Abstract: Methods and systems for performing semiconductor metrology directly on device structures are presented. A measurement model is created based on measured training data collected from at least one device structure. The trained measurement model is used to calculate process parameter values, structure parameter values, or both, directly from measurement data collected from device structures of other wafers. In some examples, measurement data from multiple targets is collected for model building, training, and measurement. In some examples, the use of measurement data associated with multiple targets eliminates, or significantly reduces, the effect of under layers in the measurement result, and enables more accurate measurements. Measurement data collected for model building, training, and measurement may be derived from measurements performed by a combination of multiple, different measurement techniques.

Abstract: Methods and systems for performing semiconductor metrology directly on device structures are presented. A measurement model is created based on measured training data collected from at least one device structure. The trained measurement model is used to calculate process parameter values, structure parameter values, or both, directly from measurement data collected from device structures of other wafers. In some examples, measurement data from multiple targets is collected for model building, training, and measurement. In some examples, the use of measurement data associated with multiple targets eliminates, or significantly reduces, the effect of under layers in the measurement result, and enables more accurate measurements. Measurement data collected for model building, training, and measurement may be derived from measurements performed by a combination of multiple, different measurement techniques.

Abstract: Defects observed by imaging tools may be classified by automatic comparison of features observed in a defect image with design information relating to corresponding portions of the image. Defect information may be generated from a defect image from a defect imaging tool. Design information relating to one or more structures to be formed on the substrate in a vicinity of the defect may be retrieved. The defect may be classified based on a combination of the defect information from the defect image and design information relating to one or more structures to be formed on the substrate in the vicinity of the defect.

Abstract: Defects observed by imaging tools may be classified by automatic comparison of features observed in a defect image with design information relating to corresponding portions of the image. Defect information may be generated from a defect image from a defect imaging tool. Design information relating to one or more structures to be formed on the substrate in a vicinity of the defect may be retrieved. The defect may be classified based on a combination of the defect information from the defect image and design information relating to one or more structures to be formed on the substrate in the vicinity of the defect.