Neural network modeling of reactive ion etching using principal component analysis of optical emission spectroscopy data

Emission Spectroscopy ◽

Network Modeling ◽

Principal Component ◽

Optical Emission ◽

Neural Network Modeling ◽

Spectroscopy Data ◽

Ion Etching

Neural network modeling of reactive ion etching using optical emission spectroscopy data

IEEE Transactions on Semiconductor Manufacturing ◽

10.1109/tsm.2003.818976 ◽

2003 ◽

Vol 16 (4) ◽

pp. 598-608 ◽

Cited By ~ 51

Author(s):

Sang Jeen Hong ◽

G.S. May ◽

Dong-Cheol Park

Keyword(s):

Neural Network ◽

Emission Spectroscopy ◽

Network Modeling ◽

Reactive Ion Etching ◽

Optical Emission ◽

Neural Network Modeling ◽

Spectroscopy Data ◽

Ion Etching

Neural network based time series modeling of optical emission spectroscopy data for fault detection in reactive ion etching

10.1117/12.485230 ◽

2003 ◽

Cited By ~ 4

Author(s):

Sang Jeen Hong ◽

Gary S. May

Keyword(s):

Neural Network ◽

Time Series ◽

Fault Detection ◽

Emission Spectroscopy ◽

Reactive Ion Etching ◽

Optical Emission ◽

Time Series Modeling ◽

Spectroscopy Data ◽

Ion Etching

Prediction of plasma etch process by using actinometry-based optical emission spectroscopy data and neural network

Journal of Materials Processing Technology ◽

10.1016/j.jmatprotec.2008.06.006 ◽

2009 ◽

Vol 209 (5) ◽

pp. 2620-2626 ◽

Cited By ~ 6

Author(s):

Byungwhan Kim ◽

Minji Kwon

Keyword(s):

Neural Network ◽

Emission Spectroscopy ◽

Optical Emission ◽

Spectroscopy Data ◽

Plasma Etch

Neural network modeling and principal component analysis of antibacterial activity of chitosan/AgCl-TiO2 colloid treated cotton fabric

Fibers and Polymers ◽

10.1007/s12221-015-1142-2 ◽

2015 ◽

Vol 16 (5) ◽

pp. 1142-1149 ◽

Cited By ~ 3

Author(s):

Samander Ali Malik ◽

Rabia Almas Arain ◽

Zeeshan Khatri ◽

Sidra Saleemi ◽

Chokri Cherif

Keyword(s):

Neural Network ◽

Antibacterial Activity ◽

Cotton Fabric ◽

Network Modeling ◽

Principal Component ◽

Component Analysis ◽

Neural Network Modeling

Principal Component Analysis of Optical Emission Spectroscopy and Mass Spectrometry: Application to Reactive Ion Etch Process Parameter Estimation Using Neural Networks

Journal of The Electrochemical Society ◽

10.1149/1.2069323 ◽

1992 ◽

Vol 139 (3) ◽

pp. 907-914 ◽

Cited By ~ 36

Author(s):

Reza Shadmehr ◽

David Angell ◽

Paul B. Chou ◽

Gottlieb S. Oehrlein ◽

Robert S. Jaffe

Keyword(s):

Mass Spectrometry ◽

Neural Networks ◽

Parameter Estimation ◽

Emission Spectroscopy ◽

Principal Component ◽

Optical Emission ◽

Process Parameter ◽

Mass Spectrometry Application

Development of an optimized multi-biomarker panel for the detection of lung cancer based on principal component analysis and artificial neural network modeling

Expert Systems with Applications ◽

10.1016/j.eswa.2012.03.008 ◽

2012 ◽

Vol 39 (12) ◽

pp. 10851-10856 ◽

Cited By ~ 15

Author(s):

José Miguel Flores-Fernández ◽

Enrique J. Herrera-López ◽

Francisco Sánchez-Llamas ◽

Antonio Rojas-Calvillo ◽

Paula Anel Cabrera-Galeana ◽

...

Keyword(s):

Neural Network ◽

Lung Cancer ◽

Artificial Neural Network ◽

Network Modeling ◽

Principal Component ◽

Component Analysis ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Biomarker Panel

Non-invasive assessment of plasma parameters inside an ion thruster combining optical emission spectroscopy and principal component analysis

EPJ Techniques and Instrumentation ◽

10.1140/epjti/s40485-021-00070-x ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Benny T. Nauschütt ◽

Limei Chen ◽

Kristof Holste ◽

Peter J. Klar

Keyword(s):

Emission Spectroscopy ◽

Principal Component ◽

Optical Emission ◽

Component Analysis ◽

Plasma Parameters ◽

Ion Thruster ◽

Non Invasive

Selecting signature optical emission spectroscopy variables using sparse principal component analysis

2008 11th International Conference on Computer and Information Technology ◽

10.1109/iccitechn.2008.4803104 ◽

2008 ◽

Author(s):

Beibei Ma ◽

Sean McLoone ◽

John Ringwood ◽

Niall Macgearailt

Keyword(s):

Emission Spectroscopy ◽

Sparse Principal Component Analysis

Principal Component ◽

Optical Emission ◽

Component Analysis ◽

Energy conservation – A novel approach of co-combustion of paint sludge and Australian lignite by principal component analysis, response surface methodology and artificial neural network modeling

Environmental Technology & Innovation ◽

10.1016/j.eti.2020.101061 ◽

2020 ◽

Vol 20 ◽

pp. 101061 ◽

Cited By ~ 2

Author(s):

Sathiya Prabhakaran S.P. ◽

Swaminathan G. ◽

Viraj V. Joshi

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Network Modeling ◽

Principal Component ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Novel Approach ◽

Paint Sludge

Correction to: Non-invasive assessment of plasma parameters inside an ion thruster combining optical emission spectroscopy and principal component analysis

EPJ Techniques and Instrumentation ◽

10.1140/epjti/s40485-021-00075-6 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Benny T. Nauschütt ◽

Limei Chen ◽

Kristof Holste ◽

Peter J. Klar

Keyword(s):

Emission Spectroscopy ◽

Principal Component ◽

Optical Emission ◽

Component Analysis ◽

Plasma Parameters ◽

Ion Thruster ◽

Non Invasive