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:
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:
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:
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:
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:
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:
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:
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:
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.