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 .
Status of Claims
Claims 1-20 are pending.
Priority
Acknowledgment is made of applicant's claim for foreign priority based on applications filed in Europe on 10/11/21 and 8/18/22. It is noted, however, that applicant has not filed a certified copy of the EP 21202040.8 and EP 22191076.3 applications as required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 4/9/24 and 5/16/25 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: S401 and S407 in Fig. 4. Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claim 2 is objected to because of the following informalities: In line 1, “detecting a fingerprint” should read –detecting the fingerprint–. Appropriate correction is required.
Claim 3 is objected to because of the following informalities: In line 1, “determining correlations” should read –determining the correlations–. Appropriate correction is required.
Claim 4 is objected to because of the following informalities: In line 1, “determining correlations” should read –determining the correlations–. Appropriate correction is required.
Claim 5 is objected to because of the following informalities: In line 1, “determining correlations” should read –determining the correlations–. Appropriate correction is required.
Claim 9 is objected to because of the following informalities: In line 1, “decomposing noise in the data sets” should read –decomposing the noise in the data sets–. Appropriate correction is required.
Claim 12 is objected to because of the following informalities:
In line 2, “a pattern formed in resist on a substrate” should read –the pattern formed in resist on the substrate–.
In line 3, “a pattern that has been transferred” should read –the pattern that has been transferred–.
Appropriate correction is required.
Claim 16 is objected to because of the following informalities: In line 1, “detecting a fingerprint” should read –detecting the fingerprint–. Appropriate correction is required.
Claim 17 is objected to because of the following informalities: In line 1, “determining correlations” should read –determining the correlations–. Appropriate correction is required.
Claim 18 is objected to because of the following informalities: In line 1, “determining correlations” should read –determining the correlations–. Appropriate correction is required.
Claim 19 is objected to because of the following informalities: In line 1, “determining correlations” should read –determining the correlations–. Appropriate correction is required.
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 claims recite methods, a computer program product, and a system for determining offsets. With respect to the analysis of claim 1 (claims 14 and 15 are similar), and claim 13:
Step 1:
With regard to Step 1, claims 1 and 13 are directed to a method; and therefore, the claims are directed to one of the statutory categories of inventions.
Step 2A, Prong One:
With regard to Step 2A, Prong One, the following limitations in claim 1 (and similarly claims 14 and 15) as drafted recite an abstract idea: “detecting a fingerprint of the mask pattern in noise of the data sets; and determining offset based on the fingerprint of the mask pattern”. The limitations recite an abstract idea, such as a process that, under its broadest reasonable interpretation, covers performance of the limitation manually or in the mind by a human. That is, a person can identify/detect the features of the mask pattern (i.e., reference template), separating the pattern from the background/noise. A person can also determine how far the actual printed pattern shifted from the mask pattern. These are concepts that fall under the grouping of abstract idea mental processes, i.e., a concept performed in the human mind, evaluation, judgment, and/or opinion of a human.
With regard to Step 2A, Prong One, the following limitations in claim 13 as drafted recite an abstract idea: “extracting a contour of a line in each of the plurality of SEM images to obtain a plurality of line contours; determining an initial set of offsets for each of the line contours; calculating a mean contour based on the line contours and the initial set of offsets; and iteratively calculating an improved set of offsets that maximises a correlation between each of the contour lines and the mean contour and updating the mean contour”. The limitations recite mathematical calculations and an abstract idea, such as a process that, under its broadest reasonable interpretation, covers performance of the limitation manually or in the mind by a human. That is, a person can identify/extract the contour line of the feature in the image, determine whether there is a shift/misalignment of the contour line, calculate an average contour line/determine which line is the best estimate, determine the shift/offset so that it matches the average contour line, and update the average contour line. These are concepts that fall under the grouping of abstract idea mathematical calculations and mental processes, i.e., a concept performed in the human mind, evaluation, judgment, and/or opinion of a human.
Step 2A, Prong Two:
The 2019 PEG defines the phrase “integration into a practical application” to require an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception. In the instant case, there are no additional steps/elements/limitations in the claims, with the exception of the following in claim 13 (method claim), claim 14 (computer program product claim), and claim 15 (system claim): “using a scanning electron microscope to obtain a plurality of SEM images by scanning a plurality of copies of a predetermined pattern in one or more samples” in claim 13, “non-transitory computer readable medium” and “computer or controller of a scanning electron microscope” in claim 14, and “scanning electron microscope (SEM) configured to scan with an electron beam and generate an image; and a non-transitory machine-readable medium storing instructions which, when executed by a processor, cause the processor in co-operation with the SEM to perform operations” in claim 15. The scanning electron microscope limitation is mere data/image gathering. The non-transitory machine-readable medium, processor, and computer/controller are generic computer components. These are regarded as adding routine and conventional elements to perform the judicial exception, and do not apply it into a practical application. Accordingly, the above-mentioned additional elements/limitations do not integrate the abstract idea into a practical application; and therefore, the claims recite an abstract idea.
Step 2B:
Because the claims fail under Step 2A, the claims are further evaluated under Step 2B. The claims herein do not include additional elements that are sufficient to amount to significantly more than the judicial exception, because as discussed above with respect to integration of the abstract idea into practical application, the additional elements/limitations to perform the steps, amount to no more than insignificant routine and conventional elements. Mere instructions to apply an exception using generic components cannot provide an inventive concept. Therefore, claims 1, 13, 14, and 15 are not patent eligible.
Furthermore, with regard to claims 2-12 and 16-20 when viewed individually, these additional steps, under their broadest reasonable interpretation, provide extra-solution activities to cover performance of the limitations as an abstract idea, and do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Accordingly, they are not patent eligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-2, 5-6, 10, 14, 16, and 19-20 are rejected under 35 U.S.C. 102(a)(1) as being anticpated by Kusnadi et al. (US 2011/0202898 A1, hereinafter “Kusnadi”).
Regarding claim 1, Kusnadi teaches, A method of determining offsets between a plurality of data sets, each data set representing a sampling area of a pattern formed on a sample, wherein each sampling area derives from a predetermined portion of a mask pattern, the method comprising (Paras. 0010-0012; Para. 0021: the invention relates to contour-based model calibration and alignment of measurement contours with simulation contours. The measure contours are derived using scanning electron microscopy (SEM) and the simulation contours are calculated contours of the printed layout features derived based on a model. Contour point errors are measured between the measurement contours and the simulation contours and alignment parameters are output; Paras. 0022-0024; Para. 0038: “During a photolithographic process, however, optical effects will prevent the shapes defined by the mask from being faithfully imaged onto the substrate. Diffractive effects, for example, may distort the image produced by a mask. Moreover, these distortions become more pronounced as the images produced by the mask become smaller relative to the wavelength of radiation used in the photolithographic process…Additionally, the image created by employing the mask in a photo lithographic process is often referred to as the printed image”; Paras. 0040-0041):
detecting a fingerprint of the mask pattern in noise of the data sets (Para. 0010; Para. 0011: “As light illuminates the mask, the transmitted light diffracts at different angles in different regions of the mask. These effects often result in defects where the intended image is not accurately “printed onto the substrate during the photolithographic process, creating flaws in the manufactured device”; Para. 0038: “During a photolithographic process, however, optical effects will prevent the shapes defined by the mask from being faithfully imaged onto the substrate. Diffractive effects, for example, may distort the image produced by a mask. Moreover, these distortions become more pronounced as the images produced by the mask become smaller relative to the wavelength of radiation used in the photolithographic process…Additionally, the image created by employing the mask in a photo lithographic process is often referred to as the printed image”; Note: the Examiner interprets the diffractive effects as noise, and the distortions and defects in the image as the fingerprint);
and determining offsets based on the fingerprint of the mask pattern (Para. 0011: “As light illuminates the mask, the transmitted light diffracts at different angles in different regions of the mask. These effects often result in defects where the intended image is not accurately “printed onto the substrate during the photolithographic process, creating flaws in the manufactured device”; Para. 0038: “During a photolithographic process, however, optical effects will prevent the shapes defined by the mask from being faithfully imaged onto the substrate. Diffractive effects, for example, may distort the image produced by a mask. Moreover, these distortions become more pronounced as the images produced by the mask become smaller relative to the wavelength of radiation used in the photolithographic process…Additionally, the image created by employing the mask in a photo lithographic process is often referred to as the printed image”; Para. 0021: the invention relates to contour-based model calibration and alignment of measurement contours with simulation contours. The measure contours are derived using scanning electron microscopy (SEM) and the simulation contours are calculated contours of the printed layout features derived based on a model. Contour point errors are measured between the measurement contours and the simulation contours and alignment parameters are output; Paras. 0022-0024; As shown in Paras. 0040-0043, distances between the simulated printed image and the target image are calculated (i.e., edge displacement error), and steps are repeated until the simulated image is sufficiently similar to the target image; Note: the Examiner interprets errors (i.e., contour point errors and edge displacement errors) as offsets).
Regarding claim 2, Kusnadi teaches the limitations as explained above in claim 1.
Kusnadi further teaches, The method according to claim 1 (see claim 1 above) wherein detecting a fingerprint of the mask pattern comprises determining correlations between the data sets for different trial offset values (Para. 0011: “As light illuminates the mask, the transmitted light diffracts at different angles in different regions of the mask. These effects often result in defects where the intended image is not accurately “printed onto the substrate during the photolithographic process, creating flaws in the manufactured device”; Para. 0038: “During a photolithographic process, however, optical effects will prevent the shapes defined by the mask from being faithfully imaged onto the substrate. Diffractive effects, for example, may distort the image produced by a mask. Moreover, these distortions become more pronounced as the images produced by the mask become smaller relative to the wavelength of radiation used in the photolithographic process…Additionally, the image created by employing the mask in a photo lithographic process is often referred to as the printed image”; Para. 0021: the invention relates to contour-based model calibration and alignment of measurement contours with simulation contours. The measure contours are derived using scanning electron microscopy (SEM) and the simulation contours are calculated contours of the printed layout features derived based on a model. Contour point errors are measured between the measurement contours and the simulation contours and alignment parameters are output; As shown in Paras. 0022-0024, the fitness of the model is determined in which alignment of the measurement contours with the simulation contours is adjusted according to the values of alignment parameters and new values of the alignment parameters are determined; As shown in Paras. 0040-0043, distances between the simulated printed image and the target image are calculated (i.e., edge displacement error), and steps are repeated until the simulated image is sufficiently similar to the target image; Paras. 0044-0057: contour alignment process; Note: the Examiner interprets the fitness of the model based on contour difference and the comparison of the simulated image to the target image as correlations, and the alignment parameters as trial offset values).
Regarding claim 5, Kusnadi teaches the limitations as explained above in claim 2.
Kusnadi further teaches, The method according to claim 2 (see claim 2 above) wherein determining correlations is an iterative process (Para. 0021: the invention relates to contour-based model calibration and alignment of measurement contours with simulation contours. The measure contours are derived using scanning electron microscopy (SEM) and the simulation contours are calculated contours of the printed layout features derived based on a model. Contour point errors are measured between the measurement contours and the simulation contours and alignment parameters are output; As shown in Paras. 0022-0024, the fitness of the model is determined in which alignment of the measurement contours with the simulation contours is adjusted according to the values of alignment parameters and new values of the alignment parameters are determined; As shown in Paras. 0040-0043, distances between the simulated printed image and the target image are calculated (i.e., edge displacement error), and comparing the simulated image to the target image is repeated a number of times, and steps are repeated until the simulated image is sufficiently similar to the target image; Paras. 0044-0057: contour alignment process in which the fitness is recalculated each time misalignment occurs and fitness is calculated for each iteration; Note: the Examiner interprets repeating of the comparison and recalculating/calculating the fitness for each iteration as an iterative process).
Regarding claim 6, Kusnadi teaches the limitations as explained above in claim 1.
Kusnadi further teaches, The method according to claim 1 (see claim 1 above) wherein the fingerprint of the mask pattern results from noise in the mask pattern (Para. 0010; Para. 0011: “As light illuminates the mask, the transmitted light diffracts at different angles in different regions of the mask. These effects often result in defects where the intended image is not accurately “printed onto the substrate during the photolithographic process, creating flaws in the manufactured device”; Para. 0038: “During a photolithographic process, however, optical effects will prevent the shapes defined by the mask from being faithfully imaged onto the substrate. Diffractive effects, for example, may distort the image produced by a mask. Moreover, these distortions become more pronounced as the images produced by the mask become smaller relative to the wavelength of radiation used in the photolithographic process…Additionally, the image created by employing the mask in a photo lithographic process is often referred to as the printed image”; Note: the Examiner interprets the diffractive effects as noise, and the distortions and defects in the image as the fingerprint; Note: As shown in Paras. 0011 and 0038, the distortions and defects (i.e., fingerprints) result from the diffractive effects (i.e., noise)).
Regarding claim 10, Kusnadi teaches the limitations as explained above in claim 1.
Kusnadi further teaches, The method according to claim 1 (see claim 1 above) wherein at least one of the data sets represents a pattern formed in resist on a substrate or a pattern that has been transferred into the substrate (Para. 0010: “the image created on the substrate, by employing the mask in the photolithographic process is referred to as the printed image”; Para. 0021: “The measurement contours are measured contours of printed layout features on a physical wafer”; Note: the Examiner selects the pattern transferred into the substrate limitation. The Examiner interprets printing on the substrate as transferring into the substrate).
Regarding claim 14, Kusnadi teaches, A computer program product comprising a non-transitory computer readable medium having instructions recorded thereon, the instructions, when executed by a computer or a controller of a scanning electron microscope, implementing a method comprising (Claim 20: “A processor-readable medium storing processor-executable instructions for causing one or more processors to perform a method of model calibration”; Para. 0015: “computer processing techniques”; Para. 0018: “Contour based calibration uses contours extracted from top-down scanning electron microscope (SEM) images of printed features on a physical wafer”; Para. 0021: “The measurement contours are measured contours of printed layout features on a physical wafer. The measured contours may be derived using scanning electron microcopy (SEM)”):
detecting a fingerprint of a mask pattern in noise of data sets (Para. 0010; Para. 0011: “As light illuminates the mask, the transmitted light diffracts at different angles in different regions of the mask. These effects often result in defects where the intended image is not accurately “printed onto the substrate during the photolithographic process, creating flaws in the manufactured device”; Para. 0038: “During a photolithographic process, however, optical effects will prevent the shapes defined by the mask from being faithfully imaged onto the substrate. Diffractive effects, for example, may distort the image produced by a mask. Moreover, these distortions become more pronounced as the images produced by the mask become smaller relative to the wavelength of radiation used in the photolithographic process…Additionally, the image created by employing the mask in a photo lithographic process is often referred to as the printed image”; Note: the Examiner interprets the diffractive effects as noise, and the distortions and defects in the image as the fingerprint);
and determining offsets based on the fingerprint of the mask pattern (Para. 0011: “As light illuminates the mask, the transmitted light diffracts at different angles in different regions of the mask. These effects often result in defects where the intended image is not accurately “printed onto the substrate during the photolithographic process, creating flaws in the manufactured device”; Para. 0038: “During a photolithographic process, however, optical effects will prevent the shapes defined by the mask from being faithfully imaged onto the substrate. Diffractive effects, for example, may distort the image produced by a mask. Moreover, these distortions become more pronounced as the images produced by the mask become smaller relative to the wavelength of radiation used in the photolithographic process…Additionally, the image created by employing the mask in a photo lithographic process is often referred to as the printed image”; Para. 0021: the invention relates to contour-based model calibration and alignment of measurement contours with simulation contours. The measure contours are derived using scanning electron microscopy (SEM) and the simulation contours are calculated contours of the printed layout features derived based on a model. Contour point errors are measured between the measurement contours and the simulation contours and alignment parameters are output; Paras. 0022-0024; As shown in Paras. 0040-0043, distances between the simulated printed image and the target image are calculated (i.e., edge displacement error), and steps are repeated until the simulated image is sufficiently similar to the target image; Note: the Examiner interprets errors (i.e., contour point errors and edge displacement errors) as offsets).
Regarding claim 16, Kusnadi teaches the limitations as explained above in claim 14.
Kusnadi further teaches, The computer program product according to claim 14 (see claim 14 above) wherein detecting a fingerprint of the mask pattern comprises determining correlations between the data sets for different trial offset values (Para. 0011: “As light illuminates the mask, the transmitted light diffracts at different angles in different regions of the mask. These effects often result in defects where the intended image is not accurately “printed onto the substrate during the photolithographic process, creating flaws in the manufactured device”; Para. 0038: “During a photolithographic process, however, optical effects will prevent the shapes defined by the mask from being faithfully imaged onto the substrate. Diffractive effects, for example, may distort the image produced by a mask. Moreover, these distortions become more pronounced as the images produced by the mask become smaller relative to the wavelength of radiation used in the photolithographic process…Additionally, the image created by employing the mask in a photo lithographic process is often referred to as the printed image”; Para. 0021: the invention relates to contour-based model calibration and alignment of measurement contours with simulation contours. The measure contours are derived using scanning electron microscopy (SEM) and the simulation contours are calculated contours of the printed layout features derived based on a model. Contour point errors are measured between the measurement contours and the simulation contours and alignment parameters are output; As shown in Paras. 0022-0024, the fitness of the model is determined in which alignment of the measurement contours with the simulation contours is adjusted according to the values of alignment parameters and new values of the alignment parameters are determined; As shown in Paras. 0040-0043, distances between the simulated printed image and the target image are calculated (i.e., edge displacement error), and steps are repeated until the simulated image is sufficiently similar to the target image; Paras. 0044-0057: contour alignment process; Note: the Examiner interprets the fitness of the model based on contour difference and the comparison of the simulated image to the target image as correlations, and the alignment parameters as trial offset values).
Regarding claim 19, Kusnadi teaches the limitations as explained above in claim 16.
Kusnadi further teaches, The computer program product according to claim 16 (see claim 16 above) wherein determining correlations is an iterative process (Para. 0021: the invention relates to contour-based model calibration and alignment of measurement contours with simulation contours. The measure contours are derived using scanning electron microscopy (SEM) and the simulation contours are calculated contours of the printed layout features derived based on a model. Contour point errors are measured between the measurement contours and the simulation contours and alignment parameters are output; As shown in Paras. 0022-0024, the fitness of the model is determined in which alignment of the measurement contours with the simulation contours is adjusted according to the values of alignment parameters and new values of the alignment parameters are determined; As shown in Paras. 0040-0043, distances between the simulated printed image and the target image are calculated (i.e., edge displacement error), and comparing the simulated image to the target image is repeated a number of times, and steps are repeated until the simulated image is sufficiently similar to the target image; Paras. 0044-0057: contour alignment process in which the fitness is recalculated each time misalignment occurs and fitness is calculated for each iteration; Note: the Examiner interprets repeating of the comparison and recalculating/calculating the fitness for each iteration as an iterative process).
Regarding claim 20, Kusnadi teaches the limitations as explained above in claim 14.
Kusnadi further teaches, The computer program product according to claim 14 (see claim 14 above) wherein the fingerprint of the mask pattern results from noise in the mask pattern (Para. 0010; Para. 0011: “As light illuminates the mask, the transmitted light diffracts at different angles in different regions of the mask. These effects often result in defects where the intended image is not accurately “printed onto the substrate during the photolithographic process, creating flaws in the manufactured device”; Para. 0038: “During a photolithographic process, however, optical effects will prevent the shapes defined by the mask from being faithfully imaged onto the substrate. Diffractive effects, for example, may distort the image produced by a mask. Moreover, these distortions become more pronounced as the images produced by the mask become smaller relative to the wavelength of radiation used in the photolithographic process…Additionally, the image created by employing the mask in a photo lithographic process is often referred to as the printed image”; Note: the Examiner interprets the diffractive effects as noise, and the distortions and defects in the image as the fingerprint; Note: As shown in Paras. 0011 and 0038, the distortions and defects (i.e., fingerprints) result from the diffractive effects (i.e., noise)).
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.
Claims 4 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over by Kusnadi et al. (US 2011/0202898 A1, hereinafter “Kusnadi”) in view of Dai et al. (US 2004/0174437 A1, hereinafter “Dai”).
Regarding claim 4, Kusnadi teaches the limitations as explained above in claim 2.
Kusnadi does not expressly disclose the following limitation: wherein determining correlations comprises using a fast Fourier transform.
However, Dai teaches, wherein determining correlations comprises using a fast Fourier transform (Paras. 0009-0010: inverse of the FFT of the first image and the second image are calculated; Para. 0012: “The method further includes generating image registration data by calculating the inverse of the complex conjugate product of the FFT of the first image and the FFT of the second image. The method further includes finding the correlation peak by calculating the magnitude of complex correlation and searching for the maximum on the correlation magnitude map. The distance between the peak and the image center is found to be the translation or shift between the image pair”; Paras. 0026-0032).
It would have been obvious before the effective filing date of the claimed invention, to one of ordinary skill in the art, to combine determining correlations using a fast Fourier transform (FFT) as taught by Dai with the method of Kusnadi in order to compare images to identify defects, differences, or irregularities (Dai, Para. 0002). Therefore, one of ordinary skill in the art would be capable to have combined the elements as claimed by known methods and that in combination, each element merely performs the same function as it does separately. It is for at least the aforementioned that the Examiner has reached a conclusion of obviousness with respect to claim 4.
Regarding claim 18, Kusnadi teaches the limitations as explained above in claim 16.
Kusnadi does not expressly disclose the following limitation: wherein determining correlations comprises using a fast Fourier transform.
However, Dai teaches, wherein determining correlations comprises using a fast Fourier transform (Paras. 0009-0010: inverse of the FFT of the first image and the second image are calculated; Para. 0012: “The method further includes generating image registration data by calculating the inverse of the complex conjugate product of the FFT of the first image and the FFT of the second image. The method further includes finding the correlation peak by calculating the magnitude of complex correlation and searching for the maximum on the correlation magnitude map. The distance between the peak and the image center is found to be the translation or shift between the image pair”; Paras. 0026-0032).
It would have been obvious before the effective filing date of the claimed invention, to one of ordinary skill in the art, to combine determining correlations using a fast Fourier transform (FFT) as taught by Dai with the method of Kusnadi in order to compare images to identify defects, differences, or irregularities (Dai, Para. 0002). Therefore, one of ordinary skill in the art would be capable to have combined the elements as claimed by known methods and that in combination, each element merely performs the same function as it does separately. It is for at least the aforementioned that the Examiner has reached a conclusion of obviousness with respect to claim 18.
Claims 7-9 are rejected under 35 U.S.C. 103 as being unpatentable over by Kusnadi et al. (US 2011/0202898 A1, hereinafter “Kusnadi”) in view of “Roughness Decomposition: An on-Wafer Methodology to Discriminate Mask, Metrology, and Shot Noise Contributions” by Lorusso et al. (hereinafter “Lorusso”).
Regarding claim 7, Kusnadi teaches the limitations as explained above in claim 1.
Kusnadi does not expressly disclose the following limitation: wherein the mask pattern comprises a series of continuous parallel lines extending across the sampling areas.
However, Lorusso teaches, wherein the mask pattern comprises a series of continuous parallel lines extending across the sampling areas (As shown in Fig. 3, the SEM images at mask level and wafer level contain multiple parallel lines:
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).
It would have been obvious before the effective filing date of the claimed invention, to one of ordinary skill in the art, to combine a mask pattern having a series of continuous parallel lines as taught by Lorusso with the method of Kusnadi in order to calculate line width roughness composition (LWR) and understand the impact of mask and scanner contributions on wafer prints (Lorusso, Pg. 2). Therefore, one of ordinary skill in the art would be capable to have combined the elements as claimed by known methods and that in combination, each element merely performs the same function as it does separately. It is for at least the aforementioned that the Examiner has reached a conclusion of obviousness with respect to claim 7.
Regarding claim 8, the combination of Kusnadi and Lorusso teaches the limitations as explained above in claim 7.
The combination of Kusnadi and Lorusso further teaches, The method according to claim 7 (see claim 7 above) wherein the data sets represent contours of the continuous parallel lines in the sampling areas (Lorusso, As shown in Pg. 4, wafer data is obtained and is illustrated in the right image of Fig. 3; Lorusso: As shown in Fig. 3, the SEM image at wafer level contains multiple straight parallel lines:
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; Note: the Examiner interprets the straight parallel lines as contours).
The proposed combination as well as the motivation for combining the Kusnadi and Lorusso references presented in the rejection of claim 7 apply to claim 8 and are incorporated herein by reference. Thus, the method recited in claim 8 is met by Kusnadi and Lorusso.
Regarding claim 9, Kusnadi teaches the limitations as explained above in claim 1.
Kusnadi does not expressly disclose the following limitation: further comprising decomposing noise in the data sets based on the offsets.
However, Lorusso teaches, further comprising decomposing noise in the data sets based on the offsets (Abstract; Pg. 1-2, 1. Introduction: “decomposition is a methodology allowing, through a smart sampling of the wafer data and a tailored mathematical approach, to identify which one of the contributors to the stochastics is more relevant, hence enabling to correct for it”; Pg. 3, 2.3 Decomposition Results; Fig. 2 illustrates LWR decomposition results in which the main contribution comes from metrology, and shot noise contribution is quite large, while the mask contribution to on-wafer roughness is marginal; Pg. 9, 3. Conclusion: “we demonstrated the importance of analyzing carefully aligned averaged wafer images”).
It would have been obvious before the effective filing date of the claimed invention, to one of ordinary skill in the art, to combine decomposing noise based on offsets as taught by Lorusso with the method of Kusnadi in order to quantify the influences of the various contributor to wafer roughness (Lorusso, Pg. 9). Therefore, one of ordinary skill in the art would be capable to have combined the elements as claimed by known methods and that in combination, each element merely performs the same function as it does separately. It is for at least the aforementioned that the Examiner has reached a conclusion of obviousness with respect to claim 9.
Claims 11-12 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over by Kusnadi et al. (US 2011/0202898 A1, hereinafter “Kusnadi”) in view of Huang et al. (US 2020/0151600 A1, hereinafter “Huang”).
Regarding claim 11, Kusnadi teaches the limitations as explained above in claim 1.
Kusnadi further teaches, The method according to claim 1 (see claim 1 above) wherein another of the data sets represents a pattern that has been transferred into the substrate (Para. 0010: “the image created on the substrate, by employing the mask in the photolithographic process is referred to as the printed image”; Para. 0021: “The measurement contours are measured contours of printed layout features on a physical wafer”; Note: the Examiner interprets printing on the substrate as transferring into the substrate).
Kusnadi does not expressly disclose the following limitation: at least one of the data sets represents a pattern formed in resist on a substrate.
However, Huang teaches, at least one of the data sets represents a pattern formed in resist on a substrate (Para. 0003: a pattern is imaged onto a target portion on a substrate that has a layer of radiation-sensitive material (resist); Para. 0004; Para. 0107: “A defect can be in a resist image, an optical image or an etch image (i.e., a pattern transferred to a layer of the substrate by etching using the resist thereon as a mask)”; As shown in Paras. 0117-0118, there is a resist layer on a substrate and there is one or more pos-resist development processes (i.e., etch)).
It would have been obvious before the effective filing date of the claimed invention, to one of ordinary skill in the art, to combine forming a pattern in resist on a substrate as taught by Huang with the method of Kusnadi in order to predict defects in a device manufacturing process (Huang, Para. 0107). Therefore, one of ordinary skill in the art would be capable to have combined the elements as claimed by known methods and that in combination, each element merely performs the same function as it does separately. It is for at least the aforementioned that the Examiner has reached a conclusion of obviousness with respect to claim 11.
Regarding claim 12, the combination of Kusnadi and Huang teaches the limitations as explained above in claim 11.
The combination of Kusnadi and Huang further teaches, The method according to claim 11 (see claim 11 above) further comprising determining a characteristic of a pattern transfer process based on the data sets that represent a pattern formed in resist on a substrate and the data sets that represent a pattern that has been transferred into the substrate and the offsets (Huang, Para. 0098: “In order that a substrate that is exposed by the lithographic apparatus is exposed correctly and consistently or in order to monitor a part of the patterning process (e.g. , a device manufacturing process) that includes at least one pattern transfer step (e.g., an optical lithography step), it is desirable to inspect a substrate or other object to measure or determine one or more properties such as alignment, overlay (which can be, for example, between structures in overlying layers or between structures in a same layer that have been provided separately to the layer by, for example, a double patterning process), line thickness, critical dimension (CD), focus offset, a material property , etc.”; Huang, Para. 0003: a pattern is imaged onto a target portion on a substrate that has a layer of radiation-sensitive material (resist); Huang, Para. 0118: “In an embodiment, the resist image can be used an input to a post-pattern transfer process model 39. The post-pattern transfer process model 39 defines performance of one or more post-resist development processes (e.g., etch, CMP, etc.) and can produce a post-etch image 40. That is, an etch image 40 can be simulated from the resist image 36 using a post-pattern transfer process model 39”; Huang, Para. 0120: “Simulation of the patterning process can, for example, predict contours, CDs, edge placement (e.g., edge placement error), pattern shift, etc. in the aerial, resist and/or etch image. That is, the aerial image 34, the resist image 36 or the etch image 40 may be used to determine a characteristic (e.g., the existence, location, type, shape, etc. of) of a pattern. Thus, the objective of the simulation is to accurately predict, for example, edge placement, and/or contours, and/or pattern shift, and/or aerial image intensity slope, and/or CD, etc. of the printed pattern. These values can be compared against an intended design to, e.g., correct the patterning process, identify where a defect is predicted to occur, etc.”; Huang: Para. 0004; Huang, Para. 0107: “A defect can be in a resist image, an optical image or an etch image (i.e., a pattern transferred to a layer of the substrate by etching using the resist thereon as a mask)”; Huang: As shown in Paras. 0117-0118, there is a resist layer on a substrate and there is one or more pos-resist development processes (i.e., etch); Kusnadi, Para. 0010: “the image created on the substrate, by employing the mask in the photolithographic process is referred to as the printed image”; Kusnadi, Paras. 0021-0024; Kusnadi: As shown in Paras. 0040-0043, distances between the simulated printed image and the target image are calculated (i.e., edge displacement error), and steps are repeated until the simulated image is sufficiently similar to the target image).
The proposed combination as well as the motivation for combining the Kusnadi and Huang references presented in the rejection of claim 11 apply to claim 12 and are incorporated herein by reference. Thus, the method recited in claim 12 is met by Kusnadi and Huang.
Regarding claim 15, Kusnadi teaches, A system comprising (Claim 14: “A system comprising one or more processors, the one or more processors programmed to perform a method of model calibration”):
a scanning electron microscope (SEM) configured to scan (Para. 0018: “Contour based calibration uses contours extracted from top-down scanning electron microscope (SEM) images of printed features on a physical wafer”; Para. 0021: “The measurement contours are measured contours of printed layout features on a physical wafer. The measured contours may be derived using scanning electron microcopy (SEM)”);
and a non-transitory machine-readable medium storing instructions which, when executed by a processor, cause the processor (Claim 20: “A processor-readable medium storing processor-executable instructions for causing one or more processors to perform a method of model calibration”; Para. 0015: “computer processing techniques”; Para. 0018: “Contour based calibration uses contours extracted from top-down scanning electron microscope (SEM) images of printed features on a physical wafer”):
detecting a fingerprint of a mask pattern in noise of data sets (Para. 0010; Para. 0011: “As light illuminates the mask, the transmitted light diffracts at different angles in different regions of the mask. These effects often result in defects where the intended image is not accurately “printed onto the substrate during the photolithographic process, creating flaws in the manufactured device”; Para. 0038: “During a photolithographic process, however, optical effects will prevent the shapes defined by the mask from being faithfully imaged onto the substrate. Diffractive effects, for example, may distort the image produced by a mask. Moreover, these distortions become more pronounced as the images produced by the mask become smaller relative to the wavelength of radiation used in the photolithographic process…Additionally, the image created by employing the mask in a photo lithographic process is often referred to as the printed image”; Note: the Examiner interprets the diffractive effects as noise, and the distortions and defects in the image as the fingerprint);
and determining offsets based on the fingerprint of the mask pattern (Para. 0011: “As light illuminates the mask, the transmitted light diffracts at different angles in different regions of the mask. These effects often result in defects where the intended image is not accurately “printed onto the substrate during the photolithographic process, creating flaws in the manufactured device”; Para. 0038: “During a photolithographic process, however, optical effects will prevent the shapes defined by the mask from being faithfully imaged onto the substrate. Diffractive effects, for example, may distort the image produced by a mask. Moreover, these distortions become more pronounced as the images produced by the mask become smaller relative to the wavelength of radiation used in the photolithographic process…Additionally, the image created by employing the mask in a photo lithographic process is often referred to as the printed image”; Para. 0021: the invention relates to contour-based model calibration and alignment of measurement contours with simulation contours. The measure contours are derived using scanning electron microscopy (SEM) and the simulation contours are calculated contours of the printed layout features derived based on a model. Contour point errors are measured between the measurement contours and the simulation contours and alignment parameters are output; Paras. 0022-0024; As shown in Paras. 0040-0043, distances between the simulated printed image and the target image are calculated (i.e., edge displacement error), and steps are repeated until the simulated image is sufficiently similar to the target image; Note: the Examiner interprets errors (i.e., contour point errors and edge displacement errors) as offsets).
Kusnadi does not expressly disclose the following limitations: configured to scan with an electron beam; the processor in co-operation with the SEM.
However, Huang teaches, configured to scan with an electron beam (Para. 0056: “FIG. 12 schematically depicts an embodiment of a scanning electron microscope (SEM) according to an embodiment”; Fig. 12: an electron beam 202 is emitted from electron source 201 of the electron beam inspection apparatus 200; Paras. 0186-0188);
the processor in co-operation with the SEM (Para. 0056: “FIG. 12 schematically depicts an embodiment of a scanning electron microscope (SEM) according to an embodiment”; Fig. 12: a processor 304 is connected to elements of the scanning electron microscope (SEM); Paras. 0186-0187; Para. 0188: “A signal detected by secondary electron detector 207 is converted to a digital signal by an analog/digital (ND) converter 208, and the digital signal is sent to an image processing system 300…In an embodiment , the processing unit 304 is configured or programmed to cause execution of a method described herein”).
It would have been obvious before the effective filing date of the claimed invention, to one of ordinary skill in the art, to combine an SEM having an electron beam to scan and a processor being in co-operation with the SEM as taught by Huang with the system of Kusnadi in order to improve prediction of out of specification physical items, such as out of specification pattern instances on a substrate produced by a device manufacturing process (Huang, Paras. 0002 and 0006). Therefore, one of ordinary skill in the art would be capable to have combined the elements as claimed by known methods and that in combination, each element merely performs the same function as it does separately. It is for at least the aforementioned that the Examiner has reached a conclusion of obviousness with respect to claim 15.
Allowable Subject Matter
Claims 3 and 17 are not rejected under prior art and would be allowable if rewritten to overcome the rejection under 35 U.S.C. 101 set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Claim 13 is not reject under prior art and would be allowable if rewritten or amended to overcome the rejection under 35 U.S.C. 101 set forth in this Office action.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Yamaguchi et al. (US 2006/0097158 A1)
Chen et al. (US 2014/0106474 A1)
Weisbuch (US 2015/0146966 A1)
Ye et al. (US 7,694,267 B1)
Contact Information
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/Daniella M. DiGuglielmo/Examiner, Art Unit 2666
/EMILY C TERRELL/Supervisory Patent Examiner, Art Unit 2666