Abstract: A metrology system may include an optical metrology sub-system to generate optical metrology measurements of optical metrology based on features of the optical metrology targets associated with at least one optical pitch and an additional metrology sub-system to generate additional metrology measurements of the optical metrology targets, where the additional metrology measurements have a higher resolution than the optical metrology measurements, and where the additional metrology sub-system further measures deviations of the optical metrology targets from a reference design. The system may further include a controller to generate accuracy measurements for the optical metrology targets based on the measurements, identify variations of a lithography process based on the deviations, correlate the accuracy measurements to the variations, and adjust at least one of the optical metrology sub-system, a lithography tool, or the reference design based on the correlations.

Abstract: A method for quantifying sensitivity of metrology to process variation including performing metrology, by a metrology tool, on at least one metrology target located at at least one site on a semiconductor wafer, thereby generating a metrology landscape, and calculating a sensitivity metric directly based on the metrology landscape, the sensitivity metric quantifying a sensitivity of the metrology landscape to process variation involved in manufacture of the semiconductor wafer.

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.

Abstract: A method for quantifying sensitivity of metrology to process variation including performing metrology, by a metrology tool, on at least one metrology target located at at least one site on a semiconductor wafer, thereby generating a metrology landscape, and calculating a sensitivity metric directly based on the metrology landscape, the sensitivity metric quantifying a sensitivity of the metrology landscape to process variation involved in manufacture of the semiconductor wafer.

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.

Abstract: An overlay metrology system includes a controller to receive, from an overlay metrology tool, overlay measurements on multiple sets of overlay targets on a sample with a range of values of a measurement parameter, where a particular set of overlay targets includes overlay targets having one of two or more overlay target designs. The controller may further determine scaling metric values for at least some of the overlay targets, where the scaling metric for a particular overlay target is based on a standard deviation of the overlay measurements of the corresponding set of overlay targets. The controller may further determine a variability of the scaling metric values for each of the two or more sets of overlay targets. The controller may further select, as an output overlay target design, one of the two or more overlay target designs having a smallest scaling metric variability.

Abstract: Systems, metrology modules and methods are provided, which identify, per wafer site, components of residuals from measurement of metrology metric(s), and optimize measurement parameters for each site, according to the identified residuals' components. Certain embodiments utilize metric landscapes to identify sensitive sites and/or to identify sites exhibiting highest accuracy, and corresponding metrics may be combined over the wafer to further enhance the metrology performance. Zonal analysis may be used to reduce the systematic errors, and disclosed per-site analysis may be used to further reduce the non-systematic error components, and relate the remaining residuals components to process variation over the wafer.

Abstract: Methods are provided for designing metrology targets and estimating the uncertainty error of metrology metric values with respect to stochastic noise such as line properties (e.g., line edge roughness, LER). Minimal required dimensions of target elements may be derived from analysis of the line properties and uncertainty error of metrology measurements, by either CDSEM (critical dimension scanning electron microscopy) or optical systems, with corresponding targets. The importance of this analysis is emphasized in view of the finding that stochastic noise may have increased importance with when using more localized models such as CPE (correctables per exposure). The uncertainty error estimation may be used for target design, enhancement of overlay estimation and evaluation of measurement reliability in multiple contexts.

Abstract: Systems, metrology modules and methods are provided, which identify, per wafer site, components of residuals from measurement of metrology metric(s), and optimize measurement parameters for each site, according to the identified residuals' components. Certain embodiments utilize metric landscapes to identify sensitive sites and/or to identify sites exhibiting highest accuracy, and corresponding metrics may be combined over the wafer to further enhance the metrology performance. Zonal analysis may be used to reduce the systematic errors, and disclosed per-site analysis may be used to further reduce the non-systematic error components, and relate the remaining residuals components to process variation over the wafer.

Abstract: The generation of flexible sparse metrology sample plans includes receiving a full set of metrology signals from one or more wafers from a metrology tool, determining a set of wafer properties based on the full set of metrology signals and calculating a wafer property metric associated with the set of wafer properties, calculating one or more independent characterization metrics based on the full set of metrology signals, and generating a flexible sparse sample plan based on the set of wafer properties, the wafer property metric, and the one or more independent characterization metrics. The one or more independent characterization metrics of the one or more properties calculated with metrology signals from the flexible sparse sampling plan is within a selected threshold from one or more independent characterization metrics of the one or more properties calculated with the full set of metrology signals.

Abstract: An overlay metrology system includes a controller to receive, from an overlay metrology tool, overlay measurements on multiple sets of overlay targets on a sample with a range of values of a measurement parameter, where a particular set of overlay targets includes overlay targets having one of two or more overlay target designs. The controller may further determine scaling metric values for at least some of the overlay targets, where the scaling metric for a particular overlay target is based on a standard deviation of the overlay measurements of the corresponding set of overlay targets. The controller may further determine a variability of the scaling metric values for each of the two or more sets of overlay targets. The controller may further select, as an output overlay target design, one of the two or more overlay target designs having a smallest scaling metric variability.

Abstract: Methods are provided for designing metrology targets and estimating the uncertainty error of metrology metric values with respect to stochastic noise such as line properties (e.g., line edge roughness, LER). Minimal required dimensions of target elements may be derived from analysis of the line properties and uncertainty error of metrology measurements, by either CDSEM (critical dimension scanning electron microscopy) or optical systems, with corresponding targets. The importance of this analysis is emphasized in view of the finding that stochastic noise may have increased importance with when using more localized models such as CPE (correctables per exposure). The uncertainty error estimation may be used for target design, enhancement of overlay estimation and evaluation of measurement reliability in multiple contexts.

Abstract: Method, metrology modules and RCA tool are provided, which use the behavior of resonance region(s) in measurement landscapes to evaluate and characterize process variation with respect to symmetric and asymmetric factors, and provide root cause analysis of the process variation with respect to process steps. Simulations of modeled stacks with different layer thicknesses and process variation factors may be used to enhance the analysis and provide improved target designs, improved algorithms and correctables for metrology measurements. Specific targets that exhibit sensitive resonance regions may be utilize to enhance the evaluation of process variation.

Abstract: Methods and respective modules which reduce sample size and measurement duration of metrology parameters by selecting a relatively small subset of measured targets to represent a distribution of parameter measurements of a large number of targets. The subset is selected by sampling a substantially equal number of measurements from each of a selected number of quantiles of the distribution. The methods and modules allow identification of targets which represent correctly the whole target measurement distribution. The methods and modules optimize quantiles and sample size selections, using accuracy scores and estimations of the robustness of the selections. Sampling and selections may be carried out iteratively to reach specified criteria that match the results which can be derived when considering the whole distribution.

Abstract: A metrology performance analysis system includes a metrology tool including one or more detectors and a controller communicatively coupled to the one or more detectors. The controller is configured to receive one or more metrology data sets associated with a metrology target from the metrology tool in which the one or more metrology data sets include one or more measured metrology metrics and the one or more measured metrology metrics indicate deviations from nominal values. The controller is further configured to determine relationships between the deviations from the nominal values and one or more selected semiconductor process variations, and determine one or more root causes of the deviations from the nominal values based on the relationships between values of the one or more metrology metrics and the one or more selected semiconductor process variations.

Abstract: Method, metrology modules and RCA tool are provided, which use the behavior of resonance region(s) in measurement landscapes to evaluate and characterize process variation with respect to symmetric and asymmetric factors, and provide root cause analysis of the process variation with respect to process steps. Simulations of modeled stacks with different layer thicknesses and process variation factors may be used to enhance the analysis and provide improved target designs, improved algorithms and correctables for metrology measurements. Specific targets that exhibit sensitive resonance regions may be utilize to enhance the evaluation of process variation.

Abstract: The generation of flexible sparse metrology sample plans includes receiving a full set of metrology signals from one or more wafers from a metrology tool, determining a set of wafer properties based on the full set of metrology signals and calculating a wafer property metric associated with the set of wafer properties, calculating one or more independent characterization metrics based on the full set of metrology signals, and generating a flexible sparse sample plan based on the set of wafer properties, the wafer property metric, and the one or more independent characterization metrics. The one or more independent characterization metrics of the one or more properties calculated with metrology signals from the flexible sparse sampling plan is within a selected threshold from one or more independent characterization metrics of the one or more properties calculated with the full set of metrology signals.

Abstract: A metrology performance analysis system includes a metrology tool including one or more detectors and a controller communicatively coupled to the one or more detectors. The controller is configured to receive one or more metrology data sets associated with a metrology target from the metrology tool in which the one or more metrology data sets include one or more measured metrology metrics and the one or more measured metrology metrics indicate deviations from nominal values. The controller is further configured to determine relationships between the deviations from the nominal values and one or more selected semiconductor process variations, and determine one or more root causes of the deviations from the nominal values based on the relationships between values of the one or more metrology metrics and the one or more selected semiconductor process variations.

Abstract: Aspects of the present disclosure describe systems and methods for calibrating a metrology tool by using proportionality factors. The proportionality factors may be obtained by measuring a substrate under different measurement conditions. Then calculating the measured metrology value and one or more quality merits. From this information, proportionality factors may be determined. Thereafter the proportionality factors may be used to quantify the inaccuracy in a metrology measurement. The proportionality factors may also be used to determine an optimize measurement recipe. It is emphasized that this abstract is provided to comply with the rules requiring an abstract that will allow a searcher or other reader to quickly ascertain the subject matter of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: The present invention may include performing a first measurement process on a wafer of a lot of wafers, wherein the first measurement process includes measuring one or more characteristics of a plurality of targets distributed across one or more fields of the wafer, determining a set of process tool correctables for a residual larger than a selected threshold level utilizing a loss function, wherein the loss function is configured to fit a model for one or more process tools, as a function of field position, to one or more of the measured characteristics of the plurality of targets, wherein the set of process tool correctables includes one or more parameters of the model that act to minimize the difference between a norm of the residual and the selected threshold, and utilizing the determined process tool correctables to monitor or adjust one or more processes of the process tools.