Asml Netherlands B.v.

Chi-Hsiang Fan

Youping Zhang

Maurits Van Der Schaar

Hakki Ergün Cekli

Marc Jurian Kea

Masashi Ishibashi

Ralph Timotheus Huijgen

Liping Ren

Marcel Theodorus Maria Van Kessel

Feng Chen

Daimian Wang

Jay Jianhui Chen

Danying Li

Wangshi Zhao

Abdalmohsen Elmalk

Kui-Jun Huang

Shengrui Zhang

A method for determining an etch profile is described. The method includes determining a masking layer profile. Loading information can be determined. The loading information indicates dependence of an etch rate for the masking layer profile on a quantity and pattern of material being etched. Flux information can be determined. The flux information indicates dependence of the etch rate on an intensity and a spread angle of radiation incident on the masking layer profile. Re-deposition information can be determined. The re-deposition information indicates dependence of the etch rate on an amount of material removed from the masking layer profile that is re-deposited back on the masking layer profile. An output etch profile for the layer of the wafer is determined based on the loading information, the flux information, and/or the re-deposition information.

Method for determining an etch profile of a layer of a wafer for a simulation system

A method, system and program for determining a position of a feature referenced to a substrate. The method includes measuring a position of the feature, receiving an intended placement of the feature and determining an estimate of a placement error based on knowledge of a relative position of a first reference feature referenced to a first layer on a substrate with respect to a second reference feature referenced to a second layer on a substrate. The updated position may be used to position the layer of the substrate having the feature, or another layer of the substrate, or another layer of another substrate.

Method of determining a position of a feature

A method for determining a stack configuration for a substrate subjected to a patterning process. The method includes obtaining (i) measurement data of a stack configuration with location information on a printed substrate, (ii) a substrate model configured to predict a stack characteristic based on a location of the substrate, and (iii) a stack map including a plurality of stack configurations based on the substrate model. The method iteratively determines values of model parameters of the substrate model based on a fitting between the measurement data and the plurality of stack configurations of the stack map, and predicts an optimum stack configuration at a particular location based on the substrate model using the values of the model parameters.

Method for determining stack configuration of substrate

A method of measuring n values of a parameter of interest (e.g., overlay) relating to a structure forming process, where n&#x3e;1. The method includes performing n measurements on each of n+1 targets, each measurement performed with measurement radiation having a different wavelength and/or polarization combination and determining the n values for a parameter of interest from the n measurements of n+1 targets, each of the n values relating to the parameter of interest for a different pair of the layers. Each target includes n+1 layers, each layer including a periodic structure, the targets including at least n biased targets having at least one biased periodic structure formed with a positional bias relative to the other layers, the biased periodic structure being in at least a different one of the layers per biased target. Also disclosed is a substrate having such a target and a patterning device for forming such a target.

Metrology method and apparatus, substrate, lithographic method and associated computer product

A method including performing a first simulation for each of a plurality of different metrology target measurement recipes using a first model, selecting a first group of metrology target measurement recipes from the plurality of metrology target measurement recipes, the first group of metrology target measurement recipes satisfying a first rule, performing a second simulation for each of the metrology target measurement recipes from the first group using a second model, and selecting a second group of metrology target measurement recipes from the first group, the second group of metrology target measurement recipes satisfying a second rule, the first model being less accurate or faster than the second model and/or the first rule being less restrictive than the second rule.

Automatic selection of metrology target measurement recipes

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San Jose, CA, United States of America

Chi-Hsiang Fan