Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on May 14, 2026 has been entered.
Response to Arguments
Applicant's arguments filed on May 14, 2026 have been fully considered but they are not persuasive.
Argument 1: Polypropylene is fundamentally different from water-absorbent resin, so CN ’524 cannot be applied
The applicant argues polypropylene is hydrophobic and nonpolar, whereas water-absorbent resins are hydrophilic and contain polar groups, so the NIR spectra and predictive behavior are fundamentally different.
Response :
This argument is not persuasive enough, on its own, to defeat obviousness.
The examiner agrees that polypropylene and water-absorbent resins differ chemically. But obviousness does not require the prior art to involve the same exact polymer. It requires whether a person of ordinary skill in the art would have been motivated to apply the known NIR/chemometric prediction framework to a related resin system with a reasonable expectation of success.
CN ’524 expressly teaches that: NIR diffuse reflectance spectra contain information about polymer structure and properties; chemometrics can be used to establish predictive calibration models; multivariate methods such as PLS and ANN are suitable.
That teaching is broad enough that a skilled artisan could reasonably expect the same general workflow to be applicable to other polymer powders, including water-absorbent resins, subject to routine model development.
The applicant’s argument is mainly about different chemistry, but the claims are not limited to a special spectral phenomenon that requires PP-only behavior. The claims broadly recite: obtaining NIR measurement data, using processed data, predicting a physical property.
That is exactly the type of routine extension that KSR-style reasoning often treats as obvious if the underlying predictive method is already known.
Best citation support from CN ’524: Background: NIR has “played an active role” in industrial control and polymer analysis. Summary: the invention is based on the fact that PP spectra contain structural information. Detailed description: multivariate methods and ANN are used to predict unknown sample properties.
Argument 2: The predicted properties in the present application are dynamic properties, not intrinsic properties
The applicant argues that CN ’524 predicts isotactic index of polypropylene, an intrinsic property, whereas the present claims predict CRC, AAP, SFC, etc., which are dynamic properties of absorbent resin after water uptake or pressurization.
Response
The claims do not require measuring those properties directly. They require using NIR measurement data to predict them. Predicting a physical property from a measured spectrum is exactly what CN ’524 does.
Even if the properties are operational or performance-related rather than purely compositional, the question is whether the use of spectral data and chemometrics to predict them would have been obvious. The applicant has not shown that such prediction is technically impossible or unexpectedly unreliable.
In addition, the Office Action can reasonably rely on the idea that once a spectral-property correlation framework is known, the choice of which property to predict is often a design choice or an ordinary application of the same framework.
Best citation support from CN ’524” “Chemometrics is a method of designing or selecting the best chemical measurement method by means of mathematics, statistics and computer science.”; “The near-infrared diffuse reflectance spectrum of the unknown sample is preprocessed… and the isotactic index is determined by the calibration model.”; ANN and PLS are described as suitable predictive tools.
Argument 3: Technical bias—NIR is only suitable for intrinsic properties, not post-absorption performance
The applicant argues that skilled artisans would not expect NIR to predict dynamic water-absorption performance and that doing so overcomes technical bias.
Response
This argument is not well supported by the record as presented.
CN ’524 itself teaches the broader principle that NIR spectral features correlate with polymer structure and that multivariate calibration can extract property information. The applicant’s claim of “technical bias” would need strong evidence that the art taught away from using NIR for performance prediction in absorbent polymers. The applicant offers mostly general reasoning and references to spectral broadening in polar materials.
That does not establish a bias against prediction. At most, it suggests that different polymers may require different preprocessing or calibration. But differences in preprocessing/model tuning are routine in chemometrics.
If the applicant had shown that absorbent resin spectra are so distorted by water that a skilled artisan would not reasonably expect successful prediction using standard NIR chemometrics, that could be more compelling. But the current argument is largely speculative.
Argument 4: CN ’524 assumes linear scattering and therefore does not fit water-absorbent resin powders or gel intermediates
The applicant argues that CN ’524’s PMSC assumes linear relationships and that water-absorbent materials exhibit nonlinear scattering due to changing morphology, surface state, and water interference.
Response
This argument is not enough to remove obviousness for at least two reasons:
The claims are not limited to PMSC. The claims recite use of near-infrared measurement data and processed data. The model can be generated by machine learning. The preprocessing can include differential processing. The claims do not require the specific PMSC assumptions of CN ’524.
CN ’524 also teaches alternative preprocessing/modeling. It expressly discloses second-order differential for powder samples. It also discloses PLS, LWR, ANN, and MLR. Those methods are not limited to a single scattering assumption in the way the applicant suggests.
So even if PMSC were imperfect for the applicant’s intended material, the reference still teaches enough to support the general idea of NIR/chemometric prediction, and modifying preprocessing/model choice to fit a different powder is routine.
Citation support from CN ’524: Powder sample preprocessing by second-order differential; Multivariate methods including PLS, LWR, and ANN; “The selection of the moving window size has a great influence” — indicating parameter tuning is part of the ordinary method, not a departure from it.
Argument 5: Water in the absorbent resin causes strong NIR interference not disclosed by CN ’524
The applicant argues that water causes significant interference in absorbent resin systems and CN ’524 does not resolve this.
Response
This is a possible technical difference, but it does not automatically make the claims non-obvious.
A prior art reference does not have to disclose every implementation detail or every possible source of interference. If the prior art teaches the general workflow and the claimed invention merely applies it to a different material system, the burden is on the applicant to show that the adaptation would have been non-routine or yielded unexpected results beyond ordinary model development.
Also, the claims as written do not recite a specific anti-water-interference preprocessing step. So this argument is not commensurate in scope with the claims.
Argument 6: Unexpected effect—rapid, low-cost, accurate prediction prevents out-of-spec products
The applicant argues that the claimed method gives unexpected advantages.
Response
The cited advantages are not clearly unexpected in light of CN ’524. CN ’524 already emphasizes: simple operation, high speed, accuracy, environmental friendliness, suitability for factory control.
So the idea that NIR prediction can be rapid and useful for process control is already present in the reference. That makes the applicant’s asserted advantages look like expected benefits of applying the same methodology to a different polymer system, not a surprising new result.
If the applicant had provided comparative evidence showing a dramatic, unexpected improvement over prior methods specifically for water-absorbent resin, that would be more persuasive. From the current record, that does not appear to have been shown.
Finally, Applicant argues that the submitted documentary evidence shows polypropylene (PP) is fundamentally different from the water-absorbent resin recited in claim 1, and that the method of CN ’524 cannot be readily applied to PP. Applicant further cites a 2022 annual report and a 2019 Frontiers in Chemistry article regarding hydrogen bonding, band broadening, and baseline shifts in IR/NIR spectra. This argument is not persuasive.
The submitted evidence does not show that CN ’524 would fail or produce unpredictable results when applied to water-absorbent resin. The Office Action properly noted that applicant had not submitted evidence showing that applying the CN ’524 approach to water-absorbent resins would fail or give unpredictable results, nor evidence of a structural or spectral reason why water-absorbent resins are outside the routine scope of NIR/chemometrics. The newly cited materials do not overcome that deficiency.
At most, the submitted references show that spectra differ depending on chemical structure, and that polar functional groups and hydrogen bonding can affect peak shape, width, and baseline. However, this does not establish that NIR/chemometric prediction would be unavailable or non-routine for water-absorbent resin powders. Differences in spectral features generally indicate that a skilled artisan may need to adjust preprocessing, calibration, or model parameters — which is consistent with ordinary chemometric practice — not that the technique becomes inapplicable.
The cited evidence discusses general spectral behavior, not a technical bar to applying NIR prediction to polymer powders. The Hiroshima City Industrial Technology Center Annual Report and the Frontiers in Chemistry article appear to explain that polar materials may exhibit broader peaks, shifted bands, overlapping absorption, or baseline changes due to hydrogen bonding and intermolecular interactions. See, e.g., Front. Chem. 2019, Vol. 7, Article 48, section “Investigations of Intermolecular Interactions.”
That evidence may support the general proposition that material composition affects spectral appearance. It does not show that a skilled artisan would have been discouraged from applying NIR spectroscopy and chemometric modeling to water-absorbent resin powders or their intermediates. In fact, the cited material tends to confirm the opposite: that NIR spectra remain informative and that spectral characteristics can be modeled despite chemical differences.
50. The applicant’s evidence is not commensurate in scope with the rejection
The rejection does not require that water-absorbent resin have the same spectrum or chemistry as polypropylene. Rather, the rejection is based on the principle that CN ’524 teaches a known NIR/chemometric prediction workflow for polymer powders, and that applying that workflow to other resin powders or properties would have been obvious absent a showing of unpredictability. The applicant’s evidence addresses that polypropylene and water-absorbent resins are chemically different. But chemical difference alone does not rebut obviousness unless accompanied by evidence that the claimed adaptation would have been technically problematic, unpredictable, or outside the ordinary skill in the art. No such showing has been made.
The cited materials do not undermine CN ’524’s teaching of NIR-based prediction
CN ’524 teaches that: NIR diffuse reflectance spectra can be obtained from resin powder samples, the spectra can be preprocessed, and multivariate methods such as PLS, LWR, and ANN can be used to predict resin properties. That teaching is not negated by the fact that polar or hydrogen-bonding materials may have different spectral features. Such differences are precisely the types of variations chemometric modeling is designed to accommodate. The cited materials therefore do not establish that the claimed subject matter would have been nonobvious.
Accordingly, applicant’s newly cited evidence is not sufficient to overcome the rejection. The evidence shows only that polymer chemistry affects NIR spectra, which is expected and routine in the field. It does not demonstrate that applying CN ’524’s NIR/chemometric approach to water-absorbent resin powders would fail, would be unpredictable, or would lie outside the ordinary skill of the art.
Therefore, the rejection of claims 1–6, 8, and 11–12 under 35 U.S.C. § 103 over CN ’524 remains properly maintained.
Further, Applicant's arguments regarding “claim Interpretation” have been fully considered but they are not persuasive.
Applicant argues that the claims should not be interpretated as means-plus function claims since the pending claims do not use the word “means”.
In response it is respectfully pointed out o applicant that according to MPEP 2181(I), a claim should be interpretated according to 112(f) if it meets the following 3 prong analysis:
A. The claim limitation uses the phrase “means” or a term used as a substitute for “means” that is generic placeholder. In this case, claim 8 clearly recites generic placeholder, “measurement data obtaining section” and “predicting section” and thus meets prong A.
B. The phrase “means” or the substitute term is modified by functional language, typically linked by the transition word “for”(e.g., “means for”) or another linking word. In claim 8, the substitute term “measurement data section” is modified by functional language “which obtains ………” and “predicting section” is modified by functional language which inputs…….and outputs ……” meeting prong B.
C. The phrase “means” or the substitute term is not modified by sufficient structure or material for performing the claimed function. In claim 8 there are no such structure recited for the measurement data section and the predicting section to perform the recited functions and thus prong C is met.
Accordingly, the interpretation is proper and maintained since it meets the 3 prong analysis. It should be also be noted that 112(f) is not a rejection but rather an interpretation.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “measurement data section” and “predicting section” in claim 8.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-6, 8, 11 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over CN1472524A (cited in the IDS) (hereinafter 524”).
As to claims 1 and 8, 524’ discloses a method and an apparatus for predicting a physical property of a resin powder, (method for determining an isotactic index (i.e., a physical property) polypropylene resin; characterized in that a representative polypropylene resin pellet sample or a powder sample is composed of a calibration (claim 1)) the resin powder being any one of a water absorbent resin powder and an intermediate product which is produced in a process for producing the water absorbent resin powder, said method comprising:
a near-infrared measurement data obtaining step of obtaining near-infrared measurement data which indicates a near-infrared absorption spectrum of the resin powder (preprocessing the near-infrared diffuse reflectance spectrum of the powder sample by second-order differential, and then performing regression analysis with corresponding isotactic index basic data by mathematical methods to establish a calibration model (paragraph 4 on page 2)); and
a predicting step of inputting, into a prediction model, at least one selected from the group consisting of the near-infrared measurement data and one or more pieces of processed data which have been generated on the basis of the near-infrared measurement data, and outputting prediction information concerning the physical property of the resin powder. (the regression analysis adopts a multivariate correction method, which can be a BP artificial neural network (see paragraph 3 on page 4); the near-infrared diffuse reflectance spectra of unknown samples are preprocessed, and the principal component scores calculated by partial least squares method are input into the established artificial neural network model to predict the properties of the unknown samples (see paragraph 5 on page 5).
524’ doesn’t explicitly disclose the resin powder being any one of a water absorbent resin powder and an intermediate product which is produced in a process for producing the water absorbent resin powder and another type of data input into the prediction model is one or more pieces of processed data which have been generated on the basis of the near-infrared measurement data.
However, disclosing the prediction of the physical properties of polypropylene resin powder samples, applying this method to either absorbent resin powder or an intermediate product which is produced in a process for producing the water absorbent resin powder are known and actively used in the field. This involves using various techniques, including machine learning and Raman spectroscopy, to model and control the properties of the resin during production.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use resin powder being one of a water absorbent resin powder and an intermediate product which is produced in a process for producing the water absorbent resin powder since it is a routine application in the art and will yield predictable results. The rational being by predicting properties and controlling them during production, manufacturers can optimize the process for higher water absorption rates, improved damage resistance, and other desirable characteristics.
Still lacking the limitation such as, another type of data input into the prediction model is one or more pieces of processed data which have been generated on the basis of the near-infrared measurement data.
However, 524’ does disclose that chemometrics is a method of designing or selecting the best chemical measurement method by means of mathematics, statistics and computer science. Further, predicting physical properties using one or more processed data generated from near-infrared measurement data is known as chemometrics.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of 524’ by using one or more pieces of processed data which have been generated on the basis of the near-infrared measurement data as input data to predict the physical property since it is common and known in the art and will achieve predictable results such as ease of operation and efficiency.
As to claim 2, 524’ further discloses forming a calibration set with representative polypropylene resin granular samples (equivalent to resin powder): preprocessing the near-infrared diffuse reflectance spectrum of the powder sample (equivalent to a near-infrared measurement data obtaining step of obtaining near-infrared measurement data which indicates a near-infrared absorption spectrum of the resin powder) by second-order differential, and then performing regression analysis with corresponding isotactic index basic data by mathematical methods to establish a calibration model (equivalent to data of a prediction model is (1) a combination of near-infrared measurement data and physical property information, the near-infrared measurement data containing near-infrared absorption spectra of a plurality of produced resin powders which have been previously produced and have each known physical property, the physical property information being on end products each of which is associated with the near-infrared measurement data) (see paragraph 4 on page 2); the regression analysis adopts a multivariate
correction method, which can be a BP artificial neural network (see paragraph 3 on page 4).
Further, it is a common approach in the art to use another set of near-infrared measurement data and the information corresponding to the intermediate product as the data combination for machine learning.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use another set of near-infrared measurement data and the information corresponding to the intermediate product as the data combination for machine learning for advantages such as, enhanced predictive accuracy, improved process understanding and optimization.
As to claims 3-5, 524’ discloses (see paragraph 3 on page 4) that the regression analysis employs a multivariate calibration method, which can be multiple linear regression (MLR), partial least squares 15 (PLS), robust partial least squares (RPLS), locally weighted regression (LWR), or BP artificial neural network (ANN), with partial least squares (PLS), locally weighted regression (LWR), or BP artificial neural network (ANN) being preferred, and BP artificial neural network (ANN) being more preferred.
As to claim 6, wherein the prediction information includes at least any one of (1) a mass average particle diameter (gel D50) of a hydrogel which is the intermediate product, (2) an absorption capacity without load (CRC) of the resin powder, (3) an absorption capacity under load (AAP) of the resin powder, (4) a saline flow conductivity (SFC) of the resin powder, (5) a mass average particle diameter (D50) of the resin powder, and (6) an amount of a solid component contained in the resin powder or a solid fraction of the resin powder would have been obvious to one of ordinary skill in the art at the time the claimed invention was made. Selecting to find a specific information would amount to a recitation of the intended use of the patented invention, without resulting in any structural difference between the claimed invention and the structure disclosed by 524’, and therefore fails to patentably distinguish the claimed invention from the prior art. See In re Casey, 152 USPQ 235 (CCPA 1967) and In re Otto, 136 USPQ 458, 459 (CCPA 1963).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to obtain prediction information that includes at least one of (1) a mass average particle diameter (gel D50) of a hydrogel which is the intermediate product, (2) an absorption capacity without load (CRC) of the resin powder, (3) an absorption capacity under load (AAP) of the resin powder, (4) a saline flow conductivity (SFC) of the resin powder, (5) a mass average particle diameter (D50) of the resin powder, and (6) an amount of a solid component contained in the resin powder or a solid fraction of the resin powder to obtain the desired information.
As to claim 11, regarding the technical solution “a step of calculating the near-infrared absorption spectrum of the resin powder from a measurement value obtained by measuring light reflected by the resin powder”, 524’ discloses a method for determining the isotactic index of polypropylene resin (equivalent to a measuring method) and specifically discloses the following content (see paragraphs 4-5 on page 2 of the description): forming a calibration set with representative polypropylene resin granular samples (equivalent to resin powder), the near-infrared diffuse reflectance spectrum of the polypropylene resin sample is used as the determination parameter (equivalent to irradiating the resin powder with near-infrared radiation), use the integrating sphere diffuse reflectance spectrum sampling accessory to measure the near-infrared diffuse reflectance spectrum while the sample cup is rotating (equivalent to calculating the near-infrared absorption spectrum of the resin powder from a measurement value obtained by measuring light reflected by the resin powder), the average spectral data of multiple parallel measurements should be taken as the sample data.
Further, measuring a near-infrared absorption spectrum of a resin powder, the near-infrared absorption spectrum being used in the method, the resin powder being either an absorbent resin powder or an intermediate product generated in the producing process of the absorbent resin powder is common and known in the art in predicting the physical properties of the absorbent resin powder.
Moreover, considering the teachings of 524’ and common knowledge, the prediction of the physical properties of polypropylene resin powder samples, applying this method to either absorbent resin powder or an intermediate product which is produced in a process for producing the water absorbent resin powder is a routine application in the art, with predictable technical effects.
In addition, for the technical solutions of “a step of calculating the near-infrared absorption spectrum of the resin powder from a measurement value obtained by measuring light transmitted by the resin powder” and “a step of calculating the near-infrared absorption spectrum of the resin powder from a measurement value obtained by measuring light reflected by the resin powder and light transmitted by the resin powder”, it is a common approach in the art to use the transmitted light or reflected light and transmitted light for measurement.
Therefore, by combining the common knowledge in the art with the teachings of 524’, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the method of 524’ wherein the method comprises measuring at least one of light reflected by the resin powder and light transmitted by the resin powder, the resin powder being any one of a water absorbent resin powder and an intermediate product which is produced in a process for producing the water absorbent resin powder to obtain predictable result such as optimized performance.
As to claim 12, selecting which property to predict (e.g. D50, CRC, AAP, SFC, moisture content, residual monomers, bulk density, etc.) does not alter the underlying method steps taught by 524’. It names the intended result of the prediction model. Such recitations of an intended use or desired output, without a structural or process change, fails to patentably distinguish over 524’. See In re Casey, 152 USPQ 235 (CCPA 1967); In re Otto, 136 USPQ 458 (CCPA 1963).
Further, under KSR and ordinary skill reasoning, once a method of collecting NIR spectra, processing, and applying multivariate models to predict a physical property is taught, it would be obvious to apply the same workflow to predict other properties of polymer/resin powders and their intermediates where a correlation can be modeled. 524’ itself teaches that spectral features reflect chemical structure and that multivariate calibration captures those correlations (pages 1-5). The selection of which property to predict is a routine design choice made to meet production or quality-control objectives and yields predictable results (a property prediction) without requiring non-obvious modifications to the method.
Claim(s) 7, 9 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over 524’ in view of Santos et al., (Santos, Alexandre & Silva, Fabricio & Lenzi, Marcelo & Pinto, Jose. (2005). Monitoring and Control of Polymerization Reactors Using NIR Spectroscopy. Polymer-Plastics Technology and Engineering. 44-1-61.10.1080/pte-200046030, provided by applicant).
As to claims 7, 9 and 10, 524’ discloses (see the second-to-last paragraph on page 3) that for powder samples, preprocessing the near-infrared diffuse reflectance spectrum data by second-order differential.
524’ discloses fails to explicitly disclose wherein the process for producing the resin powder includes a polymerization step and a drying step; the near-infrared absorption spectrum is measured at least any one of the following points in time: before the polymerization step, between the polymerization step and the drying step; and after the drying step; and any one or more production apparatuses which are used in the process for producing the resin powered are controlled on the basis of the prediction information which has been outputted in the predicting step; a production condition of the resin powder being controlled in any one or more steps for producing the resin powder (claim 9)
However, other preprocessing methods are all common approaches in the art as evidenced by Santos. (abstract, pages 1-2, section “Introduction” and page 5, 2nd and 3rd paragraph; Fig. 1, In-line, pages 7-12, section “COMMERICAL NIT TECHNOLOGY”; pages 17-18; section “MONITORING AND CONTROL OF POLYMERIZATION REACTORS”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of 524’ wherein the process for producing the resin powder includes a polymerization step and a drying step; the near-infrared absorption spectrum is measured at least any one of the following points in time: before the polymerization step, between the polymerization step and the drying step; and after the drying step; and any one or more production apparatuses which are used in the process for producing the resin powered are controlled on the basis of the prediction information which has been outputted in the predicting step and a production condition of the resin powder being controlled in any one or more steps for producing the resin powder for advantages such as identifying and correcting potential early in the process, reduce waste and improve overall efficiency of the production process.
Examiner’s Note: Even though the following references (cited in the IDS) were not used in the rejection, these references do teach that some of the limitations are common and known in the art. For example: US 2013175473A1 teaches a method for preparing a particulate water-absorbing agent containing a polyacrylic acid (salt)-type water absorbing resin as a main component and specifically discloses the method comprising a polymerization step, a drying step, and a surface-crosslinking step. Thus the reference teaches a method of producing a resin . Regarding measuring the near-infrared absorption spectrum before, between, or after different processes to achieve control of the production process, JPH11315137A discloses production of polyester resin and specifically discloses that the near-infrared spectroscopic characteristics of one or more of the raw material, intermediate reaction products, and final products during the above mentioned production process are continuously measured, the physical properties of the measured products are analyzed from the obtained near-infrared spectra, and the reaction conditions during the production process are controlled based on the analyzed data.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TARIFUR RASHID CHOWDHURY whose telephone number is (571)272-2287. The examiner can normally be reached M-F: 8 am-5 pm.
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, Allana L. Bidder can be reached at (571)2725560. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/TARIFUR R CHOWDHURY/Supervisory Patent Examiner, Art Unit 2877
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