Asml Netherlands B.v.

Sarathi Roy

Wim Tjibbo Tel

Yichen Zhang

Roy Werkman

Cédric Désiré Grouwstra

Alexander Ypma

Edo Maria Hulsebos

Nitish Kumar

Georgios Tsirogiannis

Dimitra Gkorou

Robert Jan Van Wijk

Tzu-Chao Chen

Jelle Nije

Frans Reinier Spiering

Junru Ruan

Arie Jeffrey Den Boef

Han-Kwang Nienhuys

Pieter-Jan Van Zwol

Sander Bas Roobol

Yang-Shan Huang

Ferry Zijp

Duygu Akbulut

Sietse Thijmen Van Der Post

Daan Maurits Slotboom

Weitian Kou

David Frans Simon Deckers

Tamara Druzhinina

Peter Danny Van Voorst

Hadi Yagubizade

Simon Philip Spencer Hastings

Xiuhong Wei

Bijoy Rajasekharan

Manouk Rijpstra

Mohammad Reza Kamali

Cornelis Johannes Henricus Lambregts

Pieter Gerardus Jacobus Smorenberg

Adrianus Johannes Hendrikus Schellekens

Willem Maria Julia Marcel Coene

Jeroen Van Dongen

Johannes Franciscus Martinus D'Achard Van Enschut

Jeonghyun Park

Yingchao Cui

Andrea Cavalli

Bart Laurens Sjenitzer

Chi-Fei Nien

Chang-Wei Chen

Ignacio Salvador Vazquez Rodarte

Sang Uk Kim

A method to determine a performance indicator indicative of alignment performance of a processed substrate. The method includes obtaining measurement data including a plurality of measured position values of alignment marks on the substrate and calculating a positional deviation between each measured position value and a respective expected position value. These positional deviations are used to determine a directional derivative between the alignment marks, and the directional derivatives are used to determine at least one directional derivative performance indicator.

Metrology method and associated metrology and lithographic apparatuses

A method of determining a control parameter for a lithographic process is disclosed, the method includes: defining a substrate model for representing a process parameter fingerprint across a substrate, the substrate model being defined as a combination of basis functions including at least one basis function suitable for representing variation of the process parameter fingerprint between substrates and/or batches of substrates; receiving measurements of the process parameter across at least one substrate; calculating substrate model parameters using the measurements and the basis functions; and determining the control parameter based on the substrate model parameters and the similarity of the at least one basis function to a process parameter fingerprint variation between substrates and/or batches of substrates.

Methods and apparatus for controlling a lithographic process

A method for determining lithographic matching performance includes obtaining first monitoring data from recurrent monitoring for stability control for an available EUV scanner. For a DUV scanner, second monitoring data is similarly obtained from recurrent monitoring for stability control. The EUV first monitoring data are in a first layout. The DUV second monitoring data are in a second layout. A cross-platform overlay matching performance between the first lithographic apparatus and the second lithographic apparatus is determined based on the first monitoring data and the second monitoring data. This is done by reconstructing the first and/or second monitoring data into a common layout to allow comparison of the first and second monitoring data.

Determining lithographic matching performance

A method for generating metrology sampling scheme for a patterning process, the method including: obtaining a parameter map of a parameter of a patterning process for a substrate; decomposing the parameter map to generate a fingerprint specific to an apparatus of the patterning process and/or a combination of apparatuses of the patterning process; and based on the fingerprint, generating a metrology sampling scheme for a subsequent substrate at the apparatus of the patterning process and/or the combination of apparatuses of the patterning process, wherein the sampling scheme is configured to distribute sampling points on the subsequent substrate so as to improve a metrology sampling density.

Computational metrology based sampling scheme

A method for configuring a semiconductor manufacturing process, the method including: obtaining a first value of a first parameter based on measurements associated with a first operation of a process step in the semiconductor manufacturing process and a first sampling scheme; using a recurrent neural network to determine a predicted value of the first parameter based on the first value; and using the predicted value of the first parameter in configuring a subsequent operation of the process step in the semiconductor manufacturing process.

Determining a correction to a process

A method of optimizing an apparatus for multi-stage processing of product units such as wafers, the method includes: receiving object data representing one or more parameters measured across the product units and associated with different stages of processing of the product units; and determining fingerprints of variation of the object data across the product units, the fingerprints being associated with different respective stages of processing of the product units. The fingerprints may be determined by decomposing the object data into components using principal component analysis for each different respective stage; analyzing commonality of the fingerprints through the different stages to produce commonality results; and optimizing an apparatus for processing product units based on the commonality results.

Optimizing an apparatus for multi-stage processing of product units

A method for determining a correction to a patterning process. The method includes obtaining a plurality of qualities of the patterning process (e.g., a plurality of parameter maps, or one or more corrections) derived from metrology data and data of an apparatus used in the patterning process, selecting, by a hardware computer system, a representative quality from the plurality of qualities, and determining, by the hardware computer system, a correction to the patterning process based on the representative quality.

Computational metrology based correction and control

A method of determining a sampling control scheme and/or a processing control scheme for substrates processed by a device. The method uses a fingerprint model and an evolution model to generate the control scheme. The fingerprint model is based on fingerprint data for a processing parameter of at least one substrate processed by a device, and the evolution model represents variation of the fingerprint data over time. The fingerprint model and the evolution model are analyzed and a sampling and/or processing control scheme is generated using the analysis. The sampling control scheme provides an indication for where and when to take measurements on substrates processed by the device. The processing control scheme provides an indication for how to control the processing of the substrate. Also, there is provided a method of determining which of multiple devices contributed to a fingerprint of a processing parameter.

Methods using fingerprint and evolution analysis

An optical system delivers illuminating radiation and collects radiation after interaction with a target structure on a substrate. A measurement intensity profile is used to calculate a measurement of the property of the structure. The optical system may include a solid immersion lens. In a method, the optical system is controlled to obtain a first intensity profile using a first illumination profile and a second intensity profile using a second illumination profile. The profiles are used to derive a correction for mitigating the effect of, e.g., ghost reflections. Using, e.g., half-moon illumination profiles in different orientations, the method can measure ghost reflections even where a solid immersion lens would cause total internal reflection. The optical system may include a contaminant detection system to control a movement based on received scattered detection radiation. The optical system may include an optical component having a dielectric coating to enhance evanescent wave interaction.

Method and apparatus for deriving corrections, method and apparatus for determining a property of a structure, device manufacturing method

Disclosed is a method and associated inspection apparatus for detecting variations on a surface of a substrate. The method comprises providing patterned inspection radiation to a surface of a substrate. The inspection radiation is patterned such that an amplitude of a corresponding enhanced field is modulated in a manner corresponding to the patterned inspection radiation. The scattered radiation resultant from interaction between the enhanced field and the substrate surface is received and variations on the surface of the substrate are detected based on the interaction between the enhanced field and the substrate surface. Also disclosed is a method of detecting any changes to at least one characteristic of received radiation, the said changes being induced by the generation of a surface plasmon at said surface of the optical element.

Method and apparatus for detecting substrate surface variations

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Eindhoven, Netherlands

Sarathi Roy