Abstract: Methods are provided for deriving a partially continuous dependency of metrology metric(s) on recipe parameter(s), analyzing the derived dependency, determining a metrology recipe according to the analysis, and conducting metrology measurement(s) according to the determined recipe. The dependency may be analyzed in form of a landscape such as a sensitivity landscape in which regions of low sensitivity and/or points or contours of low or zero inaccuracy are detected, analytically, numerically or experimentally, and used to configure parameters of measurement, hardware and targets to achieve high measurement accuracy. Process variation is analyzed in terms of its effects on the sensitivity landscape, and these effects are used to characterize the process variation further, to optimize the measurements and make the metrology both more robust to inaccuracy sources and more flexible with respect to different targets on the wafer and available measurement conditions.

Abstract: Methods are provided, which estimate a quality of a metrology target by calculating a noise metric of its ROI kernels, derived from application of a Fourier filter on the measured kernel with respect to a periodicity of the target's periodic structure(s); and using the calculated noise metric to indicate the target quality. An additional Fourier filter may be applied perpendicularly on the measured kernel with respect to a periodicity of a perpendicular segmentation of the periodic structure(s), and the (2D) noise metric may be derived by application of both Fourier filters. The estimated noise may be analyzed statistically to provide various types of information on the target.

Abstract: Notch detection methods and modules are provided for efficiently estimating a position of a wafer notch. Capturing an image of specified region(s) of the wafer, a principle angle is identified in a transformation, converted into polar coordinates, of the captured image. Then the wafer axes are recovered from the identified principle angle as the dominant orientations of geometric primitives in the captured region. The captured region may be selected to include the center of the wafer and/or certain patterns that enhance the identification and recovering of the axes. Multiple images and/or regions may be used to optimize image quality and detection efficiency.

Abstract: Methods and systems are provided, which identify specified metrology target abnormalities using selected metrics and classify the identified target abnormalities geometrically to link them to corresponding sources of error. Identification may be carried out by deriving target signals such as kernels from specified regions of interest (ROIs) from corresponding targets on a wafer, calculating the metrics from the target signals using respective functions and analyzing the metrics to characterize the targets.

Abstract: Metrology methods and respective software and module are provided, which identify and remove measurement inaccuracy which results from process variation leading to target asymmetries. The methods comprise identifying an inaccuracy contribution of process variation source(s) to a measured scatterometry signal (e.g., overlay) by measuring the signal across a range of measurement parameter(s) (e.g., wavelength, angle) and targets, and extracting a measurement variability over the range which is indicative of the inaccuracy contribution. The method may further assume certain functional dependencies of the resulting inaccuracy on the target asymmetry, estimate relative donations of different process variation sources and apply external calibration to further enhance the measurement accuracy.

Abstract: Methods are provided for deriving a partially continuous dependency of metrology metric(s) on recipe parameter(s), analyzing the derived dependency, determining a metrology recipe according to the analysis, and conducting metrology measurement(s) according to the determined recipe. The dependency may be analyzed in form of a landscape such as a sensitivity landscape in which regions of low sensitivity and/or points or contours of low or zero inaccuracy are detected, analytically, numerically or experimentally, and used to configure parameters of measurement, hardware and targets to achieve high measurement accuracy. Process variation is analyzed in terms of its effects on the sensitivity landscape, and these effects are used to characterize the process variation further, to optimize the measurements and make the metrology both more robust to inaccuracy sources and more flexible with respect to different targets on the wafer and available measurement conditions.

Abstract: Methods are provided, which estimate a quality of a metrology target by calculating a noise metric of its ROI kernels, derived from application of a Fourier filter on the measured kernel with respect to a periodicity of the target's periodic structure(s); and using the calculated noise metric to indicate the target quality. An additional Fourier filter may be applied perpendicularly on the measured kernel with respect to a periodicity of a perpendicular segmentation of the periodic structure(s), and the (2D) noise metric may be derived by application of both Fourier filters. The estimated noise may be analyzed statistically to provide various types of information on the target.

Abstract: Notch detection methods and modules are provided for efficiently estimating a position of a wafer notch. Capturing an image of specified region(s) of the wafer, a principle angle is identified in a transformation, converted into polar coordinates, of the captured image. Then the wafer axes are recovered from the identified principle angle as the dominant orientations of geometric primitives in the captured region. The captured region may be selected to include the center of the wafer and/or certain patterns that enhance the identification and recovering of the axes. Multiple images and/or regions may be used to optimize image quality and detection efficiency.

Abstract: Metrology methods and respective software and module are provided, which identify and remove measurement inaccuracy which results from process variation leading to target asymmetries. The methods comprise identifying an inaccuracy contribution of process variation source(s) to a measured scatterometry signal (e.g., overlay) by measuring the signal across a range of measurement parameter(s) (e.g., wavelength, angle) and targets, and extracting a measurement variability over the range which is indicative of the inaccuracy contribution. The method may further assume certain functional dependencies of the resulting inaccuracy on the target asymmetry, estimate relative donations of different process variation sources and apply external calibration to further enhance the measurement accuracy.

Abstract: Methods and systems are provided, which identify specified metrology target abnormalities using selected metrics and classify the identified target abnormalities geometrically to link them to corresponding sources of error. Identification may be carried out by deriving target signals such as kernels from specified regions of interest (ROIs) from corresponding targets on a wafer, calculating the metrics from the target signals using respective functions and analyzing the metrics to characterize the targets.