Prosecution Insights
Last updated: October 04, 2026
Application No. 18/077,814

MICROFLUIDIC SYSTEM FOR OIL SAMPLE ANALYSIS

Non-Final OA §103
Filed
Dec 08, 2022
Priority
Dec 09, 2021 — BR 10 2021 024963 3
Examiner
HERBERT, MADISON TAYLOR
Art Unit
1758
Tech Center
1700 — Chemical & Materials Engineering
Assignee
Cnpem - Centro Nacional De Pesquisa Em Energia E Materiais
OA Round
3 (Non-Final)
59%
Grant Probability
Moderate
3-4
OA Rounds
0m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 59% of resolved cases
59%
Career Allowance Rate
13 granted / 22 resolved
-5.9% vs TC avg
Strong +54% interview lift
Without
With
+53.7%
Interview Lift
resolved cases with interview
Typical timeline
3y 7m
Avg Prosecution
39 currently pending
Career history
68
Total Applications
across all art units

Statute-Specific Performance

§101
1.1%
-38.9% vs TC avg
§103
55.4%
+15.4% vs TC avg
§102
18.2%
-21.8% vs TC avg
§112
24.2%
-15.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 22 resolved cases

Office Action

§103
DETAILED ACTION 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 12 May 2026 has been entered. Response to Amendment This is an office action in response to Applicant’s arguments and remarks filed on 12 May 2026. Claims 1-9 are pending in this application. Claims 1-9 are being examined herein. Status of Objections and Rejections The rejection of claims 1-9 under 35 U.S.C. § 103 are withdrawn in view of amendments; however, a new ground of rejection is made. Response to Arguments Applicant’s arguments, see remarks pages 4-5, filed 12 May 2026, with respect to the rejection(s) of claim(s) 1-9 under 35 U.S.C. § 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Oliveira in view of Camargo and Burton, et. al. ("Review—The “Real-Time” Revolution for In situ Soil Nutrient Sensing;" citations made with respect to provided copy). Applicant argues the prior art and previous rejection of record to not teach or fairly disclose the limitations added by the amendments (Remarks, pg. 5, 02). Regarding the amendment, “a portable smartphone-controlled potentiostat configured to calculate capacitance from impedance using data from the capacitive sensors,” Examiner notes Oliveira teaches the device is capable of impedance measurements. Specifically, Oliveira teaches the smartphone controlled potentiostat can measure impedance to create analytical curves when related to corresponding capacitance (pg. 12379, col. 2, section "Analyses"). Regarding the amendment, “wherein the system is configured to predict an ionic composition profile of the extracted aqueous phase from the calculated capacitance using a trained machine-learning model,” Examiner agrees that the prior art of record does not teach or disclose this limitation. Examiner turns to Burton to remedy this deficiency. Applicant offers no additional arguments for dependent claims 2-9 aside from their dependence on claim 1. Claim Rejections - 35 USC § 103 The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action. Claims 1-8 are rejected under 35 U.S.C. 103 as being unpatentable over Oliveira, et. al. ("Low-Cost and Rapid-Production Microfluidic Electrochemical Double-Layer Capacitors for Fast and Sensitive Breast Cancer Diagnosis") in view of Camargo, et. al. (Cleanroom-free, fast, solventless, and bondless fabrication and application in high throughput liquid-liquid extraction") (citations for both made with respect to the provided copy with office action dated 29 July 2025) and Burton, et. al. ("Review—The “Real-Time” Revolution for In situ Soil Nutrient Sensing;" citations made with respect to provided copy). Regarding claim 1, Oliveira teaches low-cost microfluidic sensor with capillary capacitors for sample analysis (Abstract), comprising an electrochemical double-layer capillary capacitors embedded in a PDMS substrate (pg. 12378, col. 1, par. 02) (a portable microfluidic system) wherein the electrodes are capillaries that inserted from one side of the substate and span across the width of the substrate to come out across the other side of the substrate (Fig. 1) (wherein the microfluidic chips comprise microfluidic channels) (capacitive sensors). Oliveira teaches that pre-mixed/pre-treated sample (pg. 12380, "Modification of the MBs with Polyclonal Antibodies (MBs-Ab)" section) is introduced into the system via syringes (pg. 12378, par. 01) (syringe pumps configured to provide flow through the microfluidic chips). Oliveira teaches this device can be made portable by further comprising a hand-held potentiostat and a smart phone to control the potentiostat (pg. 12382; par. 04) (a portable smartphone-controlled potentiostat). Oliveira teaches the smartphone controlled potentiostat can measure impedance to create analytical curves when related to corresponding capacitance (pg. 12379, col. 2, section "Analyses") (configured to calculate capacitance from impedance using data from the capacitive sensors). Modified Oliveira is silent to a microfluidic chip for oil sample analysis, microfluidic chips configured to extract an aqueous phase from an oil sample having a BSW value lower than 1%. Camargo teaches a microfluidic device that provides turbulence under harsh flow rates (Abstract). Camargo teaches a microfluidic device formed through PSR (pg. 75, section 2.2 "Microfabrication") that uses multiple inlets with syringe pumps into channels to generate microemulsions to mix different fluids together by the turbulent flow (pg. 76, section 2.5 "Turbulence"; pg. 77, section 3.2 "Turbulence") and uses a potentiostat for analysis of the sample mixture (pg. 76, section 2.6 “Elastic deformation”). Camargo teaches one application that is the formation of microemulsions of water and oil to liquid-liquid extractions (pg. 75, section 2.7 "Liquid-liquid extraction) (for oil sample analysis) (microfluidic chips configured to extract an aqueous phase from an oil sample). Camargo teaches performing a liquid-liquid extraction on a microscale by a microfluidic device that reduces solvent volumes and waste production and allows for easy automation of a common preconcentration, pre-treatment step (pg. 81, section 3.6 "Comparison with the literature: liquid-liquid extraction"). It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to modify the microfluidic analysis chip of Oliveira to accommodate liquid-liquid extractions for oil samples as taught by Camargo because liquid-liquid extraction is a common pre-treatment step for mixed samples and the modification allows pre-treatment and analysis to be done on a singular, automated chip (Camargo, pg. 81, section 3.6 "Comparison with the literature: liquid-liquid extraction") with reasonable expectation of success. MPEP 2143(I)(G). Examiner notes “an oil sample having a BSW value lower than 1%” is drawn to a functional limitation of the microfluidic device. Further “an oil sample” is not a positively recited element of the microfluidic device. Therefore, the microfluidic device as taught by Oliveira in view of Camargo is capable of being used with an oil sample having a BSW value lower than 1%. Modified Oliveira is silent to wherein the system is configured to predict an ionic composition profile of the extracted aqueous phase from the calculated capacitance using a trained machine-learning model. Burton teaches applications of advanced technology to take results from electrochemical sensors to produce real-time information through decision management systems (Abstract). Burton teaches several sensors, with one type being electrochemical sensors like ion selective electrodes for measuring impedance in complex samples (Fig. 1; pg. 5, col. 1, par. 01). Burton teaches these on-site sensor systems comprise a sensor with a microcontroller, wherein the microcontroller remotely transmits and receives data over a network to a device like a smartphone. Burton teaches the smartphone is integrated with an application that features deep learning and algorithms for monitoring results and predicting future trends (Fig. 6, 7; pg. 7, col. 1). Burton teaches the Decision Management System provides monitoring levels (ionic composition profile) from the sensor system through network communication (Fig. 7, pg. 7, col. 2, par. 04) (wherein the system is configured to predict an ionic composition profile of the extracted aqueous phase from the calculated capacitance using a trained machine-learning model). Examiner notes the system of Burton are used for soil samples; however, Burton references similar systems for water samples (pg. 7, col. 2, par. 03). Examiner further notes the system of Burton and the system of modified Oliveira use electrode-based sensors for measuring impedance and transmitting that impedance data to a smart-device (smartphone), the systems are just used to analyze different types of samples. Burton is used to teach that measurement systems benefit from being paired with Artificial Intelligence to interpret the (impedance) data. Burton teaches integration of sensor systems with Internet of Thing (IoT), Artificial Intelligence, and/or Decision Management Systems provides real-time results and allows the user to optimize the next steps (pg. 8, par. 01). It would have been obvious to one skilled in the art before the effective filing date of the invention to modify the portable, remotely operated microfluidic system of modified Oliviera to be combined with a machine-learning model to predict an ionic composition profile from a sample as taught by Burton because integrated "IoT" systems provide real-time data results and feedback allowing the user to make optimized decisions for the next steps (Burton, pg. 8, par. 01) with reasonable expectation of success. MPEP 2143(I)(G). Regarding claim 2, modified Oliveira teaches a method of producing a microfluidic device by sequential steps of polymerization and scaffold removal (PSR) (pg. 12379, col. 1, "Device Prototyping" section) (wherein the microfluidic chips are built by methods of polymerization and scaffold removal (PSR)). Regarding claim 3, modified Oliveira teaches the microfluidic device is made from polydimethylsiloxane (PDMS), a silicone-based polymer (pg. 12379, col. 1, "Device Prototyping" section) (wherein the microfluidic chips comprise silicone). Regarding claim 4, modified Oliveira teaches the electrodes used in the microfluidic system are stainless steel capillaries (pg. 12379, col. 1, "Electrodes" section) (wherein the capacitive sensors comprise stainless steel capillaries). Regarding claim 5, modified Oliveira teaches the stainless steel capillaries are spaces roughly 200 µm apart (pg. 12379, col. 1, "Electrodes" section) (wherein the capacitive sensors have a spacing of 200 µm between each other). Regarding claim 6, modified Oliveira teaches the stainless steel capillaries are short-circuited with copper pieces producing an association of capacitors in parallel (pg. 12379, col. 1, "Device Prototyping" section) (wherein the stainless steel capillaries are short-circuited with copper pieces, obtaining an association of capacitors in parallel). Regarding claim 8, modified Oliveira teaches the PDMS for the microfluidic device as four to eight channels in parallel to one another (pg. 12379, col. 1, "Device Prototyping" section) (wherein the capacitive sensors have four or eight pairs of capacitors in parallel). Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Oliveira, et. al. ("Low-Cost and Rapid-Production Microfluidic Electrochemical Double-Layer Capacitors for Fast and Sensitive Breast Cancer Diagnosis") (2018), Camargo, et. al. (Cleanroom-free, fast, solventless, and bondless fabrication and application in high throughput liquid-liquid extraction") and Burton, et. al. ("Review—The “Real-Time” Revolution for In situ Soil Nutrient Sensing;" citations made with respect to provided copy) as applied to claim 2 above, and further in view of Pumps for Labs (“What is Tygon Tubing? 7 Selected Types”). Regarding claim 7, modified Oliveira teaches the stainless steel capillaries are connected to each other by Tygon tubes to complete the fluidic circuit (pg. 12379, col. 1, "Device Prototyping" section) (hoses connect the stainless steel capillaries to each other to complete a microfluidic circuit). Modified Oliveira is silent to the hoses specifically being poly(vinyl) chloride. Tygon is polymer based material, wherein the polymer can be silicone, PVC, polyurethane, fluoropolymers, or thermoplastic elastomers (Pumps for Labs, pg. 1, par. 01). Pumps for Labs teaches each material has its own unique physiochemical properties that influence use (pg. 1, par. 01). Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the invention for the Tygon hose taught by modified Oliveira to try a poly(vinyl) chloride based Tygon hose as taught by Pumps for Labs because there on only but so many polymer materials from which Tygon tubing/hoses can be made (Pumps for Labs, pg. 1, par. 01) each material with its own physiochemical properties (Pumps for Labs, pg. 1, par. 02) and the use of poly(vinyl) chloride hoses provides a likewise sought functionality with a reasonable expectation of success. MPEP 2143(I)(E). Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Oliveira, et. al. ("Low-Cost and Rapid-Production Microfluidic Electrochemical Double-Layer Capacitors for Fast and Sensitive Breast Cancer Diagnosis") (2018), Camargo, et. al. (Cleanroom-free, fast, solventless, and bondless fabrication and application in high throughput liquid-liquid extraction") and Burton, et. al. ("Review—The “Real-Time” Revolution for In situ Soil Nutrient Sensing;" citations made with respect to provided copy) as applied to claim 2 above, and further in view of Teixeira, et. al. ("Renewable Solid Electrodes in Microfluidics: Recovering the Electrochemical Activity without Treating the Surface") (all citations made with respect to the provided copy with office action dated 29 July 2025). Regarding claim 9, modified Oliveira teaches the limitations as applied to claim 2 above. Modified Oliveira is silent to the sensor obtained by soft lithography, the flat, gold interdigitated Capacitors are deposited on glass plates by physical evaporation techniques in the vapor phase. Teixeira teaches an electrode sensor formed by lithography (pg. 11201; par. 02) (wherein the microfluidic chips obtained by soft lithography) that uses stainless steel microwires coated with chromium and gold layer by electron beam vapor deposition (pg. 11201; col. 1, "Experimental Section - Electrodes" section) (comprise flat, gold interdigitated capacitors deposited on glass plates by physical evaporation techniques in vapor phase). Teixeira teaches teach a flat support of metal and glass (Fig. 1 description). Teixeira teaches this sensor method reduces the common problems of contamination, passivation, or fouling of electrodes (pg. 11199, par. 01) by using renewable solid-state electrodes (pg. 11200; par. 01). It would have been obvious to one skilled in the art before the effective filing date of the invention to substitute the PSR-based sensor of Oliveira with the lithography- based sensor of Teixeira. One of ordinary skill in the art would be motivated to do this because lithography-based production creates a sensor not prone to common problems of contamination, passivation, or fouling (Teixeira, pg. 11199, par. 01) and this involves the simple substitution of one known method (PSR-based sensor) for another (lithography-based sensor) to obtain predictable results (a sensor for a microfluidic system). See MPEP 2143(I)(B). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to MADISON T HERBERT whose telephone number is (571)270-1448. The examiner can normally be reached Monday-Friday 8:30a-5:00p. 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, Maris Kessel can be reached at (571) 270-7698. 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. /M.T.H./Examiner, Art Unit 1758 /MARIS R KESSEL/Supervisory Patent Examiner, Art Unit 1758
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Prosecution Timeline

Dec 08, 2022
Application Filed
Jul 29, 2025
Non-Final Rejection mailed — §103
Nov 26, 2025
Response Filed
Jan 16, 2026
Final Rejection mailed — §103
May 12, 2026
Request for Continued Examination
May 15, 2026
Response after Non-Final Action
Sep 09, 2026
Non-Final Rejection mailed — §103 (current)

Precedent Cases

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
59%
Grant Probability
99%
With Interview (+53.7%)
3y 7m (~0m remaining)
Median Time to Grant
High
PTA Risk
Based on 22 resolved cases by this examiner. Grant probability derived from career allowance rate.

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