between the experimentally determined result and the predicted results reflectance coefficient of a design converge as determining an as-fabricated design by performing an iterative optimization that includes backpropagating a loss metric through the original test design via a first loss function to determine a structural gradient and updating the original test design based on the structural gradient so that the updated original test design converges to the as-fabricated design.)
Feng also teaches “wherein the first loss function is based on differences in a simulated performance metric of the original test design and the as-fabricated performance metric”. (Para. 88, “The computationally predicted result R[λ]calc, and metrology generated result R[λ]exp are compared (e.g., a difference, ratio, or other metric is determined) by a "cost function calculator" 412 to output one or more cost values, e.g., identified in the figure as R[λ]exp - R[λ]calc. This comparison provides cost value(s) that reflect the magnitude of the difference (or agreement) between the predicted/simulation result, e.g., R[λ]calc, and the experimentally determined result, R[λ]exp” [wherein the first loss function is based on differences in a simulated performance metric of the original test design and the as-fabricated performance metric]. Further see Para. 87-89. The examiner has interpreted that determining a ratio metric between the experimentally determined result and the predicted results reflectance coefficient of a design as wherein the first loss function is based on differences in a simulated performance metric of the original test design and the as-fabricated performance metric.)
Feng also teaches “optimizing a fabrication model using a second loss function based on differences between the original test design and the as-fabricated design”. (Para. 104, “However, when calibrating a process simulation model using substrates having multilayer stacks of material to be etched, it is important that the simulation model use correct thickness values for each of the layers in the stack. To this end, the methods described herein may be performed in a manner in which a physical substrate comprising a multilayer stack to be used in calibration is evaluated by metrology preliminarily to determine the thickness of each layer in the stack. These thicknesses are then used in the computational representation of the substrate considered in the process simulation model [updating the thickness between design and physical layers, e.g., a second loss function based on differences between the original test design and the as-fabricated design]. In this manner, the simulation appropriately represents the physical structure that will be used to provide experimental information, obtained by metrology, for calibrating the process simulation model” [optimizing a fabrication model using second loss function]. Further see Para. 104. The examiner has interpreted that determining the correct thickness of a material as a result from the obtaining the metrology determined thickness for use in calibrating the process simulation model as optimizing a fabrication model using a second loss function based on differences between the original test design and the as-fabricated design.)
Feng also teaches “using the optimized fabrication model to optimize a new design for the new physical device”. (Para. 105, “after the process simulation model has been fully calibrated [after the fabrication model has been fully optimized, e.g., the optimized fabrication model]”. Para. 105, “the model is put into practice and used for predicting etch results and all the applications that are associated… if, during actual use of such process simulation model [using the optimized fabrication model to optimize a new design the new physical device], it is discovered that the model has failed to accurately predict the etch profile produced by a real etch process, such information can be employed to further calibrate or at least refine the calibration of the model. The simulation result for the conditions resulting in the erroneous prediction are provided to the optimization routine along with the actual results of the etch process in order to further optimize the parameter values [optimizing new design] (alpha) used in the process simulation model.” Further see Para. 105. The examiner has interpreted that actual use of the fully calibrated model to run the optimization routine and optimize parameter values for applications for a real etch process as using the optimized fabrication model to optimize a new design for the new physical device.)
Feng also teaches “transmitting the optimized new design for the new physical device to the fabrication system to cause the fabrication system to fabricate of an instance of the new physical device.” (Para. 19, “The instructions include instructions for: (a) receiving process parameter values as inputs to the optimized process simulation model; (b) executing the optimized process simulation model using the process parameter values; and (c) outputting a calculated result of the semiconductor device fabrication operation [transmitting the optimized new design for the new physical device].” Para. 25, “instructions additionally include instructions for using the calculated result to identify operating conditions of a semiconductor processing apparatus to enable fabrication of semiconductor devices by operating the semiconductor processing apparatus [design is for use in the fabrication system, e.g., to the fabrication system to cause the fabrication system] under the operating conditions.” Para. 105, “In this manner, the predictive capability of the process simulation model may be improved within the realm of physical conditions in which it is used, and/or the realm of the model is extended to new physical applications [to yield a physical instance, e.g., to fabricate of an instance of the new physical device] represented by the etch conditions for which the model incorrectly predicted an etch result.” The examiner has interpreted outputting the calculated result of the semiconductor device fabrication operation through a semiconductor processing apparatus to enable fabrication of semiconductor devices by operating the semiconductor processing apparatus as transmitting the optimized new design for the new physical device to the fabrication system to cause the fabrication system to fabricate of an instance of the new physical device.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “determining an as-fabricated design by performing an iterative optimization that includes backpropagating a loss metric through the original test design via a first loss function to determine a structural gradient and updating the original test design based on the structural gradient so that the updated original test design converges to the as-fabricated design, wherein the first loss function is based on differences in a simulated performance metric of the original test design and the as-fabricated performance metric”, “optimizing a fabrication model using a second loss function based on differences between the original test design and the as-fabricated design”, “using the optimized fabrication model to optimize a new design for the new physical device”, and “transmitting the optimized new design for the new physical device to the fabrication system to cause the fabrication system to fabricate of an instance of the new physical device” as conceptually seen from the teaching of Feng, into that of Liu because this modification of obtaining an optimized test design and optimized fabrication model and using the optimized model on new designs for the advantageous purpose of developing a model that produces increase the accuracy of the fabrication model (Feng, Para. 87-90) and representing new physical applications using the improved model and continuing to improve the model over the multiple uses and new designs (Feng, Para. 105). Further motivation to combine be that Liu and Feng are analogous art to the current claim and are directed to modeling and simulating semiconductor systems.
As per claim 3, Liu does not specifically teach, “wherein the actions further comprise: transmitting the original test design to the fabrication system for fabrication of the instance of the test physical device.”
However, Feng teaches, “wherein the actions further comprise: transmitting the original test design to the fabrication system for fabrication of the instance of the test physical device.” (Para. 19, “The instructions include instructions for: (a) receiving process parameter values as inputs to the optimized process simulation model; (b) executing the optimized process simulation model using the process parameter values; and (c) outputting a calculated result of the semiconductor device fabrication operation [transmitting the original design].” Para. 25, “instructions additionally include instructions for using the calculated result to identify operating conditions of a semiconductor processing apparatus to enable fabrication of semiconductor devices by operating the semiconductor processing apparatus [design is for use in the fabrication system] under the operating conditions.” Para. 75, “The computationally predicted result of the semiconductor device fabrication operation is compared, at operation 308, with a metrology result produced, at least in part, by performing the semiconductor device fabrication operation in a reaction chamber operating under the set of fixed process parameter values.” Further see Para. 19, 25, and 75. The examiner has interpreted that outputting the design to enable the fabrication of the device to perform the semiconductor fabrication operation in a chamber as transmitting the original test design to the fabrication system to create an instance of the design.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “wherein the actions further comprise: transmitting the original test design to the fabrication system for fabrication of the instance of the test physical device” as conceptually seen from the teaching of Feng, into that of Liu because this modification of sending designs to be fabricated for the advantageous purpose of verifying if the test design has converged to the fabrication design to show the optimization process is complete (Feng Para. 75). Further motivation to combine be that Liu and Feng are analogous art to the current claim and are directed to modeling and simulating semiconductor systems.
As per claim 4, Liu does not specifically teach, “wherein the actions further comprise: measuring accuracy of the fabrication model by comparing a scanning electron microscope (SEM) image of the instance of the test physical device to the as-fabricated design.”
However, Feng teaches “wherein the actions further comprise: measuring accuracy of the fabrication model by comparing a scanning electron microscope (SEM) image of the instance of the test physical device to the as-fabricated design.” (Para. 91, “optimization system 500 shown here in FIG. 5 compares computationally-generated feature profile (for a given input α), illustrated as 506, against an experimentally-derived measurement [comparing the design to the instance of the physical test device to determine the accuracy of the fabrication model] of the feature profile, e.g., via energy dispersive X-ray Scanning Electron Microscopy ("X-SEM"), for example, to adjust a toward convergence as illustrated at 520.” Further see Para. 91. The examiner has interpreted that comparing the computationally-generated feature profile to the experimentally-derived measurement via X-SEM as measuring the accuracy of the fabrication model by comparing a SEM image of the instance of the test physical device to the as-fabricated design.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “wherein the actions further comprise: measuring accuracy of the fabrication model by comparing a scanning electron microscope (SEM) image of the instance of the test physical device to the as-fabricated design” as conceptually seen from the teaching of Feng, into that of Liu because this modification of using SEM imaging to measuring the accuracy of the fabrication model for the advantageous purpose of obtaining and representing physical profile of the device for use in simplified and more accurate comparison of modeled and as-fabricated design structures (Feng Para. 91). Further motivation to combine be that Liu and Feng are analogous art to the current claim and are directed to modeling and simulating semiconductor systems.
As per claim 7, Liu teaches, “wherein the original test design includes at least one performance goal given an expected input.” (Para. 48, “The optimization figure of merit (FOM) was the power [performance goal] in TE0 mode at either branch…Within 50 iterations, one solution with sub-0.2 dB insertion loss [performance given an expected input] emerged, as shown in Table 1. Then 3D FDTD was run on this solution to double check the result with a mesh equal to 1/34 of the free space wavelength. The insertion loss was determined to be 0.13 dB.” Further see Para. 48. The examiner has interpreted obtaining a power figure of merit within 0.2 dB insertion loss as a performance goal given as expected inputs.)
As per claim 8, Liu teaches, “wherein determining the original test design includes providing the at least one performance goal to an inverse design process to generate the original test design.” (Para. 48, “In this design, the taper [original test design] was first digitalized into 13 segments of equal length…The optimization figure of merit (FOM) was the power [performance goal] in TE0 mode at either branch…Within 50 iterations, one solution with sub-0.2 dB insertion loss [generating test design to meet performance goal based on an input] emerged, as shown in Table 1. Then 3D FDTD was run on this solution to double check the result with a mesh equal to 1/34 of the free space wavelength. The insertion loss was determined to be 0.13 dB.” Para. 20, “simulating a functionality of the device comprises determining at least one figure of merit (FOM), wherein iteratively optimizing the device design comprises evaluating optimization criteria with use of the at least one FOM, and for each iteration of said iteratively optimizing for which optimization criteria has not been met [iterative design process using performance goal (e.g., an inverse design process)].” Further see Para. 20 and 48. The examiner has interpreted creating a solution with a power figure of merit within 0.2 dB insertion loss through an iteratively optimized design to meet the optimization criteria as determining the original test design providing a performance goal to an inverse design process to generate the original test design.)
Re Claim 11, it is a process claim, having similar limitations of claim 1. Thus claim 11 is also rejected under the similar rationale as cited in the rejection of claim 1.
Re Claim 13, it is a process claim, having similar limitations of claim 3. Thus claim 13 is also rejected under the similar rationale as cited in the rejection of claim 3.
As per claim 14, Liu does not specifically teach “measuring accuracy of the structural parameters by comparing a scanning electron microscope (SEM) image of the instance of the test physical device to the structural parameters.”
However, Feng teaches “measuring accuracy of the structural parameters by comparing a scanning electron microscope (SEM) image of the instance of the test physical device to the structural parameters.” (Para. 7, “floated process model parameters [structural parameters] includes a vertical etch rate, a lateral etch rate, a nominal etch depth, an etch selectivity, a tilt angle of ion entry, a twist angle of ion entry, a visibility into a feature, an angular distribution, a sputter maximum yield angle, and/or an etch ratio per crystal direction.” Para. 77, “The process model parameter α represents one or more floated process model parameters to be optimized over the course of optimization process 300.” Para. 91, “optimization system 500 shown here in FIG. 5 compares computationally-generated feature profile (for a given input α), illustrated as 506, against an experimentally-derived measurement [comparing the device to the design for accuracy] of the feature profile, e.g., via energy dispersive X-ray Scanning Electron Microscopy ("X-SEM"), for example, to adjust a toward convergence as illustrated at 520.” Further see Para. 7, 77, and 91. The examiner has interpreted that floated process model parameters that are compared against the X-SEM measurements of the device as structural parameters that are measured for accuracy by comparing to the SEM of the test device.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “measuring accuracy of the structural parameters by comparing a scanning electron microscope (SEM) image of the instance of the test physical device to the structural parameters” as conceptually seen from the teaching of Feng, into that of Liu because this modification of using SEM imaging to measure the accuracy of the fabrication model for the advantageous purpose of obtaining and representing physical profile of the device for use in simplified and more accurate comparison of modeled and as-fabricated design structures (Feng Para. 91). Further motivation to combine be that Liu and Feng are analogous art to the current claim and are directed to modeling and simulating semiconductor systems.
Re Claim 17, it is a process claim, having similar limitations of claim 7. Thus claim 17 is also rejected under the similar rationale as cited in the rejection of claim 7.
Re Claim 18, it is a process claim, having similar limitations of claim 8. Thus claim 18 is also rejected under the similar rationale as cited in the rejection of claim 8.
Claims 5-6 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Liu and Feng as applied to claim 1 and 11 above, and further in view of Wong, Alison, Benjamin Pope, Louis Desdoigts, Peter Tuthill, Barnaby Norris, and Chris Betters. "Phase retrieval and design with automatic differentiation: tutorial." JOSA B 38, no. 9 (2021): 2465-2478 [herein “Wong”].
As per claim 5, neither Liu nor Feng specifically teach “wherein the fabrication model includes a neural network; and wherein optimizing the fabrication model includes using at least one of gradient descent and an Adam optimizer.”
However, in the same field of endeavor namely modeling optical systems, Wong teaches “wherein the fabrication model includes a neural network; and wherein optimizing the fabrication model includes using at least one of gradient descent and an Adam optimizer.” (Pg. 2466, Col. 1, “In each of these cases, a physical optics simulation [fabrication model] is implemented in an autodiff framework and used to design phase optics by gradient descent” [wherein optimizing the fabrication model includes using gradient descent]. Pg. 2468, Col. 1, “TensorFlow was used to calculate the gradients of each pixel in the pupil plane with respect to the objective function, and the Adam [55] algorithm [Adam optimizer] was used to obtain an adaptive learning rate…additionally, we attempted reconstructions with a dense neural network and a convolutional neural network for this same task, where the output of the networks was a proposed phase pattern, similar to methods used by Hoyer” [wherein the fabrication model includes a neural network]. Fig. 2 shows the results generated by the gradient decent and Adam optimizer for 3 cases. Further see Sect. 2A-2B. The examiner has interpreted adapting a neural network to optimize the simulation using a gradient descent and the Adam optimizer as using a neural network to optimize the fabrication model using a gradient and Adam optimizer.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “wherein the fabrication model includes a neural network; and wherein optimizing the fabrication model includes using at least one of gradient descent and an Adam optimizer” as conceptually seen from the teaching of Wong, into that of Liu and Feng because this modification of using a neural network, gradient descent, and an Adam optimizer to optimize the fabrication model for the advantageous purpose of solving complex relationships, minimize error, and globally optimize solution methods (Wong, Part 2 Section A). Further motivation to combine be that Liu, Feng, and Wong are analogous art to the current claim are directed to modeling optical systems.
As per claim 6, neither Liu nor Feng specifically teach “wherein the fabrication model includes a sequence of differentiable operations; and wherein optimizing the fabrication model includes using a JAX framework.”
However, Wong teaches “wherein the fabrication model includes a sequence of differentiable operations; and wherein optimizing the fabrication model includes using a JAX framework.” (Pg. 2466, Col. 1, “Gradient-based techniques require only a differentiable objective function and so can be trivially applied to a wide variety of tasks. In this paper, we look at applying these techniques to challenges encountered in optics, which are naturally primed for this framework, as the underlying operations are straightforwardly differentiable [sequence of differentiable operations].” Pg. 2471, Col. 2, “We will use Morphine for optical simulation [for optimizing the model], which is a fork of the popular Poppy library [60] using the JAX autodiff [automatic differentiation] library [36] [JAX framework] in place of NumPy.” Further see Sect. 2A-2B. The examiner has interpreted the differentiable operations from the JAX autodiff library as optimizing the model using JAX framework and a sequence of differentiable operations.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “wherein the fabrication model includes a sequence of differentiable operations; and wherein optimizing the fabrication model includes using a JAX framework” as conceptually seen from the teaching of Wong, into that of Liu and Feng because this modification of using differentiable operations and a JAX framework to optimize the fabrication model for the advantageous purpose of offering much greater flexibility for phase retrieval (Wong Pg. 2466 Col. 2) as well as output more complex and constrained solution (Wong Pg. 2476, Col. 1). Further motivation to combine be that Liu, Feng, and Wong are analogous art to the current claim are directed to modeling optical systems.
Re Claim 15, it is a process claim, having similar limitations of claim 5. Thus claim 15 is also rejected under the similar rationale as cited in the rejection of claim 5.
Re Claim 16, it is a process claim, having similar limitations of claim 6. Thus claim 16 is also rejected under the similar rationale as cited in the rejection of claim 6.
Claims 9-10 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Liu and Feng, as applied to claims 1 and 11 above, and in further view of US 2003/0204326 A1 Opsal, et al. [herein “Opsal”].
As per claim 9, Liu nor Feng specifically teach “wherein the expected input includes one or more intended wavelength spectra for operation of the test physical device; wherein measuring performance of the instance of the test physical device includes measuring performance of the instance of the test physical device within the one or more intended wavelength spectra and outside of the one or more intended wavelength spectra.”
However, in the same field of endeavor namely modeling semiconductor systems, Opsal teaches “wherein the expected input includes one or more intended wavelength spectra for operation of the test physical device; wherein measuring performance of the instance of the test physical device includes measuring performance of the instance of the test physical device within the one or more intended wavelength spectra and outside of the one or more intended wavelength spectra.” (Para. 33, “The system 16 includes a light source 20. As noted above, scatterometry measurements are often made using a broad band light source generating a probe beam 22 having a plurality of wavelengths [input includes one or more intended wavelength spectra].” Para. 34, “Probe beam is directed to the sample [testing for operation of the test physical device]…The measured intensity of the probe beam will be effected by the amount of light scattered by the periodic structure. More specifically, the proportion of light diffracted into higher orders varies as a function of wavelength and angle of incidence such the amount of light redirected out of the path to the detector also varies thereby permitting the scattering effects to be observed [outside one of more intended wavelength spectra].” Para. 35, “a single photodetector can be used to measure spectroscopic reflected intensity as long as a tunable wavelength selective filter (monochrometer) is located in the path of the probe beam [within the one or more intended wavelength spectra]. Given the desire to minimize measurement time, a spectrometer is typically used which includes a wavelength dispersive element (grating or prism) and an array detector to measure multiple wavelengths [within and outside intended wavelength spectra] simultaneously. An array detector can also be used to measure multiple angles of incidence simultaneously.” Further see Para. 33-35. The examiner has interpreted the using a probe beam with a plurality of wavelength to measure the selective path of the probe beam and the scattering effects of the beam of the photodetector as an expected input that includes the one or more within and outside of the intended wavelength spectra.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “wherein the expected input includes one or more intended wavelength spectra for operation of the test physical device; wherein measuring performance of the instance of the test physical device includes measuring performance of the instance of the test physical device within the one or more intended wavelength spectra and outside of the one or more intended wavelength spectra” as conceptually seen from the teaching of Opsal, into that of Liu and Feng because this modification of measuring the performance of the devices inside and outside the intended wavelength spectra for the advantageous purpose of efficiently determining the design and verifying that the model will best meet the performance expectations in different conditions (Opsal Para. 40), including performance of the device both inside and outside the desired wavelength criteria. Further motivation to combine be that Liu, Feng, and Opsal are analogous art to the current claim are directed to modeling optical systems.
As per claim 10, Liu teaches, “wherein determining the original test design for the test physical device includes determining a [plurality of] test design [s] for a plurality of test physical devices to be fabricated on a single wafer; and wherein measuring performance of the instance of the test physical device includes measuring performance of instances of the plurality of test physical devices fabricated on the single wafer.” (Para. 54, “Devices [plurality of test physical devices] were measured on a wafer [a single wafer] scale setup that can map the wafer coordinate to the stage coordinate, so that any device can be easily probed after initial alignment [measuring the performance of instances of the plurality of the test devices]. Light from a tunable laser was coupled into the device under test (DUT) via a though a polarization maintaining (PM) fiber and grating coupler.” The examiner has interpreted that configuring a test design for devices on a wafer and probing the devices to measure light coupling through the device as determining a test design for a plurality of test physical devices to be fabricated on a single wafer; and wherein measuring performance of the instance of the test physical device includes measuring performance of instances of the plurality of test physical devices fabricated on the single wafer.)
Liu nor Feng specifically teach, “wherein determining the original test design for the test physical device includes determining a plurality of test designs for a plurality of test physical devices to be fabricated on a single wafer; and wherein measuring performance of the instance of the test physical device includes measuring performance of instances of the plurality of test physical devices fabricated on the single wafer.”
However, Opsal teaches, “wherein determining the original test design for the test physical device includes determining a plurality of test designs for a plurality of test physical devices to be fabricated on a single wafer; and wherein measuring performance of the instance of the test physical device includes measuring performance of instances of the plurality of test physical devices fabricated on the single wafer.” (Para. 35, “a single photodetector can be used to measure spectroscopic reflected intensity [measuring performance] as long as a tunable wavelength selective filter (monochrometer) is located in the path of the probe beam. Given the desire to minimize measurement time [measuring performance], a spectrometer is typically used which includes a wavelength dispersive element (grating or prism) and an array detector to measure multiple wavelengths [measuring performance] simultaneously. An array detector can also be used to measure multiple angles of incidence [measuring performance] simultaneously.” Para 39, “an initial model is created and calculations are performed to determine the expected response of that sample [test physical device] to interaction with light. The model is then iteratively modified until the results of the calculation are close to the actual measured [measuring performances of the instance of the device] (and normalized) data. The subject approach can be contrasted with the earlier approaches which required the fabrication of many references samples [plurality of test devices], each of which would be measured [measuring performance of multiple devices], with the results stored for later comparison to the test sample.” Further see Para. 35-39. The examiner has interpreted that the measuring of spectroscopic reflected intensity, wavelengths, and multiple angles of incidence for many reference samples as measuring the performance of instances of a plurality of test physical devices.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “a plurality of test designs for a plurality of test physical devices” as conceptually seen from the teaching of Opsal, into that of Liu and Feng because this modification of designing many devices for the advantageous purpose of comparing the model to a number of samples in determining the best fit of the model to a desired sample (Opsal Para. 39). Further motivation to combine be that Liu, Feng, and Opsal are analogous art to the current claim are directed to modeling optical systems.
Re Claim 19, it is a process claim, having similar limitations of claim 9. Thus claim 19 is also rejected under the similar rationale as cited in the rejection of claim 9.
Re Claim 20, it is a process claim, having similar limitations of claim 10. Thus claim 20 is also rejected under the similar rationale as cited in the rejection of claim 10.
Response to Arguments
Applicant's arguments filed on November 20, 2025 have been fully considered but they are not persuasive.
Applicant argues that the amended claim features are patent eligible under 35 U.S.C. § 101 because the claims do not recite mental processes as they cannot be performed practically in the human mind (See Applicant’s response, Pg. 7-8).
MPEP § 2106.04(a)(2)(III)(A) recites “claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions”, “claims can recite a mental process even if they are claimed as being performed on a computer”, and “in evaluating whether a claim that requires a computer recites a mental process, examiners should carefully consider the broadest reasonable interpretation of the claim in light of the specification. For instance, examiners should review the specification to determine if the claimed invention is described as a concept that is performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer, or 2) in a computer environment, or 3) is merely using a computer as a tool to perform the concept. In these situations, the claim is considered to recite a mental process.”
The examiner has provided the rational for the claim limitations that are being directed to a mental process in the rejection above. For example, the limitation of amended claim 1, “determining an as-fabricated design by performing an iterative optimization that includes backpropagating a loss metric through the original test design via a first loss function to determine a structural gradient and updating the original test design based on the structural gradient so that the updated original test design converges to the as-fabricated design” has been interpreted as a mental process since a person can mentally create or draw with pen and paper an as-fabricated design based on a calculated structural gradient using backpropagating differential gradient formula of the performance differences between of the initial test design and the as-fabricated design to converge the initial test design to the as-fabricated design. The iterative process of updating the initial design to meet the performance of the as-fabricated design can still be done in the mind, for example, a person, after updating the initial design and determining the initial design performance has not converged to the as-fabricated design closely enough, would then further update the initial design and repeat the process until the initial test design fully converges to the as-fabricated design. For example, the limitation of amended claim 1, “optimizing a fabrication model using a second loss function based on differences between the original test design and the as-fabricated design” has been interpreted as a mental process since a person can mentally alter or draw with pen and paper the design process that converges the initial test design to the as-fabricated design based on the simulated results and structural parameter differences between the initial test design and fabricated design. The design process of updating the initial design so that its performance will converge to the performance of the as-fabricated design is modified based on the differences between simulated results and the structural parameters between the two designs. This is process can be updated mentally or with a pen and paper.
The examiner has properly identified that the claims recite a mental concept as provided in the rejection above is proper under the framework provided in the 2019 Patent Eligibility Guidance and MPEP § 2106.04(a)(2)(III)(C). The claims are directed to judicial exception, an abstract idea.
Applicant argues that the amended claim features are patent eligible under 35 U.S.C. § 101 because the claim is integrated into a practical application as claim features recite improvements to another technology or technical field as a whole (See Applicant’s response, Pg. 8-10).
MPEP § 2106.04(d)(II) recites “examiners evaluate integration into a practical application by: (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application”. MPEP § 2106.05(a) also recites “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements.”
The examiner has provided the rational for the independent claim limitations that are being directed to a mental process in the rejection above. Furthermore, the limitation of “using the optimized fabrication model to optimize a new design for a new physical device”, have been identified as a mental process in the rejection above. For example, a person can mentally draw with pen and paper using the updated fabricated design process model from the first device a second initial design for a second device. For example, a fabricated design which would be the physical implementation of the initial design based on processes and manufacturing limitations that are altered to better represent the initial design based on their performance and structural differences, and one can take the improvements from a process used in one design and carry over certain parameters, applications, enhancements, and lessons learned from a previous design into a second design. The additional element of “transmitting the optimized new design for the new physical device to the fabrication system to cause the fabrication system to fabricate an instance of the new physical device” which are merely using the generic computer components and functions being used as a tool to perform the abstract idea and, alternatively, is merely a recitation of insignificant extra-solution data outputting activity (see MPEP § 2106.05(g)), which is Well-Understood, Routine and Conventional. Therefore, there are no additional element limitations in the independent claims which can integrate the abstract idea into a practical application by improvements to the technology as listed in MPEP § 2106.04(d)(I). Furthermore, the examiner has also provided the rational for the dependent claim limitations that are being directed to a mental process or a mathematical concept in the rejection above. With the exception of the additional element limitations in the dependent claims which are merely using the generic computer components and functions being used as a tool to perform the abstract idea, insignificant extra-solution data outputting activity, and implementing the field of use/technological environment, there are no additional limitations in the dependent claims which can integrate the abstract idea into a practical application by improvements to the technology or through the use of meaningful limitations.
Therefore, the examiner has properly identified that the claims recite mental processes, mathematical concepts, and limitations that merely use the computer as a tool to perform the abstract idea, insignificant extra-solution activities, or implement the field of use/technological environment.
Applicant argues that the combination of references does not teach each and every limitation in the amend claims 1 and 11 because cited references fail to teach “determining an as-fabricated design by performing an iterative optimization that includes backpropagating a loss metric through the original test design via a first loss function to determine a structural gradient and updating the original test design based on the structural gradient so that the updated original test design converges to the as-fabricated design, wherein the first loss function is based on differences in a simulated performance metric of the original test design and the as-fabricated performance metric”. (See Applicant’s response, Pg. 10-12).
MPEP § 2143.03 states that “All words in a claim must be considered in judging the patentability of that claim against the prior art” and “Examiners must consider all claim limitations when determining patentability of an invention over the prior art.”
As original mapped in the previous Office Action and above in claim 1, Feng discloses teach “determining an as-fabricated design by performing an iterative optimization that includes backpropagating a loss metric through the original test design via a first loss function to determine a structural gradient and updating the original test design based on the structural gradient so that the updated original test design converges to the as-fabricated design, wherein the first loss function is based on differences in a simulated performance metric of the original test design and the as-fabricated performance metric” as executing a optimization routine for multiple iterations that adjusts a floated process model parameter such as nominal etch depth using a gradient descent technique to make a cost value that determines a metric between the experimentally determined result and the predicted results reflectance coefficient of a design converge and where the metric is a ratio metric between the experimentally determined result and the predicted results reflectance coefficient of a design. Cost values and floated process model parameter value, α are adjusted until the optimization routine reaches a required convergence condition of the agreement between the predicted/simulation result and the experimentally determined result. Thus, the claimed limitation is taught.
Therefore, all of the limitations of the amended claims 1 and 11 are disclosed in Liu or Feng, and the combination of these references renders the claimed invention obvious. Therefore, applicant’s arguments are not persuasive and the rejection of claim 1 and 11 as obvious over Liu in view of Feng is maintained.
Applicant argues that the combination of references does not teach each and every limitation in the amend claims 1 and 11 because cited references fail to teach “optimizing a fabrication model using a second loss function based on differences between the original test design and the as-fabricated design”. (See Applicant’s response, Pg. 10-12).
MPEP § 2143.03 states that “All words in a claim must be considered in judging the patentability of that claim against the prior art” and “Examiners must consider all claim limitations when determining patentability of an invention over the prior art.”
As original mapped in the previous Office Action and above in claim 1, Feng discloses teach “optimizing a fabrication model using a second loss function based on differences between the original test design and the as-fabricated design” as determining the correct thickness of a material as a result from the obtaining the metrology determined thickness for use in calibrating the process simulation model. Similarly, as stated above, the predicted result converges with the experimentally determined result, then the design is shown to be optimized. Thus, the claimed limitation is taught.
Therefore, all of the limitations of the amended claims 1 and 11 are disclosed in Liu or Feng, and the combination of these references renders the claimed invention obvious. Therefore, applicant’s arguments are not persuasive and the rejection of claim 1 and 11 as obvious over Liu in view of Feng is maintained.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ma, Xu, et al. "Model-driven convolution neural network for inverse lithography." Optics express 26, no. 25 (2018): 32565-32584 teaches a method for a model-driven convolution neural network to obtain the approximate guess of inverse lithography techniques solutions.
Examiner’s Note: The examiner has cited particular columns and line numbers in the reference that applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, to fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. In the case of amending the claimed invention, the applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for the proper interpretation and also to verify and ascertain the metes and bound of the claimed invention.
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/SIMEON P DRAPEAU/ Examiner, Art Unit 2188
/RYAN F PITARO/ Supervisory Patent Examiner, Art Unit 2188