DETAILED ACTION
1. Claims 1, 4, 6, and 9 have been presented for examination.
Claims 2-3, 5, 7-8, and 10 have been cancelled.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
PRIORITY
3. Acknowledgment is made that this application is a 371 of PCT/JP2021/015043 filed 04/09/2021.
Acknowledgment is made of applicant's claim for foreign priority under 35 U.S.C. 119(a)-(d) to JAPAN 2020-079791 filed 04/28/2020.
Response to Arguments
4. Applicant's arguments filed 2/2/26 have been fully considered but they are not persuasive.
i) Following Applicants arguments and amendments the previously presented 101 rejection is MAINTAINED. Specifically, Applicants argue that the claims represent an improvement to a technology however Applicants cite only the specification to support their conclusion and the Examiner notes that the improvements upon which applicant relies (i.e., [0007]-[0009] of applicants specification particularly the aspects of “high accuracy with less calculation cost”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). The present claims do not reflect the purported improvements cited by the Applicant, with reference to the sections of the specification cited in the arguments. The present claims do not improve the functioning of the computer as well as any other technology or technical field.
Applicants further argue that the estimations recited are “far too complex to be practically performed in the human mind or with a pen and paper.” However, as noted above, Applicants alleged complexity is not found in the claims as recited. The claims represent broadly recited determinations and estimations which could practicably be performed by a person as a mental process or with the aid of pencil and paper particularly in view of the broadest reasonable interpretation of the claims.
Applicants recitation of “machine learning” does not overcome this analysis since the inclusion of “machine learning” are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. See MPEP (2106.05(f)) Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process) does not integrate a judicial exception into a practical application. (MPEP 2106.05(f)(2))
In view of Applicants amendments reciting at least the “chemical structure” aspect the Examiner notes that the claims now appear to now also fall under the abstract idea of mathematical concepts as noted below.
As such the 101 rejection is MAINTAINED.
ii) Following Applicants arguments and amendments the previously presented prior art rejection is WITHDRAWN.
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.
5. Claims 1, 4, 6, and 9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. abstract idea) without anything significantly more.
i) In view of Step 1 of the analysis, claim(s) 1 is directed to a statutory category as a machine, and claim 6 is directed to a statutory category as a process which each represent a statutory category of invention. Therefore, claims 1, 4, 6, and 9 are directed to patent eligible categories of invention.
ii) In view of Step 2A, Prong One, claims 1 and 6 recite the abstract idea of determining an estimation of a feature value of a material based on a provided descriptor and a provided feature value which constitutes an abstract idea based on Mental Processes based on concepts performed in the human mind, or with the aid of pencil and paper and Mathematical Concepts including mathematical formulas or equations as well as calculations.
As per claim 1, and similarly recited in claim 6, the limitation of “a simulator configured to estimate a feature value of a material by simulation” would be analogous to a person evaluating and determining a material feature estimate and a material feature value estimate of a material given provided information and thus fall under Mental Processes. Further the claim limitation may represent Mathematical Concepts including mathematical formulas or equations as well as calculations.
As per claim 1, and similarly recited in claim 6, the limitation of " a simulation estimation model that is configured to estimate a feature value of a simulation result of a material from a descriptor of the material, and a material feature value estimation model that is configured to estimate a feature value of the material from an estimation result of the simulation estimation model and a descriptor of the material, and” would be analogous to a person evaluating and determining a material feature estimate and a material feature value estimate of a material given provided information and thus fall under Mental Processes. Further the claim limitation may represent Mathematical Concepts including mathematical formulas or equations as well as calculations.
As per claim 1, and similarly recited in claim 6, the limitation of “determining, based at least on a chemical structural formula of a material from the tested material database at least one first descriptor, determining, based at least on a chemical structural formula of a material from the untested material database at least one second descriptor, acquiring a simulation result based on executing, using the simulator, simulation of a tested material selected based at least in part on the at least one first descriptor and the at least one second descriptor,” would be analogous to a person evaluating and determining a material feature estimate and a material feature value estimate of a material given provided information and thus fall under Mental Processes. Further the claim limitation may represent Mathematical Concepts including mathematical formulas or equations as well as calculations.
That is, other than reciting “one or more processors” as in claims 1 and 6 nothing in the claim element precludes the step from practically being performed in the mind.
Dependent claims 4 and 9 further narrow the abstract ideas, identified in the independent claims.
iii) In view of Step 2A, Prong Two, the judicial exception is not integrated into a practical application. In Claims 1 and 6, the additional element of “one or more processors” and “one or more storage devices” merely uses a computer device as a tool to perform the abstract idea. (MPEP 2106.05(f)) The limitation in claim 1, and similarly recited in claim 6, of “receiving, as an input, a chemical structural formula of the material or a descriptor of the material, wherein one or more descriptors of the material are determined based at least in part on the chemical structural formula of the material,” and “a tested material database that indicates a chemical structural formula of a tested material associated with a measurement value of a feature value of the tested material,” and “an untested material database that indicates a chemical structural formula of an untested material,” and “performing learning of the simulation estimation model based at least on the simulation result and at least one descriptor of the tested material,” and “inputting a descriptor of a first material into the simulation estimation model to acquire a first simulation estimation result of a feature value of the first material, the descriptor of the first material determined based at least in part on a chemical structural formula of the first material,” and “performing learning of the material feature estimation model based at least on the measurement value of the tested material and the simulation result,” and “inputting the first simulation estimation result and-a the descriptor of the first material or another descriptor of the first material into the material feature value estimation model to acquire a feature estimation value of the first material,” and “outputting, to a monitor, information related to the chemical structural formula of the first material and the feature estimation value of the first material” are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. See MPEP (2106.05(f)) Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process) does not integrate a judicial exception into a practical application. (MPEP 2106.05(f)(2)) Additionally the limitation of “receiving, as an input, a chemical structural formula of the material or a descriptor of the material, wherein one or more descriptors of the material are determined based at least in part on the chemical structural formula of the material,” and “a tested material database that indicates a chemical structural formula of a tested material associated with a measurement value of a feature value of the tested material,” and “an untested material database that indicates a chemical structural formula of an untested material,” and “inputting a descriptor of a first material into the simulation estimation model to acquire a first simulation estimation result of a feature value of the first material, the descriptor of the first material determined based at least in part on a chemical structural formula of the first material,” and “inputting the first simulation estimation result and-a the descriptor of the first material or another descriptor of the first material into the material feature value estimation model to acquire a feature estimation value of the first material,” and “outputting, to a monitor, information related to the chemical structural formula of the first material and the feature estimation value of the first material” in claims 1 and 6, alternatively can be viewed as insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and is not sufficient to integrate the judicial exception into a practical application. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the judicial exception is not integrated into a practical application.
Dependent claims 4 and 9 further narrow the abstract ideas, identified in the independent claims and do not introduce further additional elements for consideration beyond those addressed above.
iv) In view of Step 2B, claims 1 and 6 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Claims 1 and 6, the additional element of “one or more processors” and “one or more storage devices” merely uses a computer device as a tool to perform the abstract idea. (MPEP 2106.05(f)) The limitation in claim 1, and similarly recited in claim 6 of “receiving, as an input, a chemical structural formula of the material or a descriptor of the material, wherein one or more descriptors of the material are determined based at least in part on the chemical structural formula of the material,” and “a tested material database that indicates a chemical structural formula of a tested material associated with a measurement value of a feature value of the tested material,” and “an untested material database that indicates a chemical structural formula of an untested material,” and “performing learning of the simulation estimation model based at least on the simulation result and at least one descriptor of the tested material,” and “inputting a descriptor of a first material into the simulation estimation model to acquire a first simulation estimation result of a feature value of the first material, the descriptor of the first material determined based at least in part on a chemical structural formula of the first material,” and “performing learning of the material feature estimation model based at least on the measurement value of the tested material and the simulation result,” and “inputting the first simulation estimation result and-a the descriptor of the first material or another descriptor of the first material into the material feature value estimation model to acquire a feature estimation value of the first material,” and “outputting, to a monitor, information related to the chemical structural formula of the first material and the feature estimation value of the first material” are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. See MPEP (2106.05(f)) Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process) does not integrate a judicial exception into a practical application. (MPEP 2106.05(f)(2)) Additionally the limitation of “receiving, as an input, a chemical structural formula of the material or a descriptor of the material, wherein one or more descriptors of the material are determined based at least in part on the chemical structural formula of the material,” and “a tested material database that indicates a chemical structural formula of a tested material associated with a measurement value of a feature value of the tested material,” and “an untested material database that indicates a chemical structural formula of an untested material,” and “inputting a descriptor of a first material into the simulation estimation model to acquire a first simulation estimation result of a feature value of the first material, the descriptor of the first material determined based at least in part on a chemical structural formula of the first material,” and “inputting the first simulation estimation result and-a the descriptor of the first material or another descriptor of the first material into the material feature value estimation model to acquire a feature estimation value of the first material,” and “outputting, to a monitor, information related to the chemical structural formula of the first material and the feature estimation value of the first material” in claims 1 and 6, alternatively can be viewed as an insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and is not sufficient to integrate the judicial exception into a practical application. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the claim as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered alone or in combination, do not amount to significantly more than the judicial exception. As stated in Section I.B. of the December 16, 2014 101 Examination Guidelines, “[t]o be patent-eligible, a claim that is directed to a judicial exception must include additional features to ensure that the claim describes a process or product that applies the exception in a meaningful way, such that it is more than a drafting effort designed to monopolize the exception.”
The dependent claims include the same abstract ideas recited as recited in the independent claims, and merely incorporate additional details that narrow the abstract ideas and fail to add significantly more to the claims.
Dependent claims 4 and 9 further recites input of data into the training model which again merely uses a computer device as a tool to perform the abstract idea. (MPEP 2106.05(f)) Further the recitation represent mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. See MPEP (2106.05(f)) Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process) does not integrate a judicial exception into a practical application. (MPEP 2106.05(f)(2)) The recitation alternatively can be viewed as an insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and is not sufficient to integrate the judicial exception into a practical application.
v) Accordingly, claims 1, 4, 6, and 9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without anything significantly more.
Appropriate correction is required.
Allowable Subject Matter
6. Claims 1, 4, 6, and 9 are allowable over the prior art of record pending resolving all intervening issues such as the 101 rejection above.
The following is a statement of reasons for the indication of allowable subject matter:
Claim 1 recites:
A system that estimates a feature value of a material, the system comprising:one or more processors; and one or more storage devices,wherein the one or more storage devices are configured to store:
a simulator configured to estimate a feature value of a material by simulation based on receiving, as an input, a chemical structural formula of the material or a descriptor of the material, wherein one or more descriptors of the material are determined based at least in part on the chemical structural formula of the material,
a material feature estimation model, that includes:
a simulation estimation model that is configured to estimate a feature value of a simulation result of a material from a descriptor of the material, and
a material feature value estimation model that is configured to estimate a feature value of the material from an estimation result of the simulation estimation model and a descriptor of the material, and
a tested material database that indicates a chemical structural formula of a tested material associated with a measurement value of a feature value of the tested material, and
an untested material database that indicates a chemical structural formula of an untested material,
wherein the one or more processors are configured to perform operations that include:
determining, based at least on a chemical structural formula of a material from the tested material database at least one first descriptor,
determining, based at least on a chemical structural formula of a material from the untested material database at least one second descriptor,
acquiring a simulation result based on executing, using the simulator, simulation of a tested material selected based at least in part on the at least one first descriptor and the at least one second descriptor,
performing learning of the simulation estimation model based at least on the simulation result and at least one descriptor of the tested material,
inputting a descriptor of a first material into the simulation estimation model to acquire a first simulation estimation result of a feature value of the first material, the descriptor of the first material determined based at least in part on a chemical structural formula of the first material, and
performing learning of the material feature estimation model based at least on the measurement value of the tested material and the simulation result,
inputting the first simulation estimation result and-a the descriptor of the first material or another descriptor of the first material into the material feature value estimation model to acquire a feature estimation value of the first material, and
outputting, to a monitor, information related to the chemical structural formula of the first material and the feature estimation value of the first material.
Claim 6 recites:
A method that is executed by one or more processors configured by executable instructions, the method comprising:
determining, by the one or more processors, based at least on a chemical structural formula of a material determined from a tested material database, at least one first descriptor, wherein the tested material database indicates a chemical structural formula of a tested material associated with a measurement value of a feature value of the tested material,
determining, by the one or more processors, based at least on a chemical structural formula of a material determined from an untested material database, at least one second descriptor, wherein the untested material database indicates a chemical structural formula of an untested material,
acquiring, by the one or more processors, a simulation result based on executing, using a simulator, simulation of a tested material selected based at least in part on the at least one first descriptor and the at least one second descriptor, wherein the simulator is configured to estimate a feature value of a material by simulation based on receiving, as an input, a chemical structural formula of the material or a descriptor of the material,
performing, by the one or more processors, learning of a simulation estimation model based at least on the simulation result and at least one descriptor of the tested material, wherein the simulation estimation model is utilized with a material feature value estimation model for performing material feature estimation,
inputting, by the one or more processors, a descriptor of a first material into the simulation estimation model to acquire a first simulation estimation result of a feature value of the first material, the descriptor of the first material determined based at least in part on a chemical structural formula of the first material, and
performing, by the one or more processors, learning of the material feature estimation model based at least on the measurement value of the tested material and the simulation result,
inputting, by the one or more processors, the first simulation estimation result and-a the descriptor of the first material or another descriptor of the first material into the material feature value estimation model to acquire a feature estimation value of the first material, and
outputting, by the one or more processors, to a monitor, information related to the chemical structural formula of the first material and the feature estimation value of the first material.
The closes prior art of record teaches:
i) U.S. Patent Publication No. 20180032663, which teaches generating structures for new materials.
ii) Raccuglia, Paul, et al. "Machine-learning-assisted materials discovery using failed experiments." Nature 533.7601 (2016): 73-76. (Year: 2016) which teaches the aspects of machine learning in field of material discovery.
iii) Xu, Hongyi, et al. "A descriptor-based design methodology for developing heterogeneous microstructural materials system." Journal of Mechanical Design 136.5 (2014): 051007. (Year: 2014) which teaches the use of descriptor based design in the development of material systems.
iv) Mehrez, Loujaine, David Moens, and Dirk Vandepitte. "Stochastic identification of composite material properties from limited experimental databases, part I: Experimental database construction." Mechanical Systems and Signal Processing 27 (2012): 471-483.
v) Rossi, Marco, and Fabrice Pierron. "On the use of simulated experiments in designing tests for material characterization from full-field measurements." International Journal of Solids and Structures 49.3-4 (2012): 420-435.
vi) Pankajakshan, Praveen, et al. "Machine learning and statistical analysis for materials science: stability and transferability of fingerprint descriptors and chemical insights." Chemistry of Materials 29.10 (2017): 4190-4201 which teaches the use of machine learning and descriptors in the analysis of material science.
However, the closest prior art of record does not explicitly teach or render obvious the limitations above,
particularly in combination with the other limitations within the claims. The dependent claims are allowable for at least the same reasons as their respective independent claims.
Conclusion
7. 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.
8. All Claims are rejected.
9. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
i) U.S. Patent Publication No. 20180032663, which teaches generating structures for new materials.
ii) Raccuglia, Paul, et al. "Machine-learning-assisted materials discovery using failed experiments." Nature 533.7601 (2016): 73-76. (Year: 2016) which teaches the aspects of machine learning in field of material discovery.
iii) Xu, Hongyi, et al. "A descriptor-based design methodology for developing heterogeneous microstructural materials system." Journal of Mechanical Design 136.5 (2014): 051007. (Year: 2014) which teaches the use of descriptor based design in the development of material systems.
iv) Mehrez, Loujaine, David Moens, and Dirk Vandepitte. "Stochastic identification of composite material properties from limited experimental databases, part I: Experimental database construction." Mechanical Systems and Signal Processing 27 (2012): 471-483.
v) Rossi, Marco, and Fabrice Pierron. "On the use of simulated experiments in designing tests for material characterization from full-field measurements." International Journal of Solids and Structures 49.3-4 (2012): 420-435.
vi) Pankajakshan, Praveen, et al. "Machine learning and statistical analysis for materials science: stability and transferability of fingerprint descriptors and chemical insights." Chemistry of Materials 29.10 (2017): 4190-4201 which teaches the use of machine learning and descriptors in the analysis of material science.
10. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Saif A. Alhija whose telephone number is (571) 272-8635. The examiner can normally be reached on M-F, 10:00-6:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Renee Chavez, can be reached at (571) 270-1104. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300. Informal or draft communication, please label PROPOSED or DRAFT, can be additionally sent to the Examiners fax phone number, (571) 273-8635.
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SAA
/SAIF A ALHIJA/Primary Examiner, Art Unit 2186
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