Study of i-Line Photosensitive Materials with a Wide Depth of Focus for Fine Pitch Redistribution Layers

Yukimori, Daiki; Kunito, Mei; Ishikawa, Nobuhiro; Sekiguchi, Atsushi; Ogata, Toshiyuki

doi:10.1109/ectc32696.2021.00310

Cited by 2 publications

(1 citation statement)

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“…The proposed optimization method in this paper is based on these two methods. In addition, considering the successful application of the physical CAR models in simulation, 17 – 22 it is convenient to apply these models to predict the critical features’ sizes of the CAR profile, and it will accelerate the optimization in a cheaper and faster way 18 . For these reasons, the simulation part of this work is based on the rigorous CAR model in PROLITH 23 .…”

Section: Introductionmentioning

confidence: 99%

Optimization of chemically amplified resist formulation based on simple random sampling and kernel density estimation

Kong

Dong

et al. 2023

J. Micro/Nanopattern. Mats. Metro.

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Formulation optimization plays an important role in the research and development of chemically amplified resist (CAR). However, the CAR profile after development process is influenced by multiple resist parameters and process conditions, so it is hard to determine the optimal CAR formulation in the multivariate problem. An optimization method for the CAR formulation is developed. The simple random sampling is applied to each CAR parameter's value range independently, and the combinations of these samples from different parameters are used in the simulation of lithography profiles. Kernel density estimation is applied to analyze the simulation results. Then the CAR formulation is optimized based on the probability density distribution from the analysis results. The verification results show that the proposed optimization method can greatly improve the stability of the CAR formulation and thus generating acceptable critical features' sizes of the CAR profile.

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