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:
Aug. 11, 2026

Filed:

Aug. 07, 2023
Applicant:

Kla Corporation, Milpitas, CA (US);

Inventors:

Houssam Chouaib, Milpitas, CA (US);

Tianrong Zhan, Shanghai, CN;

Jonathan Iloreta, Menlo Park, CA (US);

Teng Gu, Shanghai, CN;

Andrei V. Shchegrov, Los Gatos, CA (US);

Assignee:

KLA Corporation, Milpitas, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G03F 7/00 (2006.01);
U.S. Cl.
CPC ...
G03F 7/70633 (2013.01); G03F 7/70625 (2013.01); G03F 7/706831 (2023.05);
Abstract

Methods and systems for generating measurement models of complex semiconductor structures based on re-useable, parametric models are presented herein. In some embodiments, the re-useable, parametric models enable measurement of high aspect ratio (HAR) structures having complex shape profiles. In these embodiments, a re-useable, parametric model includes multiple geometric sections each characterized by a different shape profile. Each shape profile is parameterized by at least one shape parameter. In a further aspect, at least one of the multiple geometric sections includes a plurality of subsections. In some other embodiments, the re-useable, parametric models enable measurement of nanowire based semiconductor structures. The re-useable, parametric models described herein are useful for generating measurement models for both optical metrology and x-ray metrology, e.g., soft x-ray metrology and hard x-ray metrology. The resulting measurement models yield more accurate measurement results with improved robustness.


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