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.
Patent No.:
Date of Patent:
Jan. 14, 2014
Filed:
Jan. 07, 2011
Haiguang Chen, Mountain View, CA (US);
Jaydeep Sinha, Livermore, CA (US);
Shouhong Tang, Santa Clara, CA (US);
John Hager, San Francisco, CA (US);
Andrew Zeng, Fremont, CA (US);
Sergey Kamensky, Campbell, CA (US);
Haiguang Chen, Mountain View, CA (US);
Jaydeep Sinha, Livermore, CA (US);
Shouhong Tang, Santa Clara, CA (US);
John Hager, San Francisco, CA (US);
Andrew Zeng, Fremont, CA (US);
Sergey Kamensky, Campbell, CA (US);
KLA-Tencor Corporation, Milpitas, CA (US);
Abstract
A method for enabling more accurate measurements of localized features on wafers is disclosed. The method includes: a) performing high order surface fitting to more effectively remove the low frequency shape components and also to reduce possible signal attenuations commonly observed from SEMI standard high pass, such as Gaussian and Double Gaussian filtering; b) constructing and applying a proper two dimensional LFM window to the residual image from the surface fitting processing stage to effectively reduce the residual artifacts at the region boundaries; c) calculating the metrics of the region using the artifact-reduced image to obtain more accurate and reliable measurements; and d) using site-based metrics obtained from front and back surface data to quantify the features of interest. Additional steps may also include: filtering data from measurements of localized features on wafers and adjusting the filtering behavior according to the statistics of extreme data samples.