Record link: 
http://hdl.handle.net/20.500.12708/136702
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Title: 
Advances in Modeling Emerging Magnetoresistive Random Access Memories: From Finite Element Methods to Machine Learning Approaches
en
Citation: 
Ender, J., Fiorentini, S., Orio, R., Hadámek, T., Bendra, M., Goes, W., Selberherr, S., & Sverdlov, V. (2022). Advances in Modeling Emerging Magnetoresistive Random Access Memories: From Finite Element Methods to Machine Learning Approaches. In V. Lukichev & K. Rudenko (Eds.), Proc. SPIE 12157, International Conference on Micro- and Nano-Electronics 2021. SPIE. https://doi.org/10.1117/12.2624595
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Publisher DOI: 
10.1117/12.2624595
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Publication Type: 
Inproceedings - Full-Paper Contribution
en
Language: 
English
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Authors: 
Ender, Johannes 
Fiorentini, Simone 
Orio, Roberto 
Hadámek, Tomás 
Bendra, Mario 
Goes, Wolfgang 
Selberherr, Siegfried 
Sverdlov, Viktor 
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Organisational Unit: 
E360 - Institut für Mikroelektronik 
E360-01 - Forschungsbereich Mikroelektronik 
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Published in: 
Proc. SPIE 12157, International Conference on Micro- and Nano-Electronics 2021 
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ISBN: 
9781510651913
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Volume: 
12157
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Date (published): 
2022
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Event name: 
International Conference on Micro- and Nano-Electronics 2021 
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Event date: 
4-Oct-2021 - 9-Oct-2021
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Event place: 
Zvenigorod, Russian Federation (the)
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Number of Pages: 
14
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Publisher: 
SPIE
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Peer reviewed: 
Yes
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Research Areas: 
Nanoelectronics: 50%
Modelling and Simulation: 50%
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Science Branch: 
Elektrotechnik, Elektronik, Informationstechnik
Nanotechnologie
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Appears in Collections:
Conference Paper

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