Asml Netherlands B.v.

Simon Philip Spencer Hastings

Cyrus Emil Tabery

Youping Zhang

Yi Zou

Yana Cheng

Chenxi Lin

Boris Menchtchikov

Maxime Philippe Frederic Genin

Wim Tjibbo Tel

Daan Maurits Slotboom

Simon Hendrik Celine Van Gorp

Abraham Slachter

Brennan Peterson

Matthijs Cox

Vadim Yourievich Timoshkov

Koen Wilhelmus Cornelis Adrianus Van Der Straten

Nicolaas Petrus Marcus Brantjes

Maxim Philippe Frederic Genin

A measurement mark is disclosed. According to certain embodiments, the measurement mark includes a set of first test structures developed in a first layer on a substrate, each of the set of first test structures comprising a plurality of first features made of first conducting material. The measurement mark also includes a set of second test structures developed in a second layer adjacent to the first layer, each of the set of second test structures comprising a plurality of second features made of second conducting material. The measurement mark is configured to indicate connectivity between the set of first test structures and associated second test structures in the set of second test structures when imaged using a voltage-contrast imaging method.

Voltage contrast metrology mark

A method for predicting yield relating to a process of manufacturing semiconductor devices on a substrate, the method including: obtaining a trained first model which translates modeled parameters into a yield parameter, the modeled parameters including: a) a geometrical parameter associated with one or more selected from: a geometric characteristic, dimension or position of a device element manufactured by the process and b) a trained free parameter; obtaining process parameter data including data regarding a process parameter characterizing the process; converting the process parameter data into values of the geometrical parameter; and predicting the yield parameter using the trained first model and the values of the geometrical parameter.

Method to predict yield of a device manufacturing process

A method for analyzing a process, the method including obtaining a multi-dimensional probability density function representing an expected distribution of values for a plurality of process parameters; obtaining a performance function relating values of the process parameters to a performance metric of the process; and using the performance function to map the probability density function to a performance probability function having the process parameters as arguments.

Method of manufacturing devices

A method for determining a correction relating to a performance metric of a semiconductor manufacturing process, the method including: obtaining a set of pre-process metrology data; processing the set of pre-process metrology data by decomposing the pre-process metrology data into one or more components which: a) correlate to the performance metric; or b) are at least partially correctable by a control process which is part of the semiconductor manufacturing process; and applying a trained model to the processed set of pre-process metrology data to determine the correction for the semiconductor manufacturing process.

Method for controlling a manufacturing process and associated apparatuses

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San Jose, CA, United States of America

Simon Philip Spencer Hastings