Automatic classification of EUV mask defects inspected using DUV inspection optics

Aravindh Rajiv; Samir Bhamidipati; Mark Pereira; Sankaranarayanan Paninjath; Neha Razdan; Stephen Kim; Jinhyuk Choi; Jonghoon Lim; Sujeong Won; Dongwook Lee; Woojin Kim; Jongha Park

doi:10.1117/12.3034707

20 November 2024 Automatic classification of EUV mask defects inspected using DUV inspection optics

Aravindh Rajiv, Samir Bhamidipati, Mark Pereira, Sankaranarayanan Paninjath, Neha Razdan, Stephen Kim, Jinhyuk Choi, Jonghoon Lim, Sujeong Won, Dongwook Lee, Woojin Kim, Jongha Park

Author Affiliations +

Proceedings Volume 13216, Photomask Technology 2024; 132162I (2024) https://doi.org/10.1117/12.3034707
Event: SPIE Photomask Technology + EUV Lithography, 2024, Monterey, California, United States

Conference Poster

Abstract

EUV lithography has been well-established over the past few years, to be the next technological milestone, to achieve lower pattern resolutions i.e. higher technology nodes. Ensuring a lower defect count however is particularly important for its use in mass-production, because of the considerably high cost of EUV masks. EUV wavelength (actinic EUV inspection) is necessary to be able to catch and characterize EUV defects correctly, particularly phase defects, originating due to imperfections in multi-layers. Defects on a patterned mask require EUV wavelengths (higher resolution) for accurate assessment of their CD impact. However, DUV optics are also employed by mask shops, along with SEM review, as a cost-effective option. Emphasizing the importance of defect handling in EUV masks, especially for EUV masks without pellicles in the memory industry, the most difficult part of EUV mask management is in controlling adder. Detecting smaller adder size is required as mask pattern size is getting smaller in higher technology nodes, which accompanies increased sensitivity of patterned mask inspection and unavoidable increase in noise signal that makes it hard to proper classify mask defects. This paper talks about the details of how DUV inspection optics are utilized to achieve an efficient pre-filtering of EUV mask defects. This, coupled with well-tested automatic defect classification algorithms of Calibre^® DefectClassify, results in a reliable solution to manage regular classification of mask defects as real or false, under such sensitive conditions.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Aravindh Rajiv, Samir Bhamidipati, Mark Pereira, Sankaranarayanan Paninjath, Neha Razdan, Stephen Kim, Jinhyuk Choi, Jonghoon Lim, Sujeong Won, Dongwook Lee, Woojin Kim, and Jongha Park "Automatic classification of EUV mask defects inspected using DUV inspection optics", Proc. SPIE 13216, Photomask Technology 2024, 132162I (20 November 2024); https://doi.org/10.1117/12.3034707

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available