Abstract: Various methods and systems for creating or performing a dynamic sampling scheme for a process during which measurements are performed on wafers are provided. One method for creating a dynamic sampling scheme for a process during which measurements are performed on wafers includes performing the measurements on all of the wafers in at least one tot at all measurement spots on the wafers. The method also includes determining an optimal sampling scheme, an enhanced sampling scheme, a reduced sampling scheme, and thresholds for the dynamic sampling scheme for the process based on results of the measurements. The thresholds correspond to values of the measurements at which the optimal sampling scheme, the enhanced sampling scheme, and the reduced sampling scheme are to be used for the process.

Abstract: Methods and systems for detection of selected defects in relatively noisy inspection data are provided. One method includes applying a spatial filter algorithm to inspection data acquired across an area on a substrate to determine a first portion of the inspection data that has a higher probability of being a selected type of defect than a second portion of the inspection data. The selected type of defect includes a non-point defect. The inspection data is generated by combining two or more raw inspection data corresponding to substantially the same locations on the substrate. The method also includes generating a two-dimensional map illustrating the first portion of the inspection data. The method further includes searching the two-dimensional map for an event that has spatial characteristics that approximately match spatial characteristics of the selected type of defect and determining if the event corresponds to a defect having the selected type.

Abstract: Systems configured to provide illumination for wafer inspection performed by a wafer inspection tool are provided. One system includes one or more pupil lenses configured to focus a first far field pattern having a shape different than a shape of light generated by a light source. The system also includes a field lens array positioned between the one or more pupil lenses and an aperture stop. In addition, the system includes a lens group configured to focus a second far field pattern generated by the field lens array to a back focal plane of the lens group. The back focal plane of the lens group is a field plane of a wafer inspection tool at which a wafer to be inspected is placed during wafer inspection.

Abstract: Methods and systems for detecting defects on a wafer are provided. One method includes determining difference values for pixels in first output for a wafer generated using a first optics mode of an inspection system and determining other values for pixels in second output for the wafer generated using a second optics mode of the inspection system. The first and second optics modes are different from each other. The method also includes generating a two-dimensional scatter plot of the difference values and the other values for the pixels in the first and second output corresponding to substantially the same locations on the wafer. The method further includes detecting defects on the wafer based on the two-dimensional scatter plot.

Abstract: Methods and systems for setting up a classifier for defects detected on a wafer are provided. One method includes generating a template for a defect classifier for defects detected on a wafer and applying the template to a training data set. The training data set includes information for defects detected on the wafer or another wafer. The method also includes determining one or more parameters for the defect classifier based on results of the applying step.

Abstract: Computer-implemented methods, computer-readable media, and systems for selecting one or more parameters for inspection of a wafer are provided.

Abstract: Methods and systems for generating a defect sample for a wafer are provided. One method includes separating defects detected on a wafer into bins having diversity in values of a first set of one or more first attributes of the defects. The method also includes selecting, independently from one or more of the bins, defects within the bins based on diversity in a second set of one or more second attributes of the defects. The selected defects are then used to create a defect sample for the wafer. In this manner, defects having diverse values of multiple attributes can be easily selected.

Abstract: Methods and systems for design based sampling and binning for yield critical defects are provided. One method includes aligning each image patch in each inspection image frame generated for a wafer by an optical subsystem of an inspection system to design information for the wafer. The method also includes deriving multiple layer design attributes at locations of defects detected in the image patches. In addition, the method includes building a decision tree with the multiple layer design attributes. The decision tree is used to separate the defects into bins with different yield impacts on a device being formed on the wafer. The method also includes binning the defects with the decision tree.

Abstract: Methods and systems for detecting defects on a wafer using defect-specific and multi-channel information are provided. One method includes acquiring information for a target on a wafer. The target includes a pattern of interest (POI) formed on the wafer and a known defect of interest (DOI) occurring proximate to or in the POI. The method also includes detecting the known DOI in target candidates by identifying potential DOI locations based on images of the target candidates acquired by a first channel of an inspection system and applying one or more detection parameters to images of the potential DOI locations acquired by a second channel of the inspection system. Therefore, the image(s) used for locating potential DOI locations and the image(s) used for detecting defects can be different.

Abstract: Methods and systems for detecting defects on a wafer are provided. One method includes acquiring output for a wafer generated by an inspection system. Different dies are printed on the wafer with different process conditions. The different process conditions correspond to different failure modes for the wafer. The method also includes comparing the output generated for a first of the different dies printed with the different process conditions corresponding to a first of the different failure modes with the output generated for a second of the different dies printed with the different process conditions corresponding to a second of the different failure modes opposite to the first of the different failure modes. In addition, the method includes detecting defects on the wafer based on results of the comparing step.

Abstract: Various embodiments for generating a defect sample for electron beam review are provided. One method includes combining, on a defect-by-defect basis, one or more first attributes for defects determined by optical inspection of a wafer on which the defects were detected with one or more second attributes for the defects determined by optical review of the wafer thereby generating combined attributes for the defects. The method also includes separating the defects into bins based on the combined attributes for the defects. The bins correspond to different defect classifications. In addition, the method includes sampling one or more of the defects for the electron beam review based on the bins into which the defects have been separated thereby generating a defect review sample for the electron beam review.

Abstract: Systems and methods for discovering defects on a wafer are provided. One method includes detecting defects on a wafer by applying a threshold to output generated by a detector in a first scan of the wafer and determining values for features of the detected defects. The method also includes automatically ranking the features, identifying feature cut-lines to group the defect into bins, and, for each of the bins, determining one or more parameters that if applied to the values for the features of the defects in each of the bins will result in a predetermined number of the defects in each of the bins. The method also includes applying the one or more determined parameters to the output generated by the detector in a second scan of the wafer to generate a defect population that has a predetermined defect count and is diversified in the values for the features.

Abstract: Methods and systems for determining one or more parameters of a wafer inspection process are provided. One method includes acquiring metrology data for a wafer generated by a wafer metrology system. The method also includes determining one or more parameters of a wafer inspection process for the wafer or another wafer based on the metrology data.

Abstract: Methods and systems for detecting defects on a wafer are provided. One system includes an illumination subsystem configured to direct light to at least one spot on a wafer. The system also includes at least one element configured to block first portion(s) of light scattered from the at least one spot from reaching a detector while allowing second portion(s) of the light scattered from the at least one spot to be detected by the detector. The first portion(s) of the light are scattered from one or more patterned features in a logic region on the wafer. The second portion(s) of the light are not scattered from the one or more patterned features. The detector is not an imaging detector. The system further includes a computer subsystem configured to detect defects on the wafer based on output of the detector.

Abstract: Methods and systems for decision tree construction for automatic classification of defects on semiconductor wafers are provided. One method includes creating a decision tree for classification of defects detected on a wafer by altering one or more floating trees in the decision tree. The one or more floating trees are sub-trees that are manipulated as individual units. In addition, the method includes classifying the defects detected on the wafer by applying the decision tree to the defects.

Abstract: Systems and methods for detecting defects on a reticle are provided. The embodiments include generating and/or using a data structure that includes pairs of predetermined segments of a reticle pattern and corresponding near-field data. The near-field data for the predetermined segments may be determined by regression based on actual image(s) of a reticle generated by a detector of a reticle inspection system. Inspecting a reticle may then include separately comparing two or more segments of a pattern included in an inspection area on the reticle to the predetermined segments and assigning near-field data to at least one of the segments based on the predetermined segment to which it is most similar. The assigned near-field data can then be used to simulate an image that would be formed for the reticle by the detector, which can be compared to an actual image generated by the detector for defect detection.

Abstract: Methods and systems for filtering scratches from wafer inspection results are provided. One method includes generating a defect candidate map that includes image data for potential defect candidates as a function of position on the wafer and removing noise from the defect candidate map to generate a filtered defect candidate map. The method also includes determining one or more characteristics of the potential defect candidates based on portions of the filtered defect candidate map corresponding to the potential defect candidates. In addition, the method includes determining if each of the potential defect candidates are scratches based on the one or more characteristics determined for each of the potential defect candidates and separating the potential defect candidates determined to be the scratches from other defects in inspection results for the wafer.

Abstract: Methods and systems for classifying defects detected on a wafer are provided. One method includes inputting information for defects detected on a wafer into each of at least two defect classifiers included in a composite defect classifier. Such a method also includes, for at least one of the defects that is assigned to two or more bins in the composite defect classifier, determining a bin for the at least one of the defects based on a rank assigned to the two or more bins. The rank is assigned to the two or more bins based on one or more characteristics determined for the two or more bins, and the one or more characteristics are determined based on a comparison of predetermined defect classifications for defects in a training set and defect classifications determined for the defects in the training set by the at least two defect classifiers.

Abstract: Systems configured to inspect a wafer are provided. One system includes an illumination subsystem configured to illuminate a set of spots on a wafer and a collection subsystem configured to collect light from the set of spots. The collection subsystem separately images the light collected from each of the individual spots onto only a corresponding first detector of a first detection subsystem. The collection subsystem also images the light collected from at least some of the individual spots onto a number of second detectors of a second detection subsystem that is less than a number of spots in the set. Output produced by the first and second detectors can be used to detect defects on the wafer.

Abstract: Methods and systems for extracting comprehensive design guidance for in-line process control of wafers are provided. One method includes automatically identifying potential marginalities in a design for a device to be formed on a wafer. The method also includes automatically generating information for the potential marginalities. The automatically generated information is used to set up process control for the wafer.