Asml Netherlands B.v.

Jiao Liang

Chen Zhang

Jen-Shiang Wang

Mu Feng

Qiang Zhang

Alvin Jianjiang Wang

Yongfa Fan

Qian Zhao

Yunbo Guo

Chang An Wang

Jiao Huang

Yunan Zheng

Systems and methods for determining one or more characteristic metrics for a portion of a pattern on a substrate are described. Pattern information for the pattern on the substrate is received. The pattern on the substrate has first and second portions. The first portion of the pattern is blocked, for example with a geometrical block mask, based on the pattern information, such that the second portion of the pattern remains unblocked. The one or more metrics are determined for the unblocked second portion of the pattern. In some embodiments, the first and second portions of the pattern correspond to different exposures in a semiconductor lithography process. The semiconductor lithography process may be a multiple patterning technology process, for example, such as a double patterning process, a triple patterning process, or a spacer double patterning process.

Determining metrics for a portion of a pattern on a substrate

A method for evaluating images of a printed pattern. The method includes obtaining a first averaged image of the printed pattern, where the first averaged image is generated by averaging raw images of the printed pattern. The method also includes identifying one or more features of the first averaged image. The method further includes evaluating the first averaged image, using an image quality classification model and based at least on the one or more features. The evaluating includes determining, by the image quality classification model, whether the first averaged image satisfies a metric.

Utilize machine learning in selecting high quality averaged SEM images from raw images automatically

A method for determining measurement data of a printed pattern on a substrate. The method involves obtaining (i) images of the substrate including a printed pattern corresponding to a reference pattern, (ii) an averaged image of the images, and (iii) a composite contour based on the averaged image. Further, the composite contour is aligned with respect to a reference contour of the reference pattern and contours are extracted from the images based on both the aligned composite contour and the output of die-to-database alignment of the composite contour. Further, the method determines a plurality of pattern measurements based on the contours and the measurement data corresponding to the printed patterns based on the plurality of the pattern measurements. Further, the method determines a one or more process variations such as stochastic variation, inter-die variation, intra-die variation and/or total variation.

Method for determining stochastic variation of printed patterns

A method for improving a process model by measuring a feature on a printed design that was constructed based in part on a target design is disclosed. The method includes obtaining a) an image of the printed design from an image capture device and b) contours based on shapes in the image. The method also includes identifying, by a pattern recognition program, patterns on the target design that include the feature and determining coordinates, on the contours, that correspond to the feature. The method further includes improving the process model by at least a) providing a measurement of the feature based on the coordinates and b) calibrating the process model based on a comparison of the measurement with a corresponding feature in the target design.

Utilize pattern recognition to improve SEM contour measurement accuracy and stability automatically

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San Jose, CA, United States of America

Jiao Liang