Kla Tencor Corporation

William Pierson

Onur Demirer

Hoyoung Heo

Jeremy Nabeth

Mark Davis Smith

Miguel Garcia-Medina

Brent A Riggs

Amnon Manassen

Michael E Adel

Ady Levy

Roie Volkovich

Liran Yerushalmi

John Charles Robinson

Mark Wagner

Pradeep Subrahmanyan

DongSub Choi

Dana Klein

Dongsub Choi

Dror Alumot

Fatima Anis

Ramkumar Karur-Shanmugam

Christian Sparka

Stuart Sherwin

Sanghuck Jeon

Soujanya Vuppala

Lipkong Yap

Choon (George) Hoong Hoo

John Robinson

Michael A Adel

The generation of flexible sparse metrology sample plans includes receiving a full set of metrology signals from one or more wafers from a metrology tool, determining a set of wafer properties based on the full set of metrology signals and calculating a wafer property metric associated with the set of wafer properties, calculating one or more independent characterization metrics based on the full set of metrology signals, and generating a flexible sparse sample plan based on the set of wafer properties, the wafer property metric, and the one or more independent characterization metrics. The one or more independent characterization metrics of the one or more properties calculated with metrology signals from the flexible sparse sampling plan is within a selected threshold from one or more independent characterization metrics of the one or more properties calculated with the full set of metrology signals.

Method and system for process control with flexible sampling

Adaptive alignment methods and systems are disclosed. An adaptive alignment system may include a scanner configured to align a wafer and an analyzer in communication with the scanner. The analyzer may be configured to: recognize at least one defined analysis area; determine whether any perturbations exist within the analysis area; and in response to at least one perturbation determined to be within the analysis area, invoke a fall back alignment strategy or report the at least one perturbation to the scanner.

Adaptive alignment methods and systems

A system for determining a sample map for alignment measurements includes a metrology tool and a controller. The controller defines a full sampling map including a plurality of measurement locations. The controller directs the metrology tool to measure alignment at each measurement location of the full sampling map for a plurality of samples to generate a reference alignment dataset, generates candidate sampling maps, each being a subset of the full sampling map. The controller may further estimate alignment as a function of location based on the two or more candidate sampling maps at each measurement location of the full sampling map, and determine a working sampling map by comparing the estimated alignment to the reference alignment dataset and selecting the candidate sampling map having a smallest number of alignment estimates exceeding a selected tolerance.

Determination of sampling maps for alignment measurements based on reduction of out of specification points

Methods and systems for providing overlay corrections are provided. A method may include: selecting an overlay model configured to perform overlay modeling for a wafer; obtaining a first set of modeled results from the overlay model, the first set of modeled results indicating adjustments applicable to a plurality of term coefficients of the overlay model; calculating a significance matrix indicating the significance of the plurality of term coefficients; identifying at least one less significant term coefficient among the plurality of term coefficients based on the calculated significance matrix; obtaining a second set of modeled results from the overlay model, the second set of modeled results indicating adjustments applicable to the plurality of term coefficients except for the identified at least one less significant term coefficient; and providing the second set of modeled results to facilitate overlay correction.

Overlay variance stabilization methods and systems

A process control system includes a controller configured to generate a reference overlay signature based on one or more overlay reference layers of a sample, extrapolate the reference overlay signature to a set of correctable fields for the exposure of a current layer of the sample to generate a full-field reference overlay signature, identify one or more alignment fields of the set of correctable fields, generate an alignment-correctable signature by modeling alignment corrections for the set of correctable fields, subtract the alignment-correctable signature from the full-field reference overlay signature to generate feedforward overlay corrections for the current layer when the one or more overlay reference layers are the same as the one or more alignment reference layers, generate lithography tool corrections based on the feedforward overlay corrections, and provide the lithography tool corrections for the current layer to the lithography tool.

Layer-to-layer feedforward overlay control with alignment corrections

A process control system may include a controller configured to receive after-development inspection (ADI) data after a lithography step for the current layer from an ADI tool, receive after etch inspection (AEI) overlay data after an exposure step of the current layer from an AEI tool, train a non-zero offset predictor with ADI data and AEI overlay data to predict a non-zero offset from input ADI data, generate values of the control parameters of the lithography tool using ADI data and non-zero offsets generated by the non-zero offset predictor, and provide the values of the control parameters to the lithography tool for fabricating the current layer on the at least one production sample.

Overlay control with non-zero offset prediction

A semiconductor tool includes an illumination source to generate an illumination beam, one or more illumination optical elements to direct a portion of the illumination beam to a sample, a detector, one or more collection optical elements to direct radiation emanating from the sample to the detector, and a controller communicatively coupled to the detector. The controller is configured to measure alignment at a plurality of locations across the sample to generate alignment data, select an analysis area for alignment zone determination, divide the analysis area into two or more alignment zones having different alignment signatures; model the alignment data of at least a first alignment zone of the two or more alignment zones using a first alignment model, and model the alignment data of at least a second alignment zone of the two or more alignment zones using a second alignment model different than the first alignment model.

Systems and methods for automated multi-zone detection and modeling

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Austin, TX, United States of America

William Pierson