DocumentCode :
1409468
Title :
The use of multilayer neural networks in material synthesis
Author :
Bensaoula, Abdelhak ; Malki, Heidar A. ; Kwari, A. Marcellino
Author_Institution :
Space Vacuum Epitaxy Center, Houston Univ., TX, USA
Volume :
11
Issue :
3
fYear :
1998
fDate :
8/1/1998 12:00:00 AM
Firstpage :
421
Lastpage :
431
Abstract :
This paper demonstrates the incorporation of a multilayer neural network in semiconductor thin film deposition processes. As a first step toward neural network-based process control, we present results from neural network pattern classification and beam analysis of reflection high energy electron diffraction RHEED images of GaAs/AlGaAs crystal surfaces during molecular beam epitaxy growth. For beam analysis, we used the neural network to detect and measure the intensity of the RHEED beam spots during the growth process and, through Fourier transformation, determined the thin film deposition rate. The neural network RHEED pattern classification and intensity analysis capability allows, powerful in situ real time monitoring of epitaxial thin film deposition processes. Our results show that a three layer network with sixteen hidden neurons and three output neurons had the highest correct classification rate with a success rate of 100% during testing and training on 13 examples
Keywords :
III-V semiconductors; aluminium compounds; gallium arsenide; image classification; molecular beam epitaxial growth; neural nets; process control; reflection high energy electron diffraction; semiconductor epitaxial layers; semiconductor growth; Fourier transformation; GaAs-AlGaAs; GaAs/AlGaAs crystal surface; RHEED image; beam intensity analysis; in situ real time monitoring; material synthesis; molecular beam epitaxy growth; multilayer neural network; pattern classification; process control; semiconductor thin film deposition; Crystalline materials; Molecular beam epitaxial growth; Multi-layer neural network; Network synthesis; Neural networks; Neurons; Pattern analysis; Pattern classification; Semiconductor materials; Sputtering;
fLanguage :
English
Journal_Title :
Semiconductor Manufacturing, IEEE Transactions on
Publisher :
ieee
ISSN :
0894-6507
Type :
jour
DOI :
10.1109/66.705377
Filename :
705377
Link To Document :
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