Asml Netherlands B.v.

Marc Johannes Noot

Simon Gijsbert Josephus Mathijssen

Kaustuve Bhattacharyya

Arie Jeffrey Den Boef

Mohammadreza Hajiahmadi

Timothy Dugan Davis

Scott Anderson Middlebrooks

Murat Bozkurt

Jin Lian

Olger Victor Zwier

Grzegorz Grzela

Peter David Engblom

Alberto Da Costa Assafrao

Martyn John Coogans

Ralph Timotheus Huijgen

Jan-Willem Gemmink

Narjes Javaheri

Farzad Farhadzadeh

Won-Jae Jang

Jinmoo Byun

Hyun-Su Kim

Rene Andreas Maria Pluijms

A method provides the steps of receiving an image from a metrology tool, determining individual units of said image and discriminating the units which provide accurate metrology values. The images are obtained by measuring the metrology target at multiple wavelengths. The discrimination between the units, when these units are pixels in said image, is based on calculating a degree of similarity between said units.

Metrology method

Disclosed are a method, computer program and a metrology apparatus for measuring a process effect parameter relating to a manufacturing process for manufacturing integrated circuits on a substrate. The method comprises determining for a structure, a first quality metric value for a quality metric from a plurality of measurement values each relating to a different measurement condition while cancelling or mitigating for the effect of the process effect parameter on the plurality of measurement values and a second quality metric value for the quality metric from at least one measurement value relating to at least one measurement condition without cancelling or mitigating for the effect of the process effect parameter on the at least one measurement value. The process effect parameter value for the process effect parameter can then be calculated from the first quality metric value and the second quality metric value, for example by calculating their difference.

Metrology method and apparatus and computer program

Disclosed is a method, and associated apparatuses, for measuring a parameter of interest relating to a structure having at least two layers. The method comprises illuminating the structure with measurement radiation and detecting scattered radiation having been scattered by said structure. The scattered radiation comprises normal and complementary higher diffraction orders. A scatterometry model which relates a scattered radiation parameter to at least a parameter of interest and an asymmetry model which relates the scattered radiation parameter to at least one asymmetry parameter are defined, the asymmetry parameter relating to one or more measurement system errors and/or an asymmetry in the target other than a misalignment between the two layers. A combination of the scatterometry model and asymmetry model is used to determine a system of equations, and the system of equations is then solved for the parameter of interest.

Metrology method and apparatus, computer program and lithographic system

A method including: for a metrology target, having a first biased target structure and a second differently biased target structure, created using a patterning process, obtaining metrology data including signal data for the first target structure versus signal data for the second target structure, the metrology data being obtained for a plurality of different metrology recipes and each metrology recipe specifying a different parameter of measurement; determining a statistic, fitted curve or fitted function through the metrology data for the plurality of different metrology recipes as a reference; and identifying at least two different metrology recipes that have a variation of the collective metrology data of the at least two different metrology recipes from a parameter of the reference that crosses or meets a certain threshold.

Metrology parameter determination and metrology recipe selection

An inspection method, and corresponding apparatus, enables classification of pupil images according to a process variable. The method comprises acquiring diffraction pupil images of a plurality of structures formed on a substrate during a lithographic process. A process variable of the lithographic process varies between formation of the structures, the variation of the process variable resulting in a variation in the diffraction pupil images. The method further comprises determining at least one discriminant function for the diffraction pupil images, the discriminant function being able to classify the pupil images in terms of the process variable.

Inspection method and apparatus, and corresponding lithographic apparatus

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Eindhoven, Netherlands

Marc Johannes Noot