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Computational Lithography for Silicon Photonics Design
IEEE Journal of Selected Topics in Quantum Electronics, 2020 A lithography model is built using physical measurements obtained from a fabricated test pattern. The method is able to accurately predict the proximity and smoothing effects characteristic of a 193~nm deep-ultraviolet (DUV) lithography process. The accuracy of the model is verified by visually inspecting the fabricated test patterns and comparing them
Enxiao Luan, Han Yun, Stephen Lin
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2020 China Semiconductor Technology International Conference (CSTIC), 2020
Machine learning based computational lithography is intended to accelerate the speed of the solutions significantly. There are three critical aspects of AI computational lithography: (1). The feature vector design, (2). The approximate mapping function construction, (3). The model training scheme.
Xuelong Shi, Shoumian Chen, Yuhang Zhao
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Machine learning based computational lithography is intended to accelerate the speed of the solutions significantly. There are three critical aspects of AI computational lithography: (1). The feature vector design, (2). The approximate mapping function construction, (3). The model training scheme.
Xuelong Shi, Shoumian Chen, Yuhang Zhao
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Inverse e-beam lithography on photomask for computational lithography
Journal of Micro/ Nanolithography, MEMS, and MOEMS, 2013Computational lithography, e.g., inverse lithography technique (ILT) and source mask optimization, is considered necessary for the “extremely low k1” lithography process of sub-20 nm device node. The ideal design of a curvilinear mask for computational lithography requires many changes during photomask fabrication.
In Kyun Shin, Jin Choi
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Development of a computational lithography roadmap
Proceedings of SPIE, 2008While lithography R&D community at large has already gotten the mind set for 32nm, all eyes are on 22nm node. Current consensus is to employ computational lithography to meet wafer CD uniformity (CDU) requirement. Resolution enhancement technologies (RET) and model OPC are the two fundamental components for computational lithography.
Robert Socha +2 more
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Photomask Technology 2020, 2020
For nanoimprint lithography, computational technologies are still being developed. In this paper, we introduce a new NIL process simulator which simulates the whole imprinting process, and evaluates the quality of the resulting resist film. To overcome the scale difference of each component of the system, which makes it difficult to calculate the ...
Junichi Seki +2 more
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For nanoimprint lithography, computational technologies are still being developed. In this paper, we introduce a new NIL process simulator which simulates the whole imprinting process, and evaluates the quality of the resulting resist film. To overcome the scale difference of each component of the system, which makes it difficult to calculate the ...
Junichi Seki +2 more
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Computational lithography: Exhausting the resolution limits of 193-nm projection lithography systems
Journal of Vacuum Science & Technology B, 2011In the recent past, scaling of semiconductor fabrication systems has been dominated by wavelength and numerical aperture modifications. This is now no longer the case for 193-nm immersion projection lithography (193i) systems as there are no technical paths for continued benefit from the in these areas.
Kafai Lai +2 more
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Impact of photomask shape uncertainties on computational lithography
2016 China Semiconductor Technology International Conference (CSTIC), 2016We devise an algorithm that can incorporate the photomask shape uncertainties in computational lithography such as inverse lithography technique. The photomask patterns are expressed by a random field under a level-set framework to represent the uncertain shape variation.
Edmund Y. Lam, Xiaofei Wu
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Streamlining Computational Lithography With Efficient Pattern Database
IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsBei Yu, Fan Yang, Martin D. F. Wong
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Using FlexRay in Computational Lithography
Japanese Journal of Applied Physics, 2011FlexRay programmable illumination and LithoTuner software is combined in several use cases. The first use case is source mask optimization (SMO) in which the process window is maximized for a static random access memory (SRAM) design. In a 55 nm half-pitch contact hole array (k 1 = 0.38, NA= 1.35, λ= 193 nm), the process window ...
Robert Socha +18 more
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