The storage capacity of 3D-NAND flash memory has been enhanced by the multi-layer dielectrics. The deposition process has become more challenging due to the tight process margin and the demand for accurate process control. To reduce product costs and ensure successful processes, process diagnosis techniques incorporating artificial intelligence (AI) have been adopted in semiconductor manufacturing. Recently there is a growing interest in process diagnosis, and numerous studies have been conducted in this field.

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[1] Sang Jeen Hong, "In-situ Process Monitoring Data of PECVD Plasma", IEEE Dataport, 2023. [Online]. Available: http://dx.doi.org/10.21227/xg5f-b066. Accessed: Feb. 25, 2024.
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doi = {10.21227/xg5f-b066},
url = {http://dx.doi.org/10.21227/xg5f-b066},
author = {Sang Jeen Hong },
publisher = {IEEE Dataport},
title = {In-situ Process Monitoring Data of PECVD Plasma},
year = {2023} }
TY - DATA
T1 - In-situ Process Monitoring Data of PECVD Plasma
AU - Sang Jeen Hong
PY - 2023
PB - IEEE Dataport
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Sang Jeen Hong. (2023). In-situ Process Monitoring Data of PECVD Plasma. IEEE Dataport. http://dx.doi.org/10.21227/xg5f-b066
Sang Jeen Hong, 2023. In-situ Process Monitoring Data of PECVD Plasma. Available at: http://dx.doi.org/10.21227/xg5f-b066.
Sang Jeen Hong. (2023). "In-situ Process Monitoring Data of PECVD Plasma." Web.
1. Sang Jeen Hong. In-situ Process Monitoring Data of PECVD Plasma [Internet]. IEEE Dataport; 2023. Available from : http://dx.doi.org/10.21227/xg5f-b066
Sang Jeen Hong. "In-situ Process Monitoring Data of PECVD Plasma." doi: 10.21227/xg5f-b066