A Machine Learning Study to Obtain an Optimal Processing Pulsed Frequency on Reactive Pulsed DC Sputtering of Aluminum Nitride Films

Xue Li Tseng, Yu Shin Chen, Hsuan Fan Chen, Hsiao Han Lo, Peter J. Wang, Yu Min Dai, Yiin Kuen Fuh, Ting-Tung Li

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

The goal of this study was to investigate how changing the pulsed frequency affects the deposition process and correlates with AlN film properties. The resulting films were then characterized in terms of their crystallinity, microstructure, and surface roughness to identify any correlations with the pulsed frequency. This approach was used to determine the optimal pulsed conditions for film deposition. Each dataset spans the wavelength range of 190nm to 850nm, comprising 1,900 features. Following data collection, we employed traditional ensemble learning methods (Random Forest), tree-based gradient boosting (Categorical Boosting), and the improved gradient-boosted algorithm (Histogram Gradient Boosting), for predicting the quality of thin films. This analysis aimed to clarify which method excels in handling semiconductor process OES data to obtain an optimal processing pulsed frequency on reactive pulsed DC sputtering of aluminum nitride films.

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主出版物標題2024 Conference of Science and Technology for Integrated Circuits, CSTIC 2024
編輯Cor Claeys, Beichao Zhang, Bin Yu, Ru Huang, Xiaowei Li, Steve X. Liang, Jianshi Tang, Hsiang-Lan Lung, Linyong Pang, Weikang Qian, Xinping Qu, Xiaoping Shi, Ying Zhang
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9798350362190
DOIs
出版狀態已出版 - 2024
事件2024 Conference of Science and Technology for Integrated Circuits, CSTIC 2024 - Shanghai, China
持續時間: 17 3月 202418 3月 2024

出版系列

名字2024 Conference of Science and Technology for Integrated Circuits, CSTIC 2024

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???event.eventtypes.event.conference???2024 Conference of Science and Technology for Integrated Circuits, CSTIC 2024
國家/地區China
城市Shanghai
期間17/03/2418/03/24

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