DETAILED ACTION
1. Claims 1 and 6 have been presented for examination.
Claims 2-5 and 7-10 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. 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 8/31/26 has been entered.
i) Following Applicants arguments and amendments the previously presented 101 rejection is MAINTAINED. Applicants argue that the machine learning models are not abstract ideas. However as noted in the previous office action and reiterated here the use 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)) This amounts to mere instructions to apply the exception (MPEP 2106.05(f)).
Applicants argue that databases are also not abstract ideas. However as noted in the previous office action and reiterated here the use of databases 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)) This amounts to mere instructions to apply the exception (MPEP 2106.05(f)). Further the use of a database represents 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.
As to Applicants arguments regarding the chemical structure not representing a mathematical concept the Examiner notes that chemical formulas and calculations can be represented by mathematical concepts and that is in addition to the judicial exception as a mental process previously argued and maintained here as well. With respect to Applicants argued improvement to technology the Examiner notes 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.
As to Applicants arguments regarding Example 48, claim 3, of the July 2024 SME examples the Examiner notes that claim 3 was rendered eligible in view of the improvement as recited in the ordered combination of “the steps (b), (c), and (d) recite an abstract idea, the ordered combination of the steps of receiving a mixed speech signal, processing the speech signal to produce masked clusters, converting the masked clusters into separate signals in time domain, extracting spectral features from one such converted signal, and generating a sequence of words from the extracted spectral features to produce a transcript reflects the technical improvement discussed in the disclosure.” However, the claims as amended do not recite the specificity of how the mere training of a machine learning model would result in technical improvement. The example claim recites specific and ordered steps to reach its technical improvement whereas the claims of the instant application as recited merely takes data from a database, trains a model with that data, and then recites an ability to formulate a chemical prediction based on that training without specific recitation of how such a training would result in their purported output which would support their arguments of the complexity and functionality of the claim. Further the example claim results in the “speech-to-text conversion of a speech signal corresponding to one source of the mixed speech signal” whereas the current claims recite the mere display of information which does not represent significantly more than the abstract idea. As such the 101 rejection is MAINTAINED.
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 and 6 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 material feature value of a simulation result of the simulator for a material from a descriptor of the material, wherein the descriptor of the material includes a plurality of elements of the material and represents a feature corresponding to the elements of the plurality of elements, wherein the feature is at least one of a molecular weight of the element or an element mixing ratio for the element, 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 “a material feature value estimation model that receives, as input, an estimation result of the simulation estimation model, wherein the material feature value estimation model is configured to estimate a feature value of the material from an estimation result of the simulation estimation model and the descriptor of the material,” 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.
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 “a tested material database that indicates a chemical structural formula of a tested material associated with a measurement value of a material feature value of each tested material,” and
“an untested material database that indicates a chemical structural formula of an untested material” and
“a simulation result database that stores simulation results generated by a simulator, wherein the simulator includes a computer program 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” and “performing training of the simulation estimation model based at least on a simulation result of a tested material obtained from the simulation result database and the descriptor of the tested material,” and “performing training of the material feature value estimation model based at least on the descriptor of the tested material, a measurement value of the tested material stored in the tested material database, and the simulation result of the tested material obtained from the simulation result database,” and “inputting a descriptor of an untested material into the trained simulation estimation model to obtain a simulation estimation result,” and “inputting the simulation estimation result and the descriptor of the untested material into the trained material feature value estimation model to acquire a feature estimation value of the untested material” and “outputting, to a monitor, information related to the chemical structural formula of the untested material and the feature estimation value of the untested 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 “a tested material database that indicates a chemical structural formula of a tested material associated with a measurement value of a material feature value of each tested material,” and “an untested material database that indicates a chemical structural formula of an untested material” and ““a simulation result database that stores simulation results generated by a simulator, wherein the simulator includes a computer program 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” and “performing training of the simulation estimation model based at least on a simulation result of a tested material obtained from the simulation result database and the descriptor of the tested material,” and “performing training of the material feature value estimation model based at least on the descriptor of the tested material, a measurement value of the tested material stored in the tested material database, and the simulation result of the tested material obtained from the simulation result database,” and “inputting a descriptor of an untested material into the trained simulation estimation model to obtain a simulation estimation result,” and “inputting the simulation estimation result and the descriptor of the untested material into the trained material feature value estimation model to acquire a feature estimation value of the untested material” and “outputting, to a monitor, information related to the chemical structural formula of the untested material and the feature estimation value of the untested 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 “a tested material database that indicates a chemical structural formula of a tested material associated with a measurement value of a material feature value of each tested material,” and “an untested material database that indicates a chemical structural formula of an untested material” and “a simulation result database that stores simulation results generated by a simulator, wherein the simulator includes a computer program 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” and “performing training of the simulation estimation model based at least on a simulation result of a tested material obtained from the simulation result database and the descriptor of the tested material,” and “performing training of the material feature value estimation model based at least on the descriptor of the tested material, a measurement value of the tested material stored in the tested material database, and the simulation result of the tested material obtained from the simulation result database,” and “inputting a descriptor of an untested material into the trained simulation estimation model to obtain a simulation estimation result,” and “inputting the simulation estimation result and the descriptor of the untested material into the trained material feature value estimation model to acquire a feature estimation value of the untested material” and “outputting, to a monitor, information related to the chemical structural formula of the untested material and the feature estimation value of the untested 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 “a tested material database that indicates a chemical structural formula of a tested material associated with a measurement value of a material feature value of each tested material,” and “an untested material database that indicates a chemical structural formula of an untested material” and “a simulation result database that stores simulation results generated by a simulator, wherein the simulator includes a computer program 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” and “performing training of the simulation estimation model based at least on a simulation result of a tested material obtained from the simulation result database and the descriptor of the tested material,” and “performing training of the material feature value estimation model based at least on the descriptor of the tested material, a measurement value of the tested material stored in the tested material database, and the simulation result of the tested material obtained from the simulation result database,” and “inputting a descriptor of an untested material into the trained simulation estimation model to obtain a simulation estimation result,” and “inputting the simulation estimation result and the descriptor of the untested material into the trained material feature value estimation model to acquire a feature estimation value of the untested material” and “outputting, to a monitor, information related to the chemical structural formula of the untested material and the feature estimation value of the untested 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.”
v) Accordingly, claims 1 and 6 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 and 6 are allowable over the prior art of record.
The following is a statement of reasons for the indication of allowable subject matter:
Claim 1 recites:
A system comprising:
one or more processors; and one or more storage devices, wherein the one or more storage devices are configured to store:
a material feature estimation model that includes:
a simulation estimation model that is configured to estimate a material feature value of a simulation result of the simulator for a material from a descriptor of the material, wherein the descriptor of the material includes a plurality of elements of the material and represents a feature corresponding to the elements of the plurality of elements, wherein the feature is at least one of a molecular weight of the element or an element mixing ratio for the element, and
a material feature value estimation model that receives, as input, an estimation result of the simulation estimation model, wherein the material feature value estimation model is configured to estimate a feature value of the material from an estimation result of the simulation estimation model and the descriptor of the material,
a tested material database that indicates a chemical structural formula of a tested material associated with a measurement value of a material feature value of each tested material, and
an untested material database that indicates a chemical structural formula of an untested material,
a simulation result database that stores simulation results generated by a simulator, wherein the simulator includes a computer program 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 the one or more processors are configured to perform operations that include:
performing training of the simulation estimation model based at least on a simulation result of a tested material obtained from the simulation result database and the descriptor of the tested material,
performing training of the material feature value estimation model based at least on the descriptor of the tested material, a measurement value of the tested material stored in the tested material database, and the simulation result of the tested material obtained from the simulation result database,
inputting a descriptor of an untested material into the trained simulation estimation model to obtain a simulation estimation result,
inputting the simulation estimation result and the descriptor of the untested material into the trained material feature value estimation model to acquire a feature estimation value of the untested material, and
outputting, to a monitor, information related to the chemical structural formula of the untested material and the feature estimation value of the untested material.
Claim 6 recites:
A method that is executed by one or more processors configured by executable instructions, the method comprising:
providing a tested material database, that associates a chemical structural formula of a tested material with a measurement value of a feature value of the tested material,
providing an untested material database, that indicates a chemical structural formula of an untested material,
providing a simulation result database that stores simulation results generated by a simulator, wherein the simulator includes a computer program 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 the descriptor of the material includes a plurality of elements of the material and represents a feature corresponding to the elements of the plurality of elements, wherein the feature is at least one of a molecular weight of the element or an element mixing ratio for the element,
performing, by the one or more processors, training of a simulation estimation model based at least on simulation result of a tested material obtained from the simulation result database and a descriptor of the tested material, wherein the simulation estimation model is utilized with a material feature value estimation model for performing material feature estimation, wherein the simulation estimation model is configured to estimate a material feature value of a simulation result of the simulator from a descriptor of the material,
performing, by the one or more processors, training of the material feature value estimation model based at least on the descriptor of the tested material, a measurement value of the tested material stored in the tested material database, and the simulation result of the tested material obtained from the simulation result database, wherein the material feature value estimation model is configured to estimate a feature value of a material based on receiving, as input, an estimation result of the simulation estimation model and the descriptor of the material,
inputting, by the one or more processors, a descriptor of an untested material into the trained simulation estimation model to obtain a simulation estimation result,
inputting, by the one or more processors, the first simulation estimation result and the descriptor of the untested material into the material feature value estimation model to acquire a feature estimation value of the untested material, and
outputting, by the one or more processors, to a monitor, information related to a chemical structural formula of the untested material and the feature estimation value of the untested 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. All Claims are rejected.
8. 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.
9. 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
