15 February 1994 Modeling the properties of PECVD silicon dioxide films using neural networks
Author Affiliations +
Abstract
Silicon dioxide films deposited by plasma-enhanced chemical vapor deposition (PECVD) are useful as interlayer dielectric for metal-insulator structures such as MOS integrated circuits and multichip modules. The PECVD for SiO2 in a SiH4/N2O gas mixture yields films with excellent physical properties. However, due to the complex nature of particle dynamics within the plasma, it is difficult to determine the exact nature of the relationship between film properties and controllable deposition conditions. Previous modeling techniques such as first principles or statistical response surface methods are limited in either efficiency or accuracy. In this study, PECVD modeling using neural networks has been introduced. Neural networks have been shown to exhibit superior performance in both accuracy and prediction capability compared to statistical models.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Seung-Soo Han, Seung-Soo Han, Martin Ceiler, Martin Ceiler, Sue Ann Bidstrup Allen, Sue Ann Bidstrup Allen, Paul A. Kohl, Paul A. Kohl, Gary Stephen May, Gary Stephen May, } "Modeling the properties of PECVD silicon dioxide films using neural networks", Proc. SPIE 2091, Microelectronic Processes, Sensors, and Controls, (15 February 1994); doi: 10.1117/12.167348; https://doi.org/10.1117/12.167348
PROCEEDINGS
10 PAGES


SHARE
Back to Top