Prosecution Insights
Last updated: April 19, 2026
Application No. 18/785,519

SEMICONDUCTOR PROCESSING TOOL AND METHODS OF OPERATION

Non-Final OA §101§103
Filed
Jul 26, 2024
Examiner
CAMPBELL, NATASHA N.
Art Unit
1714
Tech Center
1700 — Chemical & Materials Engineering
Assignee
Taiwan Semiconductor Manufacturing Company Ltd.
OA Round
1 (Non-Final)
67%
Grant Probability
Favorable
1-2
OA Rounds
3y 0m
To Grant
82%
With Interview

Examiner Intelligence

Grants 67% — above average
67%
Career Allow Rate
557 granted / 826 resolved
+2.4% vs TC avg
Moderate +14% lift
Without
With
+14.4%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
24 currently pending
Career history
850
Total Applications
across all art units

Statute-Specific Performance

§101
1.5%
-38.5% vs TC avg
§103
52.4%
+12.4% vs TC avg
§102
17.1%
-22.9% vs TC avg
§112
23.7%
-16.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 826 resolved cases

Office Action

§101 §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 § 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) steps of receiving data and determining a level of cleanliness based on the data. Under its broadest reasonable interpretation, the limitation is a simple process that covers performance of the limitation in the mind. Thus, the limitation is an abstract idea. This judicial exception is not integrated into a practical application because once the determination is made nothing is done beyond transmitting an alert to indicate that the operation is complete. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of receiving data from the gas concentration sensor and temperature sensor are recited at a high level of generality and amount to mere data-gathering, which is a form of insignificant extra-solution activity. Accordingly, even in combination, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are not eligible for patentability under 35 USC 101. 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. Claims 7-10 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Ashley (US 5,565.038), and further in view of Dimeo et al. (US 2010/0154835) and Chen (US 2022/0037137). Regarding Claims 7 and 8: Ashley teaches a method, comprising: activating a first dry-clean operation for a deposition tool; receiving, based on activating the first dry-clean operation, initial first data associated with a first concentration of a first chemical compound in a first cleaning gas; and determining, based on the initial first data, a first level of cleanliness of the deposition tool (col. 5, ll. 48-55. Ashley does not expressly disclose receiving, based on activating the first dry-clean operation, initial second data associated with a temperature of the first cleaning gas to determine the first level of cleanliness. However, Dimeo teaches a method comprising receiving temperature data of a cleaning gas which is used to detect substantial termination of an exothermic reaction of the reactive gas with contamination on a surface of the system [0122]. Dimeo additionally teaches that the concentration of gas-phase reactive material and other reaction byproducts are used to monitor the progress of the cleaning process [0159]. Thus, Dimeo suggests using both cleaning gas temperature and concentration to determine the completion of the cleaning process. 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 Ashley by receiving data indicating the temperature of the cleaning gas and the data indicating the concentration of the cleaning gas to determine the cleaning completion as suggested by Dimeo in order to provide a more accurate determination. Ashley does not expressly disclose using a machine learning model to determine the first level of cleanliness. However, Chen teaches a cleaning method comprising the use of a machine learning model to determine whether the concentration of one or more ion species of a residual gas is greater than one or more respective baseline values based upon a processing chamber cleaning history [0035-0041], wherein the machine leaning model correlates one or more historical operating conditions to a level of cleanliness [0037]. 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 controller of Ashley in view of Dimeo to use a machine learning model as claimed in order more accurately determine the cleaning endpoint, as suggested by Chen. Regarding Claims 9 and 10: Ashley, Dimeo, and Chen teach the elements of Claim7 as discussed above. Chen does not expressly disclose that one or more historical operating conditions corresponds to a dry-clean recipe. However, Ashely teaches that the cleaning operation includes parameters comprising a pressure of the cleaning gas, temperature of the cleaning gas, and flow rate of the cleaning gas (col. 9, ll. 1-20). 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 prior art controller such that the historical operating conditions correspond to a dry-clean recipe that indicates one of pressure, temperature, or flow rate of the cleaning gas given that Ashley teaches such parameters are required for efficient cleaning. Regarding Claim 12: Ashley further teaches wherein the dry-clean operation comprises: an etching operation that uses a recipe to remove a buildup of a thin-film material from an interior surface of a deposition chamber (see abstract). Regarding Claims 14, 17, and 18: Ashley teaches a method, comprising: activating a first dry-clean operation for a deposition tool; receiving, during a first dry clean operation for a first portion of a deposition tool, initial first data associated with a first concentration of a first chemical compound in a first cleaning gas; and determining, based on the initial first data, a first level of cleanliness of the deposition tool (col. 5, ll. 48-55); and deactivating the first dry clean operation based on determining that the dry clean operation is complete (col. 5, ll. 59-64). Ashley does not expressly disclose receiving, based on activating the first dry-clean operation, initial second data associated with a temperature of the first cleaning gas to determine the first level of cleanliness. However, Dimeo teaches a method comprising receiving temperature data of a cleaning gas which is used to detect substantial termination of an exothermic reaction of the reactive gas with contamination on a surface of the system [0122]. Dimeo additionally teaches that the concentration of gas-phase reactive material and other reaction byproducts are used to monitor the progress of the cleaning process [0159]. Thus, Dimeo suggests using both cleaning gas temperature and concentration to determine the completion of the cleaning process. 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 Ashley by receiving data indicating the temperature of the cleaning gas and the data indicating the concentration of the cleaning gas to determine the cleaning completion as suggested by Dimeo in order to provide a more accurate determination. Ashley does not expressly disclose using a machine learning model to determine the cleaning completion. However, Chen teaches a cleaning method comprising the use of a machine learning model to determine whether the concentration of one or more ion species of a residual gas is greater than one or more respective baseline values based upon a processing chamber cleaning history [0035-0041], wherein the machine leaning model correlates one or more historical operating conditions to a level of cleanliness [0037]. 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 controller of Ashley in view of Dimeo to use a machine learning model as claimed in order more accurately determine the cleaning endpoint, as suggested by Chen. Ashley does not expressly disclose activating a second dry clean operation based on the first level of cleanliness and receiving subsequent first and second data to determine that a second level of cleanliness has been reached. However, Hill teaches that first and second levels of cleanliness can be determined within the system by monitoring a signature substance [0014]. 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 prior art method by activating a second cleaning and receiving subsequent first and second data to determine that a second level of cleanliness has been reached in order to enhance the cleaning efficiency, as suggested by Hill. Regarding Claim 15: Ashley teaches wherein the dry-clean operation comprises using a recipe for cleaning, but does not expressly disclose using a second dry clean operation using a second dry clean operation. However, in activating a subsequent cleaning, it would be reasonably expected to use a second dry clean operation as claimed. Regarding Claim 16: Ashley teaches that the tool is a deposition tool, but does not expressly disclose the second portion is an injector nozzle. However, Ashley teaches removing deposits from the chamber walls and internal parts (col. 1, ll. 27-30). 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 prior art method by cleaning an injector nozzle in order to enhance the cleaning efficiency and perform a complete cleaning. Regarding Claim 19: Chen further teaches providing, to the machine learning model, candidate parameters associated with at least one of the first dry-clean operation or the second dry-clean operation; and receiving a likelihood that a particular outcome for a subsequent dry-clean operation, associated with the at least one of the first dry-clean operation or the second dry-clean operation, will be achieved using the candidate parameters [0035]. Claims 11 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Ashley (US 5,565.038), Dimeo et al. (US 2010/0154835) and Chen (US 2022/0037137) as applied to Claim 7 above, and further in view of Hill (US 2022/0048081). Regarding Claim 11: Ashley, Dimeo, and Chen teach the elements of Claim 7 as discussed above. Ashley does not expressly disclose the first chemical compound comprises silicon tetrafluoride. However, it is known to use silicon tetrafluoride for similar process chamber cleaning, and determining a cleaning endpoint based on the concentration of the silicon tetrafluoride during the cleaning [0032]. 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 prior art method with silicon tetrafluoride as it is a known cleaning gas suitable for cleaning process chambers, as taught by Hill. Regarding Claim 13: Ashley, Dimeo, and Chen teach the elements of Claim 7 as discussed above. Ashley does not expressly disclose activating a second dry clean operation based on the first level of cleanliness and receiving subsequent first and second data to determine that a second level of cleanliness has been reached. However, Hill teaches that first and second levels of cleanliness can be determined within the system by monitoring a signature substance [0014]. 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 prior art method by receiving subsequent first and second data to determine that a second level of cleanliness has been reached in order to enhance the cleaning efficiency, as suggested by Hill. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to NATASHA CAMPBELL whose telephone number is (571)270-7382. The examiner can normally be reached Monday-Friday 9:00 AM- 5:00 PM 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, Kaj Olsen can be reached at (571) 272-1344. 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. /NATASHA N CAMPBELL/ Primary Examiner, Art Unit 1714
Read full office action

Prosecution Timeline

Jul 26, 2024
Application Filed
Jan 10, 2026
Non-Final Rejection — §101, §103
Mar 13, 2026
Interview Requested
Mar 19, 2026
Applicant Interview (Telephonic)
Mar 20, 2026
Examiner Interview Summary

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

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Prosecution Projections

1-2
Expected OA Rounds
67%
Grant Probability
82%
With Interview (+14.4%)
3y 0m
Median Time to Grant
Low
PTA Risk
Based on 826 resolved cases by this examiner. Grant probability derived from career allow rate.

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