Prosecution Insights
Last updated: April 18, 2026
Application No. 18/629,850

INTELLIGENT AND DYNAMIC COLD PLATE FOR DATACENTER COOLING SYSTEMS

Final Rejection §102§103
Filed
Apr 08, 2024
Examiner
KIM, JAMES JAY
Art Unit
3747
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Nvidia Corporation
OA Round
2 (Final)
70%
Grant Probability
Favorable
3-4
OA Rounds
2y 4m
To Grant
97%
With Interview

Examiner Intelligence

Grants 70% — above average
70%
Career Allow Rate
467 granted / 665 resolved
At TC average
Strong +27% interview lift
Without
With
+27.1%
Interview Lift
resolved cases with interview
Typical timeline
2y 4m
Avg Prosecution
28 currently pending
Career history
693
Total Applications
across all art units

Statute-Specific Performance

§101
0.4%
-39.6% vs TC avg
§103
54.8%
+14.8% vs TC avg
§102
22.9%
-17.1% vs TC avg
§112
20.1%
-19.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 665 resolved cases

Office Action

§102 §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 . 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, 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. Claims 1-4 are rejected under 35 U.S.C. 103 as being unpatentable over Chainer et al (US 2014/0049918 hereinafter “Chainer”) in view of Cui et al (US 10,238,011) and Zhai et al (US 2019/0335575 hereinafter “Zhai”). In regards to claim 1: Chainer teaches a processor comprising one or more circuits, the one or more circuits to determine a temperature associated with at least one computing device (Paragraph [0060] recites the temperature being associated with electronic components and Paragraph [0057] recites cold plates to cool multiple processor modules), the processor issuing one or more commands to cause one or more positions corresponding to one or more overlapping sections of a plurality of fins (1312) within a cold plate (1310) to be adjusted. Chainer does not teach the temperature being based on data from one or more sensors associated with the at least one computing device and one or more fluid paths being formed by adjustable fins to control an amount of surface area of the plurality of fins exposed to a fluid and to be cooled by the fluid. Cui teaches temperature data based on one or more sensors associated with at least one computing device (Col 6, Lines 60-63). It would have been obvious to one of ordinary skill in the art at the time of filing of the application to have the processor of Chainer to determine temperature from one or more sensors as taught by Cui in order to have accurate temperature data. Cui recites “For example, the monitor may receive operating data representing temperatures of the processors, cooling liquid, and airflows, which may be captured and collected via various temperature sensors.” (Col 6, Lines 60-63). Wherein using temperature data to dictate the cooling needs is understood as vital to allowing the processor to know what the temperature is and how much cooling is required to maintain a desired temperature. Zhai teaches adjustable fins to control an amount of surface area exposed to a fluid to be cooled by the fluid (Figure 4). It would have been obvious to one of ordinary skill in the art at the time of filing of the application to modify the cooling system of Chainer to have adjustable fins as taught by Zhai in order to adjust the height of fins in conjunction with the midplate (1315) of Chainer. In regards to claim 2: Chainer teaches an output to provide signals for at least one controller (1330) to enable the adjustment to the amount of the surface area of the plurality of fins to be exposed to the fluid and to be cooled by the fluid (Paragraph [0092]). In regards to claim 3: Chainer teaches an input to receive sensor inputs from sensors associated with the at least one computing device, a rack, a secondary coolant, or the fluid, the processor to determine a first cooling requirement for the plurality of fins to be in a retracted configuration and a second cooling requirement for the plurality of fins to be in an exposed configuration, based in part on the sensor inputs (Paragraph [0060] recites temperature is monitored is one or more electronic components, Table 1 recites a temperature Tj and Paragraph [0073] recites control based on an electronic component junction temperature Tj, wherein the electronic component may comprise one or more processors (a computing device)). In regards to claim 4: Chainer one or more neural networks to receive the sensor inputs and to infer the first cooling requirement and the second cooling requirement (Paragraph [0112] recites the program code for carrying out the operations of the present invention may entirely be executed remotely on a network). Claims 6-15 are rejected under 35 U.S.C. 103 as being unpatentable over Chainer in view of Zhai. In regards to claim 6: Chainer teaches a processor comprising one or more circuits, the one or more circuits to train one or more neural networks to infer (Paragraph [0112] recites the program code for carrying out the operations of the present invention may entirely be executed remotely on a network), from sensor inputs of sensors associated with at least one computing device, that a change in a cooling requirement has occurred (Paragraph [0060] recites The monitored variable could comprise, as one example, a temperature associated with at least one of the coolant-cooled cold plate, or the one or more electronic components being cooled by the coolant-cooled cold plate), the processor issuing one or more commands to cause one or more positions corresponding to one or more overlapping sections of a plurality of fins within a cold plate to be adjusted to control an amount of surface area of the plurality of fins to be exposed to a fluid and to be cooled by the fluid (Paragraph [0093] describes the coolant carrying channel 1311 having a variable cross sectional area via adjustable midplate 1315). Chainer does not teach one or more fluid paths being formed by adjustable fins to control an amount of surface area of the plurality of fins exposed to a fluid and to be cooled by the fluid. Zhai teaches adjustable fins to control an amount of surface area exposed to a fluid to be cooled by the fluid (Figure 4). It would have been obvious to one of ordinary skill in the art at the time of filing of the application to modify the cooling system of Chainer to have adjustable fins as taught by Zhai in order to adjust the height of fins in conjunction with the midplate (1315) of Chainer. In regards to claim 7: Chainer teaches an output to provide signals for the at least one controller (1330) to enable adjustment to control the amount of the surface area of the plurality of fins to be exposed to the fluid and to be cooled by the fluid (Paragraph [0093] recites the controller 1330 controlling and adjusting the midplate 1315 which controls the amount of surface area of the fins 1312 exposed to a fluid). In regards to claim 8: Chainer teaches the one or more neural networks to receive the sensor inputs and to be trained to infer a first cooling requirement for the plurality of fins to be in a retracted configuration and a second cooling requirement for the plurality of fins to be in an exposed configuration, based in part on the sensor inputs (Paragraphs [0093] – [0096] recites control of the adjustable midplate, wherein control can be done remotely). In regards to claim 9: Chainer teaches an output to provide signals to at least one controller to cause one or more different exposures of the surface area of the plurality of fins to address different cooling requirements (Paragraph [0095] recites the controller implementing a cooling control process to expose the surface area of the fins to optimally cool the associated electronic components while at the same time reducing power consumption). In regards to claim 10: Chainer teaches an input to receive the sensor inputs associated with a temperature from the at least one computing device, the secondary coolant, or the fluid, the one or more neural networks trained to infer a change in cooling requirement has occurred based in part on the temperature and on prior temperatures, the one or more circuits to control the amount of the surface area of the plurality of fins to be exposed to the fluid and to be cooled by the fluid (Paragraph [0060] recites temperature is monitored is one or more electronic components, Table 1 recites a temperature Tj and Paragraph [0073] recites control based on an electronic component junction temperature Tj, wherein the electronic component may comprise one or more processors (a computing device)). In regards to claim 11: Chainer teaches a processor comprising one or more circuits, the one or more circuits comprising one or more neural networks to infer (Paragraph [0112] recites the program code for carrying out the operations of the present invention may entirely be executed remotely on a network), from sensor inputs of sensors associated with at least one computing device, that a change in a cooling requirement has occurred (Paragraph [0060] recites The monitored variable could comprise, as one example, a temperature associated with at least one of the coolant-cooled cold plate, or the one or more electronic components being cooled by the coolant-cooled cold plate), the processor issuing one or more commands to cause one or more positions corresponding to one or more overlapping sections of a plurality of fins within a cold plate to be adjusted to control an amount of surface area of the plurality of fins to be exposed to a fluid and to be cooled by the fluid (Paragraph [0093] describes the coolant carrying channel 1311 having a variable cross sectional area via adjustable midplate 1315). Chainer does not teach one or more fluid paths being formed by adjustable fins to control an amount of surface area of the plurality of fins exposed to a fluid and to be cooled by the fluid. Zhai teaches adjustable fins to control an amount of surface area exposed to a fluid to be cooled by the fluid (Figure 4). It would have been obvious to one of ordinary skill in the art at the time of filing of the application to modify the cooling system of Chainer to have adjustable fins as taught by Zhai in order to adjust the height of fins in conjunction with the midplate (1315) of Chainer. In regards to claim 12: Chainer teaches an output to provide signals for the at least one controller to enable adjustment to control the amount of the surface area of the plurality of fins to be exposed to the fluid and to be cooled by the fluid (Paragraph [0095] recites the controller implementing a cooling control process to expose the surface area of the fins to optimally cool the associated electronic components while at the same time reducing power consumption). In regards to claim 13: Chainer teaches the one or more neural networks to receive the sensor inputs and to infer a first cooling requirement for the plurality of fins to be in a retracted configuration and a second cooling requirement for the plurality of fins to be in an exposed configuration, based in part on the sensor inputs (Paragraphs [0093] – [0096] recites control of the adjustable midplate, wherein control can be done remotely). In regards to claim 14: Chainer teaches an output to provide signals to at least one controller to cause one or more different exposures of the surface area of the plurality of fins to address different cooling requirements (Paragraph [0095] recites the controller implementing a cooling control process to expose the surface area of the fins to optimally cool the associated electronic components while at the same time reducing power consumption). In regards to claim 15: Chainer teaches an input to receive the sensor inputs associated with a temperature from the at least one computing device, the secondary coolant, or the fluid, the one or more neural networks to infer a change in cooling requirement has occurred based in part on the temperature and on prior temperatures, the one or more circuits to control the amount of the surface area of the plurality of fins to be exposed to the fluid and to be cooled by the fluid (Paragraph [0060] recites temperature is monitored is one or more electronic components, Table 1 recites a temperature Tj and Paragraph [0073] recites control based on an electronic component junction temperature Tj, wherein the electronic component may comprise one or more processors (a computing device)). Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Chainer, Cui and Zhai as applied to claim 1 above and further in view of Malone et al (US 9,003,821 hereinafter “Malone”). In regards to claim 5: Chainer teaches one or more neural networks to control the cooling system (Paragraph [0112]) but does not teach in response to a failure of a secondary cooling loop, the one or more circuits to cause at least one controller to adjust the amount of the surface area of the plurality of fins to be exposed to the fluid that is from a local cooling loop instead of the secondary cooling loop. Malone teaches a secondary cooling loop, wherein upon a failure, increasing the cooling from a local cooling loop that picks up the extra cooling demand. It would have been obvious to one of ordinary skill in the art at the time of filing of the application to modify the system of Chainer to adjust the local cooling loop instead of a failing secondary loop as taught by Malone in order to pick up the extra cooling demand (Col 7, Lines 1-13). Response to Arguments Applicant’s arguments, see pages 1-3 of Remarks, filed 1/21/2026, with respect to the rejection(s) of claim(s) 1-15 under 35 U.S.C. 102(a)(1) and 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 newly found prior art references. The Zhai reference has been added to the rejection to address the fins being adjustable, wherein Zhai teaches a fin comprised of two parts with one part of the fin being received so that the fin can extend and retract to adjust the height of the fin. The Cui reference has been added to address the amendment of the sensor providing sensor data. Although it is understood that data is a broad term and processors are receiving some sort of data to act upon, Cui explicitly teaches a temperature sensor to provide sensor data indicative of the temperature to a processor. The usage of sensors to provide data is well established in the art for their explicit function of sensing and outputting a signal in regards to what is being sensed (ie. temperature sensors outputs temperature data, pressure sensors output pressure data). Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES JAY KIM whose telephone number is (571)270-7610. The examiner can normally be reached M-F 9-5 EST. 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, Logan Kraft can be reached at (571) 270-5065. 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. /JAMES J KIM/Examiner, Art Unit 3747 /HUNG Q NGUYEN/Primary Examiner, Art Unit 3747
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Prosecution Timeline

Apr 08, 2024
Application Filed
Oct 15, 2025
Non-Final Rejection — §102, §103
Dec 29, 2025
Applicant Interview (Telephonic)
Dec 29, 2025
Examiner Interview Summary
Jan 21, 2026
Response Filed
Apr 02, 2026
Final Rejection — §102, §103 (current)

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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
70%
Grant Probability
97%
With Interview (+27.1%)
2y 4m
Median Time to Grant
Moderate
PTA Risk
Based on 665 resolved cases by this examiner. Grant probability derived from career allow rate.

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