Artificial-Neural-Network-Driven Innovations in Time-Varying Process Diagnosis of Low-K Oxide Deposition

To address the challenges in real-time process diagnosis within the semiconductor manufacturing industry, this paper presents a novel machine learning approach for analyzing the time-varying 10th harmonics during the deposition of low-k oxide (SiOF) on a 600 Å undoped silicate glass thin liner using...

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Detalles Bibliográficos
Autores principales: Lee, Seunghwan, Park, Yonggyun, Liu, Pengzhan, Kim, Muyoung, Kim, Hyeong-U, Kim, Taesung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575315/
https://www.ncbi.nlm.nih.gov/pubmed/37837056
http://dx.doi.org/10.3390/s23198226

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575315/
https://www.ncbi.nlm.nih.gov/pubmed/37837056
http://dx.doi.org/10.3390/s23198226

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