Kla Tencor Corporation

Kla Corporation

Robert M Danen

Pavel Kolchin

Mikhail Haurylau

Grace H Chen

Lisheng Gao

Philip Measor

Stefano Palomba

Gary Janik

Richard Wallingford

David W Shortt

Jamie Michael Sullivan

Lu Chen

Steven R Lange

Grace Hsiu-Ling Chen

Rudolf C Brunner

Qiang Q Zhang

Wenjian Cai

Rex Runyon

Steve Yifeng Cui

Markus B Huber

Dieter Wilk

Meier Yitzhak Brender

Junwei Wei

Steve Short

Suwipin Martono

Shobhit Verma

Dmitri G Starodub

Dan Kapp

Abdurrahman Sezginer

Andrew V Hill

Gregory Kirk

Sangbong Park

Santosh Bhattacharyya

Charles Nenghe Wang

Prashant Aji

Soren Konecky

Paul Douglas MacDonald

Christopher Maher

Shuo Sun

Bo Hua

Stephane Durant

Peter Hill

Dmitri Starodub

Thomas Boatwright

Devashish Sharma

An inspection system may generate first-step images of multiple sample regions after a first process step and generate second-step images of the sample regions after a second process step, where the second process step modifies the sample in at least one of the sample regions. The system may further identify one of the sample regions as a test region and at least some of the remaining sample regions as comparison regions, where the second-step image of the test region is a test image and the second-step images of the comparison regions are comparison images. The system may further generate a multi-step difference image by subtracting a combination of at least one of the second-step comparison images and at least two of the first-step images from the test image. The system may further identify defects in the test region associated with the second process step based on the multi-step difference image.

Inspection with previous step subtraction

Methods and systems for discovery of defects of interest (DOI) buried within three dimensional semiconductor structures and recipe optimization are described herein. The volume of a semiconductor wafer subject to defect discovery and verification is reduced by storing images associated with a subset of the total depth of the semiconductor structures under measurement. Image patches associated with defect locations at one or more focus planes or focus ranges are recorded. The number of optical modes under consideration is reduced based on any of a comparison of one or more measured wafer level defect signatures and one or more expected wafer level defect signatures, measured defect signal to noise ratio, and defects verified without de-processing. Furthermore, verified defects and recorded images are employed to train a nuisance filter and optimize the measurement recipe. The trained nuisance filter is applied to defect images to select the optimal optical mode for production.

Defect discovery and recipe optimization for inspection of three-dimensional semiconductor structures

Disclosed are methods and apparatus for facilitating defect detection in a multilayer stack. The method includes selection of a set of structure parameters for modeling a particular multilayer stack and a particular defect contained within such particular multilayer stack and a set of operating parameters for an optical inspection system. Based on the set of structure and operating parameters, an electromagnetic simulation is performed of waves scattered from the particular multilayer stack and defect and arriving at a collection pupil of the optical inspection system. Based on the simulated waves at the collection pupil, a design of a phase filter having a plurality of positions for changing a plurality of phases within a plurality of corresponding positions of the collection pupil of the optical inspection tool is determined so as to compensate for an adverse effect of the particular multilayer stack on obtaining a defect signal for the defect within such particular multilayer stack and/or to enhance such defect signal. The design of the phase filter is then provided for fabrication or configuration of a phase filter inserted within the optical inspection system for detection of defects in multilayer stacks with the same structure parameters as the particular multilayer stack. Methods and systems for inspecting a multilayer stack for defects are also disclosed.

Phase filter for enhanced defect detection in multilayer structure

A three-dimensional calibration structure for measuring buried defects on a semiconductor device is disclosed. The three-dimensional calibration structure includes a defect standard wafer (DSW) including one or more programmed surface defects. The three-dimensional calibration structure includes a planarized layer deposited on the DSW. The three-dimensional calibration structure includes a layer stack deposited on the planarized layer. The layer stack includes two or more alternating layers. The three-dimensional calibration structure includes a cap layer deposited on the layer stack. One or more air gaps are formed in the layer stack following deposition of the cap layer. The three-dimensional calibration structure includes one or more holes formed into at least one of the cap layer, the layer stack, or the planarized layer.

Three-dimensional calibration structures and methods for measuring buried defects on a three-dimensional semiconductor wafer

Methods and systems for improved detection and classification of defects of interest (DOI) on semiconductor wafers based on three-dimensional images are described herein. Three dimensional imaging of volumes of thick, layered structures enables accurate defect detection and estimation of defect location in three dimensions at high throughput. A series of images are acquired at a number of different wafer depths. A three dimensional image of a thick semiconductor structure is generated from the series of images. Defects are identified and classified based on an analysis of the three dimensional image of the thick semiconductor structure. In some examples, the three-dimensional image stack is visualized by contour plots or cross-sectional plots to identify a characteristic defect response. In some examples, the three-dimensional image is processed algorithmically to identify and classify defects. In another aspect, the location of a defect is estimated in three dimensions based on the three dimensional image.

Three-dimensional imaging for semiconductor wafer inspection

Methods and systems for determining boundaries of patterned features formed on a specimen from an unresolved image of the specimen are provided. One system includes computer subsystem(s) configured for comparing a difference image in which patterned feature(s) are unresolved to different simulated images. The different simulated images are generated by simulating difference images generated for the patterned feature(s) formed on the specimen with different perturbations, respectively. The computer subsystem(s) are configured for, based on the comparing, assigning an amplitude to each of the different perturbations. The computer subsystem(s) are further configured for determining one or more boundaries of the patterned feature(s) formed on the specimen by applying the different perturbations to one or more designed boundaries of the patterned feature(s) with the assigned amplitudes.

Aided image reconstruction

Systems and methods for determining information for defects on a wafer are provided. One system includes an illumination subsystem configured to direct light having one or more illumination wavelengths to a wafer. The one or more illumination wavelengths are selected to cause fluorescence from one or more materials on the wafer without causing fluorescence from one or more other materials on the wafer. The system also includes a detection subsystem configured to detect only the fluorescence from the one or more materials or to detect non-fluorescent light from the wafer without detecting the fluorescence from the one or more materials. In addition, the system includes a computer subsystem configured to determine information for defects on the wafer using output generated by the detection subsystem responsive to the detected fluorescence or the detected non-fluorescent light.

Determining information for defects on wafers

Methods and systems for selecting optical modes suitable for defect inspection are disclosed. A method may include: scanning a full-stack wafer of the particular type utilizing a set of optical modes to obtain a set of full-stack wafer images; and de-processing the full-stack wafer to produce a de-processed wafer based on a location of a potential defect of interest indicated by the set of full-stack wafer images to facilitate selection of optical modes suitable for defect inspection of wafers of the particular type.

Methods and systems for selecting recipe for defect inspection

Reverse decoration can be used to detect defects in a device. The wafer can include NAND stacks or other devices. The defect can be a channel bridge, a void, or other types of defects. Reverse decoration can preserve a defect and/or can improve defect detection. A portion of a layer may be removed from a device. A layer also may be added to the device, such as on the defect, and some of the layer may be removed.

Reverse decoration for defect detection amplification

Methods and systems for determining a configuration for an optical element positioned in a collection aperture during wafer inspection are provided. One system includes a detector configured to detect light from a wafer that passes through an optical element, which includes a set of collection apertures, when the optical element has different configurations thereby generating different images for the different configurations. The system also includes a computer subsystem configured for constructing additional image(s) from two or more of the different images, and the two or more different images used to generate any one of the additional image(s) do not include only different images generated for single collection apertures in the set. The computer subsystem is further configured for selecting one of the different or additional configurations for the optical element based on the different images and the additional image(s).

Determining a configuration for an optical element positioned in a collection aperture during wafer inspection

Disclosed are methods and apparatus for optimizing a mode of an inspection tool. A first image or signal for each of a plurality of first apertures of the inspection tool is obtained, and each first image or signal pertains to a defect area. For each of a plurality of combinations of the first apertures and their first images or signals, a composite image or signal is obtained. Each composite image or signal is analyzed to determine an optimum one of the combinations of the first apertures based on a defect detection characteristic of each composite image. In one aspect, determining an optimum one of the combinations of the first apertures includes selecting a set of one or more individual apertures that result in the highest signal to noise ratio for the defect area, and the method includes setting the optimum combination of the first apertures on the inspection tool and inspecting a sample using such optimum combination of the first apertures.

Apparatus and methods for finding a best aperture and mode to enhance defect detection

A computer-based apparatus for adjusting an auto-focus in a wafer inspection system, including: a wafer adjustment system; and an electronic feedback loop system configured to compare an intensity of a first light beam rotating in a first spiral about a first central axis, and when the intensity is less than a preselected threshold, adjust, using the wafer adjustment system, a position of the wafer until the intensity reaches the preselected threshold.

System and method to determine depth for optical wafer inspection

Disclosed are methods and apparatus for optimizing a mode of an inspection tool. A first image or signal for each of a plurality of first apertures of the inspection tool is obtained, and each first image or signal pertains to a defect area. For each of a plurality of combinations of the first apertures and their first images or signals, a composite image or signal is obtained. Each composite image or signal is analyzed to determine an optimum one of the combinations of the first apertures based on a defect detection characteristic of each composite image.

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Pleasanton, CA, United States of America

Robert M Danen