Predictive modeling and analysis of HfO2 thin film process based on Bayesian information criterion using PCA-based neural networks-Reference-Cited by-同舟云学术

Predictive modeling and analysis of HfO2 thin film process based on Bayesian information criterion using PCA-based neural networks

Published:2013-05-08 Issue:9 Volume:45 Page:1334-1339
ISSN:0142-2421
Container-title:Surface and Interface Analysis
language:en
Short-container-title:Surf. Interface Anal.

Author:

Ko Young-Don¹²,Moon Pyung³,Kim Chang Eun³,Ham Moon-Ho⁴,Jeong Myong-Kee⁵,Garcia-Diaz Alberto⁶,Myoung Jae-Min⁷,Yun Ilgu³

Affiliation:

1. Bloorview Research Institute; Holland Bloorview Kids Rehabilitation Hospital; Toronto Ontario Canada

2. Institute of Biomaterials and Biomedical Engineering; University of Toronto; Toronto Ontario Canada

3. Department of Electrical and Electronic Engineering; Yonsei University; 262 Seongsanno, Seodaemun-gu Seoul 120-749 Korea

4. School of Materials Science and Engineering and Department of Nanobio Materials and Electronics; Gwangju Institute of Science and Technology; 123 Chemdan-gwagiro, Buk-gu Gwangju 500-712 Korea

5. Department of Industrial and Systems Engineering, Rutgers Center for Operations Research, Rutgers; The State University of New Jersey; Piscataway NJ 08854 USA

6. Department of Industrial and Information Engineering; University of Tennessee; Knoxville TN 37996 USA

7. Department of Materials Science and Engineering; Yonsei University; 262 Seongsanno, Seodaemun-gu Seoul 120-749 Korea

Publisher

Wiley

Subject

Materials Chemistry,Surfaces, Coatings and Films,Surfaces and Interfaces,Condensed Matter Physics,General Chemistry

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/sia.5286/fullpdf

Reference21 articles.

1. Optical energy gaps of undoped and Co-doped ZnIn2Se4 single crystals

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