Line edge roughness and intrinsic bias for two methacrylate polymer resist systems

Pawloski, Adam R.; Acheta, Alden; Levinson, Harry; Michaelson, Timothy B.; Jamieson, Andrew; Nishimura, Yukio; Willson, C. Grant

doi:10.1117/1.2200675

Cited by 26 publications

(13 citation statements)

References 28 publications

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“…The sensitivity in the model was changed by varying the base loading while keeping all other parameters fixed. We note that the base-loading method for varying sensitivity is often used in experimental studies as well [13][14][15]. The modeling results show that resist improvement relative to the photon noise limit is still possible.…”

Section: Ler Limitationsmentioning

confidence: 88%

Critical challenges for EUV resist materials

et al. 2011

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Although Extreme ultraviolet lithography (EUVL) is now well into the commercialization phase, critical challenges remain in the development of EUV resist materials. The major issue for the 22-nm half-pitch node remains simultaneously meeting resolution, line-edge roughness (LER), and sensitivity requirements. Although several materials have met the resolution requirements, LER and sensitivity remain a challenge. As we move beyond the 22-nm node, however, even resolution remains a significant challenge. Chemically amplified resists have yet to demonstrate the required resolution at any speed or LER for 16-nm half pitch and below. Going to non-chemically amplified resists, however, 16-nm resolution has been achieved with a LER of 2 nm but a sensitivity of only 70 mJ/cm 2 .

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Section: Ler Limitationsmentioning

confidence: 88%

Critical challenges for EUV resist materials

et al. 2011

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“…The resist sensitivity in the model was changed by varying the base loading while keeping all other parameters fixed. We note that the base-loading method for varying sensitivity is often used in experimental studies as well [11][12][13]. The modeling results show that resist improvement relative to the photon noise limit is still possible.…”

Section: Photon Noise Limitmentioning

confidence: 88%

EUV Resists: Illuminating the Challenges

Naulleau¹,

Anderson²,

George³

2011

J. Photopol. Sci. Technol.

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“…Therefore, any deviation in exposure or defocus will lead to over-or under-development of the photoresist. This causes geometries to differ in stability and roughness, as well as deviate from the intended size [9][10][11]. The over-or under-development at a certain area of the die will cause probabilistic shifts in mean CD, however, the direction and magnitude of those shifts is dependent on neighborhood or context, which is systematic in nature.…”

Section: Proposed Transistor-specific Modelmentioning

confidence: 99%

Transistor-Specific Delay Modeling for SSTA

Chopra¹,

Blaauw²,

Торрес³

et al. 2008

2008 Design, Automation and Test in Europe

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SSTA has received a considerable amount of attention in recent years. However, it is a general rule that any approach can only be as accurate as the underlying models. Thus, variation models are an important research topic, in addition to the development of statistical timing tools. These models attempt to predict fluctuations in parameters like doping concentration, critical dimension (CD), and ILD thickness, as well as their spatial correlations. Modeling CD variation is a difficult problem because it contains a systematic component that is context dependent as well as a probabilistic component that is caused by exposure and defocus variation. Since these variations are dependent on topology, modern-day designs can potentially contain thousands of unique CD distributions. To capture all of the individual CD distributions within statistical timing, a transistor-specific model is required. However, statistical CD models used in industry today do not distinguish between transistors contained within different standard cell types (at the same location in a die), nor do they distinguish between transistors contained within the same standard cell. In this work we verify that the current methodology is error-prone using a 90nm industrial library and lithography recipe (with industrial OPC) and propose a new SSTA delay model that on average reduces error of standard deviation from 11.8% to 4.1% when the total variation (σ/μ) is 4.9% -a 2.9X reduction. Our model is compatible with existing SSTA techniques and can easily incorporate other sources of variation such as random dopant fluctuation and line-edge roughness.

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Line edge roughness and intrinsic bias for two methacrylate polymer resist systems

Cited by 26 publications

References 28 publications

Critical challenges for EUV resist materials

Critical challenges for EUV resist materials

EUV Resists: Illuminating the Challenges

Transistor-Specific Delay Modeling for SSTA

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