Kla Tencor Corporation

Kla Corporation

Hucheng Lee

Lisheng Gao

Bjorn Brauer

Sangbong Park

Junqing Huang

Kenong Wu

Xiaochun Li

Santosh Bhattacharyya

Govindarajan Thattaisundaram

Eugene Shifrin

Yong Zhang

Jan A Lauber

Richard Wallingford

James A Smith

Yan Xiong

Erfan Soltanmohammadi

Soren Konecky

Chetana Bhaskar

Huan Jin

Bryant Mantiply

Pavan Kumar Perali

Nurmohammed Patwary

Ashok Mathew

Shuo Sun

Boshi Huang

Kedar Grama

Qing Luo

Benjamin Murray

Vladimir Tumakov

Heonju Shin

Jusang Maeng

David Dowling

Tarunark Singh

Paul Russell

Methods and systems for alignment for semiconductor applications are provided. One method includes determining different align-to-design offsets for multiple instances of an alignment target formed on a specimen by separately aligning images of the multiple instances of the alignment target generated by an imaging subsystem to a rendered image for the alignment target with different alignment methods, respectively. The method also includes identifying the multiple instances having a difference between the different align-to-design offsets below a predetermined threshold. In addition, the method includes determining a runtime align-to-design offset for the alignment target from the different align-to-design offsets determined for only the identified multiple instances. That runtime align-to-design offset can then be used in a process performed on the specimen with an imaging subsystem.

Robust image-to-design alignment for dram

Systems and methods for detecting defects on a reticle are provided. One system is configured for generating different stacked difference images for multiple instances of first patterned areas in different rows on a wafer based on images generated for the first patterned areas in the different rows. The system is also configured for performing double detection based on the different stacked difference images. The system then identifies defects on the reticle based on the defects detected by the double detection. As described further herein, the systems and methods detect defects from multiple reticle rows printed on a wafer, which can reduce noise and enable detection of substantially small repeater defects. The embodiments are particularly useful for high sensitivity repeater defect detection for extreme ultraviolet (EUV) reticles and multi-die reticles (MDR).

Print check repeater defect detection

Wafer-to-wafer and within-wafer image contrast variations can be identified and mitigated by extracting an image frame during recipe setup and then during runtime at the same location. Image contrast is determined for the two image frames. A ratio of the contrast for the two image frames can be used to determine contrast variations and focus variation.

Image contrast metrics for deriving and improving imaging conditions

With the disclosed systems and methods for DRAM and 3D NAND inspection, an image of the wafer is received based on the output for an inspection tool. Geometric measurements of a design of a plurality of memory devices on the wafer are received. A care area with higher inspection sensitivity is determined based on the geometric measurements.

Design-assisted inspection for DRAM and 3D NAND devices

Methods and systems for selecting defect detection methods for inspection of a specimen are provided. One system includes one or more computer subsystems configured for separating polygons in a care area into initial sub-groups based on a characteristic of the polygons on the specimen and determining a characteristic of noise in output generated by a detector of an inspection subsystem for the polygons in the different initial sub-groups. The computer subsystem(s) are also configured for determining final sub-groups for the polygons by combining any two or more of the different initial sub-groups having substantially the same values of the characteristic of the noise. In addition, the computer subsystem(s) are configured for selecting first and second defect detection methods for application to the output generated by the detector of the inspection subsystem during inspection of the specimen or another specimen.

Selecting defect detection methods for inspection of a specimen

A care area is determined in an image of a semiconductor wafer. The care area is divided into sub-care areas based on the shapes of polygons in a design file associated with the care area. A noise scan of a histogram for the sub-care areas is then performed. The sub-care areas are clustered into groups based on the noise scan of the histogram.

Clustering sub-care areas based on noise characteristics

Methods and systems for controlling a process for inspection of a specimen are provided. One system includes one or more computer subsystems configured for determining a statistical characteristic of difference images generated for multiple instances of a care area on a specimen and determining variation in the statistical characteristic compared to a statistical characteristic of difference images generated for multiple instances of the care area on one or more other specimens. In addition, the one or more computer subsystems are configured for determining one or more changes to one or more parameters used for detecting defects in the care area on the specimen based on the variation.

Controlling a process for inspection of a specimen

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.

Method and system for correlating optical images with scanning electron microscopy images

A method of semiconductor-wafer image alignment is performed at a semiconductor-wafer defect-inspection system. In the method, a semiconductor wafer is loaded into the semiconductor-wafer defect-inspection system. Pre-inspection alignment is performed for the semiconductor wafer. After performing the pre-inspection alignment, a first swath is executed to generate a first image of a first region on the semiconductor wafer. An offset of a target structure in the first image with respect to a known point is determined. Defect identification is performed for the first image, using the offset. After executing the first swath and determining the offset, a second swath is executed to generate a second image of a second region on the semiconductor wafer. While executing the second swath, run-time alignment of the semiconductor wafer is performed using the offset.

Defect-location determination using correction loop for pixel alignment

One or more semiconductor wafers or portions thereof are scanned using a primary optical mode, to identify defects. A plurality of the identified defects, including defects of a first class and defects of a second class, are selected and reviewed using an electron microscope. Based on this review, respective defects of the plurality are classified as defects of either the first class or the second class. The plurality of the identified defects is imaged using a plurality of secondary optical modes. One or more of the secondary optical modes are selected for use in conjunction with the primary optical mode, based on results of the scanning using the primary optical mode and the imaging using the plurality of secondary optical modes. Production semiconductor wafers are scanned for defects using the primary optical mode and the one or more selected secondary optical modes.

Optical-mode selection for multi-mode semiconductor inspection

Methods and systems for detecting defects in a logic region on a wafer are provided. One method includes acquiring information for different types of design-based care areas in a logic region of a wafer. The method also includes designating the different types of the design-based care areas as different types of sub-regions and, for a localized area within the logic region, assigning two or more instances of the sub-regions located in the localized area to a super-region. In addition, the method includes generating one scatter plot for all of the two or more instances of the sub-regions assigned to the super-region. The one scatter plot is generated with different segmentation values for the output corresponding to the different types of the sub-regions. The method further includes detecting defects in the sub-regions based on the one scatter plot.

Detecting defects in a logic region on a wafer

The disclosure is directed to providing visual feedback for inspection algorithms and difference filters used to process test and reference images from an inspection system. A user interface may be configured for displaying information and accepting user commands. A computing system communicatively coupled to the user interface may be configured to receive at least one set of test and reference images collected by the inspection system. The computing system may be further configured to provide at least one visual representation of the test and reference images via the user interface to show effects of an inspection algorithm and/or difference filter.

Visual feedback for inspection algorithms and filters

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.

Capture of repeater defects on a semiconductor wafer

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.

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Cupertino, CA, United States of America

Hucheng Lee