Asml Netherlands B.v.

Roy Werkman

Jochem Sebastiaan Wildenberg

Everhardus Cornelis Mos

Erik Johannes Maria Wallerbos

Bijoy Rajasekharan

Marinus Jochemsen

Cornelis Johannes Rijnierse

Frank Staals

Sarathi Roy

Erik Jensen

Davit Harutyunyan

Wim Tjibbo Tel

Thomas Theeuwes

Maxim Pisarenco

Edo Maria Hulsebos

Emil Peter Schmitt-Weaver

David Frans Simon Deckers

Koenraad Remi André Maria Schreel

Vahid Bastani

Fuming Wang

Cornelis Johannes Henricus Lambregts

Tom Van Hemert

Rizvi Rahman

Robertus Wilhelmus Van Der Heijden

Putra Saputra

Jurgen Johannes Henderikus Maria Schoonus

Hugo Thomas Looijestijn

Fei Jia

Junru Ruan

Jens Stäcker

Maurits Van Der Schaar

Richard Johannes Franciscus Van Haren

Franciscus Godefridus Casper Bijnen

Hubertus Johannes Gertrudus Simons

Ralph Brinkhof

Franciscus Bernardus Maria Van Bilsen

Henricus Johannes Lambertus Megens

Yana Cheng

Leonardus Henricus Marie Verstappen

Leon Paul Van Dijk

Marc Hauptmann

Weitian Kou

Chenxi Lin

Hermanus Adrianus Dillen

Bart Swinnen

Marc Jurian Kea

Hadi Yagubizade

Victor Emanuel Calado

Simon Philip Spencer Hastings

Johannes Marcus Maria Beltman

Xiuhong Wei

Lydia Marianna Vergaij-Huizer

Pieter Gerardus Jacobus Smorenberg

Samee Ur Rehman

Adam Jan Urbanczyk

Jeroen Van Dongen

Theo Wilhelmus Maria Thijssen

Ekaterina Mikhailovna Viatkina

Amir Bin Ismail

Svetla Petrova Matova

Christopher Prentice

Kevin Van De Ruit

Khalid Elbattay

Ronald Van Ittersum

Laurent Michel Marcel Depre

Erik Mathijs Maria Crombag

Paul Derwin

Luc Roumen

Henricus Jacobus Maria Verhoeven

Jeffrey Thomas Ziebarth

Allwyn Boustheen

Raheleh Pishkari

Ignacio Salvador Vazquez Rodarte

Ivo Matteo Leonardus Weijden

Ruud Rudolphus Johannes Catharinus De Wit

Hans Marinus Struijs

Maria Helena Schut

Erwin Riemens

Menno Meeldijk

Hyun-Woo Yu

Gautam Sarma

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 of controlling a semiconductor manufacturing process, the method including: obtaining first metrology data based on measurements performed after a first process step; obtaining second metrology data based on measurements performed after the first process step and at least one additional process step; estimating a contribution to the process of: a) a control action which is at least partially based on the second metrology data and/or b) the at least one additional process step by using at least partially the second metrology data; and determining a Key Performance Indicator (KPI) or a correction for the first process step using the first metrology data and the estimated contribution.

Method for controlling a semiconductor manufacturing process

A method of determining a position of a product feature on a substrate, the method includes: obtaining a plurality of position measurements of one or more product features on a substrate, wherein the measurements are referenced to either a positioning system used in displacing the substrate in between measurements or a plane parallel to the surface of the substrate; and determining a distortion component of the substrate based on the position measurements.

Method of wafer alignment using at resolution metrology on product features

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 for determining a correction for an apparatus used in a process of patterning substrates, the method including: obtaining a group structure associated with a processing history and/or similarity in fingerprint of to be processed substrates; obtaining metrology data associated with a plurality of groups within the group structure, wherein the metrology data is correlated between the groups; and determining the correction for a group out of the plurality of groups by applying a model to the metrology data, the model including at least a group-specific correction component and a common correction component.

Method for determining corrections for lithographic apparatus

A method for determining a plurality of corrections for control of at least one manufacturing apparatus used in a manufacturing process for providing product structures to a substrate in a plurality of layers, the method including: determining the plurality of corrections including a correction for each layer, based on an actuation potential of the applicable manufacturing apparatus used in the formation of each layer, wherein the determining includes determining corrections for each layer simultaneously in terms of a matching parameter.

Method for controlling a manufacturing apparatus and associated apparatuses

A method for optimizing a sequence of processes for manufacturing of product units, includes: associating measurement results of performance parameters (e.g., fingerprints) with the recorded process characteristics (e.g., context); obtaining a characteristic (e.g., context) of a previous process (e.g. deposition) in the sequence already performed on a product unit; obtaining a characteristic (e.g., context) of a subsequent process (e.g., exposure) in the sequence to be performed on the product unit; determining a predicted performance parameter (e.g., fingerprint) of the product unit associated with the sequence of previous and subsequent processes by using the obtained characteristics to retrieve measurement results of the performance parameters (e.g., fingerprints) corresponding to the recorded characteristics; and determining corrections to be applied to future processes (e.g. exposure, etch) in the sequence to be performed on the product unit, based on the determined predicted performance parameter.

Optimizing a sequence of processes for manufacturing of product units

A method of determining a set of metrology point locations, the set including a subset of potential metrology point locations on a substrate, the method including: determining a relation between noise distributions associated with a plurality of the potential metrology point locations using existing knowledge; and using the determined relation and a model associated with the substrate to determine the set.

Method of determining a set of metrology points on a substrate, associated apparatus and computer program

A method, system and program for determining a fingerprint of a parameter. The method includes determining a contribution from a device out of a plurality of devices to a fingerprint of a parameter. The method includes obtaining parameter data and usage data, wherein the parameter data is based on measurements for multiple substrates having been processed by the plurality of devices, and the usage data indicates which of the devices out of the plurality of the devices were used in the processing of each substrate; and determining the contribution using the usage data and parameter data.

Method for determining contribution to a fingerprint

A method for determining a preferred control strategy relating to control of a manufacturing process for manufacturing an integrated circuit. The method includes: obtaining process data associated with a design of said integrated circuit; and obtaining a plurality of candidate control strategies configured to control the manufacturing process based on the process data, each candidate control strategy including an associated cost metric based on an associated requirement to implement the candidate control strategy. A quality metric related to an expected performance of the manufacturing process is determined for each candidate control strategies, and a preferred control strategy is selected based on the determined quality metrics and associated cost metrics for each candidate control strategy.

Method for evaluating control strategies in a semiconductor manufacturing process

A method for estimating a parameter across a region on a substrate, the region being divided into a plurality of sub-regions, the method including: obtaining values of the parameter for at least two sub-regions out of the plurality of sub-regions; and estimating the parameter for a position on the region by evaluation of a function having said values of the parameter as input values, wherein the function: a) has piecewise defined base functions, wherein a single base function is defined across a sub-region; and b) is continuous between one or more adjacent sub-regions of the at least two sub-regions within the region.

Estimating a parameter of a substrate

A method to change an etch parameter of a substrate etching process, the method including: making a first measurement of a first metric associated with a structure on a substrate before being etched; making a second measurement of a second metric associated with a structure on a substrate after being etched; and changing the etch parameter based on a difference between the first measurement and the second measurement.

Method to change an etch parameter

A method of characterizing distortions in a lithographic process, and associated apparatuses. The method includes obtaining measurement data corresponding to a plurality of measurement locations on a substrate, the measurement data comprising measurements performed on a plurality of substrates, and comprising one or more measurements performed on one or more of the substrates for each of the measurement locations. For each of the measurement locations, a first quality value representing a quality metric and a noise value representing a noise metric is determined from the measurements performed at that measurement location. A plurality of distortion parameters is determined, each distortion parameter configured to characterize a systematic distortion in the quality metric and a statistical significance of the distortion parameters from the first quality value and from the noise value is determined. Systematic distortion is parameterized from the distortion parameters determined to be statistically significant.

Method for characterizing distortions in a lithographic process, lithographic apparatus, lithographic cell and computer program

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Eindhoven, Netherlands

Roy Werkman