Kla Tencor Corporation

Kla-tencor Technologies Corporation

Kla Corporation

Lisheng Gao

Kenong Wu

Junqing Huang

Tao Luo

Hucheng Lee

Richard Wallingford

Bjorn Brauer

Lu Chen

Grace H Chen

Ashok V Kulkarni

Eugene Shifrin

Grace Hsiu-Ling Chen

Yong Zhang

Jason Kirkwood

Robert M Danen

Mohan Mahadevan

James A Smith

Raghav Babulnath

Michal Kowalski

Ping Gu

Junqing (Jenny) Huang

David W Shortt

Santosh Bhattacharyya

Xiaochun Li

Keith B Wells

Tong Huang

Stephanie Chen

Markus B Huber

David Winslow Randall

Jianxin Zhang

Ashok Mathew

Ariel Tribble

Allen Park

Kris Bhaskar

Rudolf C Brunner

Jan A Lauber

Pavel Kolchin

Ingrid B Peterson

Songnian Rong

Tommaso Torelli

Satya Kurada

Ramon Ynzunza

Pavan Kumar

Govindarajan Thattaisundaram

Sumit Sen

Sreeram Chandrasekaran

Meng-Che Wu

Kwok Ng

Kourosh Nafisi

Benjamin Murray

Abdurrahman Sezginer

Brian Duffy

Tao-Yi Fu

Ellis Chang

Yalin Xiong

Jing Zhang

Saibal Banerjee

Patrick Huet

Michael John Van Riet

Khurram Zafar

Yan Xiong

Sharon McCauley

Xuguang Jiang

Soren Konecky

Thirupurasundari Jayaraman

Chris W Lee

Chetana Bhaskar

Cecelia Anne Campochiaro

Sylvain Muckenhirn

Cho Huak Teh

Sandeep Bhagwat

Raghavan Konuru

Steve R Lange

Christopher Maher

Hawren Fang

Chaohong Wu

Huan Jin

Shishir Suman

Srikanth Kandukuri

Rahul Lakhawat

Vivekanand Kini

Yong Gao

Gangadharan Sivaraman

Jun Lang

Shuo Sun

Avijit K Ray-Chaudhuri

Karthikeyan Subramanian

Qing Luo

Dominic David

Lalita A Balasubramanian

Jonathan Oakley

Maruti Shanbhag

Aravindh Balaji

Bjorn Braeuer

Kan Chen

Jingshan Zhong

Liu-Ming Wu

Chiuman Yeung

Michael Gordon Scott

Nan Bai

Systems and methods increase the signal to noise ratio of optical inspection of wafers to obtain higher inspection sensitivity. The computed reference image can minimize a norm of the difference of the test image and the computed reference image. A difference image between the test image and a computed reference image is determined. The computed reference image includes a linear combination of a second set of images.

Wafer inspection using difference images

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

Defects from a hot scan can be saved, such as on persistent storage, random access memory, or a split database. The persistent storage can be patch-based virtual inspector virtual analyzer (VIVA) or local storage. Repeater defect detection jobs can determined and the wafer can be inspected based on the repeater defect detection jobs. Repeater defects can be analyzed and corresponding defect records to the repeater defects can be read from the persistent storage. These results may be returned to the high level defect detection controller.

Repeater defect detection

Methods and systems for determining a layer on which a defect detected on a wafer is located are provided. One method includes detecting defects on a wafer by directing light to the wafer at first and second angles of incidence and determining locations of the defects on the wafer based on the output corresponding to the defects. For one of the defects detected in the output generated for one spot illuminated on the wafer with the light directed to the wafer at the first and second angles, the method includes comparing the locations of the one of the defects determined based on the output generated with the light directed to the one spot on the wafer at the first and second angles. The method further includes determining a layer of the wafer on which the one of the defects is located based on results of the comparing.

Previous layer nuisance reduction through oblique illumination

Methods and systems for generating a high resolution image for a specimen from one or more low resolution images of the specimen are provided. One system includes one or more computer subsystems configured for acquiring one or more low resolution images of a specimen. The system also includes one or more components executed by the one or more computer subsystems. The one or more components include a model that includes one or more first layers configured for generating a representation of the one or more low resolution images. The model also includes one or more second layers configured for generating a high resolution image of the specimen from the representation of the one or more low resolution images.

Generating high resolution images from low resolution images for semiconductor applications

Systems and methods for detecting defects on a wafer are provided. One method includes generating output for a wafer by scanning the wafer with an inspection system using first and second optical states of the inspection system. The first and second optical states are defined by different values for at least one optical parameter of the inspection system. The method also includes generating first image data for the wafer using the output generated using the first optical state and second image data for the wafer using the output generated using the second optical state. In addition, the method includes combining the first image data and the second image data corresponding to substantially the same locations on the wafer thereby creating additional image data for the wafer. The method further includes detecting defects on the wafer using the additional image data.

Systems and methods for detecting defects on a wafer

Systems and methods of a two-pass inspection methodology that dynamically creates micro care areas for inspection of repeater defects. Micro care areas can be formed around each location of a repeater defect. After inspection, additional repeater defects in the micro care areas can be identified. Attributes of the repeater defects can be compared and any repeater defects with attributes that deviate from an expected group attribute distribution can be classified as nuisance.

Dynamic care areas for defect detection

Methods and systems are disclosed that provide nuisance reduction in images, such as semiconductor images that include one or more metal lines. A potential defect is correlated against pixel grey level intensity charts for two perpendicular axes. A position of the potential defect relative to a pattern, such as a metal line, is determined along the two axes. The potential defect can be classified as a defect of interest or nuisance event.

Nuisance reduction using location-based attributes

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

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.

Automatic recipe stability monitoring and reporting

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.

Adaptive local threshold and color filtering

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.

High sensitivity repeater defect detection

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.

Intra-die defect detection

Growing community of inventors

Morgan Hill, CA, United States of America

Lisheng Gao