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Thermodynamic and Kinetic Analysis of Hydrogen Sensing in Pt/AlGaN/GaN Schottky Diodes at High Temperatures

IEEE sensors journal, 2008-06, Vol.8 (6), p.903-909

2008

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Operation of Pt/AlGaN/GaN-Heterojunction Field-Effect-Transistor Hydrogen Sensors With Low Detection Limit and High Sensitivity

IEEE electron device letters, 2008-11, Vol.29 (11), p.1193-1195

2008

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Passivation effects in Ni∕AlGaN∕GaN Schottky diodes by annealing

Applied physics letters, 2006-07, Vol.89 (5)

2006

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AlGaN/GaN Schottky diode hydrogen sensor performance at high temperatures with different catalytic metals

Solid-state electronics, 2005-08, Vol.49 (8), p.1330-1334

2005

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Chemically gated AlGaN∕GaN heterostructure field effect transistors for polar liquid sensing

Applied physics letters, 2006-11, Vol.89 (22)

2006

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Hydrogen sensing performance dependence on catalytic metal thickness of Pt/AlGaN/GaN Schottky diodes

Physica status solidi. C, 2010-07, Vol.7 (7-8), p.1838-1840

2010

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Chemically gated Al Ga N ∕ Ga N heterostructure field effect transistorsfor polar liquid sensing

Applied physics letters, 2006-11, Vol.89 (22), p.223503-223503-3

2006

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Pt - Al Ga N ∕ Ga N Schottky diodes operated at 800 ° C for hydrogen sensing

Applied physics letters, 2005-09, Vol.87 (13), p.133501-133501-3

2005

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AlGaN/GaN Heterostructure Field Effect Transistors for High Temperature Hydrogen Sensing with Enhanced Sensitivity

2007 IEEE International Electron Devices Meeting, 2007, p.835-838

2007

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Fabrication and characterization of aluminium gallium nitride/gallium nitride heterostructure devices for hydrogen gas sensing at high temperature

Song, Junghui

2009

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Passivation effects in Ni ∕ Al Ga N ∕ Ga N Schottky diodes by annealing

Applied physics letters, 2006-08, Vol.89 (5), p.053516-053516-3

2006

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High temperature hydrogen sensors based on AlGaN/GaN heterostructures

Proceedings of IEEE Sensors, 2004, 2004, p.158-161 vol.1

2004

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Characterization of Post-Gate Annealing Impact on Traps in AlGaN/GaN Schottky Diodes by Capacitance and Conductance Dispersion

2005 International Semiconductor Device Research Symposium, 2005, p.254-255

2005

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Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction

IEEE transactions on industrial informatics, 2020-12, Vol.16 (12), p.7233-7242

2020

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Image-based process monitoring using deep learning framework

Chemometrics and intelligent laboratory systems, 2019-06, Vol.189, p.8-17

2019

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Deep Neural Network-Embedded Stochastic Nonlinear State-Space Models and Their Applications to Process Monitoring

IEEE transaction on neural networks and learning systems, 2022-12, Vol.33 (12), p.7682-7694

2022

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Synthesizing labeled data to enhance soft sensor performance in data-scarce regions

Control engineering practice, 2021-10, Vol.115, p.104903, Article 104903

2021

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Performance Analysis of Dynamic PCA for Closed-Loop Process Monitoring and Its Improvement by Output Oversampling Scheme

IEEE transactions on control systems technology, 2019-01, Vol.27 (1), p.378-385

2019

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Data-driven sensor fault diagnosis systems for linear feedback control loops

Journal of process control, 2017-06, Vol.54, p.152-171

2017

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Data-Driven Operation Modeling and Optimal Design for Batch Cooling Crystallization with a Case Study on β‑LGA

Industrial & engineering chemistry research, 2022-12, Vol.61 (51), p.18795-18809

2022

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Using multivariate pattern segmentation to assess process performance and mine good operation conditions for dynamic chemical industry

Chemical engineering science, 2019-06, Vol.201, p.339-348

2019

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A sparse loading-based contribution method for multivariate control performance diagnosis

Journal of process control, 2020-01, Vol.85, p.199-213

2020

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Robust Self-Supervised Model and Its Application for Fault Detection

Industrial & engineering chemistry research, 2017-07, Vol.56 (26), p.7503-7515

2017

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Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes

IEEE access, 2019, Vol.7, p.22554-22565

2019

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Multilevel MVU models with localized construction for monitoring processes with large scale data

Journal of process control, 2018-07, Vol.67, p.176-196

2018

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Thermodynamic and Kinetic Analysis of Hydrogen Sensing in Pt/AlGaN/GaN Schottky Diodes at High Temperatures

Operation of Pt/AlGaN/GaN-Heterojunction Field-Effect-Transistor Hydrogen Sensors With Low Detection Limit and High Sensitivity

Passivation effects in Ni∕AlGaN∕GaN Schottky diodes by annealing

AlGaN/GaN Schottky diode hydrogen sensor performance at high temperatures with different catalytic metals

Chemically gated AlGaN∕GaN heterostructure field effect transistors for polar liquid sensing

Hydrogen sensing performance dependence on catalytic metal thickness of Pt/AlGaN/GaN Schottky diodes

Chemically gated Al Ga N ∕ Ga N heterostructure field effect transistorsfor polar liquid sensing

Pt - Al Ga N ∕ Ga N Schottky diodes operated at 800 ° C for hydrogen sensing

AlGaN/GaN Heterostructure Field Effect Transistors for High Temperature Hydrogen Sensing with Enhanced Sensitivity

Fabrication and characterization of aluminium gallium nitride/gallium nitride heterostructure devices for hydrogen gas sensing at high temperature

Passivation effects in Ni ∕ Al Ga N ∕ Ga N Schottky diodes by annealing

High temperature hydrogen sensors based on AlGaN/GaN heterostructures

Characterization of Post-Gate Annealing Impact on Traps in AlGaN/GaN Schottky Diodes by Capacitance and Conductance Dispersion

Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction

Image-based process monitoring using deep learning framework

Deep Neural Network-Embedded Stochastic Nonlinear State-Space Models and Their Applications to Process Monitoring

Synthesizing labeled data to enhance soft sensor performance in data-scarce regions

Performance Analysis of Dynamic PCA for Closed-Loop Process Monitoring and Its Improvement by Output Oversampling Scheme

Data-driven sensor fault diagnosis systems for linear feedback control loops

Data-Driven Operation Modeling and Optimal Design for Batch Cooling Crystallization with a Case Study on β‑LGA

Using multivariate pattern segmentation to assess process performance and mine good operation conditions for dynamic chemical industry

A sparse loading-based contribution method for multivariate control performance diagnosis

Robust Self-Supervised Model and Its Application for Fault Detection

Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes

Multilevel MVU models with localized construction for monitoring processes with large scale data

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