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 .
Claims Status
Claim(s) 1-7 are currently pending and under examination herein.
Claim(s) 1-7 are rejected.
Priority
The instant application is a National Stage of International Application No. PCT/JP2022/018415 filed 21 Apr 2022 and claims foreign priority to Japan Patent Application No. JP2021-073162, filed 23 Apr 2021. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. As such, the effective filing date of claims 1-7 is 23 Apr 2021.
For any intervening prior art before the international filing date but after foreign priority date, applicant cannot rely upon the certified copy of the foreign priority application to overcome a 35 U.S.C. §102 or §103 rejection because a translation of said application has not been made of record in accordance with 37 CFR 1.55. When an English language translation of a non-English language foreign application is required, the translation must be that of the certified copy (of the foreign application as filed) submitted together with a statement that the translation of the certified copy is accurate. See MPEP §§ 215 and 216. Applicant may provide an accurate English translation of the certified copy of the foreign application to perfect priority.
Information Disclosure Statement
The Information Disclosure Statements filed on 10 Jan 2024, 14 Mar 2025, 27 Feb 2025 and 29 Jan 2026 are compliant with the provisions of 37 CFR 1.97 and have been considered. A signed copy of list of references cited from the/each IDS is included with this Office Action.
Claim Interpretation
For examination purposes, “reflect” will be interpreted to mean “provide.”
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Where applicant acts as his or her own lexicographer to specifically define a term of a claim contrary to its ordinary meaning, the written description must clearly redefine the claim term and set forth the uncommon definition so as to put one reasonably skilled in the art on notice that the applicant intended to so redefine that claim term. Process Control Corp. v. HydReclaim Corp., 190 F.3d 1350, 1357, 52 USPQ2d 1029, 1033 (Fed. Cir. 1999). The term “reflect” in claims 1, 2, 5, 6, and 7 is used by the claim to mean “provide,” while the accepted meaning is “to block and redirect” or “to mirror.” The term is indefinite because the specification does not clearly redefine the term.
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 1-7 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea/law of nature/natural phenomenon without significantly more.
Step 2A, Prong 1 Considerations
In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1 : YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea/law of nature/natural phenomenon:
Claims 1, 6 and 7 recite receiving partial structure data, reflect blending ratio data and input input data.
Claim 2 recites receiving partial structure data.
Claim 4 recites multiplying, adding, or concatenating values and compiling those values
Therefore, these limitations fall under the “Mental process” and “Mathematical concepts” groupings of abstract ideas. While claims 1-7 recite performing some aspects of the analysis “by at least on processor,” “executed by a computer,” or by “ non-transitory computer-readable storage media,” there are no additional limitations that indicate that this analysis engine requires anything other than carrying out the recited mental process or mathematical concept in a generic computer environment. Merely reciting that a mental process is being performed in a generic computer environment does not preclude the steps from being performed practically in the human mind or with pen and paper as claimed. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then if falls within the “Mental processes” grouping of abstract ideas. As such, claims 1-7 recite an abstract idea/law of nature/natural phenomenon (Step 2A, Prong 1 : YES).
Step 2A, Prong 2 Considerations
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology or applies or uses the recited judicial exception to affect a particular condition. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment or mere instructions to apply the recited judicial exception via a computer medium and/or use of a hardware processor. Specifically, the claims recite the following additional elements:
Claims 1, 6 and 7 recite generating partial structure input data.
There are no limitations that indicate that the claimed system, method or storage medium require anything other than generic computing systems. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. The steps for predicting properties of a material based on structural data by computational means are well-understood, routine and conventional functions such as performing repetitive calculations and mere data extracting (see MPEP 2106.05(d)(2)). As such, claims 1-7 are directed to an abstract idea/law of nature/natural phenomenon (Step 2A, Prong 2 : NO).
Step 2B (MPEP 2106.05.A i-vi)
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to mere instructions to apply the recited exception in a generic way or in a generic computing environment.
As discussed above, there are no additional limitations to indicate that the claimed system and method requires anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. The limitation for use of a computer-implemented system, one or more hardware processes, or use of a non-transitory computer-readable storage system amount to mere instructions to apply the judicial exception in a generic way because the executable steps are so generically recited. MPEP 2106.05(d) discloses that a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry are not enough to qualify as “significantly more” when recited in a claim with a judicial exception. The additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B : No). As such, claims 1-7 are not patent eligible.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-7 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-7 of U.S. Patent No. 12682986. Although the claims at issue are not identical, they are not patentably distinct from each other because of the following:
Instant application claim
Reference patent instant application maps to:
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Claims 1, 6 and 7 of the instant application recites a property prediction system predicting properties of a material based on a plurality of raw materials having a known partial structure, the system comprising at least one processor, wherein the at least one processor is configured to: receive at least input of partial structure data for specifying the known partial structure of each of the plurality of raw materials and blending ratio data indicating a ratio of blending of each of the plurality of raw materials; generate partial structure input data indicating the known partial structure, on the basis of the partial structure data for each of the plurality of raw materials; reflect blending ratio data relevant to the plurality of raw materials on partial structure input data of the plurality of raw materials; and input input data based on partial structure input data for each of the plurality of raw materials on which the blending ratio data is reflected to a machine learning model. Claims 1, 6 and 7 of the reference patent discloses the same elements of claims 1, 6 and 7, respectively, with the added elements of converting the partial structure data to a vector using molecular description and multiplying each of the elements of the vector by the blending ratio data and adding or averaging elements of each vector, followed by causing the machine learning model to output property prediction results. However, the same mathematical manipulations (conversion to a vector, multiplies, adds) are recited in claim 4 of the instant application.
Claim 2 of the instant application recites the property prediction system according to claim 1, wherein the at least one processor is configured to: receive partial structure data for specifying the known partial structure in a molecule configuring each of the plurality of raw materials and the number of known partial structures in the molecule; and reflect a value obtained by multiplying blending ratio data relevant to the plurality of raw materials and the number of known partial structures together on the partial structure input data of the plurality of raw materials. Claim 2 of the reference patent discloses specifying a value of the partial structure in the structure of the raw material data.
Claim 3 of the instant application recites the property prediction system according to claim 1, wherein the partial structure input data is molecular structure information indicating a structure of the known partial structure. Claim 3 of the reference patent discloses identical claim language.
Claim 4 of the instant application recites the property prediction system according to claim 1, wherein any one of wherein the at least one processor multiplies, adds, or concatenates a value based on blending ratio data for each of the plurality of raw materials with respect to a plurality of vectors based on the partial structure input data for each of the plurality of raw materials, and compiles the plurality of multiplied, added, or concatenated vectors on one vector to input the one vector to the machine learning model. Claim 1 of the reference patent discloses the same mathematical manipulations as described above.
Claim 5 of the instant application recites the property prediction system according to claim 1, wherein the at least one processor further reflects a value indicating a difference in the raw materials on data, which is partial structure input data for each of the plurality of raw materials, and compiles the data on one data piece to input the one data piece to the machine learning model. Claim 4 of the reference patent discloses nearly identical claim language.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-7 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Pruksawan (Pruksawan et al. 2019 Science and Technology of Advanced Materials 20(1) pgs. 1010-1021).
Claims 1, 6 and 7 1st elements recite a property prediction system predicting properties of a material based on a plurality of raw materials having a known partial structure, the system comprising at least one processor, wherein the at least one processor is configured to receive at least input of partial structure data for specifying the known partial structure of each of the plurality of raw materials and blending ratio data indicating a ratio of blending of each of the plurality of raw materials. Pruksawan teaches prediction and optimization of epoxy adhesive strength from experimental data which includes partial structure data and stoichiometric ratios for blending raw materials (see §Abstract).
Claims 1, 6 and 7 2nd elements recite generating partial structure input data indicating the known partial structure, on the basis of the partial structure data for each of the plurality of raw materials. Pruksawan teaches generating partial structure input data on the basis of partial structure data for the mixtures (see §Introduction pg. 1011 col. 2 2nd ¶).
Claims 1, 6 and 7 3rd elements recite reflecting blending ratio data relevant to the plurality of raw materials on partial structure input data of the plurality of raw materials. Pruksawan teaches stoichiometric ratios changing based on experimental input data (see §3.2.3 Bayesian optimization).
Claims 1,6 and 7 4th elements recite inputting input data based on partial structure input data for each of the plurality of raw materials on which the blending ratio data is reflected to a machine learning model. Pruksawan teaches stoichiometric ratios changing based on experimental input data and updating those values (see §3.2.3 Bayesian optimization).
Claim 2 1st element recites the property prediction system according to claim 1 wherein the at least one processor is configured to: receive partial structure data for specifying the known partial structure in a molecule configuring each of the plurality of raw materials and the number of known partial structures in the molecule. Pruksawan teaches partial structure data for specifying known partial structure in a molecule configuration (see Fig. 1 and §2.4 ML Method 1st ¶ on data pre-processing).
Claim 2 2nd element recites reflecting a value obtained by multiplying blending ratio data relevant to the plurality of raw materials and the number of known partial structures together on the partial structure input data of the plurality of raw materials. Pruksawan teaches a predicted adhesive joint strength values that is reflective of stoichiometric (blending ratio) data (see §Fig. 6).
Claim 3 recites the property prediction system according to claim 1,wherein the partial structure input data is molecular structure information indicating a structure of the known partial structure. Pruksawan teaches molecular structure information as input data (see Table 1 and §2.3. Selection of experimental conditions for the initial data set).
Claim 4 recites the property prediction system according to claim 1 wherein the at least one processor multiplies, adds, or concatenates a value based on blending ratio data for each of the plurality of raw materials with respect to a plurality of vectors based on the partial structure input data for each of the plurality of raw materials, and compiles the plurality of multiplied, added, or concatenated vectors on one vector to input the one vector to the machine learning model. Pruksawan teaches data pre-processing in this manner (see §’s 2.4 ML Method and 2.4.1. Data pre-processing and splitting).
Claim 5 recites the property prediction system according to claim 1 wherein the at least one processor further reflects a value indicating a difference in the raw materials on data, which is partial structure input data for each of the plurality of raw materials, and compiles the data on one data piece to input the one data piece to the machine learning model. Pruksawan teaches providing an adhesive joint strength value as an indication of the result from the machine learning algorithm and inputting that value back into the machine learning model until an adhesive with the desired properties is achieved (see Fig. 3).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Pilana et al. 2013 Scientific Reports 3(2810) pgs. 1-6.
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/M.S.C./Examiner, Art Unit 1687
/Karlheinz R. Skowronek/Supervisory Patent Examiner, Art Unit 1687
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