Dry etch proximity modeling in mask fabrication

Yuri Granik

doi:10.1117/12.504052

28 August 2003 Dry etch proximity modeling in mask fabrication

Yuri Granik

Proceedings Volume 5130, Photomask and Next-Generation Lithography Mask Technology X; (2003) https://doi.org/10.1117/12.504052
Event: Photomask and Next Generation Lithography Mask Technology X, 2003, Yokohama, Japan

Abstract

Microloading in photomask fabrication is a key parameter in process optimization. A Variable Bias Model has been successfully used in explaining etch proximity behavior during wafer etching. This model recently became part of the VT5 model suit. In this study, we apply variable bias modeling to the dry etching in mask fabrication. A special etch test pattern is used to characterize etch bias under various process conditions. We show that etch proximity is adequately described by two proximity parameters: density and separation. The model coefficients depend on the process parameters and can be used to characterize and explain etch behavior in terms of microloading and etch aperture effects. Ability to explain mask etching is important for accurate OPC modeling. While some modeling methodologies consider mask and wafer processes as a single "black box," we found that more accurate OPC models are generated by building separate models for mask-making, optical, and wafer processing steps. We show how variable etch model can be used to compensate for iso-dense mask bias and how this step fits into OPC flow.

Citation Download Citation

Yuri Granik "Dry etch proximity modeling in mask fabrication", Proc. SPIE 5130, Photomask and Next-Generation Lithography Mask Technology X, (28 August 2003); https://doi.org/10.1117/12.504052

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