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. 13, 2024

Filed:

Mar. 11, 2021
Applicant:

Applied Materials Israel Ltd., Rehovot, IL;

Inventors:

Eric Chin Hong Ng, Milpitas, CA (US);

Edward Budiarto, Fremont, CA (US);

Sergey Starik, Kyiv, UA;

Todd J. Egan, Fremont, CA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H01L 21/66 (2006.01); G01B 11/06 (2006.01); G01N 21/21 (2006.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
H01L 22/12 (2013.01); G01B 11/0625 (2013.01); G01B 11/0633 (2013.01); G01B 11/0641 (2013.01); G01B 11/065 (2013.01); G01B 11/0683 (2013.01); G06N 20/00 (2019.01); H01L 22/20 (2013.01); G01B 2210/56 (2013.01); G01N 21/211 (2013.01); G01N 2021/213 (2013.01);
Abstract

An optical metrology model for in-line thickness measurements of a film overlying non-ideal structures on a substrate is generated by performing pre-measurements prior to deposition of the film and performing post-measurements after the deposition. The pre- and post-measurements are performed at at least one of multiple polarization angles or multiple orientations of the substrate. Differences in reflectance between the pre- and post-measurements are determined at the multiple polarization angles and the multiple orientations. At least one of the multiple polarization angles or the multiple orientations are identified where the differences in reflectance are indicative of a suppressed influence from the non-ideal structures. The optical metrology model is generated using the identified polarization angles and the identified orientations as inputs to a machine-learning algorithm.


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