DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Amendment
1- The amendment filed on 09/08/2026 has been entered and fully considered. Claims 1-20 remain pending in the application, where the independent claims have been amended.
Response to Arguments
2- Examiner has considered Applicants’ proposed amendments and acknowledges they overcome the 35 USC 112 rejection of the pending claims as set forth in the non-final office action mailed on 6/12/2026. The above rejections are therefore withdrawn.
3- Applicants’ amendments and their corresponding arguments with respect to the rejections of the pending claims under 35 USC § 102 and 103 have been fully considered but are found not persuasive to overcome the prior art used in the previous office action, despite the fact that the amendments have changed the scope of the invention and overcome the rejection as written in the previous office action.
4- Therefore, the amendments necessitated, upon further consideration, new grounds of rejection using additional teachings from the same references used in the previous office action. The new limitations are addressed in the rejections here under in more details.
Claim Rejections - 35 USC § 103
5- 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.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under pre-AIA 35 U.S.C. 103(a) 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.
In addition, the functional recitation in the claims (e.g. "configured to" or "adapted to" or the like) that does not limit a claim limitation to a particular structure does not limit the scope of the claim. It has been held that the recitation that an element is "adapted to", "configured to", "designed to", or "operable to" perform a function is not a positive limitation but only requires the ability to so perform and may not constitute a limitation in a patentable sense. In re Hutchinson, 69 USPQ 139. (See MPEP 2111.04); see also In In re Giannelli, 739 F.3d 1375, 1378, 109 USPQ2d 1333, 1336 (Fed. Cir. 2014).
Also, it should be noted that it has been held that a recitation with respect to the manner in which a claimed device is intended to be employed does not differentiate the claimed device from a prior art apparatus satisfying the claimed structural limitations Ex-parte Masham 2 USPQ2d 1647 1987).
The claimed system in the instant application is capable of performing the claimed functionality, as is the prior art used in the present office action. The Examiner notes that where the patent office has reason to believe that a functional limitation asserted to be critical for establishing novelty in the claimed subject matter may, in fact, be an inherent characteristic of the prior art, it possesses the authority to require the applicant to prove that the subject matter shown to be in the prior art does not possess the characteristic relied on. In re Swinehart and sfiligoj, 169 USPQ 226 (C.C.P.A. 1971).
6- Claims 1-20 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Cao et al. (PGPUB No. 2018/0322234) in view of Yamazaki et al. (PGPUB No. 2025/0031415).
As to claims 1/16-17 and 11, Cao teaches a device, and its method of use, for transforming measurement data (Figs. 1-7 and Abstract), the device comprising: a receiver/first device (¶ 2, 4, 19, 27; imaging means with processor 202 or one of its modules in Figs. 1, 3-4) configured to receive first measurement data, the first measurement data including a plurality of target regions of a first semiconductor chip; wherein the step is optically measured on a respective target region of the first semiconductor chip (¶ 2. 5-7, 19, 26-27, 32 for ex.; images of pattern 102/104) on which a chemical mechanical polishing -CMP- process is performed (¶ 20, 26-27), and receive layout data, the layout data including a layout in the first semiconductor chip (Abstract, ¶ 5-7, 19-20); and a processor/second device configured to based on the layout data, generate density data, the density data including an image to which layout density is applied (¶ 45, 47, 54), the layout density indicating a ratio of area occupied by the layout in a unit resolution region (¶ 52; proportionality is considered), input the density data and the first measurement data to an artificial intelligence model (¶ 32, 44-46, 51), and predict, as an output of the artificial intelligence model, second measurement data, the second measurement data including a step height value per target region of a second semiconductor chip (Abstract, ¶ 5-7 ; predict PSGs), the second semiconductor chip comprising the first semiconductor chip and a metal deposited on the first semiconductor chip (¶ 19-23 for ex; during semiconductor printing processes, metal deposition is necessarily involved in terms of electrodes, gates, sources or the like).
Cao does not teach the plurality of target regions presenting a plurality of step height values and each step height value of the plurality of step height values measures a height of the respective target region in a direction perpendicular to the respective target region.
However, Cao discloses measuring different target regions (162/164 in Fig. 1) and wherein the IC layouts 100, and its corresponding manufactured layout 160, are modelized and measured in two and three dimensions, i.e. step height values measured, wherein each step height value of the plurality of step height values measures a height of the respective target region in a direction perpendicular to the respective target region (¶ 25). In addition, in a similar field of endeavor, Yamazaki teaches semiconductor device and its processing devices/methods (Abstract and Figs. 1-58), and wherein measuring and controlling the thickness, height steps, of the layer regions is considered (¶ 245, 255 for ex.).
Therefore, it would have been obvious to one with ordinary skills in the art before the effective filing date of the instant application to use the apparatus and method of Cao in view of Yamazaki’s suggestions so that the plurality of target regions presenting a plurality of step height values and each step height value of the plurality of step height values measures a height of the respective target region in a direction perpendicular to the respective target region, with the advantage of effectively optimizing fast processing of the data filtering, and fast processing of the semiconductor layer properties.
Moreover, Cao teaches:
(claims 2/12/18) wherein the receiver/second device is configured to receive raw data of the first measurement data via the communicator, remove noise from the raw data based on a noise removal algorithm, and input, to the artificial intelligence model, the first measurement data with the noise removed therefrom (¶ 48; 53-54).
As to claims 4, 13/19, Cao teaches device of claims 1, 16 and method of claim 11, wherein the density data includes a plurality of images of a plurality of different layouts in the first semiconductor chip (¶ 24, 26-27, 36, 54).
(claim 5) wherein a size of the image comprised in the density data is greater than or equal to a size of the target region of the first semiconductor chip (Fig. 1).
(claims 6, 7/14, 8/20, 15) wherein the artificial intelligence model comprises a neural network, the neural network including an input layer, a hidden layer, and an output layer; wherein the hidden layer comprises a convolution layer, a pooling layer, a fully connected layer, and a regression layer; (claims 8/15/20) wherein the processor/second device is configured to train the artificial intelligence model with a learning data set based on supervised learning, the learning data set comprising the first measurement data, the density data, and the second measurement data (Abstract, ¶ 5-7, 23, 27, 32, 42).
(claim 10) wherein the processor is configured to optimize a size of a unit resolution region based on a learning result of the artificial intelligence model (¶ 26 for ex.)
As to claim 3, Cao teaches device of claim 2.
Cao does not teach expressly wherein the noise removal algorithm comprises fast Fourier transform (FFT), and wherein the processor is configured to transform a domain of the raw data to a frequency domain of the FFT based on the FFT, remove the noise from the raw data based on reflecting at least one mask in FFT spectrum with respect to the raw data, and transform the frequency domain of the FFT to the domain of the raw data.
However, in a similar field of endeavor, Yamazaki teaches semiconductor device and its processing devices/methods (Abstract and Figs. 1-58) wherein FFT imaging and filtering, i.e. mask, are used to process density images (¶ 463, 465).
Therefore, it would have been obvious to one with ordinary skills in the art before the effective filing date of the instant application to use the apparatus and method of Cao in view of Yamazaki’s suggestions so that the noise removal algorithm comprises fast Fourier transform (FFT), and wherein the processor is configured to transform a domain of the raw data to a frequency domain of the FFT based on the FFT, remove the noise from the raw data based on reflecting at least one mask in FFT spectrum with respect to the raw data, and transform the frequency domain of the FFT to the domain of the raw data, with the advantage of effectively optimizing fast processing of the data filtering.
As to claim 9, Cao teaches device of claim 8.
Cao does not teach expressly wherein the processor is configured to based on the artificial intelligence model learning according to the supervised learning, remove, based on a noise removal algorithm, noise from first raw data of the first measurement data and remove, based on the noise removal algorithm, noise from second raw data of the second measurement data, and set, as the learning data set, the first measurement data with noise removed therefrom, the density data, and the second measurement data with noise removed therefrom, even though it teaches using ANN to remove unwanted data from the images (¶ 32, 48; 53-54).
Moreover, Yamazaki teaches using artificial intelligence with FFT and image filtering on density data, and the measurement data (¶ 463-466, 847-856 for ex.)
Therefore, it would have been obvious to one with ordinary skills in the art before the effective filing date of the instant application to use the apparatus and method of Cao in view of Yamazaki’s suggestions so that the processor is configured to based on the artificial intelligence model learning according to the supervised learning, remove, based on a noise removal algorithm, noise from first raw data of the first measurement data and remove, based on the noise removal algorithm, noise from second raw data of the second measurement data, and set, as the learning data set, the first measurement data with noise removed therefrom, the density data, and the second measurement data with noise removed therefrom, with the advantage of effectively optimizing the processing of the semiconductor layer properties.
Relevant Prior art
US 20230138706 appear to teach also most of the claimed apparatus and its method of use but fails to teach the claimed invention as a whole.
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).
The examiner has pointed out particular references contained in the prior art of record in the body of this action for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. Applicant should consider the entire prior art as applicable as to the limitations of the claims. It is respectfully requested from the applicant, in preparing the response, to consider fully the entire references as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMED AMARA whose telephone number is (571)272-7847. The examiner can normally be reached on Monday-Friday: 9:00-17:00.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tarifur Chowdhury can be reached on (571)272-2287. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Mohamed K AMARA/
Primary Examiner, Art Unit 2877
