Dr. Dandan Han Profile

Dr. Dandan Han

at Univ. of Chinese Academy of Sciences

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Proceedings Article | 9 April 2024 Poster + Paper

A novel kinetic framework-based multiscale modeling of spatial atomic layer deposition process

Sen Deng, Hua Shao, Dandan Han, Rui Chen, Yayi Wei

Proceedings Volume 12958, 129580Q (2024) https://doi.org/10.1117/12.3010331

KEYWORDS: Atomic layer deposition, Molecules, Silicon, Deposition processes, Process modeling, Modeling, Vacuum chambers, Silicon films, Silicon nitride

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Atomic layer deposition (ALD) technology is a self-limiting film deposition process that grows films on substrates through repeated process cycles of precursor dosing, purge, co-reactant dosing and purge. This technology is widely utilized in advanced technology node processes due to its merits of excellent step coverage and atomic scale film thickness control. However, as the industry moves to three-dimensional (3D) device architectures, ALD faces emerging challenges such as the bottle neck phenomenon in extremely high aspect ratio structure with nanometer scale trench or hole open. ALD modeling provides insights into the underlying mechanisms and help engineers optimize the process. There has been research on different kind of ALD process models on film conformity, growth profile and saturation behavior at multiscale from reactor to micro-feature and molecular level. Angel Yanguas-Gil et al. proposed a reactor scale model which discussed the ideal and non-ideal self-limited processes in a cylindrical and a 300 mm wafer cross-flow reactor. Adomaitis et al. presented a multiscale model to describe the reactant transport in a high aspect ratio nanopore and growth of ALD film based on continuum and Monte Carlo model. In this work, we propose an ALD model in order to simulate the spatial ALD process, coupling with surface reaction kinetics theory and hydrodynamics model. Firstly, we analyze and model the adsorption process of precursor molecules and co-reactant molecules, as well as their transport mechanism in ALD reactor chamber. Secondly, we discuss how the substrate temperature, precursor and co-reactant partial pressure, and reaction probabilities influence coverage distribution and growth per cycle in spatial ALD process. This model enables the possibility of spatial ALD process parameter optimization in an efficient and economy way.

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