Abstract: Repeater analysis at a first threshold identifies repeater defects. The repeater defects are located at a coordinate that is the same on each reticle. Images on every reticle of the semiconductor wafer at the coordinate are received, and a plurality of signed difference images are obtained. A repeater threshold for signed difference images is calculated, as is consistency of the polarity. The threshold is applied to the images and a number of defects per each repeater that remain are determined. A secondary repeater threshold can be applied for nuisance filtering.

Abstract: Systems and methods for monitoring stability of a wafer inspection recipe over time are provided. One method includes collecting inspection results over time. The inspection results are generated by at least one wafer inspection tool while performing the wafer inspection recipe on wafers at different points in time. The method also includes identifying abnormal variation in the inspection results by comparing the inspection results generated at different times to each other. In addition, the method includes determining if the abnormal variation is attributable to the wafers, the wafer inspection recipe, or one or more of the at least one wafer inspection tool thereby determining if the wafer inspection recipe is stable over time.

Abstract: Repeater analysis at a first threshold identifies repeater defects. The repeater defects are located at a coordinate that is the same on each reticle. Images on every reticle of the semiconductor wafer at the coordinate are received, and a plurality of signed difference images are obtained. A repeater threshold for signed difference images is calculated, as is consistency of the polarity. The threshold is applied to the images and a number of defects per each repeater that remain are determined. A secondary repeater threshold can be applied for nuisance filtering.

Abstract: The correlation of optical images with SEM images includes acquiring a full optical image of a sample by scanning the sample with an optical inspection sub-system, storing the full optical image, identifying a location of a feature-of-interest present in the full optical image with an additional sources, acquiring an SEM image of a portion of the sample that includes the feature at the identified location with a SEM tool, acquiring an optical image portion at the location identified by the additional source, the image portions including a reference structure, correlating the image portion and the SEM image based on the presence of the feature-of-interest and the reference structure in both the image portions and the SEM image, and transferring a location of the feature-of-interest in the SEM image into the coordinate system of the image portion of the full optical image to form a corrected optical image.

Abstract: The correlation of optical images with SEM images includes acquiring a full optical image of a sample by scanning the sample with an optical inspection sub-system, storing the full optical image, identifying a location of a feature-of-interest present in the full optical image with an additional sources, acquiring an SEM image of a portion of the sample that includes the feature at the identified location with a SEM tool, acquiring an optical image portion at the location identified by the additional source, the image portions including a reference structure, correlating the image portion and the SEM image based on the presence of the feature-of-interest and the reference structure in both the image portions and the SEM image, and transferring a location of the feature-of-interest in the SEM image into the coordinate system of the image portion of the full optical image to form a corrected optical image.

Abstract: Methods and systems for detecting defects on a wafer using adaptive local thresholding and color filtering are provided. One method includes determining local statistics of pixels in output for a wafer generated using an inspection system, determining which of the pixels are outliers based on the local statistics, and comparing the outliers to the pixels surrounding the outliers to identify the outliers that do not belong to a cluster of outliers as defect candidates. The method also includes determining a value for a difference in color between the pixels of the defect candidates and the pixels surrounding the defect candidates. The method further includes identifying the defect candidates that have a value for the difference in color greater than or equal to a predetermined value as nuisance defects and the defect candidates that have a value for the difference in color less than the predetermined value as real defects.

Abstract: Systems and methods for detecting defects on a reticle are provided. One system includes computer subsystem(s) that include one or more image processing components that acquire images generated by an inspection subsystem for a wafer, a main user interface component that provides information generated for the wafer and the reticle to a user and receives instructions from the user, and an interface component that provides an interface between the one or more image processing components and the main user interface. Unlike currently used systems, the one or more image processing components are configured for performing repeater defect detection by applying a repeater defect detection algorithm to the images acquired by the one or more image processing components, and the repeater defect detection algorithm is configured to detect defects on the wafer using a hot threshold and to identify the defects that are repeater defects.

Abstract: Methods and systems for detecting defects on a specimen are provided. One system includes one or more computer subsystems configured for acquiring images generated by an imaging subsystem at multiple instances of a pattern of interest (POI) within a die formed on the specimen. The multiple instances include two or more instances that are located at aperiodic locations within the die. The computer subsystem(s) are also configured for generating a POI reference image from two or more of the images generated at the multiple instances of the POI within the die. The computer subsystem(s) are further configured for comparing the images generated at the multiple instances of the POI within the die to the POI reference image and detecting defects in the multiple instances of the POI based on results of the comparing.

Abstract: A method includes identifying a first set of a first care area with a first sensitivity threshold, the first care area associated with a first design of interest within a block of repeating cells in design data; identifying an additional set of an additional care area with an additional sensitivity threshold, the additional care area associated with an additional design of interest within the block of repeating cells in design data; identifying one or more defects within the first set of the first care areas in one or more images of a selected region of a sample based on the first sensitivity threshold; and identifying one or more defects within the additional set of the additional care areas in the one or more images of the selected region of the sample based on the additional sensitivity threshold.

Abstract: Systems and methods for removing nuisance data from a defect scan of a wafer are disclosed. A processor receives a design file corresponding to a wafer having one or more z-layers. The processor receives critical areas of the wafer and instructs a subsystem to capture corresponding images of the wafer. Defect locations are received and the design file is aligned with the defect locations. Nuisance data is identified using the potential defect location and the one or more z-layers of the aligned design file. The processor then removes the identified nuisance data from the one or more potential defect locations.

Abstract: Methods and systems for determining a position of a defect in an electron beam image of a wafer are provided. One method includes determining a second position of a defect with respect to patterns imaged in a test image based on a first position of the defect in a difference image. The method also includes determining a third position of the defect with respect to the patterns in an electron beam image for the defect and determining an association between the first and third positions. In addition, the method includes determining a position of another defect in an electron beam image based on a first position of the other defect in a difference image and the determined association.

Abstract: Methods and systems for detecting defects on a specimen are provided. One method includes identifying first and second portions of dies on a specimen as edge dies and center dies, respectively. The method also includes determining first and second inspection methods for the first and second portions, respectively. Parameter(s) of comparisons performed in the first and second inspection methods are different. The method further includes detecting defects in at least one of the edge dies using the first inspection method and detecting defects in at least one of the center dies using the second inspection method.

Abstract: Systems and methods for detecting defects on a reticle are provided. One system includes computer subsystem(s) that include one or more image processing components that acquire images generated by an inspection subsystem for a wafer, a main user interface component that provides information generated for the wafer and the reticle to a user and receives instructions from the user, and an interface component that provides an interface between the one or more image processing components and the main user interface. Unlike currently used systems, the one or more image processing components are configured for performing repeater defect detection by applying a repeater defect detection algorithm to the images acquired by the one or more image processing components, and the repeater defect detection algorithm is configured to detect defects on the wafer using a hot threshold and to identify the defects that are repeater defects.

Abstract: Systems and methods for removing nuisance data from a defect scan of a wafer are disclosed. A processor receives a design file corresponding to a wafer having one or more z-layers. The processor receives critical areas of the wafer and instructs a subsystem to capture corresponding images of the wafer. Defect locations are received and the design file is aligned with the defect locations. Nuisance data is identified using the potential defect location and the one or more z-layers of the aligned design file. The processor then removes the identified nuisance data from the one or more potential defect locations.

Abstract: Methods and systems for detecting defects on a wafer using adaptive local thresholding and color filtering are provided. One method includes determining local statistics of pixels in output for a wafer generated using an inspection system, determining which of the pixels are outliers based on the local statistics, and comparing the outliers to the pixels surrounding the outliers to identify the outliers that do not belong to a cluster of outliers as defect candidates, The method also includes determining a value for a difference in color between the pixels of the defect candidates and the pixels surrounding the defect candidates.

Abstract: A method includes identifying a first set of a first care area with a first sensitivity threshold, the first care area associated with a first design of interest within a block of repeating cells in design data; identifying an additional set of an additional care area with an additional sensitivity threshold, the additional care area associated with an additional design of interest within the block of repeating cells in design data; identifying one or more defects within the first set of the first care areas in one or more images of a selected region of a sample based on the first sensitivity threshold; and identifying one or more defects within the additional set of the additional care areas in the one or more images of the selected region of the sample based on the additional sensitivity threshold.

Abstract: Systems and methods for detecting defects on a specimen based on structural information are provided. One system includes one or more computer subsystems configured for separating the output generated by a detector of an inspection subsystem in an array area on a specimen into at least first and second segments of the output based on characteristic(s) of structure(s) in the array area such that the output in different segments has been generated in different locations in the array area in which the structure(s) having different values of the characteristic(s) are formed. The computer subsystem(s) are also configured for detecting defects on the specimen by applying one or more defect detection methods to the output based on whether the output is in the first segment or the second segment.

Abstract: Methods and systems for detecting defects on a wafer using adaptive local thresholding and color filtering are provided. One method includes determining local statistics of pixels in output for a wafer generated using an inspection system, determining which of the pixels are outliers based on the local statistics, and comparing the outliers to the pixels surrounding the outliers to identify the outliers that do not belong to a cluster of outliers as defect candidates. The method also includes determining a value for a difference in color between the pixels of the defect candidates and the pixels surrounding the defect candidates. The method further includes identifying the defect candidates that have a value for the difference in color greater than or equal to a predetermined value as nuisance defects and the defect candidates that have a value for the difference in color less than the predetermined value as real defects.

Abstract: Methods and systems for determining a position of a defect in an electron beam image of a wafer are provided. One method includes determining a second position of a defect with respect to patterns imaged in a test image based on a first position of the defect in a difference image. The method also includes determining a third position of the defect with respect to the patterns in an electron beam image for the defect and determining an association between the first and third positions. In addition, the method includes determining a position of another defect in an electron beam image based on a first position of the other defect in a difference image and the determined association.

Abstract: Methods and systems for detecting defects on a specimen are provided. One system includes one or more computer subsystems configured for acquiring images generated by an imaging subsystem at multiple instances of a pattern of interest (POI) within a die formed on the specimen. The multiple instances include two or more instances that are located at aperiodic locations within the die. The computer subsystem(s) are also configured for generating a POI reference image from two or more of the images generated at the multiple instances of the POI within the die. The computer subsystem(s) are further configured for comparing the images generated at the multiple instances of the POI within the die to the POI reference image and detecting defects in the multiple instances of the POI based on results of the comparing.