An efficient plasma-surface interaction surrogate model for sputtering processes based on autoencoder neural networks

Simulations of thin film sputter deposition require the separation of the plasma and material transport in the gas-phase from the growth/sputtering processes at the bounding surfaces. Interface models based on analytic expressions or look-up tables inherently restrict this complex interaction to a b...

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Veröffentlicht in:	arXiv.org
Hauptverfasser:	Gergs, Tobias, Borislavov, Borislav, Trieschmann, Jan
Format:	Paper
Sprache:	Englisch
Veröffentlicht:	Ithaca Cornell University Library, arXiv.org 06.09.2021
Schlagworte:	Aluminum Angular distribution Artificial neural networks Degrees of freedom Energy distribution Lookup tables Machine learning Multilayer perceptrons Neural networks Regression Sputtering Stoichiometry Thin films Titanium
ISSN:	2331-8422
Online-Zugang:	Volltext
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