scholarly journals Real-time optical control of Ga1−xInxP film growth by p-polarized reflectance

1999 ◽  
Vol 17 (4) ◽  
pp. 1300-1306 ◽  
Author(s):  
N. Dietz ◽  
V. Woods ◽  
K. Ito ◽  
I. Lauko
Keyword(s):  
Real Time ◽  
Film Growth ◽  
Optical Control ◽  
Polarized Reflectance

scholarly journals Real-time Optical Control of Ga(1-x)In(x)P Film Growth

1999 ◽  
Author(s):  
N. Dietz ◽  
V. Woods ◽  
K. Ito ◽  
I. Lauko
Keyword(s):  
Real Time ◽  
Film Growth ◽  
Optical Control

Artificial Neural Networks Estimation for Thicknesses of Multilayer Nano-Scale Films

2019 ◽  
Vol 962 ◽  
pp. 41-48
Author(s):  
Tzong Daw Wu ◽  
Jiun Shen Chen ◽  
Ching Pei Tseng ◽  
Cheng Chang Hsieh
Keyword(s):  
Thin Films ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Real Time ◽  
Film Growth ◽  
Mean Squared Error ◽  
Squared Error ◽  
Thin Film Optics ◽  
The Mean ◽  
Artificial Neural

This study presents a real-time method for determining the thickness of each layer in multilayer thin films. Artificial neural networks (ANNs) were introduced to estimate thicknesses from a transmittance spectrum. After training via theoretical spectra which were generated by thin-film optics and modified by noise, ANNs were applied to estimate the thicknesses of four-layer nanoscale films which were TiO2, Ag, Ti, and TiO2 thin films assembled sequentially on polyethylene terephthalate (PET) substrates. The results reveal that the mean squared error of the estimation is 2.6 nm2, and is accurate enough to monitor film growth in real time.

Copper Film Growth by Chemical Vapor Deposition: Electrical and Optical Measurements in Real Time, and Studies of Morphology

1993 ◽  
Vol 140 (3) ◽  
pp. 789-796 ◽  
Author(s):  
B. Lecohier ◽  
B. Calpini ◽  
J. ‐M. Philippoz ◽  
H. van den Bergh ◽  
D. Laub ◽  
...  
Keyword(s):  
Chemical Vapor Deposition ◽  
Real Time ◽  
Vapor Deposition ◽  
Film Growth ◽  
Copper Film ◽  
Chemical Vapor ◽  
Optical Measurements
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