Kla Tencor Corporation

Kla Corporation

Raghavan Konuru

Martin Plihal

Saravanan Paramasivam

Prasanti Uppaluri

Thirupurasundari Jayaraman

Lisheng Gao

Santosh Bhattacharyya

Arpit Yati

Raghav Babulnath

Ankit Jain

Michael Lennek

Srikanth Kandukuri

Niveditha Lakshmi Narasimhan

Rahul Lakhawat

Gangadharan Sivaraman

Pavan Kumar

Arun Lobo

Arpit Jain

Karthikeyan Subramanian

Raj Kuppa

Hema Prasad

Saiyashwanth Momula

Naema Bhatti

Aditya Gulati

Methods and systems for determining information for a specimen are provided. One system includes a computer subsystem and one or more components executed by the computer subsystem. The one or more components include a deep learning model configured for denoising an image of a specimen generated by an imaging subsystem. The computer subsystem is configured for determining information for the specimen from the denoised image.

Deep learning image denoising for semiconductor-based applications

Methods and systems for selecting a mode for inspection of a specimen are provided. One method includes determining how separable defects of interest (DOIs) and nuisances detected on a specimen are in one or more modes of an inspection subsystem. The separability of the modes for the Dais and nuisances is used to select a subset of the modes for inspection of other specimens of the same type. Other characteristics of the performance of the modes may be used in combination with the separability to select the modes. The subset of modes selected based on the separability may also be an initial subset of modes for which additional analysis is performed to determine the final subset of the modes.

Mode selection for inspection

Deskew for image review, such as SEM review, aligns inspection and review coordinate systems. Deskew can be automated using design files or inspection images. A controller that communicates with a review tool can align a file of the wafer, such as a design file or an inspection image, to an image of the wafer from the review tool; compare alignment sites of the file to alignment sites of the image from the review tool; and generate a deskew transform of coordinates of the alignment sites of the file and coordinates of alignment sites of the image from the review tool. The image of the wafer may not contain defects.

Automatic deskew using design files or inspection images

Methods and systems for determining a position of output generated by an inspection subsystem in design data space are provided. In general, some embodiments described herein are configured for substantially accurately aligning inspection subsystem output generated for a specimen to a design for the specimen despite deformation of the design in the inspection subsystem output. In addition, some embodiments are configured for generating and/or using alignment targets that can be shared across multiple specimens of the same layer and design rule for alignment of inspection subsystem output generated for a specimen to a design for the specimen.

Sub-pixel alignment of inspection to design

Methods and systems for setting up a classifier for defects detected on a wafer are provided. One method includes generating a template for a defect classifier for defects detected on a wafer and applying the template to a training data set. The training data set includes information for defects detected on the wafer or another wafer. The method also includes determining one or more parameters for the defect classifier based on results of the applying step.

Creating defect classifiers and nuisance filters

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Andhra Pradesh, India

Raghavan Konuru