Presentation + Paper
27 March 2017 Separating the optical contributions to line-edge roughness in EUV lithography using stochastic simulations
Author Affiliations +
Abstract
Minimization and control of line-edge roughness (LER) and contact-edge roughness (CER) is one of the current challenges limiting EUV line-space and contact hole printability. One significant contributor to feature roughness and CD variability in EUV is photon shot noise (PSN); others are the physical and chemical processes in photoresists, known as resist stochastic effect. Different approaches are available to mitigate each of these contributions. In order to facilitate this mitigation, it is important to assess the magnitude of each of these contributions separately from others. In this paper, we present and test a computational approach based on the concept of an ‘ideal resist’. An ideal resist is assumed to be devoid of all resist stochastic effects. Hence, such an ideal resist can only be simulated as an ‘ideal resist model’ (IRM) through explicit utilization of the Poisson statistics of PSN2 or direct Monte Carlo simulation of photon absorption in resist. LER estimated using IRM, thus quantifies the exclusive contribution of PSN to LER. The result of the simulation study done using IRM indicates higher magnitude of contribution (60%) from PSN to LER with respect to total or final LER for a sufficiently optimized high dose ‘state of the art’ EUV chemically amplified resist (CAR) model.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Anindarupa Chunder, Azat Latypov, Yulu Chen, John J. Biafore, Harry J. Levinson, and Todd Bailey "Separating the optical contributions to line-edge roughness in EUV lithography using stochastic simulations", Proc. SPIE 10146, Advances in Patterning Materials and Processes XXXIV, 101460B (27 March 2017); https://doi.org/10.1117/12.2258693
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Line edge roughness

Stochastic processes

Calibration

Extreme ultraviolet lithography

Extreme ultraviolet

Monte Carlo methods

Edge roughness

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