Applied Materials Israel Limited

Shaul Cohen

Shalom Elkayam

Noam Zac

Amit Batikoff

Ron Katzir

Lavi Jacov Shachar

Imry Kissos

Tal Ben-Shlomo

Elad Ben Baruch

Ishai Schwarzband

Doron Girmonsky

Shay Attal

Mor Baram

Dror Alumot

Guy Maoz

Lee Moldovan

Kfir Ben-Zikri

There is provided a system and method of runtime examination of a semiconductor specimen. The method includes obtaining a runtime image representative of an inspection area of the specimen, the runtime image having a relatively low signal-to-noise ratio (SNR); and processing the runtime image using a machine learning (ML) model to obtain examination data specific for a given examination application, wherein the ML model is previously trained for the given examination application using one or more training samples, each training sample representative of a respective reference area sharing the same design pattern as the inspection area and comprising: a first training image of the respective reference area having a relatively low SNR; and label data indicative of ground truth in the respective reference area pertaining to the given examination application, the label data obtained by annotating a second training image of the respective reference area having a relatively high SNR.

Machine learning based examination of a semiconductor specimen and training thereof

There are provided systems and methods of obtaining a segmented image of a semiconductor specimen, the image comprising first structural elements, obtaining a reference image of the semiconductor specimen, the reference image being based on design data and comprising second structural elements, determining, for at least one pair of elements including a first structural element and a corresponding second structural element, data Dinformative of a spatial transformation required in order to match the elements of the pair in accordance with a matching criterion, and determining at least one of data informative of a defect in the first structural element and data informative of edge roughness of the first structural element using at least D.

Determination of defects and/or edge roughness in a specimen based on a reference image

There is provided a system and method of segmenting an image of a fabricated semiconductor specimen. The method includes: obtaining a first probability map corresponding to the image representative of at least a portion of the fabricated semiconductor specimen and indicative of predicted probabilities of pixels in the image to correspond to one or more first structural elements presented in the image, obtaining a first label map informative of one or more segments representative of second structural elements and labels associated with the segments, performing simulation on the first label map to obtain a second probability map indicative of simulated probabilities of pixels in the first label map to correspond to the one or more segments, and generating a second label map based on the first probability map and the second probability map, the second label map being usable for segmentation of the image with enhanced repeatability.

Segmentation of an image of a semiconductor specimen

There is provided a system and method of generating a training set for training a Deep Neural Network usable for examination of a specimen. The method includes: for each given training image in a group: i) generating a first batch of training patches, including cropping the given training image into a first plurality of original patches; and augmenting at least part of the first plurality of original patches in order to simulate variations caused by a physical process of the specimen; and ii) generating a second batch of training patches, including: shifting the plurality of first positions on the given training image to obtain a second plurality of original patches, and repeating the augmenting to the second plurality of original patches to generate a second plurality of augmented patches; and including at least the first second batches of training patches corresponding to each given training image in the training set.

Generating a training set usable for examination of a semiconductor specimen

There is provided a system and method of examination of a semiconductor specimen using an examination recipe. The method includes obtaining a registered image pair, for each design-based structural element associated with a given layer, calculating an edge attribute, using a trained classifier to determine a class of the design-based structural element, and generating a layer score usable to determine validity of the registered image pair. There is also provided a system and method of generating the examination recipe usable for examination of a semiconductor specimen.

Examination of a semiconductor specimen

An apparatus, method and non-transitory computer readable storage medium for registering between an image and a description of a multi-layer object, the apparatus comprising: a memory for storing an image of the object and at least part of the description, the part comprising a first description of a first layer and a second description of a second layer of the object; and a processor operatively connected to the memory for: matching the first description to a first part of the image, the first part informative of a part of the first layer, thereby determining a first matching offset; matching the second description to a second part of the image, the second part informative of a part of the second layer, thereby determining a second matching offset; and registering between the image and the description of the multi-layer object based on the at least on the first and second matching offsets.

Registration between an image of an object and a description

One or more metrology objects and one or more metrology operations may be identified. A design-based representation of a first metrology object of the one or more metrology objects may be received. Furthermore, an image-based representation of the first metrology object of the one or more metrology objects may be received where the one or more metrology operations include a first metrology operation associated with the first metrology object that is to be performed on the image-based representation of the first metrology object. The design-based representation of the first metrology object may be mapped with the image-based representation of the first metrology object. The first metrology operation may be performed based on the mapping.

Method of performing metrology operations and system thereof

A method for evaluating an object, the method may include acquiring, by a charged particle beam system, an image of an area of a reference object, wherein the area includes multiple instances of a structure of interest, and the structure of interest is of a nanometric scale; determining multiple types of attributes from the image; reducing a number of the attributes to provide reduced attribute information; generating guidelines, based on the reduced attribute information and on reference data, for evaluating the reduced attribute information; and evaluating an actual object by implementing the guidelines.

Evaluating an object

There are provided system and method of performing metrology operations related to a specimen. The method comprises: generating an examination recipe in accordance with a metrology application, the examination recipe specifying one or more metrology objects and one or more metrology operations related to the metrology application; obtaining an image-based representation of the specimen and a design-based representation of the specimen; mapping between the design-based representation of at least first metrology object and the image-based representation of at least first metrology object; and performing at least first metrology operation of the one or more metrology operations according to the examination recipe using the mapping, the at least first metrology operation specified as related to the at least first metrology object and to be performed on at least the image-based representation of the specimen.

There are provided system and method of performing metrology operations related to a specimen. The method comprises: accommodating definitions of metrology objects and metrology operations, at least one of the group consisting of the metrology objects and the metrology operations being defined using design data; accommodating a design-based representation and an image-based representation of the specimen, the design-based representation of the specimen comprising design-based representation of at least first metrology object, the image-based representation of the specimen comprising image-based representation of the at least first metrology object, the metrology operations including at least first metrology operation defined as related to the at least first metrology object and performed on at least the image-based representation of the specimen; mapping between the design-based representation and the image-based representation of the at least first metrology object; and performing the at least first metrology operation according to definition thereof using the mapping.

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Irus, Israel

Shaul Cohen