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:
Jun. 29, 2021

Filed:

Nov. 29, 2017
Applicant:

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

Inventors:

Santosh Bhattacharyya, San Jose, CA (US);

Devashish Sharma, San Jose, CA (US);

Christopher Maher, San Jose, CA (US);

Bo Hua, Shanghai, CN;

Philip Measor, San Jose, CA (US);

Robert M. Danen, Pleasanton, CA (US);

Assignee:

KLA-Tencor Corporation, Milpitas, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G01N 21/95 (2006.01); G01R 31/311 (2006.01); G01N 21/956 (2006.01); G01N 23/04 (2018.01); G01R 31/28 (2006.01); G06T 7/00 (2017.01); G01N 21/88 (2006.01);
U.S. Cl.
CPC ...
G01N 21/9505 (2013.01); G01N 21/956 (2013.01); G01N 23/04 (2013.01); G01R 31/2831 (2013.01); G01R 31/311 (2013.01); G06T 7/001 (2013.01); G01N 2021/8883 (2013.01); G01N 2223/6462 (2013.01); G06T 2207/10061 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30148 (2013.01);
Abstract

Methods and systems for discovery of defects of interest (DOI) buried within three dimensional semiconductor structures and recipe optimization are described herein. The volume of a semiconductor wafer subject to defect discovery and verification is reduced by storing images associated with a subset of the total depth of the semiconductor structures under measurement. Image patches associated with defect locations at one or more focus planes or focus ranges are recorded. The number of optical modes under consideration is reduced based on any of a comparison of one or more measured wafer level defect signatures and one or more expected wafer level defect signatures, measured defect signal to noise ratio, and defects verified without de-processing. Furthermore, verified defects and recorded images are employed to train a nuisance filter and optimize the measurement recipe. The trained nuisance filter is applied to defect images to select the optimal optical mode for production.


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