Prosecution Insights
Last updated: July 17, 2026
Application No. 18/290,857

NANOWIRE-BASED DEVICE FOR IMPLEMENTING A RESERVOIR FOR A NEURAL NETWORK

Non-Final OA §101§103
Filed
Jan 22, 2024
Priority
Jul 21, 2021 — IT 102021000019277 +1 more
Examiner
MRABI, HASSAN
Art Unit
2147
Tech Center
2100 — Computer Architecture & Software
Assignee
Istituto Nazionale Di Ricerca Metrologica
OA Round
1 (Non-Final)
78%
Grant Probability
Favorable
1-2
OA Rounds
3m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 78% — above average
78%
Career Allowance Rate
291 granted / 371 resolved
+23.4% vs TC avg
Strong +33% interview lift
Without
With
+32.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 9m
Avg Prosecution
28 currently pending
Career history
398
Total Applications
across all art units

Statute-Specific Performance

§101
5.7%
-34.3% vs TC avg
§103
86.4%
+46.4% vs TC avg
§102
4.9%
-35.1% vs TC avg
§112
0.4%
-39.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 371 resolved cases

Office Action

§101 §103
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 . DETAILED ACTION This Office Action is sent in response to Application’s Communication received on 01/22/2024 for application number 18/290857. The Office hereby acknowledges receipt of the following and placed of record in file: Specification, Drawing, Abstract, Oath/Declaration, and Claims. Claims (1-7) and 8 are presented for examination. Information Disclosure Statement The information disclosure statements (IDS) submitted on 01/30/2024 was filed prior to current Office Action. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. 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 non-statutory subject matter. Regarding claims 1-8, the claims refer to a device and a system. Page. 8 of this instant specification, have provided evidence that the claimed system is software per se, wherein a plurality of a network exhibits differences applied across electrodes and temporary variation of conductivity. Page. 8 describes that a reservoir may be any neural network implemented as a software, therefore; the claims do not define structural and functional descriptive material used in interrelationship between the computer software and the hardware like a memory or processor. Descriptive material can be characterized as either “functional descriptive material” or “nonfunctional descriptive material.” Both types of “descriptive material” are nonstatutory when claimed as descriptive material per se, 33 F.3d at 1360, 31 USPQ2d at 1759. When functional descriptive material is recorded on some computer-readable medium, it becomes structurally and functional interrelated to the medium and will be statutory in most cases since use of technology permits the function of the descriptive material to be realized. Compare In re Lowry, 32 F.3d 1579, 1583-84, 32 USPQ2d 1031, 1035 (Fed. Cir. 1994). Claim Rejections - 35 USC § 103 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 of this title, 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. Claims 1-5 and 7 are rejected under AIA 35 U.S.C. 103(a) as being unpatentable over of Vianello et al. US Patent Application Publication US 20200321397 A1 (hereinafter Vianello) in view of CARIO LAURENT et al. Foreign Application Publication FR 3071646 A1 (hereinafter Cario). Regarding claim 1, Vianello teaches A device for implementing a reservoir for a neural network, comprising: a network of nanowires disposed on a substrate; wherein said network of nanowires comprises a plurality of nanowires spread over a surface of said substrate ([0001], [0008-0009], [0020-0021] wherein Vianello describes a technical domain that relates to neural networks training using a reservoir computing paradigms and describing steps of fabricating a recurrent-neural-network computer and describing growing nanowires on structured platinum electrodes) wherein, when a potential difference is applied across two electrodes, said network of nanowires exhibits a temporary variation of conductivity ([0013], [0015], [0033], [0166] wherein Vianello discloses a semiconductor for producing nanometer scale and precipitating conduits between electrodes). Vianello does not teach a plurality of electrodes; each electrode being electrically connected to at least one respective nanowire. However in analogous art of nanowire-based device, Cario teaches a plurality of electrodes; each electrode being electrically connected to at least one respective nanowire (Page. 7 ¶ 1-3 wherein Cario discloses an electric dipole comprising nanowires and wherein a layer of metallic material constituting the two input and output electrodes of the neuron is deposited on a substrate plate). It would have been obvious to a person in the ordinary skill in the art before the effective filing date of the claimed invention to combine Vianello with Cario by incorporating the method of a plurality of electrodes; each electrode being electrically connected to at least one respective nanowire of Cario into the method of a network of nanowires disposed on a substrate; wherein said network of nanowires comprises a plurality of nanowires spread over a surface of said substrate of Vianello for the purpose of implementing one electric dipole and the artificial single-component neuron according to the invention that requires little energy and has a high potential for integration into the electronic circuits. (Cario: page. 7, ¶ 2). Regarding claim 2, Vianello as modified by Cario teaches wherein said device comprises 2n electrodes; wherein a number n of electrodes correspond to n input electrodes suitable for receiving a respective input signal; wherein a number n of electrodes correspond to n output electrodes; each output electrode being suitable for emitting a signal as a function of said input signals ([0057], [0122], [0138], [0179] wherein Vianello discloses a physical neural network (i.e., a Knowm.TM.) that have two components to function properly. First, the physical neural network has one or more neuron-like nodes that sum a signal and output a signal based on the amount of input signal received. Such a neuron-like node is generally non-linear in output. In other words, there should be a certain threshold for input signals, below which nothing is output and above which a constant or nearly constant output is generated or allowed to pass. This is a very basic requirement of standard software-based neural networks, and can be accomplished by an activation function. The second requirement of a physical neural network is the inclusion of a connection network composed of a plurality of interconnected connections (i.e., nanoconnections)). Regarding claim 3, Vianello as modified by Cario teach wherein said device comprises n electrodes; wherein each electrode is suitable for receiving a respective input signal; wherein a number n-1 of electrodes is further associated with a respective output terminal suitable for emitting a signal as a function of said input signals ([0057], [0122], [0138], [0179] wherein Vianello discloses a physical neural network (i.e., a Knowm.TM.) that have two components to function properly. First, the physical neural network has one or more neuron-like nodes that sum a signal and output a signal based on the amount of input signal received. Such a neuron-like node is generally non-linear in output. In other words, there should be a certain threshold for input signals, below which nothing is output and above which a constant or nearly constant output is generated or allowed to pass. This is a very basic requirement of standard software-based neural networks, and can be accomplished by an activation function. The second requirement of a physical neural network is the inclusion of a connection network composed of a plurality of interconnected connections (i.e., nanoconnections)), (FIG. 9, page. 9 ¶ 2 wherein Cario describes a test the response of the functional material to the application of different series of electrical pulses emitted by the generator). Regarding claim 4, Vianello as modified by Cario teach wherein each nanowire of the network of nanowires comprises a metal core and an insulating coating ([0013], [0033] wherein Vianello describes metal oxide semiconductor and an insulating layer can be associated with the input layer, and another insulating layer associated with the output layer). Regarding claim 5, Vianello as modified by Cario teach wherein said metal core is made of an electro-chemically active material, and said insulating coating is preferably made of a polymeric material or a metal oxide ([0013], [0015] wherein Vianello discloses standard silicon based complementary metal oxide semiconductor). Regarding claim 7, Vianello as modified by Cario teach wherein said substrate is an insulating substrate ([0033], [0175] wherein Vianello discloses nanoconductors form nanoconnections at one or more intersections between the input electrodes and the output electrodes in accordance with an increase in a strength or frequency of the electric field applied across the gap from the input layer to the output layer. Additionally, an insulating layer can be associated with the input layer, and another insulating layer associated with the output layer). Claim 6 is rejected under AIA 35 U.S.C. 103(a) as being unpatentable over of Vianello et al. US Patent Application Publication US 20200321397 A1 (hereinafter Vianello) in view of CARIO LAURENT et al. Foreign Application Publication FR 3071646 A1 (hereinafter Cario) further in view GAO Shuang et al. Foreign Application Publication CN 107706205 A (hereinafter Gao). Regarding claim 6, Vianello and Cario do not teach wherein said metal core is made of an electro-chemically inert material, and said insulating coating is preferably made of a material configured to allow a phenomenon of "resistive switching" by oxygen vacancy migration. However in analogous art of nanowire-based device, Gao teaches wherein said metal core is made of an electro-chemically inert material, and said insulating coating is preferably made of a material configured to allow a phenomenon of "resistive switching" by oxygen vacancy migration (Abstract, page. 3, ¶ 10 wherein Gao provides a unipolar resistive-switching memory with high resistance-change stability, its core is chemically inert anode/oxide storage medium/chemical active cathode three-layer-film structure according to the thermodynamic principle. oxide storage medium and chemical activity between the anode and the cathode will spontaneously to interfacial reaction between the oxide storage medium layer and the chemically active cathode layer form an interface layer containing a large amount of oxygen vacancies and the suboxide; when the chemical inert anode layer and the chemically active cathode layer when a voltage is applied. the interface layer can promote the growth of conductive filaments near the cathode, and on the other hand, it can act as series resistance for inhibiting excessive growth of conductive filament, finally the conductive filament between the anode and the cathode having a tip structure near the anode, so, in the heat fusing process of the conductive filament, Joule heat effect of the current is concentrated near the tip structure, such that the conductive filament only break at the tip structure, and the residual part is capable of generating the electric field concentration effect, the conductive filament formed preferentially occurs at the position. so as to inhibit random formation and disconnection of the conductive filament, which can obtain high stability of unipolar resistive-switching behavior, is expected to greatly promote practical process of unipolar resistive-switching memory). It would have been obvious to a person in the ordinary skill in the art before the effective filing date of the claimed invention to combine Gao with Vianello and Cario by incorporating the method of wherein said metal core is made of an electro-chemically inert material, and said insulating coating is preferably made of a material configured to allow a phenomenon of "resistive switching" by oxygen vacancy migration of Gao into the method of a network of nanowires disposed on a substrate; wherein said network of nanowires comprises a plurality of nanowires spread over a surface of said substrate of Vianello and Cario for the purpose of obtaining high stability of unipolar resistive-switching behavior (Gao: Abstract). Claim 8 is rejected under AIA 35 U.S.C. 103(a) as being unpatentable over of Vianello et al. US Patent Application Publication US 20200321397 A1 (hereinafter Vianello) in view of CARIO LAURENT et al. Foreign Application Publication FR 3071646 A1 (hereinafter Cario) further in view Nugent. US Application Publication US 20090228416 A1 (hereinafter Nugent). Regarding claim 8, Vianello and Cario do not teach a reservoir computing system comprising: a device according to said device comprising a plurality of electrodes; and a readout; wherein at least half of said plurality of electrodes are connected as inputs to said readout. However in analogous art of nanowire-based device, Nugent teaches teach a reservoir computing system comprising: a device according to said device comprising a plurality of electrodes; and a readout; wherein at least half of said plurality of electrodes are connected as inputs to said readout (Abstract, [0032-0033] wherein Nugent discloses a physical neural network synapse chip and a method for forming such a synapse chip. The synapse chip can be configured to include an input layer comprising a plurality of input electrodes and an output layer comprising a plurality of output electrodes, such that the output electrodes are located perpendicular to the input electrodes. A gap is generally formed between the input layer and the output layer. A solution can then be provided which is prepared from a plurality of nanoconductors and a dielectric solvent. The solution is located within the gap, such that an electric field is applied across the gap from the input layer to the output layer to form nanoconnections of a physical neural network implemented by the synapse chip. Such a gap can thus be configured as an electrode gap. The input electrodes can be configured as an array of input electrodes, while the output electrodes can be configured as an array of output electrodes). It would have been obvious to a person in the ordinary skill in the art before the effective filing date of the claimed invention to combine Nugent with Vianello and Cario by incorporating the method of teach a reservoir computing system comprising: a device according to said device comprising a plurality of electrodes; and a readout; wherein at least half of said plurality of electrodes are connected as inputs to said readout of Nugent into the method of a network of nanowires disposed on a substrate; wherein said network of nanowires comprises a plurality of nanowires spread over a surface of said substrate of Vianello and Cario for the purpose of providing a solution to form electrical conduits between electrodes (Nugent: [0033]). Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Any inquiry concerning this communication or earlier communications from the examiner should be directed to HASSAN MRABI whose telephone number is (571)272-8875. The examiner can normally be reached on Monday-Friday, 7:30am-5pm. Alt, Friday, EST. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Viker Lamardo can be reached on 571-270-5871. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /HASSAN MRABI/Examiner, Art Unit 2144
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Prosecution Timeline

Jan 22, 2024
Application Filed
Jul 01, 2026
Non-Final Rejection mailed — §101, §103 (current)

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Prosecution Projections

1-2
Expected OA Rounds
78%
Grant Probability
99%
With Interview (+32.9%)
2y 9m (~3m remaining)
Median Time to Grant
Low
PTA Risk
Based on 371 resolved cases by this examiner. Grant probability derived from career allowance rate.

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