TW201245906A - Method and system for providing a quality metric for improved process control - Google Patents

Abstract

The present invention may include acquiring a plurality of overlay metrology measurement signals from a plurality of metrology targets distributed across one or more fields of a wafer of a lot of wafers, determining a plurality of overlay estimates for each of the plurality of overlay metrology measurement signals using a plurality of overlay algorithms, generating a plurality of overlay estimate distributions, and generating a first plurality of quality metrics utilizing the generated plurality of overlay estimate distributions, wherein each quality metric corresponds with one overlay estimate distribution of the generated plurality of overlay estimate distributions, each quality metric a function of a width of a corresponding generated overlay estimate distribution, each quality metric further being a function of asymmetry present in an overlay metrology measurement signal from an associated metrology target.

Description

201245906 VI. Description of the Invention: [Technical Field of the Invention] The present invention relates to a method and system for providing quality metrics suitable for improving program control in semiconductor wafer fabrication. Claims for the earliest available valid application date from the applications listed below ("Related Application j") (for example, claiming the earliest available priority period other than the provisional patent application or claiming a provisional patent application, related application Any and all parent applications, grandparents' applications, and great-grandparents' applications, etc. under 35 USC § 119(e)).

For the purposes of the additional statutory requirements of the USPTO, this application constitutes the application of Daniel Kandel, Guy Cohen, Vladimir Levinski and Noam Sapiens as the inventor's title "METHODS TO REDUCE SYSTEMATIC BIAS IN OVERLAY METROLOGY", filed on April 6, 2011. ORLITHOGRAPHY PROCESS CONTROL is one of the official (non-provisional) patent applications of the US Provisional Patent Application (Application Serial No. 61/472,545). For the purposes of additional statutory requirements of the USPTO, this application constitutes the application of the date of April 11, 2011, named Daniel Kandel, Guy Cohen, Vladimir Levinski, Noam Sapiens, Alex Shulman and Vladimir Kamenetsky as the inventor entitled "METHODS TO" REDUCE SYSTEMATIC BIAS IN OVERLAY METROLOGY OR LITHOGRAPHY PROCESS CONTROL" is one of the official (non-provisional) patent applications of the US Provisional Patent Application (Application Serial No. 61/474,167). 163677.doc 201245906 For the purposes of additional statutory requirements of the USPTO, this application constitutes the date of July 7, 2011, and the names of Guy Cohen, Eran Amit and Dana Klein as inventors are entitled "METHODS FOR CALCULATING CORRECTABLES WITH BETTER ACCURACY" One of the official (non-provisional) patent applications of the US Provisional Patent Application (Application Serial No. 61/509,842). For the purposes of the additional statutory requirements of the USPTO, this application constitutes the US provisional date of February 10, 2012, which named Guy Cohen, Dana Klein and Eran Amit as the inventor's title "METHODS FOR CALCULATING CORRECTABLES WITH BETTER ACCURACY" A formal (non-provisional) patent application for a patent application (application serial number 61/597, 504). For the purposes of additional statutory requirements of the USPTO, this application constitutes February 13, 2012. The applications were named Daniel Kandel, Vladimir Levinski, Noam Sapiens, Guy Cohen, Dana Klein, Eran Amit and Irina Vakshtein as inventors. One of the official (non-provisional) patent applications of the US Provisional Patent Application (Application Serial No. ij No. 61/598, 140) of "METHODS FOR CALCULATING CORRECTABLES USING A QUALITY METRIC". [Prior Art] Fabricating semiconductor devices such as logic and memory devices typically involves processing a substrate such as a semiconductor wafer using a number of semiconductor fabrication processes to form various features and multiple levels of the semiconductor device. For example, lithography A semiconductor fabrication process involving transferring a pattern from a mask to a 163677.doc 201245906-resistor disposed on a semiconductor wafer. Additional examples of semiconductor fabrication processes including, but not limited to, chemical mechanical polishing (CMp), etching, deposition, and ion implantation can fabricate multiple semiconductor devices into a single configuration on a single semiconductor wafer and then separate them into individual Semiconductor device. A metrology program is used at various steps during a semiconductor fabrication process to monitor and control one or more semiconductor layer programs. For example, a metrology program is used to measure one or more characteristics of a wafer, such as the size (eg, line width, thickness, etc.) of features formed on the wafer during a program step. The one or more characteristics are measured to determine the quality of the program step. One such feature includes stacking errors. A stack of measurements typically specifies the accuracy of alignment of a first patterned layer relative to a second rounded layer disposed above or below it, or a first pattern relative to one of the same layer disposed on the same layer The accuracy of the alignment of the second pattern. The stacking error is typically determined by one of the structures having one or more layers formed on a workpiece (e.g., a semiconductor wafer). The material structure can be in the form of a grating, and such gratings can be periodic. If the two layers or patterns are formed correctly, the structure of one (four) or pattern tends to be aligned with respect to the structure of the other layer or pattern. If the two layers or patterns are not formed correctly, then the structure on one layer or pattern tends to be offset or misaligned relative to the structure on the other layer or pattern. The overlay error is the alignment error between any of the patterns used in the (4) phase of the semiconductor integrated circuit fabrication. In general, the understanding of variations across wafers and wafers is limited to fixed sampling and therefore the overlay error is only detected for known selected locations. In addition, if one of the measured characteristics of the wafer (such as the overlap error) is not acceptable (eg, 'out of a predetermined range of the characteristic'), then one or more characteristics can be measured. The program's - or multiple parameters are changed such that the additional wafers fabricated by the program have acceptable characteristics. In the case of overlay error, a lithography procedure can be used to adjust the tiling process to maintain the overlay error within the desired range. For example, the stacking measurement can be fed to the calculation of one of the "correctable values (e_etaMes)" and other statistical data that can be used by the operator to better align the lithography tools used in wafer processing. in. Therefore, it is critical to measure the stack-to-error error of the set of metrics as accurately as possible. - Given group # Inaccuracies in the measurement of metrics can be caused by various (four) factors... One such factor exists in the incompleteness of a given f to the target. The target structure asymmetry represents one of the target incompleteness of most important types of stacking inaccuracies. The overlap of target asymmetry and target incompleteness with a given metrology technique can result in (iv) the relative bulk accuracy of the wealth. Accordingly, it is desirable to provide systems and methods suitable for mitigating the effects of stacking on a wafer or a plurality of (four) targets on target asymmetry. SUMMARY OF THE INVENTION A computer-implemented method for providing a quality metric suitable for improving program control in an I-conductor wafer fabrication is disclosed. In one aspect, a method can include, but is not limited to, obtaining a plurality of stacked pairs of metrology 1 signals from a plurality of metrology targets across a plurality of wafers in a batch of wafers, Each stack of metric measurement signals corresponds to one of the plurality of metrics, the measurement 163677.doc 201245906 is obtained by using the first-measurement formula; _ stacked pair metric measurement signal is applied by a plurality of stacked pairs algorithm to determine (4) a plurality of stacked pairs of weights and measures (four) metering 'every-stack pair estimation is determined by using the same in the stacking algorithm; by using the A plurality of stacked pair estimates yielding a plurality of stacked-pair estimated distributions from the plurality of stacked-pair metric-measured signals from the plurality of metrology targets to generate a plurality of stacked-pair estimated distributions; and utilizing the generated plurality of stacked Estimating the distribution to generate a first-plural quality metric, wherein each quality metric corresponds to one of the plurality of stacked pairs of estimated distributions, and each quality metric is produced correspondingly Stacked one on the estimated distribution width - function, for each quality metric is further based on the presence of the target from an associated one of the metrology stacked one function asymmetry of metrology measurement signal. The method can further include identifying, in at least one direction, one of the plurality of metrology targets having a quality metric greater than a selected outlier level from the one of the plurality of quality metrics generated for the plurality of metrology targets One or more metrology targets; determining a plurality of corrected metrology targets 'where the plurality of corrected metrology targets will have the identified one or more metrology targets excluded from a quality metric that exceeds a selected outlier level Excluding the plurality of metrology targets; and using the determined plurality of corrected metrology targets to calculate a set of correctable values. Additionally, the method can include obtaining at least an additional plurality of overlay metric measurement signals from the plurality of metrology targets across the one or more field distributions of the wafers in the batch of wafers, the at least additional plurality of stacks Each of the pair of metrics measured in the metric measurement signal corresponds to the plurality of weights and measures 163,677.doc 201245906 target-measured target, the at least one additional plurality of pairs of measured metrics using at least-additional measurements Recognizing the plurality of pairs of measurement signals by applying the plurality of overlay algorithms to each of the at least one additional plurality of measurements 彳 § Up to >, an additional plurality of stacked pair estimates, each of the at least one additional plurality of stacked pairs estimates is determined by using the equal stack algorithm; by using the plurality of stacked pairs A stacking estimate of each of the at least one additional plurality of stacked pairs of measured signals from the plurality of metrology targets is generated. Solving at least an additional plurality of stacked pairs of estimated distributions; and utilizing the generated at least one additional plurality of stacked pairs of estimated distributions to generate at least an additional plurality of quality metrics, wherein each of the at least one of the plurality of quality metrics Corresponding to one of the at least one additional plurality of stacked pairs of estimated distributions generated, the at least one of the plurality of quality metrics is corresponding to one of the at least one of the plurality of stacked pairs of estimated distributions Generating a function of one of a width of the stacking estimate; by comparing one of the first plurality of quality metrics associated with the first measurement recipe with the at least one additional plurality associated with the at least one additional measurement recipe One of the quality measures is distributed to determine a program measurement recipe. In another aspect, a method can include, but is not limited to, obtaining a metric measurement signal from one or more of one of the plurality of wafers or one of the plurality of fields; The obtained metric measurement signal uses a plurality of overlay algorithm to determine a plurality of stacked pair estimates, and each stack pair estimate is determined by using one of the equal stack algorithms; using the complex stack pair estimate Generating a stack of estimated distributions; and utilizing the generated overlap estimate 163677.doc 201245906 to generate a quality metric of the one or more metrology targets, the quality metric being one of the widths of the generated distribution estimates a function that is configured to be non-zero in the case of an asymmetric stack-to-measurement signal, the quality measure being a function of one of the widths of the generated stack-to-estimate distribution 'the quality metric step-step exists The measure obtained from an associated metrology target measures a function of the asymmetry in the measured signal. A method of computer implementation for providing a set of processing tool correctable values is not disclosed. In another aspect, a method can include, but is not limited to, widely acquiring one of a plurality of metrology targets across one or more of a plurality of wafers in a batch of wafers. a result; obtaining a quality metric associated with each of the acquired overlay metrics; using the acquired overlay metric result of each metric target and the associated quality metric result to determine one of each metric target Modifying the overlay value, wherein the modified overlay value for each metrology target varies with at least one material parameter factor; computing a plurality of material parameter factors a set of correctable values and a set of residuals corresponding to the set of correctable values; Determining a value of a material parameter factor suitable for at least substantially minimizing the set of residuals; and identifying a set of correctable values associated with the at least substantially minimized group residual. Revealing a method for identifying a processing tool that is correctable a method of computer variability in one of the values. In one aspect, the method may include (but is not limited to): obtaining a wafer across the wafer - or One of a plurality of metrology targets of each of the plurality of metrology targets is a pair of weights and weights; a quality metric associated with each of the acquired overlays of the weights; and the acquired stack of each of the weights Determining a plurality of modified overlay values for the plurality of metrology targets by the weighting and weighting result and the quality function of the plurality of metrology targets; the quality function varies with the quality metric obtained for each of the weighting targets; A plurality of modified overlay values determine the set of processing calibratable values of the plurality of randomly selected samples obtained by the plurality of weighted and measured targets and the plurality of randomly selected samples of the associated quality metrics Generating a complex array processing tool to correct values, wherein each of the random samples has the same size; and identifying one of the correctable values of the complex array processing tool. A computer for generating a metrology sampling plan is not disclosed. Method of implementation. In one aspect, a method can include, but is not limited to, self-crossing a wafer in a batch of wafers The plurality of metrology targets of the one or more field distributions acquire a plurality of stacked pairs of metric measurement signals, each of the pair of metric measurement signals corresponding to one of the plurality of metrology targets; by each pair The metric measurement signal is applied to a plurality of stacked pairs to determine a plurality of stacked pairs of each of the plurality of stacked read reading signals, each of the pairwise estimates using the Manned Pair algorithm Determining from the plurality of weights and measures targets by using the plurality of stacked pairs of estimates: the plurality of stacked pairs of metrics measuring each of the measured signals (four) (four) > fabric to generate a plurality of stacked pairs of estimated distributions; The plurality of stacked pairs of estimated distributions are generated to generate a plurality of quality metrics, wherein each quality metric corresponds to one of the plurality of stacked pairs of estimated distributions, and each quality metric further exists in the central ό 4 a function that exists from one of the associated metrology targets, the asymmetry of the defending 詈, the defending h I« 占山重衡; and the use of the metric The target whine < produced by the first plurality of quality metrics 163677.doc 201245906 to generate one or more metrology sampling plan. Signature map) reveals a technique for providing a program map (process - method can include (but not target; computer-implemented method on a wafer. Limited in one aspect): formed on a mask a plurality of agents into a plurality of device-related objects; obtaining a first set of weights and measures results from the plurality of proxy targets after comparing a lithography process and before the first etching process of the wafer Determining, by the first plurality of proxy targets, at least one second set of metrology results from the plurality of proxy targets to determine a first program signature that varies with a location across the wafer; causing the first program signature to Specific program path correlation; measuring a device-related offset after the first etch process by performing a first set of metric measurements on the plurality of device-related targets of the wafer. An offset between a metrology structure and a device of the wafer; determining each additional processing layer that varies with the location of the wafer and one of each additional non-lithographic program path of the wafer An extra-envelope symbol; an additional device-related offset after each additional processing layer and each additional non-lithographic program path of the wafer and the use of the determined first button pattern and such Each of the additional characterization signatures and the first measurement device related offset and the first additional device related offset to generate a program map data library. A method for providing a semiconductor suitable for improvement A system of quality metrics in wafer fabrication. In one aspect, a system can include (but is not limited to) a metrology system configured to self-span one wafer of wafers A plurality of metrology targets of one or more field distributions of the circle obtain a plurality of pairs of metric measurement signals, and each stack of metrics measures the signal pair 163677.doc • 12· 201245906 should measure one of the plurality of weights and measures targets The target, the plurality of overlay metric measurement signals are obtained using a first measurement recipe; and a computing system configured to: apply a plurality of stack calculus calculations for each stack metric measurement signal a method for determining a plurality of stacked pairs of each of the plurality of stacked signals to measure the measured signal, each stacked pair of estimates being determined by using the equalized pair of algorithms; by using the plurality of The stackwise estimate produces a multiplicity of the plurality of pairs of metrics from the plurality of weights and measures (4) to produce a plurality of stacked pairs of estimated distributions; and using the generated plurality of stacked pairs to estimate The distribution is to generate a first plurality of quality metrics, wherein each of the product f metrics corresponds to the one of the plurality of stacked pairs of estimated distributions, and each of the quality metrics corresponds to the generated pairwise estimated distribution One of the width functions 'each quality metric step-step system exists in one of the asymmetry functions from one of the associated metrology targets to the metric measurement signal. It should be understood that the foregoing general description and the following details The present invention is to be construed as illustrative only and not restrictive. BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are incorporated in the claims [Embodiment] Those skilled in the art can better understand the many advantages of the present invention by using the reference map. Reference will now be made in detail to the claims herein Referring generally to Figure 19, a method and system for providing quality control of a program control in a semiconductor wafer fabrication process is provided in accordance with the present invention. Stacking inaccuracy stems from a variety of factors. One such factor includes the presence of an asymmetric target structure (e.g., a bottom target layer or a top target layer) on one or more of a set of sampled overlay weights and targets. The presence of a stack-to-target asymmetry can result in geometric ambiguity in one of the given stack-to-target measurements. Geometry stack ambiguity can in turn lead to systematic error enhancement via nonlinear interaction with the stack pair metrology program itself. The net effect can result in a significant stacking inaccuracy (up to 10 nm). The present invention is directed to a method and system for providing a quality metric that is configured to quantize a stack misalignment associated with each stack of measured signals obtained from various metrology targets of a sampled semiconductor wafer. The invention further relates to utilizing the quality metric to improve program control via outlier selection and weighting recipe improvement or optimization. Further recognizing that after the quality metric generation and analysis, the metric measurement of the present invention can be used to calculate a correction value for correcting a processing tool associated with performing a given procedure on the semiconductor wafer. Known as "correctable value"). As used throughout this disclosure, the term "correctable value" generally refers to information that can be used to correct the alignment of a lithography tool or scanner tool to improve control of subsequent lithographic patterning relative to the overlay effect. In a general sense, the correctable value allows wafer processing to be performed within a predefined desired range by providing feedback and feedforward to improve processing tool alignment. As used throughout this disclosure, the term "weight measurement scenario" refers to a particular combination of a measure tool and a measure object. However, within a given 163677.doc •14·201245906 weights and measures scenario, there are a wide range of possible weights and measures that can be performed under the measurement measurement. The term "wafer" as used in the context of the present invention generally refers to a substrate formed from one-half of a conductor or a non-semiconductor material. For example, a semiconductor or non-semiconductor material can include, but is not limited to, single crystal, gallium antimonide, and indium distorted. The wafer may comprise one or more layers. For example, such layers can include, but are not limited to, a resist, a dielectric material, a conductive material, and a half conductive material. Many different types of such layers are known in the art, and the term wafer as used herein is intended to encompass one of the layers on which all types of layers can be formed. Typical semiconductor programs include wafer processing in batches. As used herein, a "batch" is a group of wafers that are co-processed (e.g., a group of 25 wafers). Each of the wafers in the batch consists of a number of exposure fields from lithography processing tools (e.g., 'stepper, scanner, etc.). Within each field there may be a functional unit in which the multi-grain grain system eventually becomes a single wafer. On the product wafer, the overlay pair of metrology targets are typically placed in the scribe line (for example, placed in the four corners of the field). This system typically does not have an area of circuitry around the perimeter of the exposure field (and outside the die). In some instances, 'putting the overlay target in the deep etched region of the region between the dies rather than the perimeter of the field, β placing the stack on the product wafer in the main grain region Quite rare 'this is because the circuit urgently needs this area. However, 'engineered and characterized wafers (non-product wafers) typically have many overlapping targets throughout the center of the field that do not involve such limitations. One or more layers formed on a wafer may be patterned or unpatterned. For example, a wafer may comprise a plurality of grains, each of which has repeatability Patterned features. The formation and processing of such material layers can ultimately result in a complete device. Many different types of devices can be formed on a wafer, and the term wafer as used herein is intended to encompass a wafer on which any of the types of devices known in the art are fabricated. 1A and 1B illustrate cross-sectional views of a symmetric metrology target and an asymmetry weighing target. It is recognized that the metrology target of Figures 1A and 1B can include a first layer (e.g., processing layer) target structure and a second layer (e.g., anti-surname layer) target structure. For example, as shown in FIG. 1a, the overlay metrology target 1〇〇 may include a processing layer structure 1〇4 and a corresponding anti-reagent layer target structure 102. In addition, due to the symmetrical nature of the metrology target 1 ' 'and thus the first layer (eg, processing layer) target 104 and a second layer (eg, 'resist layer) target associated with the stack of 1 〇 6 good A well-defined 1〇2. In this respect, there is no ambiguity in the measure of the pairwise measure corresponding to one of the idealized weights and measures targets. In contrast, Figure 1B illustrates a non-ideal metrology target 11 that includes one of the target structures 112 having an asymmetry. In this sense, target 11A includes a symmetric processing layer target structure 114 and an asymmetric resist layer target structure 112. The asymmetry in the resist layer target structure 丨丨 2 is due to the unequal corner angles 116 & and 116] 3 of the target structure 112 (ie, the left wall angle 116a is 90. and the right wall angle 116b is not equal to 90. ) formed. Therefore, the treatment layer structure n4 of the target 110 has a well-defined symmetry center, and the resist layer structure 112 of the target 110 does not have a well-defined symmetry center. This symmetry difference between the two layers in turn forms one of the geometric ambiguities in the resist layer structure 112. For example, the stacked pairs defined with respect to the top 118a of the resist layer structure ι ΐ 2 163 677.doc • 16 - 201245906 are different from the overlapping pairs defined with respect to the bottom portion 118b of the resist layer structure. This ambiguity associated with the asymmetric resist layer structure 112, in turn, forms a stack 116 that is not well defined. It is further noted that if a given metric measurement tool is sensitive to the asymmetry of the overlay mark, the presence of asymmetry (such as the asymmetry depicted in Figure IB) may result in an increase in the measured signal. Symmetry, resulting in stack-to-measure inaccuracy. It is well known in the art that the metrology tool settings can affect the outcome of a metric measurement. In this regard, the measured overlay is not defined solely by an offset between the structures belonging to the layer in question. As a first example, when a different focus plane is selected, the measurement results can be systematically changed. As a second example, when a different illumination spectrum is utilized in the measurement, the measurement results can also be systematically changed (i.e., 'the illumination selection changes non-randomly). This equivalence can be attributed to at least two sources. The first source is related to the weighting target itself. For example, as shown in Figure 2, if the target profile is asymmetrical, one of the offsets in the focus plane of the metrology system will produce a visible side offset in one of the weights and measures. In this way, the illumination associated with a first focus length F1 can strongly interact with the top surface of the top layer target structure 2〇2, while the illumination with a focus length F2 can interact strongly with the bottom surface of the top layer target structure 2〇2. . Thus, the overlay measurement 206 between a top structure 202 and the bottom structure 204 can include a corresponding stack of ambiguities 2〇8. Alternately 'as shown in Figure 3' if there is a layer with spectrally dependent absorption characteristics (such as, but not limited to, a polycrystalline germanium or carbon hard mask combined with one of the asymmetric target structures in the buried layer) The stacking pair can vary with the illumination spectrum 163677.doc 201245906. In this way 'according to the particular material in question and the incident illumination, the illumination associated with a first wavelength can only penetrate the layer of material to a first depth (~) n the illumination of the second wavelength can penetrate to another_ Depth (four). Due to this variation, different illuminations will interact with the underlying target structure 304 in different ways. In this regard, the overlay measurement 306 between a top structure 3〇2 and the bottom structure 3〇4 can include a corresponding stack of ambiguities 3〇8. As discussed in further detail herein, one aspect of the present invention provides a system and method suitable for identifying a set of parameters that optimize or at least improve the overlay measurement results of a measurement formulation. It is noted that even if the metrics are systematic, the system name is perfect and does not induce a system offset of the metric result or any other form of systematic bias. One of the most important additional target-related properties in the scatterometry is related to the fact that more than one single cell is performing a metric on the metric target. The weighted ambiguity associated with & cell and crystal stagnation variability is also estimated by the methods described herein. Sources of illumination asymmetry may include, but are not limited to: 0 sidewall asymmetry of the previous layer and the current layer; (1) the height difference between the current layer and the previous layer, iii) the measured layer below The difference in height between the intermediate layers between the layers; iv) the variation due to local defects. The following is a theoretical explanation of the accuracy of the asymmetry-induced stacking. In the case of imaging-based stack-to-weight measurement, the portion of a collected image corresponding to the target layer with asymmetry can be written as: image 2m, 2m (χ~ΟΡΖ) (Equation 1) where ~α+Ι, +1+1,... corresponds to the amplitude of the difference of the electric field of the signal used to form the image 163677.doc -18- 201245906, and nine, nine, ... correspond to the phase of the signal used to form the image. The assumption of signal symmetry can be expressed as: For each n, a + n = amn Due to the geometric center of the phase determination signal of the electric field (Equation 2), the destruction of phase symmetry corresponds to a geometric overlap pair ambiguity. In addition, the destruction of the symmetry of the amplitudes & and ^ results in an overlay inaccuracy that exceeds the geometric ambiguity. For example, where the majority of the measurement error is from the first diffraction order, the overlap inaccuracy Δ is expressed as:

Φ*\ ~Φ~\ -Λ- CC · a+i ~ai a+] + Λ-1 (Equation 3) where α is associated with one or more material parameters associated with the metrology configuration (eg, wavelength, focus, The angle of illumination and the like vary. The parent term in Equation 3 represents geometric ambiguity. It is expected that for a suitable stack-to-target design, one geometric ambiguity of less than 1 nm can be achieved. In addition, the second term of Equation 3 represents the additional inaccuracy associated with the sensitivity of the given metrology technique to the target asymmetry. For some material parameters, a can take a value of 1〇, in which case the second term of Equation 3 produces a stacking inaccuracy of 5 nm or 5 mm in size. For the sake of simplicity, the above set asymmetry of a given stack pair target in only one layer of the overlay target (e. g., the handle layer or the resist layer). Further setting the target structure is actually periodic, which has a period of p. However, it is recognized that similar results can be achieved in the case where there is asymmetry in the two target layers and the target is non-periodic. In the case of a DBO based metrology, the overlay pair consists of a number of grating-on-grid structures, according to the assumptions described above, one of the grating structures on the gratings. The ones are symmetrical and the other are asymmetric. It is recognized that the stack can be self-calculated as one of the differences between the +1st diffraction order and the _th diffraction stage. This differential signal can be expressed as: 2λι· signal l〇c 丨切+1.〇,~7((10)+. 伽)+ (Equation 4) -+ W吣.伽)+...2 where % represents the (rt + w) diffraction from the grating mark on the grating consisting of the πth diffraction order from the asymmetric grating and the mth diffraction stage from the symmetrical grating The amplitude of the stage. As with the imaging-based stack-to-weight measurement, where the majority of the signal error is caused by the first diffraction order from the asymmetric grating, the inaccuracy is in the form: P ( Φ*\. 〇~Φ-\Λ 2^\ 2

(Equation 5) where α re-depends on one or more material parameters associated with the metrology configuration (eg, wavelength, focus, illumination angle, and the like). Here, the first term also corresponds to the geometric ambiguity that is expected to be less than i nm in the case of a well-designed overlay pair. The second item determines the inaccuracy of the ambiguity. In the case of DBO weights and measures, the second term can reach amplitudes greater than or equal to 1 〇. * Note that, in a general sense, DBO metrics can be more sensitive to overlay-symmetric asymmetry than imaging overlay metrics. It is recognized herein that this can be attributed to the fact that the measured signals are averaged over a wider range of wavelengths and angles based on the image-wise stack-to-weights. Since 163677.doc •20· 201245906 is not as accurate as the wavelength and angle drive, the average works to statistically reduce the observed inaccuracies. 4A and 4B illustrate the effect of illumination wavelength and asymmetry angle on a measured pair of targets. As shown in Figure 4A, in the case of a symmetric target, the illumination wavelength has no effect on the deviation of the measured wavelength. In contrast, as shown in Figure 4B, the illumination wavelength has a large impact on the measured stacking in the case of domestic water. Figure 5 illustrates the application of a program control suitable for improving a semiconductor wafer fabrication process. One of the quality metrics is one of the systems 500. In one embodiment, system 500 can include a metrology system 5〇2, such as a stack-to-weight system 504 configured to perform a stack-to-weight measurement at a identified location of semiconductor wafer 506. In another embodiment, the metrology system 5〇2 can be configured to accept instructions from another subsystem of the system 500 to perform a specified metrology plan. For example, metrology system 502 can accept instructions from one or more computing systems 5〇8 of system 500. Upon receiving an instruction from computing system 508, metrology system 502 can perform the overlay weights and measures at the location of semiconductor wafer 506 identified in the provided instructions. As will be discussed later, the instructions provided by computer system 508 can include a quality metric generation program algorithm 512 configured to generate one or more quality metrics associated with each stack measurement of system 502. Figure 6 illustrates a conceptual illustration of a quality metric generation procedure in accordance with an embodiment of the present invention. The quality metric generation program 600 can include applying N number of overlay algorithms 604 to one or more of the acquired metric signals 602 (e.g., obtained using an associated metrology tool) (eg, 163677.doc 201245906 as a pair) Wide algorithm 1, overlay pair algorithm 2 and overlay pair algorithm 3) to calculate N pairs of estimates (eg 1 pair estimate t, stack pair estimate 2 and stack pair estimate 3). Then, based on the calculated span and distribution of the stacked pairs, a quality metric of each of the sampled metrology targets of a wafer can be generated. 6 〇 8 » In this sense, for each stack of metrics Get it. The smear metric 608 is a measure or estimate of the variation of the result of the overlay as a function of the set of applied overlay algorithms. It is noted herein that the quality metric of the present invention provides a quantitative assessment of the accuracy of the overlay results associated with one of a given metrology target. In this sense, each stack value of one of the weights of a wafer is accompanied by a quality metric corresponding to one of the accuracy of the particular stack-to-measurement of the target under discussion. It is further contemplated that the quality metrics of the present invention are applicable to all imaging metrology targets such as, but not limited to, BiB, AIM, BI 〇ss 〇 m, and multi-layer AIMid. Referring again to Figure 5, in another aspect, it is noted that the results of the quality metric generation program algorithm 512 can be used for a variety of purposes. In one embodiment, system 500 can include a stack of measurement recipe optimization programs 514. The overlay pair measurement recipe optimization program 514 is an algorithm configured to calculate an optimal or modified overlay measurement recipe using the set of quality metrics of the present invention as an input. In this regard, the overlay pair measurement recipe optimization program 514 can utilize a plurality of sets of quality metrics obtained from the set of measured metrology targets to determine a measure of the accuracy of the overlay accuracy (eg, illumination wavelength, Filter configuration, polarization configuration, illumination angle and the like). It is further recognized that the results of the recipe optimization algorithm algorithm 514 can be implemented for subsequent stacking measurements on the same wafer or other 163677.doc • 22·201245906 wafers in the batch of wafers. In this sense, the modified or optimized metrology recipe (calculated using the recipe optimization program 5 14) can be fed back to the metrology system 5〇2. Formulation optimization using the resulting quality metrics of the present invention will be discussed in further detail herein. In another embodiment, system 500 can include a metrology target outlier removal program 516 » a metrology target outlier removal program 516 is an algorithm configured to utilize the quality of the set of the present invention. The metric acts as an input to identify and remove outliers. In this regard, the outlier removal program 516 can identify metrology targets having large quality metrics, and thus large overlay inaccuracies, and ignore them for subsequent processing tool correctable value calculation purposes. It will be appreciated that the removal of the outlier target in the correction of the correctable value is advantageous because it focuses more on the target with greater accuracy in the correction of the correctable value, thereby improving the correctable value calculation. The weighted target outlier removal using the quality metrics produced by the present invention will be discussed in further detail herein. In another embodiment, system 5A can include a sampling plan generation program 519. The sampling plan generation program 519 is an algorithm configured to generate one or more stacked versus metrology sampling plans using the generated quality metrics of the present invention as an input. In this regard, the sampling plan generation program 519 forms a sampling plan, such as a sub-sampling plan, that allows for a greater weighting of the identified high quality targets and a lower weighting of the low quality weighting targets. In another aspect, the sampling plan generation program 5 19 can form one of the reduced low quality targets by increasing the sampling rate for a group of identified low quality targets. 163677.doc -23· 201245906 Sampling Plan . The metrology sampling plan generation using the quality metrics produced by the present invention will be discussed in further detail herein. In another embodiment, system 500 can include a correctable value generating program 518. The correctable value generation program 518 is an algorithm configured to generate one or more sets of processing tool correctable values using the generated quality metrics. It is noted that the correctable value calculated by computer system 508 can then be fed back to one of system 500 processing tools, such as a scanner tool or lithography tool. It is further noted that the correctable value generation program 518 can utilize the output of other analytical routines of the present invention to calculate a set of processing tool correctable values. For example, the correctable value generation program 518 of the present invention can utilize the output of the outlier removal algorithm 516 prior to calculating the set of processing tool correctable values. Processing tool calculations are discussed in further detail in this article. The computer system 508 can be implemented in an embodiment - wV from the distressed version of the sample system in one or more of the wafers in the counter-batch wafer by the metrology system 502 (for example, humiliation Xu County &amp; "Distance Weights and Measures System 504" performs a set of volatility values H multiple computer systems _ can be step-by-step configured to receive measurements using the self-reading sample program Value to calculate or identify quality metrics, one = most tatometric formula, a set of high value targets (ie, identify outliers:: = value calculation removed) or - group processing tool to correct values. Whereas a computer system 508 can then transmit instructions to one (four): a tool (eg, a scanner tool or lithography to condition the tool. Another option is and / or the system - or multiple processes:: computer system 508 is available In the case of the supervisor, the residual of the cloth exceeds the predetermined (four). In this sense, 'in the case of - Fu Zhuan' computer system 508 edible j 163677.doc -24- 201245906 "failed" the batch of wafers. Further, may "Reprocessing" the batch of wafers. It will be appreciated that the steps set forth above and throughout the remainder of the invention may be by a single The brain system 508 or (alternatively selected) a plurality of computing systems 5〇8. Further, different subsystems of the system 5, such as the metrology system 5〇2, may comprise at least the steps suitable for implementing the steps set forth above. One of the parts is a computing system. Therefore, the above description should not be taken as limiting of one of the inventions but merely by way of example. In another embodiment, one or more computer systems 5〇8 may indicate from this document One of the set of procedures described is a set of processing tool readable values transmitted to one or more processing tools. Additionally, one or more computer systems 508 can be configured to perform the method implementations set forth herein. Any (any) other step of any of the examples. In other embodiments, computer system 508 can be communicatively coupled to metrology system 502 or another processing tool in any manner known in the art. For example, the one or more computer systems 5〇8 can be coupled to one of the computer systems of a metrology system 502 (eg, a stack of computer systems of the metrology system 5〇4) or coupled to one of the processing tools Brain system. In another example, the metrology system 502 and a processing tool can be controlled by a single computing system. In this manner, the computing system 5〇8 of the system can be coupled to a single metrology-processing tool computer system. The one or more computing systems 508 of the system 5 can be configured to receive and/or retrieve data or information from other systems via a transmission medium that can include one of a wired portion and/or a wireless portion (eg, from a Test results from inspection systems, weights and measures from another metrology system, or from one of the systems such as KLA-Tencors® analyzer 163677.doc • 25- 201245906 Process tool correctable values in this way, the transmission medium can act as A data link between computing system 508 and other subsystems of system 500. In addition, the computing system 5 〇 8 can transmit data to an external system via a transmission medium. For example, computer system 508 can transmit the calculated quality metrics, processing tool correctable values, optimized measurement recipes to a separate metrology system that is independent of the system 500. Computing system 508 can include, but is not limited to, a personal computer system, a large computer system, a workstation, an imaging computer, a parallel processor, or any other device known in the art. In general, the term "computer system" can be used broadly to encompass any device having one or more processors that execute instructions from a memory medium. Program instructions 5 10 that implement methods such as those described herein may be transmitted or stored on the carrier medium by carrier medium 520. The carrier medium can be a transmission medium such as a wire, cable or wireless transmission link. The carrier medium may also include a storage medium such as a read only memory, a random access memory, a magnetic or optical disk, or a magnetic tape. The embodiment of the system 5 illustrated in Figure 5 can be further configured as described herein. Additionally, system 500 can be configured to perform any (any) other steps of any of the method embodiments set forth herein. Figure 7 is a flow chart illustrating one of the steps performed in a method 7 for providing one of the quality metrics suitable for improving program control in a semiconductor wafer fabrication process. In a first step 702, a first selected measurement recipe can be used to obtain a plurality of weights and targets from one of a plurality of wafers or a plurality of field distributions of 163677.doc -26-201245906. The overlay metric measures the measured signal. In this sense, a metric measurement signal can be obtained for each of the plurality of metrology targets. In an embodiment, a metrology program can measure one or more of a plurality of targets across one or more of a plurality of wafers in a batch of wafers (eg, Stacking error). In another embodiment, the weighting system 502 (e.g., overlay metric (4)) of the system 5 previously described herein may be utilized to obtain the one or more metric signals. In this way, the open c丄^, σ, -i are transmitted by a data link (for example, a wired or helmet line signal) to the external computing system using the metrology signal obtained by the metric system 502. 508: In one embodiment, the method stone 700 is included in the one or more of the at least one batch, and the one or more measurements are performed on the measurement point of the circle The equal-to-measure pair metrics... The daily metric measurement measures. As shown in FIG. 7B and FIG. 7C, the measurement location may include one or more of a plurality of bright circles 506. Field 752. For example, as shown in Fig. 7Β Φ.r-·National β, the wafer 506 is formed on the upper field 752. The graph 7PllbH is only shown in Fig. 7B. The specific number and field 752, Y 曰 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍 昍The plurality of fields in the plurality of fields are at least one of the plurality of fields on the other of the first batch of execution waves capable of forming a device structure and/or a shaped material structure formed in the fields In addition, every 1 = t test in the fields may include all of the measurement columns performed during the metrology procedure, one or more different measurements.) In another embodiment, one sample All measurement locations measured in the program 163677.doc •27.201245906 can be used to select multiple targets within each measurement field of the wafer in the batch. For example, 5, as shown in Figure 7C, is formed in Field 752 on a wafer 506 can include a plurality of targets 754. Although a particular number and configuration target 754 in field 752 is shown in Figure 78, the number and configuration of targets 754 in field 752 can depend on, for example, The device formed on wafer 506 varies. Target 754 can include device structures and/or test structures. Thus, in this embodiment, measurements can be performed on any number of targets 754 formed in each field 752. The measurements may also include all measurements performed during the metrology procedure (eg, one or more different measurements). In another embodiment, the results of the measurements performed in the sampling step include variations involving the measurement procedure Information. Can be used in this technology. Knowing any way to determine the variation of the measurement (eg, standard deviation, variation, etc.) because the variation in the measurement will usually indicate the deviation of the program or program deviation, so the number of batches measured in a sampling step can be based on The program or program varies from one to the other. The source of variation identified or determined in this step may include any source of variation, including (but not limited to) overlay variation, variation of other characteristics of the wafer 'batch and batch variation, wafer and crystal Circular variation, field-to-field variation, side-to-side variation, statistical sources of variation, and the like, or any combination thereof. In an additional aspect, a first selected measurement recipe can be utilized from one or more of a wafer The metrology target acquires the one or more metrology signals. Those skilled in the art will recognize that a metrology recipe can include a large number of parameter choices. For example, the measurement recipe can include, but is not limited to, illumination wavelength, illumination angle, focus, filter characteristics, polarization, and the like. In a further aspect of the invention as will be described in further detail herein, portion 163677.doc -28-201245906 may be utilized to optimize or at least improve implementation by system 500 using quality metric results generated by program flow 700. The weighting formula. </ RTI> <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; In a second step 7〇4, a plurality of stacked pairs of metrics can be determined by applying a plurality of overlapping pairs to each of the stacked metric measurement signals to determine a plurality of each of the stacked metric measurement signals of step 3〇2. Stacked pair estimation. In one aspect, a plurality of different algorithms can be applied to each of the weights and signals obtained from each of the selected plurality of metrology targets of the wafer 5〇6 to determine a stack-by-estimation estimate for each of the weights and signals. . For example, the overlay estimation algorithm (4) can each be applied to each of the signals acquired by the set of measured and measured targets from a wafer, and each algorithm calculates an independent stack of each target. In the estimated H-mode, each of the implemented algorithms can be configured to provide one of the symmetric signals in a precise symmetry [...], and in the case of a signal system symmetry, in the plurality of algorithms The various /寅 algorithms provide different estimates of approximate symmetric centers. In this sense, a metric with a non-zero asymmetry will result in a different value for each target of the target measured by the calculus. The stacking pair estimates are generated from each of the metric scales - a stack of estimated distributions to produce, for that matter, the measurement for a wafer in a third step 706 can be utilized by step 704 The measure of the weighted target measured in the measurement signal

163677.doc -29- 201245906 The estimated distribution. In this regard, step 706 forms a stack-to-estimate distribution for each of the measured metrology targets. It is further noted herein that the geometric stack pair ambiguity, along with the stack ambiguity enhancement, is expressed as one of the magnitudes or spans of the magnitude of the estimated distribution of each of the analyzed metrology signals. In this regard, the greater the ambiguity of the stack of a given metrology signal, the greater the span or width of an associated stack pair estimate (generated by the algorithm 1-N of step 704). In a fourth step 708, a plurality of quality metrics can be generated. In one aspect, the complex plurality of quality metric values can be generated using the overlay pair estimate distribution generated in step 706 of routine 700. In this regard, each of the generated quality metrics is associated with one of the stacks of steps 7〇6 for an estimated distribution. Each generated quality metric varies with a corresponding stack of widths or spans of the estimated distribution and represents a measure of ambiguity and inaccuracy associated with a given signal from a given metrology target acquisition 戋 estimate . In another aspect, the quality metric of step 708 is configured to be zero in the case of a fully symmetric signal and is proportional to the overlap inaccuracy associated with a given asymmetric signal. It is noted that in order for a symmetry signal to produce a quality metric of zero, each of the overlay algorithms of step 704 must be configured to produce the same-to-multiply pair estimate of each of the pairs of weights and measures. The quality metric obtained is a measure or estimate of the asymmetry-induced variation of the results as a function of the stack-to-application algorithm applied by the set. In this regard, one of the one or more quality *minimum 贞厪1 values associated with one or more of the weighted target acquisitions is provided for analysis of the asymmetry induced stack FIG. 8A illustrates a wafer map 800 of a stacked pair inaccuracy map 163677.doc 201245906 according to the present invention, illustrating the direction and magnitude of the inaccuracy of the associated stack of pairs of signals. In this sense, the X and Y components of the arrow in the map 8〇〇 correspond to the inaccuracy of the X stack and the γ stack, respectively. The graph illustrates the multiple qualities produced in accordance with an embodiment of the present invention. Measure. Note that each quality metric of Figure 8B corresponds to one of the set of measured metric targets. It is further noted that the quality metric distribution or quality metric "cloud" is wider in the χ γ direction, corresponding to the pair of weights and measures The less accurate the measurement is. As will be discussed in further detail herein, methods and systems for reducing the size of a quality metric cloud include outlier removal and recipe optimization. In another embodiment of the present invention, a stack obtained from each of a set of measured metrology targets may be corrected for a system offset (TISi induced shift; TIS) prior to implementing the quality metric generation program 700. For weights and measures signals. This is particularly advantageous because the quality metric of the present invention is configured to detect any asymmetry present in an acquired metrology signal, including the asymmetry formed by the optics of the metrology system. Thus, for a metrology system 502 having one of the optical components that produce a significant TIS, it is advantageous to first apply a TIS correction to the acquired metrology signal, thereby allowing a more accurate assessment of the target induced overlay inaccuracy. FIG. 9 is a flow chart showing an additional program flow 900 in accordance with another embodiment of the present invention. The program flow 9 involves utilizing the quality metrics generated in the program 7 to identify outliers in the sampled metrology target of one of the wafers. In step 〇2, one or more outlier metric targets of the plurality of metric targets are identified. In this regard, it is known that 163677.doc •31 · 201245906 does not show a measure of the quality metric of one of the quality metrics that deviate significantly from the distribution of one of the other metrics in the sampled target. For example, as shown in Figure 8B, three peripheral quality metrics are identified (e.g., delimited by a circle). The eigenvalue quality metric corresponds to a metric target having a high degree of asymmetry (compared to a non-outlier target) and thus a high stack inaccuracy among the plurality of sampled metric targets. It is recognized herein that the identification of outliers in the quality metric distribution produced in the program 7 can be implemented in any manner known in the art. In this sense, any quantitative analysis suite can be used to identify the weighted target outliers. In addition, a quality metric of a metrology target can be automatically defined as an outlier by a user or via a statistical analysis suite programmed with a threshold definition and analysis routine. In this regard, for example, system 5〇〇 can be programmed to automatically identify outlier quality metrics based on: i) the quality metric of the sampled target exceeds a selected location; or Π) One of the peripheral quality metrics is selected as a percentage (for example, a quality metric of up to 10% is defined as a peripheral). The quality metric distribution (e.g., the quality metric distribution of the avatar) may be displayed on a display device (not shown) of system 500 in the case of the user selected. The user can then manually select a quality metric that is considered to be an outlier. In a second step 904, the set of corrected metrology targets can be generated by excluding the outlier target identified in step 9〇2. In this regard, the set of corrected metrology targets can be formed by the outlier value weighting target identified by the metrology target removal step 902 for the correctable value calculation. In a third step 906, the set of 163677.doc • 32· 201245906 positive metrology targets formed in step 904 is used to calculate the -group processing tool correctable value. In this sense, the set of stack-correctable values is calculated using only the stack-pair information of the set of quantified targets remaining in the set of corrected metrology targets. In another step, the process tool calibratable values calculated via computing system 508 can be transmitted to a processing tool coupled in a s mode (eg, a stepper or scanner using a stack of weights and measures results) The calibratable values of the processing tool (e.g., stepper or scanner) are generally set forth in U.S. Patent No. 7,876,438, issued on Jan. 25, 2011, which is hereby incorporated by reference. A flow chart of an additional program flow 1000 in accordance with another embodiment of the invention. The program flow 1 involves identifying a modified overlay pair measurement recipe or an optimized overlay using the quality metrics generated in the program 7〇〇 Measurement Formulation In a first step 丨〇〇2, at least one additional measurement recipe can be utilized to obtain an additional plurality of overlay metric measurement signals from the plurality of metrology targets. In a second step 丨〇〇 4, wherein the at least one additional plurality of pairs of measurement signals are determined by applying the plurality of overlay algorithms to each of the at least one additional plurality of measurement signals At least an additional plurality of stacked pairs of estimates for each of the at least one additional plurality of pairs of measurement signals from the plurality of metrology targets by using the plurality of stacked pairs of estimates Each of the stacked pairs of estimated distributions produces at least an additional plurality of stacked pairs of estimated distributions. In a fourth step 1008, at least a plurality of stacked pairs of estimated distributions may be utilized to generate at least a plurality of quality metrics. The fifth step 1 〇 1 ' can be distributed by comparing one of the first plurality of quality metrics associated with the first measurement recipe with the at least amount 163677.doc -33 associated with the at least one additional measurement recipe 201245906 Outer multiple quality metrics - distribution to determine - modified or optimized procedure to measure the formula. In this regard, the quality can be performed multiple times with different target measurement recipes by generating cycles for each quality metric The metric generation program finds an improved or possibly optimal stack-to-measurement recipe. For example, in a first cycle, a set can be performed using a first measurement recipe. The measurement is used to find the quality metric of the sampled and measured target. Then, in a second German ring, a stack measurement can be performed using a second measurement formula to find the quality of the sampled measurement target. a metric in which the second formulation changes relative to the first formulation (eg, 'wavelength changes, focus position changes' illumination direction changes, and the like). Then, the quality acquired in each quality metric loop can be generated The plurality of distributions of the metrics are compared to each other to identify a measurement recipe that produces a minimum quality metric distribution. Figure 11 illustrates the use of a first filter and a second filter to obtain a quality metric distribution, as measured by XY quality. The smaller air distribution in the distribution illustrates that the color filter 2 provides a smaller inaccuracy of the corresponding overlay metric measurement. Thus, when selected between filter 1 and filter 2 in subsequent metric measurements, the use of filter 2 will provide increased stacking accuracy and, in turn, improved processing tool correctable values. It is further recognized that this program can be repeated in any number of increments (eg, 1, 2, 3) for any number of recipe parameters (eg, 'wavelength, focus position, illumination direction, polarization configuration, filter configuration, and the like). Or up to and including N times). Figure 12A is a flow diagram illustrating one of the steps performed in method 1200 for providing a process 163677.doc -34 - 201245906 tool correctable value in accordance with an embodiment of the present invention. Program 1200 involves calculating a set of process tool correctable values based on the generated quality metrics of program 7. In a first step 12〇2, one of the plurality of metrology targets across one of the plurality of wafers or one of the plurality of field distributions is acquired for a stack-to-weight measurement result. In one embodiment, the stack-to-weight measurement results for each of the plurality of metrology targets can be obtained by performing one or more overlay metric measurements on the metrology target using the metrology system 5〇2. In a second step 12〇4, one of the quality metrics associated with each of the acquired overlay weights is obtained. In one embodiment, the quality metric can be generated using a program consistent with the various methods and embodiments set forth throughout the present invention. In this regard, after obtaining the weightedness results for each of the set of measurement metrics, the system 500 can calculate a quality metric for each of the specialized metrics. In a third step 1206, it may be determined that one of the scale-to-weights results obtained using each of the weights and measures and the associated quality-measurement result of the associated quality-measurement result is modified by the overlay value. In one aspect, the modified overlay value for each metrology target varies with at least one material parameter factor α of the metrology scene (e.g., dependent on wavelength, focus position, illumination angle, and the like). For example, the modified overlay can be written as: (Equation 6) indicates that the measured stack is accurate = beat meowed +/02 W) where OVLaccurate represents the modified overlay, 〇 vLmeasured for 'and / (4) from Represents a quality function that is dependent on the quality metric (QM) associated with each of the weighting targets. In one embodiment, the product 163677.doc -35 - 201245906 prime function may be represented by a linear function with respect to a material parameter factor a. In this case, the modified overlay can be written as:

^accurate = ^measured ^QM (Equation 7) where (X re-presents the material parameter factor, where QM represents the calculated quality metric or each of the stacked-pair measurements of the present invention. β is recognized herein, Equation 7 The above quality function is not limiting and should only be considered as illustrative. The expected quality function / <ρΜ) can take a variety of mathematical forms. In a fourth step 1208, one of a plurality of material parameter factors can be calculated as a correctable value function and a set of residuals corresponding to the correctable value function. In this regard, the parameter a can be changed and the residual associated with each correctable value function can be calculated for the alpha value. In another aspect, any type of correctable value function known in the art can be performed to fit OVLaecurate. For example, the correctable value function can include a linear or higher order correctable value function. Using one or more of the correctable value functions known in the art, a series of correctable value functions (one per _α value) can be shoddy. For example, a correctable value function and corresponding residuals can be calculated for α!, Α, h, and up to and including αΝ. The function for calculating the correction value is generally described in U.S. Patent No. 7,876,438, issued Jan. 25, 2011, which is incorporated herein by reference. In a fifth step 1210, a value of one of the material parameter factors suitable for at least substantially minimizing the set of residuals is determined. In this regard, the residual associated with each of α丨...αΝ can be analyzed to determine the minimum overlap residual level. For example, Figure 11 illustrates plotting a graph 1220 of one of the set of residual values from step 1208 calculated for each of a number of alpha values 163677.doc - 36 - 201245906 along with a corresponding trend line 1222. As observed in FIG. 11, for the set of given residuals 'approximate - 3.66 one alpha value produces a minimum residual value for a given metrology scenario", in step 1212, the at least substantially minimized group of identities can be identified The set of correctable values associated with the difference. For example, to account for the residual minimization provided in step 121A, a set of correctable values can be calculated using the residual relative to the alpha minimization. It is further contemplated that the alpha identified in step 1210 can be applied during subsequent wafer analysis in the batch of wafers. In another embodiment, the set of correctable values generated in step 1212 can be transmitted to one or more processing tools (e.g., steppers or scanners). In an additional aspect, a TIS correction procedure can be applied to the acquired plurality of overlay metric measurement signals prior to analysis to reduce the TIS induced asymmetry present in the signals. Figure 13 is a flow chart illustrating one of the steps performed in a method 1300 for identifying one of the process tool correctable values. In step 13〇2, a stack-to-weight measurement result for each of the plurality of metrology targets of one or more field distributions of one of the wafers may be acquired. In one embodiment, the stack-to-weights results for each of the plurality of scale targets may be obtained by performing one or more overlay metric measurements on the equals and targets using the metrology system 502. In step 1304, a quality metric associated with each of the acquired overlay weights is obtained. In one embodiment, the 163677.doc -37-201245906 quality metric can be generated using a program consistent with the various methods and embodiments set forth throughout the present invention. In this regard, after obtaining the weights and measures results for each of the set of metrology and metrology targets, system 500 can calculate a quality metric for each of the metrics. In step 1306, a plurality of modified overlay values of the plurality of weighted and quantized targets obtained by each of the weighted and measured targets and the plurality of weighted and measured targets of a quality function are determined. In one aspect, the quality function varies with the quality metrics obtained for each metric target. In an embodiment A, the modified overlay of step 1306 can take the form of the form observed in Equations 6 and/or 7 of the program 12〇〇. It is recognized that the quality function /(^Mj can be in any number of mathematical forms β. In step 1308, the stacked pair of weights and measures obtained for the plurality of weights and targets can be determined by using the plurality of modified pairs of values. And one of a plurality of randomly selected samples of the associated quality metrics, the set of processing tool correctable values to generate a complex array processing tool correctable value, wherein each of the random samples has the same size In this sense, a plurality of random subsamplings can be performed in which a selected number or selected percentage of available data points are generated. In this regard, each of the plurality of subsamples can include the same number of sampled data points ( For example, 90%, 80%, 50%, and the like. For example, a random sample of ν number of data points of 90°/. of the overlay-to-weight measurement result of step 1302 may be performed, wherein each random sample represents a pair One of the available data points is randomly sampled (but with the same number of sampled data points). Then, each of the number of random samples can be used to generate The group processing tool can correct the values. It is further noted that each of the correctable values can be calculated using the same quality function to calculate each of 163677.doc -38 · 201245906. In step 1310, the complex array processing tool can be identified. One of the correction values varies. It is recognized herein that the variation between the correctable values of the set of processing tools calculated in step 1308 indicates its quality. Further recognizing that the N number of correctable values are observed The smaller the variation, the better it can be corrected. This paper notes that the quality value attached to each pair of values is provided to estimate one of the non-random errors in the quantitative test. However, it may have associated with it. It is higher than the error of the stack-to-measurement error. As explained above, the motivation for using it is when the non-random error is higher than the random error. In the case where the non-random error is greater than the random error, it is worthwhile to correct Large random error value (should be remembered that the random error can be averaged to a small value over a large number of measurements) while reducing the overlap value of the non-random error. Figure Illustrated according to the invention An embodiment is directed to a flow chart for generating a metrology sample-method-like method. The program 1400 involves generating a metrology sampling plan based on the generated quality metrics of the program 7. In step 14 And obtaining a plurality of stacked metric measurement signals from a plurality of metrology targets distributed across one or more of the one of the plurality of wafers. In step 14〇4, by each pair The metric measurement signal is applied to a plurality of stacked pairs to determine the plurality of overlapping 罝 罝 罝 罝 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 A plurality of stacked pairs of estimated distributions are generated for estimating one of the plurality of stacked pairs of measured metrics from the plurality of metrology targets. In step 14〇8, 163677.doc •39·201245906 uses the first plurality of quality metrics of the plurality of stacked pairs to estimate the distribution. In step 141 0, the first plurality of quality metrics generated by the plurality of metrology targets can be utilized to generate one or more metrology sampling plans. In this regard, the subsampling plan or the alternative sampling plan can be selected based on the quality metric associated with the set of metrology targets. After identifying the new sampling plan, system 500 can apply the sampling plan during the metrology measurement of subsequent wafers of the batch of wafers. In one embodiment, 'generating one or more of the first plurality of quality metrics generated using the plurality of metrology targets to identify one or more low quality targets, wherein the one or more low Quality objectives are excluded from one or more of the metrology sampling plans produced. In this regard, the low target metrology target can be identified via its corresponding quality metric (in the case of a metrology scenario) and excluded from the sampling plan for subsequent measurements. Figures 1 5A through 1C illustrate one of a series of quality metrics for three different wavelengths of illumination. Figure 1 5A shows the quality of three different wavelengths (white, red, and green) obtained from a stack of 215 targets. Figure 15B shows that 6 targets with the lowest quality have been removed (i.e., 60 targets with the highest quality metric value), leaving 155 targets for sampling (i.e., 'N= 155 samples) The remaining quality metrics after that. In addition, Figure 15C depicts the remaining quality metric values after the 115 targets with the lowest quality values have been removed, leaving 100 targets for sampling (i.e., N = 100 samples). The applicant pointed out that although the above description discusses the target selection from the exclusion of the low-quality I63677.doc •40· 201245906 quality objectives, it also directly selects a set of high-quality targets to be included in the sampling plan. Figures 16A through 16D illustrate the initial overlap of n = 2 15 in the y direction and the residual and R2 values of subsequent adjusted samples of N = 155 and N = l. It is observed directly in Figures 16A through 16D that the residual magnitude is reduced for \= 155 and N = 100 for all of the three wavelengths sampled with respect to the initial N = 215 samples. Similarly, Figures 16A through 16D show a general increase in R2 for each subsampling plan (e.g., N = 100 and N = 155) at each wavelength. Those skilled in the art will recognize that such improved residuals and R2 characteristics will in turn result in improved process tool correctable values that can be fed to an associated processing tool. In one embodiment 'using the first plurality of quality metrics generated by the plurality of metrology targets to generate one or more metrology sampling plans to identify one or more low quality targets, wherein the one or more lows are The quality goal is excluded from the one or more metrology sampling plans generated and the one or more low quality targets are replaced with one or more additional metrology targets that are close to the one or more low quality target locations. In this regard, the low target metrology target can be identified and excluded from the sampling plan for subsequent measurements via its corresponding quality metric (in the case of a metrology scenario), while being close to the excluded low quality target Additional targets for positioning are inserted into the sampling plan utilized on subsequent batches of the batch. 18A-18B illustrate the residual and R2 values of the initial and the adjusted samples in the X and y directions, which replace the low quality target with a target close to the excluded low quality target. . Figure 8 A Figure 163677.doc 201245906 illustrates the reduction of the residual level in either the χ direction and the y direction after replacing the low quality target with the target of proximity positioning. Similarly, the graph illustrates that one of the R2 values increases after replacing the low quality target with a near-targeting goal. In addition, those skilled in the art will recognize that such improved residuals and R characteristics, in turn, will result in improved process tool correctable values that can be fed to an associated processing tool. Program 1400 can further include utilizing the first A plurality of quality metrics for identifying a plurality of quality regions of the wafer, each of the quality regions comprising a metrology target having substantially similar quality levels. For example, as shown in Fig. 19, a first quality zone 19〇2 to 1906 can be identified such that all of the targets 1901 contained therein have substantially the same quality. In another embodiment, the sampling rate implemented during a subsequent stack-to-weight program may vary with the identified quality region. For example, the number of targets sampled in Zones 〇2, 丨904 and 1 906 may depend on the quality level of the targets contained in their zones. In another aspect, in the initial sampling plan, the metric measurement program can include measuring a full wafer map, measuring a full batch of spectra, or measuring a batch of wafers. After defining a sampling plan for the first wafer based on its quality metric, the identified sampling plan can be applied to the next wafer while also providing a predefined constraint. For example, the constraint can be composed of several sub-constraints, and Each sub-constraint will trigger a need for a minor change to the sampling plan. This program can continue to accumulate to subsequent batches. These constraints can be based on the quality metric of the measured wafer/wafer statistics (eg, standard deviation, average, range, etc.) while taking into account the sample size. 163677.doc -42· 201245906 Referring now to Figures 20A-20F, a method and system for providing a program map map is set forth in accordance with an embodiment of the present invention. In this regard, a program map map solution (hereinafter referred to as "the pr〇cess signature mapper") can help to improve the patterning program control in the fabrication of semiconductor devices. Figure 20A illustrates An embodiment of a lithography program control loop is illustrated. The lithography program control loop can include, but is not limited to: a reticle 2, a scanner 2004, and a program tracking module 〇〇6 configured to track a plurality of non-lithographic programs Path 2008; - metrology system 2〇1〇; and an advanced program control (APC) system 2012. In a typical lithography control loop 2, a lithography process on a wafer that has been exposed to both the previously processed layer and the current processing layer (as well as other processes such as etching and polishing on previous layers) The metrology target execution is intended to be fed back to the metric measurement 2010 in the control loop of the lithography program. Although the purpose of the lithography program is to enable correction of lithography deviation, the actual measurement overlay can be biased by the effects associated with the non-lithographic program 2〇〇8 and will depend on the particular wafer. The horizontal path. (10) herein recognizes that the bias is considered a measure of ambiguity, as previously described herein. At other skill levels, the metrology data collected from wafers from an arbitrary prior program path is used by the APC system 2012 for calculation and then fed to the lithography exposure program (ie, scanner 2〇〇4). Historical average correctable value. One object of the present invention is to quantify the dependence of a measured stack on a particular program path of a wafer. This program is called a program graph map. Figure 20B illustrates a program flow for a program map map in accordance with an embodiment of the present invention. In step 2〇12, after a lithography procedure, 163677.doc -43- 201245906 uses a stack of weights and measures (such as 'imaging weights or scatterometry') before the faceting procedure and after a buttoning procedure. A plurality of proxy targets formed on a reticle (test reticle or product reticle) are measured. In this regard, as shown in FIG. 20C, one of the first set of metrology results 2022 and the wafer can be obtained from a plurality of proxy targets by comparing one lithography procedure and one of the first etching processes of the 曰a circle. The first etch process is followed by at least one second set of metrology results 2024 obtained from the plurality of proxy targets (eg, determining the difference therebetween) to determine a first program signature that varies with the position across the wafer. 2026. Additionally, the first program round can be correlated to a particular program path, as shown in Figure 20C. In this regard, the two metrics that vary with the position across the wafer can be calibrated to measure the variation between 2021 and 2〇23 (formerly known as DI-FI bias) to specify a specific program path, including ( But not limited to, program sequences, identification codes for specific processing tools, time stamps, and the like. In step 2014, a device related offset can be measured after the first etch process. In this regard, the device-related offset can be measured by performing a first set of metric measurements on the plurality of device-related targets of the wafer after the first etch process. It is noted herein that the device-dependent offset of the present invention represents an offset between a metrology structure and a device of the wafer, wherein the metrology feature typically has a different (substantially greater than) device feature size. In another embodiment, as shown in FIG. 20D, a metric measurement 2034 (eg, CD-SEM or AFM amount) may be performed by a device-related target that is characteristic of both the wafer-containing device and the metrology-like size. Measure) to measure the device related offset. Furthermore, this weighting step is performed after etching. Device-related quantities 163677.doc • 44· 201245906 The example of the test is generally described in “Improved Overlay Metrology Device Correlation on 90-nm Logic Processes j by Ueno et. al,

Metrology, Inspection, and Process Control for Microlithography XVIII, edited by Silver, Richard M. SPIE, Volume 53 75, pp. 222-231 (2004), which is incorporated herein in its entirety by reference. Further, a program map map can be generated using each of the determined first etch signature and the additional etch signature and the first gauge relative offset and each additional device offset. In this regard, the results of step 2012 and/or step 2014 can be stored in the memory of the system and used to form a library of program signature maps. In step 2016, steps 2012 and 2014 may be repeated for each layer and for each non-lithographic program path of the control loop. In this regard, step 2〇16T includes an additional button pattern for each additional processing layer that varies with the position of the wafer and an additional non-lithographic program path of the mother of the aa circle. In addition, step 2016 can include measuring an additional device-related offset after each additional processing layer and each additional non-lithographic program path of the wafer. Since the list of possible permutations of the program paths may be large, the set of program paths selected for characterization is defined based on the matching and inherent variability within the family of processing tools. If the processing tool exhibits a good match, it may not be necessary to measure the independent program path for each-matched tool. In another step, the program can be periodically updated to keep the program's symbol database up-to-date, allowing for performance monitoring of program deviations. Figure 20E illustrates one embodiment of a program map map library in a control loop in a lithography program 163677.doc • 45- 201245906, in accordance with an embodiment of the present invention. The program control loop 2040 can include, but is not limited to: a stacking information and design rules module 2042 that computes the metrology module 2〇44; a mask 2〇46 that is configured to receive the proxy target design and Device related target design information; 1 tracing machine 2048; - tracking module 205〇 configured to track a plurality of non-diagram programs 2056, metrology system 2〇52; program image map device 2〇54, group State to receive the weighting result from agent target 2058 and device related target 2〇6〇; and an APC 2062. Once the program mapper data set has been obtained, it can be used in the ApC control loop 2062. As shown in Figure 20E, the metrology data is delivered to a program circular locator 2054 that implements program-specific calibration for each batch or per wafer path. This corrected data is then transmitted to an APC-loop 2062 that produces a historical average correctable value, which is generated using methods known in the art. In this manner, the program map map module 2054 should be compatible with the existing Apc infrastructure of currently existing production equipment. In a general sense, one of the program offset forms may be varied with field and wafer position or, more specifically, in the form of a standard correctable value associated with the degree of freedom of correction of the processing tool. 54 calculated path dependent program signs. Figure 20F illustrates an embodiment of a program signature map in accordance with an embodiment of the present invention. All correction terms are known, based on the calibration data 〇 VLppn(x, y) generated from the measurement of the proxy target of the post-measurement processing for each of the n program paths (step 2052) and The measurement of the device-related target after etching on the CD-SEM or AFM writes an equation representing a given pair of devices at any point (x, y) at I63677.doc -46 - 201245906 on the wafer. In the simplest case, the device-dependent correction is constantly offset from one of the wafer or field position or program path due to the feature size dependence of the processing characteristics. However, in more general cases, wafer and field locations and lithography procedures need to be considered. By way of example, if the offset between the characteristics of the device size and the size of the weights is due to scanner aberration induced pattern placement errors, then the offset will likely vary across the slit of the scanner. Therefore, for each of the m lithography paths, device related data 〇VLlpm(x, y) needs to be collected (step 2054). In an alternate embodiment, the device-related data may even be measured for each of the non-lithographic program paths. In all cases, the next step is by conventional exposure tools as is known in the art. The correction value model generates a standard set of correctable values CPPn &amp; ClPin from each of the specific data sets (step 2056 and step 2〇58) the correctable value modeling is generally described in "Fundamental pHneiples Qf"

Optical Lithography, by Chris Mack, Wiley &amp; sons, 2007 is hereby incorporated by reference in its entirety. In step 2〇6〇, a program graph mapper for each program/lithographic path arrangement represented by the following equation is generated to correct the value: Then, as shown in FIG. 2GF_, the data is stored in the program graph. Tina: In the database 2062. It should be noted that the correctable values recited above produce * values: contain several different possible modelling scenarios. For example, the calibratable can include only the standard set of linear crystal values of the translation in Uy, wafer and field level rotation, and wafer and field level. Another 163677.doc 47- 201245906 exposure tool and its freedom of correction Degrees, which may include higher order terms such as trapezoids and other higher order wafer and field terms. For program correctable values, regardless of the lithography correctable value, it may be appropriate to produce a particular correctable value that most effectively describes the associated program offset. It will now be explained - typical production weights and measures and program control scenarios. At this stage, weights and measures are performed on a product wafer. Depending on the correctable value model and the Apc method, sampling can be based on different sampling plans. The product wafer data 〇VLpWm n can then be modeled by the standard methods described above to produce the production from the lithography path m and the program path n and subsequently to the program map map. The circle can be corrected to the value CpWm,n. The program map extractor subtracts the program map spectrometer correctable value from the current product wafer correctable value to generate a corrected product wafer correctable value c'pwn&gt;m represented by the following equation: C Pwn,m = Cpw„,m-Cpsrn„,m (Equation 9) then 'transfer the corrected product wafer correctable value to the APC system and the program controls the af usage (such as by means of an exponential window moving average method or in the art) The responsibilities of the _ _ other suitable technology) continue. All of the methods set forth herein may include depositing the results of one or more of the method embodiments in a storage medium. These results may include the . It can be stored in any of the ways known in the art. The storage medium may comprise any of the storage media or materials known in the art as described herein. After the results have been stored, the results can be accessed in the storage medium and used by any of the methods or system embodiments described herein, formatted 163677.doc • 48· 201245906 for use in one The user displays that by any software module, method or system, etc., "for example, after the method generates a subsampling plan, the method may include storing the subsampling plan in one of the storage media. In the weight loss formula. Additionally, the results or outputs of the embodiments set forth herein may be stored and accessed by a metrology system, such as a CD SEM, such that a metrology system may use the subsampling plan for metrology, assuming that the metrology system understands the output file . In addition, the results may be stored "permanently", "semi-permanently", temporarily or at a certain time period. For example, the storage medium can be a random access memory (RAM) and the results do not have to persist in the storage medium indefinitely. It is further contemplated that each of the embodiments of the methods set forth above may include any other steps of any other method described herein. Additionally, each of the embodiments of the methods set forth above can be performed by any of the systems set forth herein. Those skilled in the art will appreciate that there are various vehicles (e.g., hardware, software, and/or levitons) to which the procedures and/or systems and/or other techniques described herein may be affected, and preferably. The vehicle will vary depending on the context in which the programs and/or systems and/or other technologies are deployed. For example, if an implementer determines that speed and accuracy are extremely important, the implementer may select - the primary hardware and / or the striker carrier; the other option is that if flexibility is extremely important, then The implementer may select - the primary software implementation 'or ' or another option is that the implementer may select a hardware-software and/or a certain combination of the body. Accordingly, there are several possible vehicles to which the procedures and/or devices and/or other techniques set forth herein may be affected, none of which is inherently superior to the other, 163677.doc -49-201245906, Any vehicle to be utilized is selected based on one of the context in which the vehicle will be deployed and the specific concerns of the implementer (eg, speed, flexibility, or predictability), either of which may vary. Those skilled in the art will recognize that optical stereotypes of embodiments will typically employ optically oriented hardware, software, and/or a lept. Those skilled in the art will recognize that the devices and/or procedures described herein are described in the context of this disclosure, and that the use of engineering practices to integrate such illustrated devices and/or procedures into a data processing system is common. . That is, at least a portion of the devices and/or procedures set forth herein may be integrated into a data processing system via a reasonable amount of experimentation. Those skilled in the art will recognize that a typical data processing system typically includes one or more of the following: a system unit housing; a video display device; a memory such as volatile and non-volatile memory; , such as a microprocessor and digital signal processor; computing entities, such as operating systems, drivers, graphical user interfaces, and applications; one or more interactive devices, such as a trackpad or screen; and/or control system, A feedback loop and control motor are included (eg, feedback for sensing position and/or rate; control motor for moving and/or adjusting components and/or quantities). A typical data processing system can be implemented using any suitable commercially available component, such as those typically found in data computing/communication and/or network computing/communication systems. The subject matter described herein often illustrates different components that are included in or connected to different other components. It should be understood that the architectures depicted are merely illustrative and that many other architectures that achieve the same functionality can be implemented. In a conceptual sense, any group that achieves the same functionality is effectively "associated" to achieve the desired functionality. Thus, regardless of the architecture or the intermediate components, any two components herein combined to achieve a particular functionality are considered to be "associated" with each other to achieve the desired functionality. Similarly, any two components so associated can be considered as "connected" or "coupled" to each other to achieve the desired functionality. Achieve the desired functionality. Specific examples of coupling may include, but are not limited to, components that may be physically and/or physically interacting and/or components that may interact wirelessly and/or wirelessly and/or interact logically and/or may be logically The component of interaction. Although specific aspects of the subject matter described herein have been shown and described, it will be apparent to those skilled in the art that the subject matter of the disclosure herein In the case of a change and modification, and therefore, the scope of the patent application is intended to cover all such changes and modifications as such changes and modifications as the true spirit of the subject matter described herein Within the bounds of the general. Further, it is to be understood that the invention is defined by the scope of the accompanying claims. While the invention has been described with respect to the specific embodiments of the present invention, it is understood that various modifications and embodiments of the invention may be made without departing from the scope and spirit of the invention. Therefore, the scope of the invention should be limited only by the scope of the accompanying claims. It is believed that the present invention and its various advantages are understood by the foregoing description of the invention and the invention may be Change I63677.doc •51 · 201245906 and the meaning of the following patent application scope. The recitations are merely illustrative and encompass such changes. BRIEF DESCRIPTION OF THE DRAWINGS Symmetrical Target Asymmetry Objective FIG. 1A illustrates a cross-sectional view of a metrology target having a structure in accordance with an embodiment of the present invention. Figure 1B illustrates a cross-sectional view of a metrology target having a standard structure in accordance with an embodiment of the present invention. 2 illustrates a cross-sectional view of the effect of a metrology target having one asymmetric target structure and illumination having more than one focus, in accordance with an embodiment of the present invention. Figure 3 illustrates a cross-sectional view of the effect of one of the asymmetric target structures and the illumination having more than one wavelength, in accordance with an embodiment of the present invention. 4A illustrates modeled data obtained from a symmetric target structure at multiple wavelengths in accordance with an embodiment of the present invention. Figure 4B illustrates modeled data obtained from an asymmetric target structure at multiple wavelengths in accordance with an embodiment of the present invention. Figure 5 illustrates a block diagram of a system suitable for providing a quality metric suitable for improving program control in a semiconductor wafer fabrication in accordance with an embodiment of the present invention. Figure 6 illustrates a conceptual diagram of a method suitable for providing a quality metric suitable for improving program control in the fabrication of a semiconductor wafer in accordance with an embodiment of the present invention. Figure 7A illustrates a flow chart of one of the methods suitable for providing one of the quality metrics of program control suitable for improved semiconductor wafer fabrication in accordance with an embodiment of the present invention. Figure 7B illustrates a top plan view of a semiconductor wafer having one of a plurality of fields in accordance with an embodiment of the present invention. Figure 7C illustrates a top plan view of a semiconductor wafer having a plurality of metrology targets and each of the plurality of fields of the wafer, in accordance with an embodiment of the present invention. Figure 8A illustrates a set of modeled overlay inaccuracies data as a function of position on the surface of the wafer in accordance with an embodiment of the present invention. Figure 8B illustrates a set of modeled quality metrics obtained from a plurality of metrology targets in accordance with an embodiment of the present invention. Figure 9 illustrates a flow diagram of one method for metrology outlier removal based on an alternate embodiment of the present invention. Figure 10 illustrates a flow diagram of one of the methods for stacking measurement recipe enhancements in accordance with an alternate embodiment of the present invention. Figure 11 illustrates a set of modeled quality metrics obtained from a plurality of metrology targets at two different wavelengths in accordance with an embodiment of the present invention. Figure 12A illustrates an alternative embodiment for processing a worker in accordance with the present invention.

Alternative embodiments follow the parameter - group data. An alternate embodiment is for identifying a flow chart of one of a plurality of sets of methods. Figure 13 illustrates one of the variations of the process tool correctable values in accordance with the present invention. 163677.doc • 53· 201245906 illustrates a method for generating one or more metrology sampling plans in accordance with an alternate embodiment of the present invention. One of the flowcharts. 15A through 15C illustrate a plurality of sets of data representing quality metric cloud data at different low quality target removal levels in accordance with an alternate embodiment of the present invention. Figures 16A through 16D illustrate a plurality of sets of data for residual data and &amp; 2 data at different low quality target removal levels in accordance with an alternate embodiment of the present invention. Figure 17B illustrates a plurality of sets of data for quality metric cloud data with and without low quality target replacement in accordance with an alternate embodiment of the present invention. Figures 18A-18B graphically illustrate sets of data for residual data and R2 data with and without low quality target replacement in accordance with an alternate embodiment of the present invention. Figure 19 illustrates a top view of a plurality of target quality regions in accordance with an alternate embodiment of the present invention. Figure 20A illustrates a block diagram of a lithography control loop in accordance with an alternate embodiment of the present invention. Figure 20B illustrates a flow diagram of one of the methods for providing a program map map in accordance with an alternate embodiment of the present invention. Figure 20C illustrates a conceptual diagram of a lithography/post etch bias after a change in position on a wafer in accordance with an alternate embodiment of the present invention. Figure 20D illustrates one of the device related metrics performed to quantify the offset between the metrology structure and a device in accordance with an alternate embodiment of the present invention. 163677.doc • 54· 201245906 Conceptual diagram. Figure 20E illustrates a block diagram of one of the lithography control loops equipped with a program map maper in accordance with an alternate embodiment of the present invention. [Main Element Symbol Description] Fig. 20F illustrates a flow chart of one of the methods for generating a program map map correctable value in accordance with an alternative embodiment of the present invention. 100 stacks of metrology targets 102 Corresponding to the anti-money layer target structure 104 Processing layer structure 106 Stacked pairs 110 Non-ideal metrology targets 112 Target structures 114 Processing layer structures 116a Corners 116 Stacks 116b Corners 118a Anti-surname layer structure top 118b Bottom structure of anti-surname layer structure 202 top structure 204 bottom structure 206 stack pair measurement 208 stack pair ambiguity 302 top structure 304 bottom structure 163677.doc 201245906 306 308 500 502 504 506 506 508 510 512 514 516 518 519 520 600 602 604 608 752 754 1220 1222 1901 Stack-to-measurement stack-to-ambiguity system metrology system stack-to-weight system semiconductor wafer semiconductor wafer computing system program instruction quality metric generation program algorithm stack-to-measurement formula optimization program metrology target off-group value Remove program correctable value generator program sampling plan generation program carrier media quality metric generation program metrics balance signal pair algorithm quality metric field target curve trend line target 163677.doc -56- 201245906 1902 first quality zone 1904 first quality District 1906 First Quality Zone 200 0 Typical lithography program control loop 2002 reticle 2004 scanner 2006 program tracking module 2008 non-lithography program 2010 lithography program 2012 advanced program control (APC) system 2021 metrology target 2022 first set of metrics results 2023 metrics target 2024 Second Group Weights and Measures Results 2026 First Program Diagram 2034 Weights and Measures Targets 2040 Program Control Loops 2042 Stacking Information and Design Rules Module 2044 Calculation Weights and Measures Module 2046 Mask 2048 Scanner 2050 Tracking Module 2052 Weights and Measures System 2054 Program Signs Mapper/Program Graph Program Module 163677.doc -57- 201245906 2056 Non-lithography program 2058 Agent target 2060 Device related target 2062 Advanced program control ύλΐ First depth &lt;1λ2 Another depth FI First focus length F2 Focus length 163677.doc -58-

Claims (1)

201245906 VII. Scope of Application: ι_ A computer-implemented method for providing a quality metric suitable for improving program control in a semiconductor wafer fabrication, comprising the following procedures: Self-crossing a wafer in a batch of wafers The plurality of metrology targets of the one or more field distributions obtain a plurality of stacked pairs of metric measurement signals, and each of the plurality of pairs of metric measurement signals corresponds to one of the plurality of metrology targets; the plurality of pairs of metrics The measurement signal is obtained by using a first measurement formula; determining a plurality of each of the plurality of overlay measurement metrics by applying a plurality of overlay algorithms to each of the overlay metric measurement signals a stack pair estimate, each stack pair estimate is determined using one of the equal stack algorithms; generating the plurality of overlay metrics from the plurality of weights and targets by using the plurality of stack pairs to estimate One of each of the stacks estimates the distribution to produce a plurality of stacked pairs of estimated distributions; and utilizes the resulting plurality of stacked pairs to estimate the distribution纟 a first plurality of quality metrics, wherein each quality metric corresponds to one of the plurality of stacked pairs of estimated distributions, and each of the _ quality metrics corresponds to a width of the generated pairwise estimated distribution The function, each quality metric is further a function of the asymmetry in the overlay metric measurement signal from the associated metric target. Product 2. A method of obtaining a plurality of stacked pairs of one of the wafers in the wafer, such as the method of claim 1, wherein the plurality of metrological measurements of the self-crossing or the plurality of field distributions include: 163677.doc 201245906 A stack of metric measurements is performed on a plurality of metrology targets across one or more of the field distributions of one of the wafers. 3. The method of claim 1, further comprising: performing a systematic offset (TIS) correction procedure on at least some of the plurality of stacked metric metric signals obtained. 4. The method of claim 1, wherein each of the plurality of generated quality metrics is configured to identify a stack of deviations from a metric target having a substantially symmetrical target structure. 5. The method of claim 1, further comprising: identifying, by the at least one direction from the plurality of quality metrics generated for the plurality of metrology targets, having a greater than - selected distance Group value level - one or more weighting metrics of the quality metric; determining a plurality of corrected metric targets, wherein the plurality of corrected metric targets will have a quality metric that deviates from one of the selected outlier levels Identifying—or multiple metrology targets are excluded from the plurality of metrology targets; and utilizing the determined plurality of corrected metrology targets to calculate a set of correctable values. 6. The method of claim 1, further comprising: transmitting the set of correctable values to - or a plurality of processing tools. 7. The method of claim 1, further comprising: obtaining at least an additional plurality of overlay metrics from the plurality of metrology targets of the one or more field distributions of the wafer in the batch of wafers 163677 .doc -2- 201245906, the at least one additional plurality of pairs of metrics measuring the signal-to-stack metric measurement signal corresponding to the plurality of metrology targets, the at least one additional plurality of pairs of weights and measures The measurement signal is obtained using at least one additional measurement recipe; the at least one additional plurality of stacks is determined by applying the plurality of overlay algorithms to each of the at least one additional plurality of measurement signals At least an additional plurality of stacked pairs of each of the measured signals, each of the at least one additional plurality of stacked pairs being determined using one of the equalized pairs of different methods; The plurality of stacked pair estimates yields at least one additional complex of the one of the at least one additional plurality of pairs of measured signals from the plurality of metrology targets a stack of estimated distributions; and utilizing the generated at least one additional plurality of pairs of estimated distributions to generate at least an additional plurality of quality metrics, wherein the at least one of the plurality of quality metrics has a maternal quality metric corresponding to the at least one additional complex number generated a stackwise estimated distribution of the plurality of stacked pairs of estimated metrics, each of the at least one additional plurality of quality metrics being one of the at least one additional plurality of stacked pairs of estimated distributions corresponding to a width of the generated pairwise estimated distribution a function; by comparing the distribution of the first plurality of quality metrics associated with the first measurement recipe with the distribution of the at least one additional measurement recipe &gt; one of an additional plurality of quality metrics Determine a program measurement recipe. 8. The method of claim 7, wherein the at least one of the first plurality of quality metrics associated with the first measurement 163677.doc 201245906 formula is associated with the at least one additional measurement recipe. Determining, by one of the plurality of quality metrics, a program measurement recipe includes: distributing and correlating to the at least one additional measurement recipe by comparing one of the first plurality of quality metrics associated with the first measurement recipe The at least one additional plurality of quality metrics are distributed to determine an optimal measurement formula 'the optimal measurement recipe is associated with the plurality of quality metrics of the first plurality of metrics and the at least one additional plurality of metrics have along at least one One of the directions is substantially minimally distributed. 9. The method of claim 7, wherein at least one of the first measurement recipe and the at least one additional measurement recipe comprises: an illumination wavelength, a filter configuration, an illumination direction, a focus position, or At least one of the polarization configurations. 10. A computer implemented method for determining a quality metric suitable for improving program control in a semiconductor wafer fabrication: one or more of one or more of the wafers in a batch of wafers The metrology target acquires a metric measurement signal; and applies a plurality of superposition pairs to determine a plurality of superposition pairs by using the obtained metric measurement signal, and each stack estimation algorithm utilizes the equalization algorithm Determining; using the plurality of stacked pair estimates to generate a stack of estimated distributions; and utilizing the generated stacked pair of estimated distributions to generate a quality metric of the one or more metrology targets, the quality metric being generated A function of one of the widths of the stack of estimated distributions, the quality metric being configured to be non-zero in the case of an asymmetric stack 163677.doc 201245906 for the measurement signal, which is an estimate of the quality pair One of the functions of asymmetry. Yu Zi Law, which includes: Obtaining one of the quality metrics associated with each of the acquired overlay metrics; determining the plurality of metrics of the plurality of metrology targets using the acquired overlay metrics and the associated quality metrics for each metric target Modifying the overlay value 'where the modified overlay function is a function of at least one material parameter factor; generating one of a plurality of material parameter factors processing tool correctable value function and a set of residuals corresponding to the processing tool correctable value function Determining a value of the material parameter factor suitable for at least substantially minimizing the set of residuals; and determining a set of process correctable values associated with the set of at least substantially minimized residuals. 12. The method of claim 11, wherein the obtaining one of the quality metrics associated with each of the acquired overlay weights and measures comprises: utilizing a quality metric generation program to generate each acquired overlay 163677.doc 201245906 A quality measure that measures one of the results. 13. The method of claim 11 wherein the obtaining of one of the plurality of metrology targets across one of the plurality of wafers or the plurality of field distribution targets is a pair of weights and measures. - Each of the plurality of metrology targets of one or more field distributions in one of the wafers - the metrology target execution-stacking measurement. 14. The method of claim π, further comprising: transmitting the set of processing tool correctable values associated with the set of at least substantially minimized residuals to one or more processing tools. 15. The method of claim 11, further comprising: performing a system offset (Tis) correction procedure on the at least one of the plurality of pairs of metric measurement signals obtained. 16. The method of claim 11, wherein the modified overlay function is a linear function of at least one material parameter factor. 17. The method of claim U, wherein the modified overlay function is a function of at least one of an illumination wavelength, a focus position, an illumination direction, and a polarization configuration. A computer-implemented method for identifying a variation of one of the correction values of a processing tool, which includes: one = one of a plurality of wafers - or a plurality of field distributions; One of each of the weights and measures targets is a pair of weights: a quantity of quality exhibited by each of the acquired pairs of weights and measures, I63677.doc 201245906 Using each of the weights and measures of the target ^ ^ σ #^ Λ The obtained pair of weights and measures results and the number of the weighted and measured targets are modified by the stipulations of the metrics. One of the quality metrics obtained by the weighting and measuring target; by using the plurality of repaired 咕 咕 对 对Generating a complex array of virtual and ugly values for each of the plurality of randomly selected samples of the plurality of weighted weights and the plurality of randomly selected samples of the associated quality metrics The levee tool can correct the value, wherein each of the random samples has the same size; and identify one of the correctable values of the complex array processing tool. 19. The method of claim 18, The obtaining of one of the quality metrics associated with each of the acquired overlay weights and measures comprises: utilizing a quality metric generation program to generate a quality metric for each of the acquired overlay metrics results. The method, wherein the obtaining of one of a plurality of metrology targets across one or more of the plurality of wafers in one of the plurality of wafers is a stacking of the weights and measures, including: one of the plurality of wafers across the wafer Each of the plurality of metrology targets of the one or more field distributions performs a man-pair measurement for each of the metrology targets. 21. A computer implemented method for generating a metrology sampling plan, comprising: A plurality of metrology targets of one or more field distributions of one of the wafers acquires a plurality of overlay metric measurement signals, and each stack metric measurement signal corresponds to one of the plurality of metrology targets 163677 .doc 201245906 balance target; determining the complex number of pairs of metrics in the measured signal by applying a plurality of stacked pairs to each pair of metric measurement signals a plurality of stacked pair estimates, each of which is determined by one of the equal stack algorithms; the plurality of stacks from the plurality of weights and targets are generated by using the plurality of stacked pairs Generating a plurality of stacked pairs of estimated distributions for each of the metrics of the measured signals; generating a first plurality of quality metrics using the plurality of stacked pairs of estimated distributions, wherein each quality metric corresponds to And estimating a distribution of the plurality of stacked pairs of estimated distributions, each quality metric further being a function of asymmetry in a pair of metric measurement signals from an associated metrology target; And generating the one or more metrology sampling plans using the first plurality of quality metrics generated by the plurality of metrology targets. 22. The method of claim 21, wherein the generating the one or more metrology sampling plans using the first plurality of quality metrics generated by the plurality of metrology targets comprises: utilizing the plurality of metrology targets to generate the first A plurality of quality metrics are generated to generate one or more metrology sampling plans to identify one or more low quality targets 'excluding the one or more low quality targets from the one or more metrology sampling plans generated. 23. The method of claim 21, wherein the utilizing the first plurality of quality metrics generated by the plurality of metrology targets to generate one or more metrics 163677.doc 201245906-like plan includes: utilizing the plurality of metrology targets Generating a first plurality of quality metrics to generate one or more metrology sampling plans to identify one or more low quality targets of the wafer, wherein the one or more low quality targets are excluded from the generated one or The one or more low quality targets are replaced by a plurality of metrology sampling plans and with one or more additional metrology targets that are close to one or more low quality target locations. 24. The method of claim 21, further comprising: utilizing the first plurality of quality metrics to identify a plurality of quality regions of the wafer, each of the quality regions comprising a plurality of substantially similar quality levels Weights and measures targets. 25. The method of claim 24, wherein a metrology sampling rate at one or more locations across the wafer is defined by each of the plurality of quality regions. 26. The method of claim 21, further comprising: performing one or more metric measurements on a subsequent wafer using the generated sampling plan. 27_ - A computer implemented method for providing a program map map, comprising: forming a plurality of proxy targets on a reticle; forming a plurality of device-related targets on a wafer; by comparing a lithography program And obtaining at least one of the first set of metrology results from the plurality of proxy targets and the at least one obtained from the plurality of proxy targets after the first etching process of the wafer, before the first surname program of the wafer a second set of metrology results to determine a change in the position of the 163677.doc 201245906 across the wafer - the program flag is associated with a particular program path; A plurality of device-related targets perform a first set of metric measurements to measure a device-dependent offset after the program, the device-related offset is a bias between a weight-loss structure and a device of the wafer; Determining each additional processing layer that varies with the location of the wafer and one of the outer non-lithographic process paths of the day of the Japanese yen; additional measurements are performed at each additional processing layer An additional device-related offset after each additional non-lithographic program path of the wafer; and utilizing the determined first surname signature and each of the additional surname signatures and the first The measurement device phase offset and each additional device related offset are used to generate a program map map library. 28. The method of claim 27, wherein the comparing obtains one of the first set of metrology results from the plurality of proxy targets after a lithography procedure and prior to the first etch process of the wafer with the wafer The at least one second set of weights and measures obtained from the plurality of proxy targets after the first etching process comprises: determining the number of the first etching process from one of the lithography _ τ 攸 隹 隹 录The proxy target obtains a difference between the first set of weighted results and the at least one second set of weighted results obtained from the plurality of proxy targets after the first-money program of the wafer. 29. The method of claim 27, wherein obtaining a plurality of proxy targets from a lithography program 163677.doc 201245906 by performing a first set of metric measurements on the plurality of proxy targets after a lithography program The method of claim 27, wherein the method of claim 27, wherein at least one second is performed on the plurality of proxy targets after the first etching process of the wafer The group metric measures the at least one second set of metrology results from the plurality of proxy targets after the first etch process of the wafer. The method of claim 27, wherein the one or more overlays are used to obtain the first set of metrology results from the plurality of proxy targets and the at least one second set of metrology results from the plurality of proxy targets At least one of them. The method of claim 27, wherein the measuring a device-related offset after the first etching process by performing a first set of metric measurements on the plurality of device-related targets of the wafer comprises: Performing a first set of metrics on the target of the wafer for the benefit of the wafer, the first set of metrics is measured to measure the value of the number in the chain (a) after the sequence - the device-related offset 'the first group Metric measurement, balance measurement system utilization - CD-SEM based measurement and measurement system or a degree based on AFM | You pay attention to at least one of the system to order. The method of claim 27, wherein at least one of the light shields. A test reticle or a product, such as the method of claim 27, further comprising: utilizing the generated program pattern data to make a loop. It is known as an advanced program control. The method of claim 27, which further includes. 163677.doc 201245906 Generates a set of program map map correctable values. 36. A system for providing a quality metric suitable for improving program control in a semiconductor wafer fabrication, the method comprising the steps of: a metrology system configured to self-span one of a plurality of wafers Or a plurality of metrology targets of the plurality of field distributions to obtain a plurality of pairs of metric measurement signals, each of the pair of metric measurement signals corresponding to one of the plurality of metrology targets, the plurality of overlay metrics The number is obtained using a first measurement recipe; and a computing system is configured to: determine the plurality of overlay metric measurement signals by applying a plurality of overlay algorithms to each of the overlay metric measurement signals a plurality of stacked pairs of estimates for each of the 'overlap pairs' estimates are determined using one of the equal stacking algorithms; by using the plurality of stacked pairs of estimates to generate a plurality of scales from the plurality of scales And the plurality of stacked pairs of metrics measure one of each of the measured signals to produce a plurality of stacked pairs of estimated distributions; and using the generated plurality of stacked pairs to estimate the distribution Generating a first plurality of quality metrics, wherein each of the quality metrics corresponds to one of the plurality of stacked pairs of estimated distributions, and each of the quality metrics corresponds to a width of the generated pairwise estimated distribution A function, each quality metric is further a function of one of the asymmetry in the overlay metric measurement signal from one of the associated metrology targets. 3 7. The system of the claim 36, wherein the computing system is further configured to benefit 163677.doc 201245906 to measure the target using the first plurality of quality metrics generated. 38. The system of claim 36 Wherein the computing system uses the first plurality of quality metrics generated to formulate the formula. 39. The system of claim 36, wherein the computing system uses the generated first-plural quality metrics to produce a correctable 40. The system of claim 6, wherein the computing system uses the generated first plurality of quality metrics to generate a stroke. 41. The system of claim 36, wherein the computing system enters a program map data Library 163677.doc or multiple outliers are configured to facilitate the optimal stacking step configuration to facilitate or multiple processing steps configured to facilitate or multiple sampling steps configured J3