Abstract:
Methods applicable in metrology modules and tools are provided, which enable adjusting metrology measurement parameters with respect to process variation, without re-initiating metrology recipe setup. Methods comprise, during an initial metrology recipe setup, recording a metrology process window and deriving baseline information therefrom, and during operation, quantifying the process variation with respect to the baseline information, and adjusting the metrology measurement parameters within the metrology process window with respect to the quantified process variation. The quick adjustment of metrology parameters avoids metrology-related process delays and releases prior art bottlenecks related thereto. Models of effects of various process variation factors on the metrology measurements may be used to enhance the derivation of required metrology tuning and enable their application with minimal delays to the production process.
Abstract:
Methods, metrology modules and target designs are provided, which improve the accuracy of metrology measurements. Methods provide flexible handling of multiple measurement recipes and setups and enable relating them to landscape features that indicate their relation to resonance regions and to flat regions. Clustering of recipes, self-consistency tests, common processing of aggregated measurements, noise reduction, cluster analysis, detailed analysis of the landscape and targets with skewed cells are employed separately or in combination to provide cumulative improvements of measurement accuracy.
Abstract:
A method of determining overlay (“OVL”) in a pattern in a semiconductor wafer manufacturing process comprises capturing images from a cell in a metrology target formed in at least two different layers in the wafer with parts of the target offset in opposing directions with respect to corresponding parts in a different layer. The images may be captured using radiation of multiple different wavelengths, each image including +1 and −1 diffraction patterns. A first and second differential signal may be determined for respective pixels in each image by subtracting opposing pixels from the +1 and −1 diffraction orders for each of the multiple wavelengths. An OVL for the respective pixels may be determined based on analyzing the differential signals from multiple wavelengths simultaneously. Then an OVL for the pattern may be determined as a weighted average of the OVL of the respective pixels.
Abstract:
A method of determining overlay (“OVL”) in a pattern in a semiconductor wafer manufacturing process comprises capturing images from a cell in a metrology target formed in at least two different layers in the wafer with parts of the target offset in opposing directions with respect to corresponding parts in a different layer. The images may be captured using radiation of multiple different wavelengths, each image including +1 and −1 diffraction patterns. A first and second differential signal may be determined for respective pixels in each image by subtracting opposing pixels from the +1 and −1 diffraction orders for each of the multiple wavelengths. An OVL for the respective pixels may be determined based on analyzing the differential signals from multiple wavelengths simultaneously. Then an OVL for the pattern may be determined as a weighted average of the OVL of the respective pixels.
Abstract:
Methods applicable in metrology modules and tools are provided, which enable adjusting metrology measurement parameters with respect to process variation, without re-initiating metrology recipe setup. Methods comprise, during an initial metrology recipe setup, recording a metrology process window and deriving baseline information therefrom, and during operation, quantifying the process variation with respect to the baseline information, and adjusting the metrology measurement parameters within the metrology process window with respect to the quantified process variation. The quick adjustment of metrology parameters avoids metrology-related process delays and releases prior art bottlenecks related thereto. Models of effects of various process variation factors on the metrology measurements may be used to enhance the derivation of required metrology tuning and enable their application with minimal delays to the production process.
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, metrology modules and target designs are provided, which improve the accuracy of metrology measurements. Methods provide flexible handling of multiple measurement recipes and setups and enable relating them to landscape features that indicate their relation to resonance regions and to flat regions. Clustering of recipes, self-consistency tests, common processing of aggregated measurements, noise reduction, cluster analysis, detailed analysis of the landscape and targets with skewed cells are employed separately or in combination to provide cumulative improvements of measurement accuracy.
Abstract:
Methods, metrology modules and target designs are provided, which improve the accuracy of metrology measurements. Methods provide flexible handling of multiple measurement recipes and setups and enable relating them to landscape features that indicate their relation to resonance regions and to flat regions. Clustering of recipes, self-consistency tests, common processing of aggregated measurements, noise reduction, cluster analysis, detailed analysis of the landscape and targets with skewed cells are employed separately or in combination to provide cumulative improvements of measurement accuracy.