The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 19, 2020

Filed:

Feb. 22, 2019
Applicant:

Fractilia, Llc, Austin, TX (US);

Inventor:

Chris Mack, Austin, TX (US);

Assignee:

FRACTILIA, LLC, Austin, TX (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G03F 7/20 (2006.01); H01J 37/22 (2006.01); H01J 37/28 (2006.01); G03F 1/36 (2012.01);
U.S. Cl.
CPC ...
G03F 7/70625 (2013.01); G03F 1/36 (2013.01); G03F 7/70441 (2013.01); G03F 7/70616 (2013.01); H01J 37/222 (2013.01); H01J 37/28 (2013.01); H01J 2237/2813 (2013.01);
Abstract

Systems and methods are disclosed that remove noise from roughness measurements to determine roughness of a feature in a pattern structure. In one embodiment, a method for determining roughness of a feature in a pattern structure includes generating, using an imaging device, a set of one or more images, each including measured linescan information that includes noise. The method also includes detecting edges of the features within the pattern structure of each image without filtering the images, generating a biased power spectral density (PSD) dataset representing feature geometry information corresponding to the edge detection measurements, evaluating a high-frequency portion of the biased PSD dataset to determine a noise model for predicting noise over all frequencies of the biased PSD dataset, and subtracting the noise predicted by the determined noise model from a biased roughness measure to obtain an unbiased roughness measure.


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