Machine Learning Assisted Classification of Aluminum Nitride Thin Film Stress via In-Situ Optical Emission Spectroscopy Data.

Yu-Pu Yang, Te-Yun Lu, Hsiao-Han Lo, Wei-Lun Chen, Peter J Wang, Walter Lai, Yiin-Kuen Fuh, Tomi T Li

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Article in Materials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed

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1 citing paper in PubMed.

Impact of Pulse Parameters of a DC Power Generator on the Microstructural and Mechanical Properties of Sputtered AlN Film with In-Situ OES Data Analysis.Materials (Basel, Switzerland) · 2023
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8 authors.

Yu-Pu YangDepartment of Mechanical Engineering, National Central University, Taoyuan 32001, Taiwan.

Te-Yun LuDepartment of Mechanical Engineering, National Central University, Taoyuan 32001, Taiwan.

Hsiao-Han LoDepartment of Mechanical Engineering, National Central University, Taoyuan 32001, Taiwan.

Wei-Lun ChenDepartment of Mechanical Engineering, National Central University, Taoyuan 32001, Taiwan.

Peter J WangDelta Electronics Inc., Taoyuan 32063, Taiwan.

Walter LaiDelta Electronics Inc., Taoyuan 32063, Taiwan.

Yiin-Kuen FuhDepartment of Mechanical Engineering, National Central University, Taoyuan 32001, Taiwan.ORCID 0000-0001-5322-0718

Tomi T LiDepartment of Mechanical Engineering, National Central University, Taoyuan 32001, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we submit a complex set of in-situ data collected by optical emission spectroscopy (OES) during the process of aluminum nitride (AlN) thin film. Changing the sputtering power and nitrogen(N

Indexed as

aluminum nitride (AlN)artificial neural networks (ANNs)in-situmachine learningprincipal component analysis (PCA)thin film stress

Identifiers

PMID34442969

DOI10.3390/ma14164445

PMCPMC8400567

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