28 May 2021 Power spectral density as template for modeling a metal-oxide nanocluster resist to obtain accurate resist roughness profiles
Author Affiliations +
Abstract

Background: The metal-oxide resist (MOR) is a promising type of nonchemically amplified resist (CAR) for EUV lithography. This family of resists shows some advantages over the conventional CARs. Even though a prior MOR model exists, no documented references for the application described could be found in open literature to develop a physically rational lithographic model that can accurately simulate and predict lithographic results for these resists.

Aim: Increase the fundamental understanding of this class of resists by creating a model that also considers these aspects of the resist.

Approach: Model the metal-oxo clusters of the MOR as nanoparticles with an effective radius that operate under excluded volume.

Results: We show the possibility to include both the packing noise effect, as well as accurate roughness (characteristics) predictions by utilizing power spectral density (PSD) plots.

Conclusions: Varying the calibrated model parameters has a clear effect on the overall roughness of the resist lines and is reflected in the PSD behavior. In contrast to experimental data, changing the resist film thickness did not result in a change in PSD behavior.

© 2021 Society of Photo-Optical Instrumentation Engineers (SPIE) 1932-5150/2021/$28.00 © 2021 SPIE
Joren Severi, Ulrich Welling, Danilo De Simone, and Stefan De Gendt "Power spectral density as template for modeling a metal-oxide nanocluster resist to obtain accurate resist roughness profiles," Journal of Micro/Nanopatterning, Materials, and Metrology 20(2), 024601 (28 May 2021). https://doi.org/10.1117/1.JMM.20.2.024601
Received: 15 March 2021; Accepted: 14 May 2021; Published: 28 May 2021
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Calibration

Data modeling

Particles

3D modeling

Line edge roughness

Extreme ultraviolet lithography

Fourier transforms

Back to Top