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 § 102
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 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 2, 4, 5, 7-15, and 17-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Tirapu-Azpiroz et al (8,458,626).
Tirapu-Azpiroz et al disclose a method for calibrating a sub-lithographic assist feature (SRAF) printing model known to be a pixel-based target image printing technique to deliver light to the target patterns and determine pattern variations prior to improve the resolution pf the final printed lithographic pattern, wherein the method includes the following steps:
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In the reference, the first method step involves obtaining the plurality of images of a patterned resist layer using SRAFs from a lithographic mask pattern (instant (i); column 17, lines 4-48, which is a mask image or aerial image, column 4, line 48 to column 5, line 60 instant claim 4 step (1)), calibrating that SRAF model against the images, an obtaining the range of threshold values on the photomask corresponding to the various SRAF configurations (variance data of the pixels, instant (ii); column 17, line 49 to column 18, line 25). The calibrated SRAF printing model determines a single SRAF printing image (determining the model based on the variance date; column 17, lines 30-48, column 21, line 43 to column 22, line 19), and the SRAF model to the printed from the variance data is computed and stored by a lithography simulator program (column 6, line 26 to column 7, line 21), and the variance data from the program determines the printing and the modified SRAFs to eliminate or reduce the SRAF printing (column 23, lines 14-30), equivalent to the last step of the claimed method as set forth by the instant claims 1 and 4.
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The reference further teaches that the images of the patterned resist layer are generated by Sem and data gathered is performed by metrology, wherein the SEM is the metrology tool (column 9, line 61 to column 10, line 27, column 17, lines 30-48; instant claim 2). As discussed above, the values of the parameters are determined and adjusted based upon the threshold of the variance data (column 17, lines 4-48, column 23, lines 17-30; instant claims 4 and 5). Furthermore, as discussed above, the method includes the steps as claimed wherein the variance data is determined as compared to the pattern to determine assist features that are likely to be printed (instant claim 8), identifying the model images to determine the variance data associated with the intensity values and calibrating the variance and resist values to meet the desired threshold and determine with SRAF features are likely to be printed in different areas (figures 4 and 5, column 20, lines 35-64, column 21, line 43 to column 22, line 31, column 23, lines 4-9; instant claims 9-11, 13,and 14).
The reference further teaches that the model (as discussed above) is used adjust the assist features of the OPC or mask pattern to reduce the assist features from printing (from the mask or optical model, column 3, lines 39-65, column 4, line 6 to column 5, line 33, column 22, line 4 to column 23, line 22; instant claim 12). The reference further teaches that the model preferably includes a polynomial with various terms, each containing a coefficient multiplying a basis function which describes a characteristic, and the coefficient values of the polynomial are calibrated in an iterative calibration process to provide the smallest difference between the measured and simulated values and the photoresist model is expressed as the polynomial using the optimized coefficients (column 15, line 65 to column 51; instant claim 7, third option).
The invention as claimed by claim 15 is drawn to the computer-readable media which comprises instructions to be executed by one or more processors to perform the method as claim by claims 1, 4, and 8-10. The reference clearly discusses the program and data for the desired pattern and computing the mask shapes and calibrate corrected patterns, and given the teachings of the references as discussed above for the method, the lithographic printing program would include the steps to be executed to prepare the resist including the methods as claimed (throughout, wherein a design and process is input into the patterning device to execute the described steps; instant claims 15 and 17-20).
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.
Claim(s) 3, 6, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tirapu-Azpiroz et al in view of Su et al (2020/0356011).
Tirapu-Azpiroz et al has been discussed above. The reference teaches a method of using assist features to determine the variance data, however the reference fails to specifically that the variance data is represented as another pixelated image, each pixel assigned a variance value of grey scale values of each pixel of the plurality of images, or wherein the model parameters is based on a gradient of the difference between the outputted variance map and inputted variance. The references teaches that modifications may be made to the process steps.
Su et al disclose a process of training a machine learning model configured to predict the optical proximity corrections prior to be printed on a substrate, wherein the process includes placing assist features by the machine. The assist features are pixelated ([0074]-[0076], [0082], [0084]), and the pixelated image characteristics used to align the assist features includes gray-scale images as required by the instant claims 3 and 16. Additionally, the parameters are adjusted using an iterative process using a gradient map of the patterning device pattern to calculate and use the variance data from the gradient map to guide the application and place the assist features as required by the instant claim 6 ([0086]).
Given the teachings of the references, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the instant invention to perform the method of Tirapu-Azpiroz et al, choosing as the images, using pixelated image as the variance data using pixel gray-scale data, or wherein the model parameters are based on the gradients of the difference between an outputted variance map and the inputted variance and using the gradient as a guide to reduce the difference in the adjusting step as taught to be known modifications to similar processes by Su et al.
Response to Arguments
Applicant's arguments filed 12/4/2025 have been fully considered but they are not persuasive. Applicant has argued that the Tirapu-Azpiroz et al reference fails to mention variance data associated with pixels (response, page 9, paragraph 3, and page 10, paragraph 1). Applicant argues that the word “pixel” doesn’t appear in the reference. However, it is well known in the art (see Kim et al and Xiao et al, as two of many examples) that the SRAF process utilizes pixel;-based calculations in their correction methods, and one of ordinary skill in the art would immediately understand that by the reference using a SRAF process, the method of the reference is a pixel-based correction method, therefore deviance / variance data of the mask pattern would be pixel-based. Therefore, this argument is unpersuasive.
Applicant has further argued that the portion of reference cited as teaching the process wherein the threshold values are the constant resist threshold (CTR) values not the variance data, however, the office cited the entire portion of the reference, but clearly explains that the variance data is that gathered from the patterned resist layer (performing metrology on the patterned resist), wherein the features (images resolved main features on the lithographic mask. As SEM images of various mask patterns including different sizes of SRAFs are gathered, some printing SRAFs are visible within a subset of the SEM images derived from mask patterns including a sufficiently large set of SRAFs sizes. The SEM images can be taken at nominal dose and focus conditions and at conditions other than the nominal dose and focus conditions.; see above citations column 9 and 10). The initial model image values comprised comparing the mask image with the model values for various regions and determine variance with the topography including the CTR and comparing with the aerial mask images to determine printing probabilities and adjust the SRAF printing model to minimize the difference between the measured and mask images, which is the claimed determining variance data for the mask pattern and the arguments are not persuasive (column 3, lines 7-column 5, line 41).
Additional arguments to the Tiapu-Azpiroz in view of Su et al reference, which further details the types of pixelated data, are to the above cited argument presented by applicant to the reference SRAF model not using pixel data, which has been addressed above, and is unpersuasive for the reasons cited above.
Conclusion
THIS ACTION IS MADE FINAL. 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 AMANDA C WALKE whose telephone number is (571)272-1337. The examiner can normally be reached Monday to Thursday 5:30am to 4pm.
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/AMANDA C. WALKE/Primary Examiner, Art Unit 1722