Kla Corporation

Nireekshan K Reddy

Vladimir Levinski

Amnon Manassen

Daria Negri

Yuri Paskover

Anna Golotsvan

Yossi Simon

Nachshon Rothman

Andrew V Hill

Yoram Uziel

Nadav Gutman

Avi Abramov

Yonatan Vaknin

Nir BenDavid

Dror Yaacov

Roie Volkovich

A system for use with a misregistration metrology tool (MMT), the system including a database including a plurality of process variation (PV) categories and a corresponding plurality of parameter sets and a process variation accommodation engine (PVAE) including a measurement site process variation category associator (MSPVCA) operative to associate a measurement site being measured by the MMT, at least partially based on an MMT output relating to the measurement site, with a measurement site process variation category (MSPVC), the MSPVC being one of the plurality of PV categories, a measurement site parameter set retriever (MSPSR) operative to retrieve a measurement site parameter set (MSPS) corresponding to the MSPVC and a measurement site parameter set communicator (MSPSC) operative to communicate the MSPS to the MMT.

Systems and methods for measurement of misregistration and amelioration thereof

An adaptive modeling method for generating misregistration data for a semiconductor device wafer (SDW) including calculating a fitting function for a group of SDWs (GSDW) having units, including measuring an SDW in said GSDW, thereby generating test data sets corresponding to the units, removing non-unit-specific values (NUSVs) from the test data sets, thereby generating cleaned test data sets, and analyzing the cleaned test data sets, thereby generating the fitting function, and generating misregistration data for at least one additional SDW (ASDW) in the GSDW, including measuring the ASDW, thereby generating run data sets, removing NUSVs from the run data sets, thereby generating cleaned run data sets, fitting each of the cleaned run data sets to the fitting function, thereby generating coefficient sets, and calculating misregistration data for the ASDW, at least partially based on the fitting function and the coefficient sets.

Adaptive modeling misregistration measurement system and method

A metrology system may arrange metrology measurements for a plurality of metrology targets distributed in a plurality of fields on one or samples into a signal vector, where the metrology measurements associated with the metrology targets in each of the plurality of fields are grouped within the signal vector. The system may further decompose the signal vector into reconstruction vectors associated with different spectral components of the signal vector. The system may further classify a subset of the reconstruction vectors as components of a metrology model, where a sum of the components corresponds to a metrology model describing the metrology measurements on the one or more samples. The system may further generate control signals to control one or more processing tools based on the metrology model.

Universal metrology model

A system may include a controller for receiving one or more images of a metrology target including periodic features with one or more known pitches, pre-processing the one or more images using a decomposition technique to generate one or more pre-processed images, and generating one or more metrology measurements for the metrology target based on the one or more pre-processed images. Pre-processing a particular image of the one or more images may include constructing one or more trajectory matrices from the particular image, generating reconstruction components associated with the particular image from the one or more trajectory matrices using the decomposition technique, and generating a particular one of the one or more pre-processed images by based on a subset of the reconstruction components including signals with at least one of the one or more known pitches.

Image pre-processing for overlay metrology using decomposition techniques

A method includes generating a sequence of images of a semiconductor wafer from first and second detectors. The first detector images the wafer with first imaging parameters and the second detector images the wafer with second imaging parameters. The first or second imaging parameters are varied across the sequence of images to provide variation at sites across the wafer. The method includes providing a metric indicative of center-of-symmetry variations of first and second target features as a function of the varied imaging parameters based on the sequence of images. The method includes identifying a landscape of values of the varied image parameters for which the metric are below a predefined limit. The method includes generating a recipe for metrology measurements in which the varied imaging parameters are set to values within the landscape. The method includes generating metrology measurements from a production wafer based on the recipe.

Enhancing performance of overlay metrology

A method for metrology includes directing at least one illumination beam to illuminate a semiconductor wafer on which at least first and second patterned layers have been deposited in succession, including a first target feature in the first patterned layer and a second target feature in the second patterned layer, overlaid on the first target feature. A sequence of images of the first and second target features is captured while varying one or more imaging parameters over the sequence. The images in the sequence are processed in order to identify respective centers of symmetry of the first and second target features in the images and measure variations in the centers of symmetry as a function of the varying image parameters. The measured variations are applied in measuring an overlay error between the first and second patterned layers.

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Tel Aviv, Israel

Nireekshan K Reddy