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:
Jul. 05, 2022

Filed:

Feb. 23, 2018
Applicant:

Kla-tencor Corporation, Milpitas, CA (US);

Inventors:

Tianrong Zhan, Shanghai, CN;

Yin Xu, Shanghai, CN;

Liequan Lee, Fremont, CA (US);

Assignee:

KLA-TENCOR CORPORATION, Milpitas, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H01L 21/66 (2006.01); G06N 3/04 (2006.01); G01N 21/88 (2006.01); G01N 21/95 (2006.01); G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
H01L 22/12 (2013.01); G01N 21/8806 (2013.01); G01N 21/9501 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); H01L 22/20 (2013.01);
Abstract

Machine learning techniques are used to predict values of fixed parameters when given reference values of critical parameters. For example, a neural network can be trained based on one or more critical parameters and a low-dimensional real-valued vector associated with a spectrum, such as a spectroscopic ellipsometry spectrum or a specular reflectance spectrum. Another neural network can map the low-dimensional real-valued vector. When using two neural networks, one neural network can be trained to map the spectra to the low-dimensional real-valued vector. Another neural network can be trained to predict the fixed parameter based on the critical parameters and the low-dimensional real-valued vector from the other neural network.


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