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 .
Claim Objections
Claims 1-8 are objected to because of the following informalities:
Claim 1 recites “AIMD” which should not be abbreviated.
Claims 2-8 depend from objected claim 1 and therefore are also objected.
Further, claims 5-8 recites at line 1, “any one of ” should be deleted.
Appropriate correction is required.
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 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claim 1 recites “an apparatus for providing…comprising: a classification unit for generating…stable state” which is a machine.
Step 2, Prong 1: Judicial exception? Yes.
Claim 1 recites “a classification unit for generating a classification information by classifying…by comparing an output value…with a preset threshold value”, “a first verification unit for selecting information…using Ewald summation from generated classification information…a second verification unit…stable state” which may be carried out as a mental process if the algorithm is simple enough, and as a mathematical process if the algorithm is more complicated. Therefore, the claimed invention recites an abstract idea. Claim 1 recites mental processes that may be carried out in the human mind or with the aid of pencil and paper in simple situations, or by hardware processors, for more complicated situations.
The claimed invention thus recited as an abstract idea. Claim 1 recites mathematical concepts and/or mental processes, that may be carried out in human mind or with the aid of pencil and paper in simple situations. The claim does not recite a particular equation or algorithm for making the recited combining and performing steps, this just means that the abstract idea is being recited broadly enough to monopolize all possible equations or algorithms that might be used (Please also see MPEP 2106.04(a)(2)(III)(A), (B), (C), and (D).
Step 2A, Prong 2: Practical application? No.
The limitation “a second verification unit for selecting and providing final information on a structure having high ionic conductivity using AMID simulation from the information from the information on the structure in the electrochemically stable state” providing nothing more than mere information and data gathering and nothing more than instructions to select and provide information on a structure having high ionic conductivity using AMID simulation….See MPEP 2106.05(f) which provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instruction to implement an abstract idea: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception.
Limitations “classification unit…a first verification…and second verification unit…” do not show in details how to accomplish the classification information generation, the selection of information, and selection and providing of final information. steps are not performed by any particular machine. They are all mere instructions. The limitations are merely data gathering.
The classification unit, first verification unit, and second verification unit are not particular machines as recited in the claim and in light of Specification.
The “(selected and provided) information on a structure having high ionic conductivity using AIMD simulation from the information on the structure in the electrochemically stable state” is data and insignificant extra solution.
Claim 1 when viewed as a whole or in ordered combination does not provide meaningful limitations beyond generally linking the use of the judicial exception to a particular environment to transform the judicial exception into patent-eligible subject matter (see MPEP 2106.05(e)).
Per MPEP 2106.04(d)(1) and 2106.05(a), the claim as a whole does not provide an improvement to other technology or technical field. The claim limitations as recited when viewed as a whole do not include the components or steps of the invention that provide the improvement described in the specification.
The recited limitations “units” are not particular machined. The recited “structure” and “conductive material” are field of use.
Step 2B: the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, for reasons that are analogous to the discussion of additional elements at Prong 2.
Dependent claim 2 adds a limitation “an extraction unit for receiving test data and extracting material characteristic information…” is data and merely data gathering which are data and data gathering merely extending the abstract idea without adding any additional elements. The extraction unit is not particular machine.
Dependent claim adds a limitation “a learning unit for training…model wherein the learning unit receives learning data and uses it to improve precision in selecting….by training the sodium superion conductor material search model in a supervised manner” which are data and data gathering merely extending the abstract idea without adding any additional elements. The learning unit is not a particular machine.
Dependent claim 4 adds a limitation “an optimization unit for optimizing the preset threshold value of the classification unit, wherein the optimizing unit optimizes the preset threshold value by adjusting accuracy …” which are data and data gathering merely extending the abstract idea without adding any additional elements.
Dependent claims 5-8 add “wherein sodium superion conductor material displayed ….” which are data and data gathering merely extending the abstract idea without adding any additional elements. The claim does not positively recite the act of displaying. If the claim positively recited “displaying the material…”, the claim would not be eligible because the term is recited so generically (no details whatsoever are provided other than displaying the data) that it represents no more than mere instructions to apply the judicial exception. This limitation can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis.
Limitation “wherein sodium superion conductor material displayed…” represents extra solution activity because it is a mere nomial or tangential addition to the claim. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014). This limitation represents extra-solution activity because it is a mere nominal or tangential addition to the claim. See MPEP 2106.05(g), discussing limitations that the Federal Circuit has considered to be insignificant extra-solution activity, for instance the step of printing a menu that was generated through an abstract process in Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1241-42 (Fed. Cir. 2016) and the mere generic presentation of collected and analyzed data in Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354 (Fed. Cir. 2016).
The term “displayed” is not specifically defined in the Specification. In the absence of a specific definition of “displayed/displaying" the Examiner must interpret the words in accordance with their usual definition.
Conclusion
Claims 1-8 are patentably distinguishable over the prior art of record.
Ouyang et al. (Synthetic accessibility and stability rules of NASICONs, Nature Communications, https://doi.org/10.1038/s41467-021-26006-3 (submitted by Applicants) (hereinafter “Ouyang”).
Regarding claim 1, Ouyang discloses an apparatus for providing sodium superion conductor material information using a machine learning method comprising:
a classification unit for generating classification information (generate features set with 1895020 candidate features) by classifying sodium superion conductor material information by comparing an output value obtained by inputting material characteristic information into a sodium superion conductor material search model with a preset threshold value (Page 7, At machine-learned tolerance factor for NASICONs: model is limited to 2D with 24 basic physical properties. Iteratively apply 17 mathematical operators to generate features set with candidate features. MLR is performed to identify the best combination of two features for raking the relative stability);
a first verification unit for selecting information on a structure in an electrochemically stable state using Ewald summation (Page 7, Fig. 5 description: Ewald summation) from the generated classification information (Page 7, col. 2, last 3 lines-Page 8, col. 1: The optimal 2D descriptor was chosen as the one that nest validates the accuracy of the pairwise ranking matrix. The distribution of the computed/learned 2D descriptor space is plotted at Fig. 5 with Ewald summation).
However, does not explicitly disclose “a second verification unit for selecting and providing final information on a structure having high ionic conductivity using AIMD simulation from the information on the structure in the electrochemically stable state”.
Wang et al. (USPAP. 20220131180) (submitted by Applicants) discloses rechargeable lithium ion batteries comprising at least one lithium salt-graphite composite electrode. In particular, the disclosure provides a rechargeable “water-in-bisalt” lithium ion battery with a high potential where at least a portion of the lithium salt is phase separated from the aqueous electrolyte, and where the anionic-redox reaction occurs within the graphitic lattice. Ewald summation method is used in MD simulations for handling the electrostatic interactions between permanent changes with permanent charges and permanent charges with induced dipole moments with k=6.sup.3 vectors (Abstract; Par. 95).
Wang does not disclose “a second verification unit for selecting and providing final information on a structure having high ionic conductivity using AIMD simulation from the information on the structure in the electrochemically stable state”.
Therefore, regarding claim 1, the closest prior art of record either alone or in combination fails to anticipate or render obvious the combination wherein “a second verification unit for selecting and providing final information on a structure having high ionic conductivity using AIMD simulation from the information on the structure in the electrochemically stable state” in combination with other limitations in the claims as defined by Applicants.
Claims 2-8 depend from claim 1 and therefore are patentably distinguishable from the prior art of record.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
USPAP. 20250218554 discloses a system and method are provided for a machine-learning drive framework for predicting ionic conductivity of solid-state electrolytes. In use, the method and/or system may include receiving, at a machine learning system, two or more molecular structures from at least one structural dataset, where the two or more molecular structures relate to ionic mobility. Additionally, atomic weights are calculated for the two or more molecular structures, and the machine learning system is trained based on the two or more molecular structures, where the training relies on at least one intrinsic atomic feature and the calculated atomic weights for the two or more molecular structures. Further, a bias-correction is applied for the two or more molecular structures to improve the training of the machine learning system. Further, one or more molecular dynamics (MD) simulations are outputted, using the machine learning system, for the two or more molecular structures. The molecular structures that are received from the at least one dataset may include initial data obtained using ab-initio (AIMD) simulation via the DFT process. For purposes of the present description, AIMD may be thought of as having two aspects: one may be the number of atoms being simulated and the other may be the time period during which the simulation is taking place. As such, an AIMD simulation may address the manner in which atoms interact with one another over an amount of time adequate to perform the necessary calculations. Further, AIMD simulation may be used to accurately predict a material's electronic structure, energetics, and various properties, which in turn may allow greater understanding regarding the intricacies of atomic and molecular interactions. (Abstract; Pars. 60-69).
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/PHUONG HUYNH/ Primary Examiner, Art Unit 2857 February 14, 2026