Application of Principal Component Analysis to EUV multilayer defect printing

Dongbo Xu; Peter Evanschitzky; Andreas Erdmann

doi:10.1117/12.2190784

23 September 2015 Application of Principal Component Analysis to EUV multilayer defect printing

Dongbo Xu, Peter Evanschitzky, Andreas Erdmann

Proceedings Volume 9630, Optical Systems Design 2015: Computational Optics; 96300Y (2015) https://doi.org/10.1117/12.2190784
Event: SPIE Optical Systems Design, 2015, Jena, Germany

Abstract

This paper proposes a new method for the characterization of multilayer defects on EUV masks. To reconstruct the defect geometry parameters from the intensity and phase of a defect, the Principal Component Analysis (PCA) is employed to parametrize the intensity and phase distributions into principal component coefficients. In order to construct the base functions of PCA, a combination of a reference multilayer defect and appropriate pupil filters is introduced to obtain the designed sets of intensity and phase distributions. Finally, an Artificial Neural Network (ANN) is applied to correlate the principal component coefficients of the intensity and the phase of the defect with the defect geometry parameters and to reconstruct the unknown defect geometry parameters.

Citation Download Citation

Dongbo Xu, Peter Evanschitzky, and Andreas Erdmann "Application of Principal Component Analysis to EUV multilayer defect printing", Proc. SPIE 9630, Optical Systems Design 2015: Computational Optics, 96300Y (23 September 2015); https://doi.org/10.1117/12.2190784

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