A machine learning approach to model the impact of line edge roughness on gate-all-around nanowire FETs while reducing the carbon footprint

Antonio García-Loureiro; Natalia Seoane; Julián G. Fernández; Enrique Comesaña; Juan C. Pichel

doi:10.1371/journal.pone.0288964

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Peer-reviewed

Research Article

A machine learning approach to model the impact of line edge roughness on gate-all-around nanowire FETs while reducing the carbon footprint

Antonio García-Loureiro ,

Contributed equally to this work with: Antonio García-Loureiro, Natalia Seoane, Julián G. Fernández, Enrique Comesaña, Juan C. Pichel

Roles Funding acquisition, Investigation, Software, Supervision

* E-mail: antonio.garcia.loureiro@usc.es

Affiliation CITIUS, Universidade de Santiago de Compostela, Santiago de Compostela, Spain

https://orcid.org/0000-0003-0574-1513

⨯
Natalia Seoane ,

Contributed equally to this work with: Antonio García-Loureiro, Natalia Seoane, Julián G. Fernández, Enrique Comesaña, Juan C. Pichel

Roles Software, Writing – original draft, Writing – review & editing

Affiliation CITIUS, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
⨯
Julián G. Fernández ,

Contributed equally to this work with: Antonio García-Loureiro, Natalia Seoane, Julián G. Fernández, Enrique Comesaña, Juan C. Pichel

Roles Software

Affiliation CITIUS, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
⨯
Enrique Comesaña ,

Contributed equally to this work with: Antonio García-Loureiro, Natalia Seoane, Julián G. Fernández, Enrique Comesaña, Juan C. Pichel

Roles Software

Affiliation Departamento de Electrónica e Computación, Universidade de Santiago de Compostela, Lugo, Spain
⨯
Juan C. Pichel

Contributed equally to this work with: Antonio García-Loureiro, Natalia Seoane, Julián G. Fernández, Enrique Comesaña, Juan C. Pichel

Roles Conceptualization, Software, Supervision, Writing – original draft, Writing – review & editing

Affiliation CITIUS, Universidade de Santiago de Compostela, Santiago de Compostela, Spain

https://orcid.org/0000-0001-9505-6493

⨯

A machine learning approach to model the impact of line edge roughness on gate-all-around nanowire FETs while reducing the carbon footprint

Antonio García-Loureiro,
Natalia Seoane,
Julián G. Fernández,
Enrique Comesaña,
Juan C. Pichel

Published: July 24, 2023
https://doi.org/10.1371/journal.pone.0288964

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