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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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 05/13/2024. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
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Claim Rejections- 35 USC §101
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 judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Regarding claim 1,
A method of optimizing an overlay measurement condition, the method comprising:
executing, by a processor, instructions stored in a non-transitory storage medium to perform operations comprising:
measuring, for each overlay measurement condition of multiple overlay measurement conditions, an overlay at multiple positions of a substrate;
calculating, for each of the multiple overlay measurement conditions, key parameter indexes (KPIs) based on the measured overlay;
converting, for each of the multiple overlay measurement conditions, the KPIs into key parameter function (KPF) values based on a KPF, wherein each of the KPFs has a same dimensional representation;
integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value; and
selecting an optimized overlay measurement condition from among the multiple overlay measurement conditions based on the integrated KPF values associated with each of the multiple overlay measurement conditions.
The claim limitations underlined above is abstract idea, and the remaining limitations are “additional elements”.
Step 1 (Statutory Category): Yes. we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (a mathematical manipulation). Therefore, it is directed to a statutory category, i.e., a mathematical manipulation.
Step 2 A, Prong-1 (the claim is evaluated to determine whether it is directed to a judicial-exception/abstract-idea): Yes.
In the above claim, the underlined portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exception. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, it falls into the grouping of subject matter when recited as such in a claim limitation that covers mental processes – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion and mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations, a mathematical manipulation).
For example, steps of “executing, by a processor, instructions stored in a non-transitory storage medium to perform operations; calculating, for each of the multiple overlay measurement conditions, key parameter indexes (KPIs) based on the measured overlay;” “converting, for each of the multiple overlay measurement conditions, the KPIs into key parameter function (KPF) values based on a KPF, wherein each of the KPFs has a same dimensional representation”, and “integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value”, represents the mathematical concepts. Steps of calculating, converting, Integrating, and generating KPF values are mathematical calculation executed by a processor/computer see (Specification [0027], [0040]-[0047], [0060]-[0071] ) are abstract idea. These steps represent a process (a mathematical manipulation) that, under its broadest reasonable interpretation, it encompasses calculating KPI values based on the measurement data and further analyzing/processing to convert into KPF, and Integrating to generate an integrated KPF values making evaluation/judgement based on the calculation under multiple measurement conditions. In addition, the step of “selecting an optimized overlay measurement condition from among the multiple overlay measurement conditions based on the integrated KPF values associated with each of the multiple overlay measurement conditions” is directed to an abstract idea /mathematical concept because the determination is made based on mathematical calculations.
Step 2A, Prong-2 (the claim is evaluated to determine whether the judicial exception/abstract-idea is integrated into a Practical Application): No.
Claim 1 recites additional elements “measuring, for each overlay measurement condition of multiple overlay measurement conditions, an overlay at multiple positions of a substrate”, is a data gathering steps for the particular technological environment or field of use. The additional element “measuring overlay measurement” under different measurement condition represent mere data gathering steps and only add an insignificant extra-solution activity to the judicial exception. The additional elements, considered individually and in combination with the other claim elements do not reflect an improvement to other technology or technical field, and, therefore, do not integrate the judicial exception into a practical application. Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
Step 2B (the claim is evaluated to determine whether recites additional elements that amount to an inventive concept, or also, the additional elements are significantly more than the recited the judicial-exception/abstract-idea): No. the additional element(s) are just insignificant extra-solution activity which are simply routine and conventional steps previously known to the pertinent industry that includes acquiring data from external factors such as pipe environmental and dimensional data. Therefore, the claim does not include additional element(s) significantly more, and/or, does not amount to more than the judicial-exception/abstract-idea itself and the claim is not patent eligible.
claims 2-10 are rejected under 35 U.S.C. 101 because claims depend on
claim 1, therefore, has the abstract idea of claim 1 and also has the routine and conventional structure above of claim 1. In addition, claims 2-10 further recite the elements which are simply more standard computational, mathematical-calculation to data gathering /generate data and/ or a model, and. Furthermore, claims 2-10 do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Regarding claim 11,
An overlay measurement method comprising:
executing, by a processor, instructions stored in a non-transitory storage medium to perform operations comprising:
identifying an optimized overlay measurement condition;
setting an overlay measurement recipe based on the optimized overlay measurement condition; and
measuring an overlay based on the overlay measurement recipe, wherein identifying the optimized overlay measurement condition comprises:
measuring, for each overlay measurement condition of multiple overlay measurement conditions, a sample overlay at multiple positions of a substrate,
calculating, for each of the multiple overlay measurement conditions, key parameter indexes (KPIs) based on the measured sample overlay,
converting, for each of the multiple overlay measurement conditions, the KPIs into key parameter function (KPF) values based on a KPF, wherein each of the KPIs has a same dimensional representation,
integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value, and
selecting the optimized overlay measurement condition from among the multiple overlay measurement conditions based on the integrated KPF values associated with each of the multiple overlay measurement conditions.
The claim limitations underlined above is abstract idea, and the remaining limitations are “additional elements”.
Step 1 (Statutory Category): Yes. we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (a mathematical manipulation). Therefore, it is directed to a statutory category, i.e., a mathematical manipulation.
Step 2 A, Prong-1 (the claim is evaluated to determine whether it is directed to a judicial-exception/abstract-idea): Yes.
In the above claim, the underlined portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exception. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, it falls into the grouping of subject matter when recited as such in a claim limitation that covers mental processes – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion and mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations, a mathematical manipulation).
For example, steps of “executing, by a processor, instructions stored in a non-transitory storage medium to perform operations; “calculating, for each of the multiple overlay measurement conditions, key parameter indexes (KPIs) based on the measured overlay;” “converting, for each of the multiple overlay measurement conditions, the KPIs into key parameter function (KPF) values based on a KPF, wherein each of the KPFs has a same dimensional representation”, and “integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value”, represents the mathematical concepts. Steps of calculating, converting, Integrating, and generating KPF values are mathematical calculation executed by a processor/computer see (Specification [0027], [0040]-[0047], [0060]-[0071] ) are abstract idea. These steps represent a process (a mathematical manipulation) that, under its broadest reasonable interpretation, it encompasses calculating KPI values based on the measurement data and further analyzing/processing to convert into KPF, and Integrating to generate an integrated KPF values making evaluation/judgement based on the calculation under multiple measurement conditions. In addition, the step of “selecting an optimized overlay measurement condition from among the multiple overlay measurement conditions based on the integrated KPF values associated with each of the multiple overlay measurement conditions” is directed to an abstract idea /mathematical concept because the determination is made based on mathematical calculations.
Step 2A, Prong-2 (the claim is evaluated to determine whether the judicial exception/abstract-idea is integrated into a Practical Application): No.
Claim 1 recites additional elements “identifying an optimized overlay measurement condition;” “setting an overlay measurement recipe based on the optimized overlay measurement condition;” and “measuring an overlay based on the overlay measurement recipe, wherein identifying the optimized overlay measurement condition comprises:” “measuring, for each overlay measurement condition of multiple overlay measurement conditions, a sample overlay at multiple positions of a substrate”, are a data gathering steps for the particular technological environment or field of use. The additional element “setting overlay measurement recipe”, identifying measurement condition and “measuring overlay measurement” under different measurement condition represent mere data gathering steps and only add an insignificant extra-solution activity to the judicial exception. The additional elements, considered individually and in combination with the other claim elements do not reflect an improvement to other technology or technical field, and, therefore, do not integrate the judicial exception into a practical application. Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
Step 2B (the claim is evaluated to determine whether recites additional elements that amount to an inventive concept, or also, the additional elements are significantly more than the recited the judicial-exception/abstract-idea): No. the additional element(s) are just insignificant extra-solution activity which are simply routine and conventional steps previously known to the pertinent industry that includes acquiring data from external factors such as pipe environmental and dimensional data. Therefore, the claim does not include additional element(s) significantly more, and/or, does not amount to more than the judicial-exception/abstract-idea itself and the claim is not patent eligible.
claims 11-17 are rejected under 35 U.S.C. 101 because claims depend on
claim 1, therefore, has the abstract idea of claim 11 and also has the routine and conventional structure above of claim 11. In addition, claims 11-17 further recite the elements which are simply more standard computational, mathematical-calculation to data gathering /generate data and/ or a model, and. Furthermore, claims 11-17 do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Regarding claim 18,
A method of optimizing an overlay measurement condition, the method comprising:
executing, by a processor, instructions stored in a non-transitory storage medium to perform operations comprising:
measuring, for each overlay measurement condition of multiple overlay measurement conditions, an overlay at multiple positions on a substrate;
calculating, for each of the multiple overlay measurement conditions, key parameter indexes (KPIs) based on the measured overlay;
converting, for each of the multiple overlay measurement conditions, the KPIs into a key parameter function (KPF) value by removing the dimensional representation of the KPIs;
integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value by adding the KPF values to each other; and
selecting the overlay measurement condition from among the multiple overlay measurement conditions associated with a largest integrated KPF value from among the integrated KPF values.
The claim limitations underlined above is abstract idea, and the remaining limitations are “additional elements”.
Step 1 (Statutory Category): Yes. we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (a mathematical manipulation). Therefore, it is directed to a statutory category, i.e., a mathematical manipulation.
Step 2 A, Prong-1 (the claim is evaluated to determine whether it is directed to a judicial-exception/abstract-idea): Yes.
In the above claim, the underlined portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exception. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, it falls into the grouping of subject matter when recited as such in a claim limitation that covers mental processes – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion and mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations, a mathematical manipulation).
For example, steps of “A method of optimizing an overlay measurement condition, the method comprising: executing, by a processor, instructions stored in a non-transitory storage medium to perform operations comprising;” “calculating, for each of the multiple overlay measurement conditions, key parameter indexes (KPIs) based on the measured overlay;” “converting, for each of the multiple overlay measurement conditions, the KPIs into key parameter function (KPF) values based on a KPF, wherein each of the KPFs has a same dimensional representation”, and “integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value”, represents the mathematical concepts. Steps of calculating, converting, Integrating, and generating KPF values are mathematical calculation executed by a processor/computer see (Specification [0027], [0040]-[0047], [0060]-[0071] ) are abstract idea. These steps represent a process (a mathematical manipulation) that, under its broadest reasonable interpretation, it encompasses calculating KPI values based on the measurement data and further analyzing/processing to convert into KPF, and Integrating to generate an integrated KPF values making evaluation/judgement based on the calculation under multiple measurement conditions. In addition, the step of “selecting an optimized overlay measurement condition from among the multiple overlay measurement conditions based on the integrated KPF values associated with each of the multiple overlay measurement conditions” is directed to an abstract idea /mathematical concept because the determination is made based on mathematical calculations.
Step 2A, Prong-2 (the claim is evaluated to determine whether the judicial exception/abstract-idea is integrated into a Practical Application): No.
Claim 1 recites additional elements “measuring, for each overlay measurement condition of multiple overlay measurement conditions, an overlay at multiple positions of a substrate”, is a data gathering steps for the particular technological environment or field of use. The additional element “measuring overlay measurement” under different measurement condition represent mere data gathering steps and only add an insignificant extra-solution activity to the judicial exception. The additional elements, considered individually and in combination with the other claim elements do not reflect an improvement to other technology or technical field, and, therefore, do not integrate the judicial exception into a practical application. Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
Step 2B (the claim is evaluated to determine whether recites additional elements that amount to an inventive concept, or also, the additional elements are significantly more than the recited the judicial-exception/abstract-idea): No. the additional element(s) are just insignificant extra-solution activity which are simply routine and conventional steps previously known to the pertinent industry that includes acquiring data from external factors such as pipe environmental and dimensional data. Therefore, the claim does not include additional element(s) significantly more, and/or, does not amount to more than the judicial-exception/abstract-idea itself and the claim is not patent eligible.
claims 19-20 are rejected under 35 U.S.C. 101 because claims depend on
claim 18, therefore, has the abstract idea of claim 18 and also has the routine and conventional structure above of claim 18. In addition, claims 19-20 further recite the elements which are simply more standard computational, mathematical-calculation to data gathering /generate data and/ or a model, and. Furthermore, claims 19-20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Slotboom et al. (US 2018/0373162 A1, hereinafter Slotboom) and in view of Alexander Alexandrovich DANILIN. (US 2018/0356736 A1, hereinafter Danilin, IDS ref.).
Regarding Claim 1, Slotboom teaches,
A method of optimizing an overlay measurement condition (Slotboom, Figure 6, [0101] “At 610, a metrology target optimization is performed. A preliminary optimized set of m different overlay targets are designed based on information of the intended process.”), the method comprising:
executing, by a processor, instructions stored in a non-transitory storage medium to perform operations (Slotboom, [0140] “Alternatively, the calculation steps may be wholly or partly performed within a processor a metrology tool, and/or the control unit LACU and/or supervisory control system SCS of FIGS. 1 and 2. There may also be provided a data storage medium ( e.g., semiconductor memory, magnetic or optical disk) having such a computer program stored therein in non-transient form”) comprising:
measuring, for each overlay measurement condition of multiple overlay measurement conditions, an overlay at multiple positions of a substrate (Slotboom, [0019]” (iv) based on the measurements of position measurement marks and performance measurement targets after actual performance of the patterning process in step (ii), revising a selection of position measurement mark type used in the patterning process for measuring positional deviations across the substrate.); [0108] After, in step 616 the metrology apparatus, for example an angle-resolved scatterometer, is used to measure overlay as a parameter of performance of the lithographic process. This measurement is done the same way as it will be in the high-volume APC control loops of FIG. 4, except that in this development phase multiple different overlay target types may be measured, and each will be measured using multiple different recipes. In one type of scatterometer, for example, it may be possible to measure diffraction patterns using seven different wavelengths of radiation, and two different polarizations for each wavelength. Measurement points will be distributed across the wafer, and a number determined by the feedback model implemented in the APC system”. Different recipe with different position, wavelength angle are the example of different measurement condition).
calculating, for each of the multiple overlay measurement conditions, key parameter indexes (KPIs) based on the measured overlay;(Slotboom, Figure 3, At 322 information relating for example to parameters such as critical dimension, sidewall angles and overlay is determined and passed to an Advanced Process
Control (APC) module 324. This data is also passed to the stability module 300. Process corrections 326 are calculated and used by the supervisory control system (SCS) 328, providing control of the lithocell 304, in communication
with the stability module 300”. NOTE: critical dimension, sidewall angles and overlay are the key parameters are calculated under different measurement conditions by advanced process control module 324). and
selecting an optimized overlay measurement condition from among the multiple overlay measurement conditions based on the integrated KPF values associated with each of the multiple overlay measurement conditions. (Slotboom, abstract “In a set-up phase, the method selects an alignment mark type and alignment recipe from among a plurality of candidate mark types by reference to expected parameters of the patterning process. After exposing a number of test substrates using the patterning process, a preferred metrology target type and metrology recipe are
selected by comparing measured performance ( e.g. overlay) of performance of the patterning process measured by a reference technique”).
Slotboom, is silent on converting, for each of the multiple overlay measurement conditions, the KPIs into key parameter function (KPF) values based on a KPF, wherein each of the KPFs has a same dimensional representation;
integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value; and
selecting an optimized overlay measurement condition from among the multiple overlay measurement conditions based on the integrated KPF values associated with each of the multiple overlay measurement conditions.
However, Danilin teaches converting, for each of the multiple overlay measurement conditions, the KPIs into key parameter function (KPF) values based on a KPF (Danilin, [0004] A key performance parameter of the lithographic apparatus is the overlay error. This error, often referred to simply as "overlay", is the error in placing a product features in the correct position relative to features formed in previous layers”[0065] Accordingly, it is a matter of implementation whether the performance model 2015 delivers its output firstly in the form of a prediction, which then has to be converted to correction parameters, or whether it is arranged to deliver directly the necessary correction parameters”), wherein each of the KPFs has a same dimensional representation (Danilin, [0066] “The database 2014 may be indexed so that measurements can be selected based on any number of index variables. Each measurement is effectively positioned at a point in a multi-dimensional space, whose dimensions are the indexing variables. Indexing variables for each performance measurement may be for example inter-field position (xw, yw), intra-field position (xf, yf) and field center position (xc, ye)”. The index variables in database 2014 can be used in the performance model 2015 to predict performance when those variables vary in a production situation. [0066] )”);
integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value (Danilin, Figure 9, [0112] In the next step (2), the dynamic component DYINTRA-DYN-SU of the intra-field performance model is calculated, using the residual component 906 as input. This being the intra-field component, measurement data from all the fields having scan up exposure is combined into intra field measurement data 912 with spatial dimensions corresponding to the dimensions of the largest field size. Intra field
position is indicated by coordinates xf, yf. This being a dynamic component, the data is not only indexed by intra-field position, but also indexed by the normalized time value T as a third dimension”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Slotboom’s method for optimization of performance parameter to incorporate Danilin’s method of indexing key performance parameter and combining the parameters to predict optimized overlay measurement condition and calibration with the benefit of improving accuracy of the lithographic apparatus performance by reducing the overlay error and optimize the lithographic patterning process (Danilin, Abstract). It would have been obvious to a person of ordinary skill to include the well-known performance model optimization combined with different variable functions and optimizing substrate processing in order to yield the predicted results of accurate lithographic processing apparatus performance, yet with higher accuracy and efficiency (KSR).
Regarding Claim 2, combination of Slotboom and Danilin teaches the method of claim 1,
Slotboom further teaches wherein the KPF is based on the multiple overlay measurement conditions. ((Slotboom, Figure 5, multi layers L1, L2 [0019]” (iv) based on the measurements of position measurement marks and performance measurement targets after actual performance of the patterning process in step (ii), revising a selection of position measurement mark type used in the patterning process for measuring positional deviations across the substrate.); [0108] After, in step 616 the metrology apparatus, for example an angle-resolved scatterometer, is used to measure overlay as a parameter of performance of the lithographic process. This measurement is done the same way as it will be in the high volume APC control loops of FIG. 4, except that in this development phase multiple different overlay target types may be measured, and each will be measured using multiple different recipes. In one type of scatterometer, for example, it may be possible to measure diffraction patterns using seven different wavelengths of radiation, and two different polarizations for each wavelength. Measurement points will be distributed across the wafer, and a number determined by the feedback model implemented in the APC system”. Different recipe with different position, wavelength angle is the example of different measurement condition)
Regarding Claim 3, combination of Slotboom and Danilin teaches the method of claim 1,
Slotboom is silent on wherein the KPF converts a respective dimensional representation of the KPIs to the same dimensional representation based on the multiple overlay measurement conditions.
However, Danilin teaches wherein the KPF converts a respective dimensional representation of the KPIs to the same dimensional representation based on the multiple overlay measurement conditions (Danilin, Figure 2, [0066] “The database 2014 may be indexed so that measurements can be selected based on any number of index variables. Each measurement is effectively positioned at a point in a multi-dimensional space, whose dimensions are the indexing variables. Indexing variables for each performance measurement may be for example inter-field position (xw, yw), intra-field position (xf, yf) and field center position (xc, ye)”. The index variables in database 2014 can be used in the performance model 2015 to predict performance when those variables vary in a production situation. [0066])”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Slotboom’s method for optimization of performance parameter to incorporate Danilin’s method of indexing key performance parameter and combining the parameters to predict optimized overlay measurement condition and calibration with the benefit of improving accuracy of the lithographic apparatus performance by reducing the overlay error and optimize the lithographic patterning process (Danilin, Abstract). It would have been obvious to a person of ordinary skill to include the well-known performance model optimization combined with different variable functions and optimizing substrate processing in order to yield the predicted results of accurate lithographic processing apparatus performance, yet with higher accuracy and efficiency (KSR).
Regarding Claim 4, combination of Slotboom and Danilin teaches the method of claim 1,
Slotboom is silent on wherein integrating the KPF values to generate the integrated KPF value further comprises adding each of the KPF values to each other.
However, Danilin teaches wherein integrating the KPF values to generate the integrated KPF value further comprises adding each of the KPF values to each other (Danilin, Figure 9, [0112] In the next step (2), the dynamic component DYINTRA-DYN-SU of the intra-field performance model is calculated, using the residual component 906 as input. This being the intra-field component, measurement data from all the fields having scan up exposure is combined into intra field measurement data 912 with spatial dimensions corresponding to the dimensions of the largest field size. Intra field position is indicated by coordinates xf, yf. This being a dynamic component, the data is not only indexed by intra-field position, but also indexed by the normalized time value T as a third dimension”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Slotboom’s method for optimization of performance parameter to incorporate Danilin’s method of indexing key performance parameter and combining the parameters to predict optimized overlay measurement condition and calibration with the benefit of improving accuracy of the lithographic apparatus performance by reducing the overlay error and optimize the lithographic patterning process (Danilin, Abstract). It would have been obvious to a person of ordinary skill to include the well-known performance model optimization combined with different variable functions and optimizing substrate processing in order to yield the predicted results of accurate lithographic processing apparatus performance, yet with higher accuracy and efficiency (KSR).
Regarding Claim 5, combination of Slotboom and Danilin teaches the method of claim 1,
Slotboom is silent on wherein integrating the KPF values to generate the integrated KPF value further comprises assigning a weighted value to each of the KPF values.
However, Danilin teaches wherein integrating the KPF values to generate the integrated KPF value further comprises assigning a weighted value to each of the KPF values. (Danilin, “[0112] the measurement data for different parts of a field may be assigned different time values. Time increases continuously as the exposure slit of the lithographic apparatus scans up or down across the field. On the other hand for simplicity in the present embodiment, all the measurement data from each field is assigned a single time value, corresponding to the exposure time of the field center. It is a matter of implementation whether the actual time values are converted to normalized time scale when they are entered in the database, or whether conversion happens when the database is interrogated”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Slotboom’s method for optimization of performance parameter to incorporate Danilin’s method of indexing key performance parameter and combining the parameters to predict optimized overlay measurement condition and calibration with the benefit of improving accuracy of the lithographic apparatus performance by reducing the overlay error and optimize the lithographic patterning process (Danilin, Abstract). It would have been obvious to a person of ordinary skill to include the well-known performance model optimization combined with different variable functions and optimizing substrate processing in order to yield the predicted results of accurate lithographic processing apparatus performance, yet with higher accuracy and efficiency (KSR).
Regarding Claim 6, combination of Slotboom and Danilin teaches the method of claim 1,
Slotboom further teaches wherein selecting the optimized overlay measurement condition (Slotboom, [0017] (iii) selecting a preferred candidate type of performance measurement target by comparing performance of the patterning process as measured using the different types of performance measurement targets with performance of the patterning process measured by other means”) further comprises identifying an overlay measurement condition from among the multiple overlay measurement conditions that is associated with a largest integrated KPF value from among the integrated KPF values (Slotboom, [0030] a module for selecting a type of position measurement mark for the patterning process from among a plurality of candidate mark types by reference to expected parameters of the patterning process; [0031] a module for selecting a preferred candidate type of performance measurement target from among a plurality of candidate types of performance measurement targets applied to one or more substrates by comparing performance of the patterning process as measured using the different types of performance measurement targets with actual performance of the patterning process measured by other means”) .
Regarding Claim 7, combination of Slotboom and Danilin teaches the method of claim 1,
Slotboom further teaches wherein the multiple positions are associated with alignment marks of the substrate, and wherein the alignment marks comprise at least one of an image based overlay (IBO) (Slotboom, Figure2- 3, [0072] “At 202, alignment measurements using the substrate marks Pl etc. and image sensors (not shown) are used to measure and record alignment of the substrate relative to
substrate table WTa/WTb”) and a fringe based overlay (FBO).
Regarding Claim 8, combination of Slotboom and Danilin teaches the method of claim 7,
Slotboom further teaches wherein the multiple overlay measurement conditions comprise at least one of a wavelength (Slotboom, [0071] “Some layers may be exposed in a tool working at DUY wavelengths, while others are exposed
using EUV wavelength radiation” of a light source, a focus of the light source (Slotboom, [0079] The second (APC) control loop is based on measurements of performance parameters such as focus, dose, and overlay on actual product wafers”), and a design of the alignment marks. (Slotboom, [0072] “several alignment marks across the substrate W' will be measured using alignment sensor AS. These measurements are used in one embodiment to establish a substrate model (sometimes referred to as the "wafer grid"), which maps very accurately the distribution of marks across the substrate, including any distortion relative to a nominal rectangular grid”).
Regarding Claim 9, combination of Slotboom and Danilin teaches the method of claim 1,
Slotboom further teaches further comprising measuring the overlay on multiple substrates. (Slotboom, abstract, processing a number of substrates.”).
Regarding Claim 10, combination of Slotboom and Danilin teaches the method of claim 1,
Slotboom further teaches wherein a number of the multiple positions is based on the multiple overlay measurement conditions. (Slotboom, [0118] In addition to variations of mark types and recipes, the positions of alignment marks and metrology targets can also be varied and co-optimized as part of the process. The
co-optimization process for overlay performance control may be coupled to optimization of performance control in other parameters, for example, focus. For example, targets for focus metrology may compete for space with metrology
targets for overlay, and/or with alignment marks. Co-optimization of all these variables can be implemented, to ensure that (for example) improved overlay performance does not come at the expense of degraded focus performance”)
Regarding Claim 11, Slotboom teaches,
An overlay measurement method comprising:
executing, by a processor, instructions stored in a non-transitory storage medium to perform operations (Slotboom, [0140] “Alternatively, the calculation steps may be wholly or partly performed within a processor a metrology tool, and/or the control unit LACU and/or supervisory control system SCS of FIGS. 1 and 2. There may also be provided a data storage medium ( e.g., semiconductor memory, magnetic or optical disk) having such a computer program stored therein in non-transient form”) comprising:
identifying an optimized overlay measurement condition; setting an overlay measurement recipe based on the optimized overlay measurement condition; and measuring an overlay based on the overlay measurement recipe, wherein identifying the optimized overlay measurement condition (Slotboom, abstract “In a set-up phase, the method selects an alignment mark type and alignment recipe from among a plurality of candidate mark types by reference to expected parameters of the patterning process. After exposing a number of test substrates using the patterning process, a preferred metrology target type and metrology recipe are
selected by comparing measured performance ( e.g. overlay) of performance of the patterning process measured by a reference technique”). comprises:
measuring, for each overlay measurement condition of multiple overlay measurement conditions, a sample overlay at multiple positions of a substrate(Slotboom, [0019]” (iv) based on the measurements of position measurement marks and performance measurement targets after actual performance of the patterning process in step (ii), revising a selection of position measurement mark type used in the patterning process for measuring positional deviations across the substrate.); [0108] After, in step 616 the metrology apparatus, for example an angle-resolved catterometer, is used to measure overlay as a parameter of performance of the lithographic process. This measurement is done the same way as it will be in the high volume APC control loops of FIG. 4, except that in this development phase multiple different overlay target types may be measured, and each will be measured using multiple different recipes. In one type of scatterometer, for example, it may be possible to measure diffraction patterns using seven different wavelengths of radiation, and two different polarizations for each wavelength. Measurement points will be distributed across the wafer, and a number determined by the feedback model implemented in the APC system”. Different recipe with different position, wavelength angle are the example of different measurement condition)
calculating, for each of the multiple overlay measurement conditions, key parameter indexes (KPIs) based on the measured sample overlay;(Slotboom, Figure 3, At 322 information relating for example to parameters such as critical dimension, sidewall angles and overlay is determined and passed to an Advanced Process
Control (APC) module 324. This data is also passed to the stability module 300. Process corrections 326 are calculated and used by the supervisory control system (SCS) 328, providing control of the lithocell 304, in communication
with the stability module 300”. NOTE: critical dimension, sidewall angles and overlay are the key parameters are calculated under different measurement conditions by advanced process control module 324). and
selecting an optimized overlay measurement condition from among the multiple overlay measurement conditions based on the integrated KPF values associated with each of the multiple overlay measurement conditions. (Slotboom, abstract “In a set-up phase, the method selects an alignment mark type and alignment recipe from among a plurality of candidate mark types by reference to expected parameters of the patterning process. After exposing a number of test substrates using the patterning process, a preferred metrology target type and metrology recipe are
selected by comparing measured performance ( e.g. overlay) of performance of the patterning process measured by a reference technique”).
Slotboom, is silent on converting, for each of the multiple overlay measurement conditions, the KPIs into key parameter function (KPF) values based on a KPF, wherein each of the KPFs has a same dimensional representation;
integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value; and
selecting an optimized overlay measurement condition from among the multiple overlay measurement conditions based on the integrated KPF values associated with each of the multiple overlay measurement conditions.
However, Danilin teaches converting , for each of the multiple overlay measurement conditions, the KPIs into key parameter function (KPF) values based on a KPF(Danilin, [0004] A key performance parameter of the lithographic apparatus is the overlay error. This error, often referred to simply as "overlay", is the error in placing a product features in the correct position relative to features formed in previous layers”[0065] Accordingly, it is a matter of implementation whether the performance model 2015 delivers its output firstly in the form of a prediction, which then has to be converted to correction parameters, or whether it is arranged to deliver directly the necessary correction parameters”), wherein each of the KPFs has a same dimensional representation (Danilin, [0066] “The database 2014 may be indexed so that measurements can be selected based on any number of index variables. Each measurement is effectively positioned at a point in a multi-dimensional space, whose dimensions are the indexing variables. Indexing variables for each performance measurement may be for example inter-field position (xw, yw), intra-field position (xf, yf) and field center position (xc, ye)”. The index variables in database 2014 can be used in the performance model 2015 to predict performance when those variables vary in a production situation. [0066] )”);
integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value (Danilin, Figure 9, [0112] In the next step (2), the dynamic component DYINTRA-DYN-SU of the intra-field performance model is calculated, using the residual component 906 as input. This being the intra-field component, measurement data from all the fields having scan up exposure is combined into intra field measurement data 912 with spatial dimensions corresponding to the dimensions of the largest field size. Intra field
position is indicated by coordinates xf, yf. This being a dynamic component, the data is not only indexed by intra-field position, but also indexed by the normalized time value T as a third dimension”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Slotboom’s method for optimization of performance parameter to incorporate Danilin’s method of indexing key performance parameter and combining the parameters to predict optimized overlay measurement condition and calibration with the benefit of improving accuracy of the lithographic apparatus performance by reducing the overlay error and optimize the lithographic patterning process (Danilin, Abstract). It would have been obvious to a person of ordinary skill to include the well-known performance model optimization combined with different variable functions and optimizing substrate processing in order to yield the predicted results of accurate lithographic processing apparatus performance, yet with higher accuracy and efficiency (KSR).
Regarding Claim 12, combination of Slotboom and Danilin teaches the overlay measurement method of claim 11,
Slotboom further teaches wherein the KPF is based on the multiple overlay measurement conditions. ((Slotboom, Figure 5, multi layers L1, L2 [0019]” (iv) based on the measurements of position measurement marks and performance measurement targets after actual performance of the patterning process in step (ii), revising a selection of position measurement mark type used in the patterning process for measuring positional deviations across the substrate.); [0108] After, in step 616 the metrology apparatus, for example an angle-resolved scatterometer, is used to measure overlay as a parameter of performance of the lithographic process. This measurement is done the same way as it will be in the high volume APC control loops of FIG. 4, except that in this development phase multiple different overlay target types may be measured, and each will be measured using multiple different recipes. In one type of scatterometer, for example, it may be possible to measure diffraction patterns using seven different wavelengths of radiation, and two different polarizations for each wavelength. Measurement points will be distributed across the wafer, and a number determined by the feedback model implemented in the APC system”. Different recipe with different position, wavelength angle are the example of different measurement condition)
Regarding Claim 13, combination of Slotboom and Danilin teaches the overlay measurement method of claim 11,
Slotboom is silent on wherein the KPF converts a respective dimensional representation of the KPIs to the same dimensional representation based on the multiple overlay measurement conditions.
However, Danilin teaches wherein the KPF converts a respective dimensional representation of the KPIs to the same dimensional representation based on the multiple overlay measurement conditions (Danilin, Figure 2, [0066] “The database 2014 may be indexed so that measurements can be selected based on any number of index variables. Each measurement is effectively positioned at a point in a multi-dimensional space, whose dimensions are the indexing variables. Indexing variables for each performance measurement may be for example inter-field position (xw, yw), intra-field position (xf, yf) and field center position (xc, ye)”. The index variables in database 2014 can be used in the performance model 2015 to predict performance when those variables vary in a production situation. [0066] )”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Slotboom’s method for optimization of performance parameter to incorporate Danilin’s method of indexing key performance parameter and combining the parameters to predict optimized overlay measurement condition and calibration with the benefit of improving accuracy of the lithographic apparatus performance by reducing the overlay error and optimize the lithographic patterning process (Danilin, Abstract). It would have been obvious to a person of ordinary skill to include the well-known performance model optimization combined with different variable functions and optimizing substrate processing in order to yield the predicted results of accurate lithographic processing apparatus performance, yet with higher accuracy and efficiency (KSR).
Regarding Claim 14, combination of Slotboom and Danilin teaches the overlay measurement method of claim 11,
Slotboom is silent on wherein integrating the KPF values to generate the integrated KPF value further comprises assigning a weighted value to each of the KPF values.
However, Danilin teaches wherein integrating the KPF values to generate the integrated KPF value further comprises assigning a weighted value to each of the KPF values. (Danilin, “[0112] the measurement data for different parts of a field may be assigned different time values. Time increases continuously as the exposure slit of the lithographic apparatus scans up or down across the field. On the other hand for simplicity in the present embodiment, all the measurement data from each field is assigned a single time value, corresponding to the exposure time of the field center. It is a matter of implementation whether the actual time values are converted to normalized time scale when they are entered in the database, or whether conversion happens when the database is interrogated”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Slotboom’s method for optimization of performance parameter to incorporate Danilin’s method of indexing key performance parameter and combining the parameters to predict optimized overlay measurement condition and calibration with the benefit of improving accuracy of the lithographic apparatus performance by reducing the overlay error and optimize the lithographic patterning process (Danilin, Abstract). It would have been obvious to a person of ordinary skill to include the well-known performance model optimization combined with different variable functions and optimizing substrate processing in order to yield the predicted results of accurate lithographic processing apparatus performance, yet with higher accuracy and efficiency (KSR).
Regarding Claim 15, combination of Slotboom and Danilin teaches the overlay measurement method of claim 14,
Slotboom further teaches wherein selecting the optimized overlay measurement condition (Slotboom, [0017] (iii) selecting a preferred candidate type of performance measurement target by comparing performance of the
patterning process as measured using the different types of
performance measurement targets with performance of the
patterning process measured by other means”) further comprises identifying an overlay measurement condition from among the multiple overlay measurement conditions that is associated with a largest integrated KPF value from among the integrated KPF values (Slotboom, [0030] a module for selecting a type of position measurement mark for the patterning process from among a plurality of candidate mark types by reference to expected parameters of the patterning process; [0031] a module for selecting a preferred candidate type of performance measurement target from among a plurality of candidate types of performance measurement targets applied to one or more substrates by comparing performance of the patterning process as measured using the different types of performance measurement targets with actual performance of the patterning process measured by other means”) .
Regarding Claim 16, combination of Slotboom and Danilin teaches the overlay measurement method of claim 11,
Slotboom further teaches further comprising measuring the sample overlay of multiple substrates (Slotboom, abstract, number of substrate), and a number of the multiple positions is based on the multiple overlay measurement conditions. Slotboom, [0118] In addition to variations of mark types and recipes, the positions of alignment marks and metrology targets can also be varied and co-optimized as part of the process. The co-optimization process for overlay performance control may be coupled to optimization of performance control in other parameters, for example, focus. For example, targets for focus metrology may compete for space with metrology targets for overlay, and/or with alignment marks. Co-optimization of all these variables can be implemented, to ensure that (for example) improved overlay performance does not come at the expense of degraded focus performance”).
Regarding Claim 17, combination of Slotboom and Danilin teaches the overlay measurement method of claim 11,
Slotboom further teaches further comprising feeding back the overlay measurement condition associated with the overlay measured that is based on the overlay measurement recipe. (Slotboom, [0120] In the outer loop illustrated in FIG. 6, the optimization of a run-to-run control strategy is implemented. A data processing apparatus is programmed to determine which feedback strategy, out of a number of possible candidates, results in the best possible overlay for the products
and layers of interest. There are several components to the run-to-run (R2R) optimization system implemented in the present embodiment: [0121] a first module is provided to calculate what overlay would have been achieved, if a different R2R strategy had been applied than one currently in operation”).
Regarding Claim 18, Slotboom teaches
A method of optimizing an overlay measurement condition, the method comprising:
executing, by a processor, instructions stored in a non-transitory storage medium to perform operations (Slotboom, [0140] “Alternatively, the calculation steps may be wholly or partly performed within a processor a metrology tool, and/or the control unit LACU and/or supervisory control system SCS of FIGS. 1 and 2. There may also be provided a data storage medium ( e.g., semiconductor memory, magnetic or optical disk) having such a computer program stored therein in non-transient form”) comprising:
measuring, for each overlay measurement condition of multiple overlay measurement conditions, an overlay at multiple positions of a substrate (Slotboom, [0019]” (iv) based on the measurements of position measurement marks and performance measurement targets after actual performance of the patterning process in step (ii), revising a selection of position measurement mark type used in the patterning process for measuring positional deviations across the substrate.); [0108] After, in step 616 the metrology apparatus, for example an angle-resolved scatterometer, is used to measure overlay as a parameter of performance of the lithographic process. This measurement is done the same way as it will be in the high volume APC control loops of FIG. 4, except that in this development phase multiple different overlay target types may be measured, and each will be measured using multiple different recipes. In one type of scatterometer, for example, it may be possible to measure diffraction patterns using seven different wavelengths of radiation, and two different polarizations for each wavelength. Measurement points will be distributed across the wafer, and a number determined by the feedback model implemented in the APC system”. Different recipe with different position, wavelength angle are the example of different measurement condition).
calculating, for each of the multiple overlay measurement conditions, key parameter indexes (KPIs) based on the measured overlay;(Slotboom, Figure 3, At 322 information relating for example to parameters such as critical dimension, sidewall angles and overlay is determined and passed to an Advanced Process
Control (APC) module 324. This data is also passed to the stability module 300. Process corrections 326 are calculated and used by the supervisory control system (SCS) 328, providing control of the lithocell 304, in communication
with the stability module 300”. NOTE: critical dimension, sidewall angles and overlay are the key parameters are calculated under different measurement conditions by advanced process control module 324). and
selecting an optimized overlay measurement condition from among the multiple overlay measurement conditions based on the integrated KPF values associated with each of the multiple overlay measurement conditions. (Slotboom, abstract “In a set-up phase, the method selects an alignment mark type and alignment recipe from among a plurality of candidate mark types by reference to expected parameters of the patterning process. After exposing a number of test substrates using the patterning process, a preferred metrology target type and metrology recipe are
selected by comparing measured performance ( e.g. overlay) of performance of the patterning process measured by a reference technique”).
Slotboom, is silent on converting, for each of the multiple overlay measurement conditions, the KPIs into key parameter function (KPF) values based on a KPF, wherein each of the KPFs has a same dimensional representation;
integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value; and
selecting an optimized overlay measurement condition from among the multiple overlay measurement conditions based on the integrated KPF values associated with each of the multiple overlay measurement conditions.
However, Danilin teaches converting , for each of the multiple overlay measurement conditions, the KPIs into key parameter function (KPF) values based on a KPF(Danilin, [0004] A key performance parameter of the lithographic apparatus is the overlay error. This error, often referred to simply as "overlay", is the error in placing a product features in the correct position relative to features formed in previous layers”[0065] Accordingly, it is a matter of implementation whether the performance model 2015 delivers its output firstly in the form of a prediction, which then has to be converted to correction parameters, or whether it is arranged to deliver directly the necessary correction parameters”), wherein each of the KPFs has a same dimensional representation (Danilin, [0066] “The database 2014 may be indexed so that measurements can be selected based on any number of index variables. Each measurement is effectively positioned at a point in a multi-dimensional space, whose dimensions are the indexing variables. Indexing variables for each performance measurement may be for example inter-field position (xw, yw), intra-field position (xf, yf) and field center position (xc, ye)”. The index variables in database 2014 can be used in the performance model 2015 to predict performance when those variables vary in a production situation. [0066] )”);
integrating, for each of the multiple overlay measurement conditions, the KPF values to generate an integrated KPF value (Danilin, Figure 9, [0112] In the next step (2), the dynamic component DYINTRA-DYN-SU of the intra-field performance model is calculated, using the residual component 906 as input. This being the intra-field component, measurement data from all the fields having scan up exposure is combined into intra field measurement data 912 with spatial dimensions corresponding to the dimensions of the largest field size. Intra field
position is indicated by coordinates xf, yf. This being a dynamic component, the data is not only indexed by intra-field position, but also indexed by the normalized time value T as a third dimension”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Slotboom’s method for optimization of performance parameter to incorporate Danilin’s method of indexing key performance parameter and combining the parameters to predict optimized overlay measurement condition and calibration with the benefit of improving accuracy of the lithographic apparatus performance by reducing the overlay error and optimize the lithographic patterning process (Danilin, Abstract). It would have been obvious to a person of ordinary skill to include the well-known performance model optimization combined with different variable functions and optimizing substrate processing in order to yield the predicted results of accurate lithographic processing apparatus performance, yet with higher accuracy and efficiency (KSR).
Regarding Claim 19, combination of Slotboom and Danilin teaches the method of claim 18,
Slotboom is silent on wherein the KPIs have different dimensional representations.
However, Danilin teaches wherein the KPIs have different dimensional representations
wherein the KPIs have different dimensional representations.
However, Danilin teaches wherein the KPIs have different dimensional representations Danilin, Figure 2, [0066] “The database 2014 may be indexed so that measurements can be selected based on any number of index variables. Each measurement is effectively positioned at a point in a multi-dimensional space, whose dimensions are the indexing variables. Indexing variables for each performance measurement may be for example inter-field position (xw, yw), intra-field position (xf, yf) and field center position (xc, ye)”. The index variables in database 2014 can be used in the performance model 2015 to predict performance when those variables vary in a production situation. [0066] )”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Slotboom’s method for optimization of performance parameter to incorporate Danilin’s method of indexing key performance parameter and combining the parameters to predict optimized overlay measurement condition and calibration with the benefit of improving accuracy of the lithographic apparatus performance by reducing the overlay error and optimize the lithographic patterning process (Danilin, Abstract). It would have been obvious to a person of ordinary skill to include the well-known performance model optimization combined with different variable functions and optimizing substrate processing in order to yield the predicted results of accurate lithographic processing apparatus performance, yet with higher accuracy and efficiency (KSR).
Regarding Claim 20, combination of Slotboom and Danilin teaches the method of claim 18,
Slotboom is silent on wherein integrating the KPF values to generate the integrated KPF value further comprises assigning a weighted value to each of the KPF values.
However, Danilin teaches wherein integrating the KPF values to generate the integrated KPF value further comprises assigning a weighted value to each of the KPF values. (Danilin, “[0112] the measurement data for different parts of a field may be assigned different time values. Time increases continuously as the exposure slit of the lithographic apparatus scans up or down across the field. On the other hand for simplicity in the present embodiment, all the measurement data from each field is assigned a single time value, corresponding to the exposure time of the field center. It is a matter of implementation whether the actual time values are converted to normalized time scale when they are entered in the database, or whether conversion happens when the database is interrogated”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Slotboom’s method for optimization of performance parameter to incorporate Danilin’s method of indexing key performance parameter and combining the parameters to predict optimized overlay measurement condition and calibration with the benefit of improving accuracy of the lithographic apparatus performance by reducing the overlay error and optimize the lithographic patterning process (Danilin, Abstract). It would have been obvious to a person of ordinary skill to include the well-known performance model optimization combined with different variable functions and optimizing substrate processing in order to yield the predicted results of accurate lithographic processing apparatus performance, yet with higher accuracy and efficiency (KSR).
Conclusion
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Hulsebos et al. (US 2020/0201194 A1) recites “In a method of controlling a lithographic apparatus, historical performance measurements are used to calculate a process model relating to a lithographic process. Current positions of a plurality of alignment marks provided on a current substrate are measured and used to calculate a substrate model relating to a current substrate. Additionally, historical position measurements obtained at the time of processing the prior substrates are used with the historical performance measurements to calculate a model mapping. The model
mapping is applied to modify the substrate model. The lithographic apparatus is controlled using the process model and the modified substrate model together. Overlay performance is improved by avoiding over- or under-correction of correlated components of the process model and the substrate model. The model mapping may be a subspace mapping, and dimensionality of the model mapping may be reduced, before it is used” (Abstract).
Manassen et al. (US 2022/0317577 A1) recites “A method for metrology includes directing at least one illumination beam to illuminate a semiconductor wafer on
which at least first and second patterned layers have been deposited in succession, including a first target feature in the first patterned layer and a second target feature in the second patterned layer, overlaid on the first target feature. A sequence of images of the first and second target features is captured while varying one or more imaging parameters over the sequence. The images in the sequence are processed
in order to identify respective centers of symmetry of the first and second target features in the images and measure variations in the centers of symmetry as a function of the
varying image parameters. The measured variations are applied in measuring an overlay error between the first and second patterned layers” (abstract).
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/DILARA SULTANA/Examiner, Art Unit 2858 08/20/2026
/EMAN A ALKAFAWI/Supervisory Patent Examiner, Art Unit 2858 9/2/2026
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