Kla Corporation

Kla Tencor Corporation

Purdue Research Foundation

Vaibhav Gaind

Bjorn Brauer

Mark Shi Wang

Grace H Chen

Jason Kirkwood

Kevin John Webb

Brian Zahler Bentz

Timothy Cheng-Hsien Wu

Amrit Poudel

Nisha Amthul

A semiconductor-inspection tool scans a semiconductor die using a plurality of optical modes. A plurality of defects on the semiconductor die are identified based on results of the scanning. Respective defects of the plurality of defects correspond to respective pixel sets of the semiconductor-inspection tool. The scanning fails to resolve the respective defects. The results include multi-dimensional data based on pixel intensity for the respective pixel sets, wherein each dimension of the multi-dimensional data corresponds to a distinct mode of the plurality of optical modes. A discriminant function is applied to the results to transform the multi-dimensional data for the respective pixel sets into respective scores. Based at least in part on the respective scores, the respective defects are divided into distinct classes.

Multimode defect classification in semiconductor inspection

Methods and systems for aligning images of a specimen generated with different modes of an imaging subsystem are provided. One method includes separately aligning first and second images generated with first and second modes, respectively, to a design for the specimen. For a location of interest in the first image, the method includes generating a first difference image for the location of interest and the first mode and generating a second difference image for the location of interest and the second mode. The method also includes aligning the first and second difference images to each other and determining information for the location of interest from results of the aligning.

Multi-imaging mode image alignment

Methods and systems for selecting mode(s) for inspection of specimens are provided. One method includes statistically predicting if data points in a set correspond to defects or nuisances on a specimen. The data points include attribute(s) determined for discrete locations on the specimen from output generated by two or more modes of an inspection system. Events have been detected at the discrete locations with at least one of the modes. The method also includes determining a quantitative measure for each of two or more different combinations of the modes thereby determining different quantitative measures. The quantitative measure for each of the different combinations is responsive to how well one of the combinations detects the defects and minimizes detection of the nuisances. The method further includes selecting one or more of the modes for inspection of specimens of the same type as the specimen based on the determined quantitative measures.

Statistical learning-based mode selection for multi-mode inspection

Methods for locating blood vessels, lesions, and other discontinuities in tissue such as, but not limited to, the greater palatine artery (GPA) in the hard palate using an optical imaging process, surgical procedures utilizing the identified locations of discontinuities, and devices suitable for use during surgical procedures. According to one aspect, such a method locates a blood vessel or lesion in tissue by imaging the tissue via a diffuse optical imaging (DOI) process that measures light that travels through the tissue, and then locates the blood vessel or lesion in the tissue based on a difference in absorption of the light between the tissue and the blood vessel or lesion.

Methods for locating discontinuities in tissue using optical imaging, surgical procedures, and devices for use during surgical procedures

A system for detecting defects on a semiconductor sample includes an illumination module for directing a nonzero-order Gaussian illumination beam towards a plurality of locations on a sample and a collection module for detecting light scattered from the sample in response to the nonzero-order Gaussian illumination beams and generating a plurality of output images or signals for each location on the sample. The system further comprises a processor system for detecting defects by (i) processing the output images or signals so as to retain filtered image or signal portions that substantially match a point spread function of the one or more nonzero-order Gaussian illumination beams, and (ii) analyzing the filtered image or signal portions to detect defects on the sample.

Methods and apparatus for speckle suppression in laser dark-field systems

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.

Growing community of inventors

Fremont, CA, United States of America

Vaibhav Gaind