Mechanistic model of line edge roughness

Mark D. Smith

doi:10.1117/12.659627

29 March 2006 Mechanistic model of line edge roughness

Mark D. Smith

Proceedings Volume 6153, Advances in Resist Technology and Processing XXIII; 61530X (2006) https://doi.org/10.1117/12.659627
Event: SPIE 31st International Symposium on Advanced Lithography, 2006, San Jose, California, United States

Abstract

Physically-based photoresist models, such as those in PROLITH, have been very successful in describing photolithography from a continuum standpoint. These models allow engineers to accurately predict the final resist CD on the wafer and to analyze process robustness, such as calculation of focus-exposure process windows. However, as feature sizes continue to shrink, we are beginning to see yield-limiting phenomena that are due to the molecular nature of photoresist materials. One example of this is line-edge roughness (LER). LER is believed to be due to fluctuations during the exposure process (shot noise) and post-exposure bake (thermal diffusion and reaction). We present a model that explicitly takes into account the molecular nature of the photoresist during the exposure and post-exposure bake processes. We do this by writing a master equation that describes the probability that acid molecules are generated during exposure, and then describes the evolution of the acid, quencher, and blocking-group probability distributions during the bake process. We show how all the parameters in this model can be simply derived from the parameters in a calibrated PROLITH continuum model. Finally, we demonstrate prediction of LER from an accurately tuned PROLITH continuum model and compare the LER predictions with experimental results.

Citation Download Citation

Mark D. Smith "Mechanistic model of line edge roughness", Proc. SPIE 6153, Advances in Resist Technology and Processing XXIII, 61530X (29 March 2006); https://doi.org/10.1117/12.659627

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