Platinum–aluminum nitride–silicon carbide diodes as combustible gas sensors

2000 ◽  
Vol 87 (6) ◽  
pp. 3101-3107 ◽  
Author(s):  
A. Samman ◽  
S. Gebremariam ◽  
L. Rimai ◽  
X. Zhang ◽  
J. Hangas ◽  
...  
Keyword(s):  
Silicon Carbide ◽  
Aluminum Nitride ◽  
Gas Sensors ◽  
Combustible Gas

Silicon-carbide MOS capacitors with laser-ablated Pt gate as combustible gas sensors

2000 ◽  
Vol 63 (1-2) ◽  
pp. 91-102 ◽  
Author(s):  
A. Samman ◽  
S. Gebremariam ◽  
L. Rimai ◽  
X. Zhang ◽  
J. Hangas ◽  
...  
Keyword(s):  
Silicon Carbide ◽  
Gas Sensors ◽  
Mos Capacitors ◽  
Combustible Gas

Synthesis of Aluminum Nitride-Silicon Carbide Solid Solutions by Combustion Nitridation

2004 ◽  
Vol 83 (5) ◽  
pp. 1108-1112 ◽  
Author(s):  
Manshi Ohyanagi ◽  
Kenshiro Shirai ◽  
Nadejda Balandina ◽  
Masaaki Hisa ◽  
Zuhair A. Munir
Keyword(s):  
Silicon Carbide ◽  
Aluminum Nitride ◽  
Solid Solutions

Crystal quality and growth evolution of aluminum nitride on silicon carbide

2006 ◽  
Vol 203 (7) ◽  
pp. 1708-1711 ◽  
Author(s):  
Craig G. Moe ◽  
Yuan Wu ◽  
Stacia Keller ◽  
James S. Speck ◽  
Steven P. DenBaars ◽  
...  
Keyword(s):  
Silicon Carbide ◽  
Aluminum Nitride ◽  
Crystal Quality ◽  
Growth Evolution

scholarly journals Combustible Gas Classification Modeling using Support Vector Machine and Pairing Plot Scheme

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5018 ◽  
Author(s):  
Kyu-Won Jang ◽  
Jong-Hyeok Choi ◽  
Ji-Hoon Jeon ◽  
Hyun-Seok Kim
Keyword(s):  
Support Vector Machine ◽  
Gas Sensors ◽  
Learning Algorithm ◽  
Support Vector ◽  
Detection Accuracy ◽  
Minimum Concentration ◽  
Industrial Sites ◽  
Combustible Gas ◽  
Proposed Model ◽  
Combustible Gases

Combustible gases, such as CH4 and CO, directly or indirectly affect the human body. Thus, leakage detection of combustible gases is essential for various industrial sites and daily life. Many types of gas sensors are used to identify these combustible gases, but since gas sensors generally have low selectivity among gases, coupling issues often arise which adversely affect gas detection accuracy. To solve this problem, we built a decoupling algorithm with different gas sensors using a machine learning algorithm. Commercially available semiconductor sensors were employed to detect CH4 and CO, and then support vector machine (SVM) applied as a supervised learning algorithm for gas classification. We also introduced a pairing plot scheme to more effectively classify gas type. The proposed model classified CH4 and CO gases 100% correctly at all levels above the minimum concentration the gas sensors could detect. Consequently, SVM with pairing plot is a memory efficient and promising method for more accurate gas classification.

Recent progress in silicon carbide field effect gas sensors

2020 ◽  
pp. 309-346
Author(s):  
M. Andersson ◽  
A. Lloyd Spetz ◽  
D. Puglisi
Keyword(s):  
Silicon Carbide ◽  
Gas Sensors ◽  
Field Effect ◽  
Recent Progress

Seeded PVT Growth of Aluminum Nitride on Silicon Carbide

2003 ◽  
Vol 433-436 ◽  
pp. 983-986 ◽  
Author(s):  
Boris M. Epelbaum ◽  
Matthias Bickermann ◽  
Albrecht Winnacker
Keyword(s):  
Silicon Carbide ◽  
Aluminum Nitride
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