scholarly journals Impact of a Diverse Combination of Metal Oxide Gas Sensors on Machine Learning-Based Gas Recognition in Mixed Gases

ACS Omega ◽  
2021 ◽  
Author(s):  
Garam Bae ◽  
Minji Kim ◽  
Wooseok Song ◽  
Sung Myung ◽  
Sun Sook Lee ◽  
...  
Keyword(s):  
Machine Learning ◽  
Metal Oxide ◽  
Gas Sensors ◽  
Metal Oxide Gas Sensors ◽  
Mixed Gases

scholarly journals Design and Validation of a Portable Machine Learning-Based Electronic Nose

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3923
Author(s):  
Yixu Huang ◽  
Iyll-Joon Doh ◽  
Euiwon Bae
Keyword(s):  
Machine Learning ◽  
Metal Oxide ◽  
Electronic Nose ◽  
Gas Sensors ◽  
Machine Learning Algorithms ◽  
Supervised Machine Learning ◽  
Support Vector ◽  
Metal Oxide Sensors ◽  
Metal Oxide Gas Sensors

Volatile organic compounds (VOCs) are chemicals emitted by various groups, such as foods, bacteria, and plants. While there are specific pathways and biological features significantly related to such VOCs, detection of these is achieved mostly by human odor testing or high-end methods such as gas chromatography–mass spectrometry that can analyze the gaseous component. However, odor characterization can be quite helpful in the rapid classification of some samples in sufficient concentrations. Lower-cost metal-oxide gas sensors have the potential to allow the same type of detection with less training required. Here, we report a portable, battery-powered electronic nose system that utilizes multiple metal-oxide gas sensors and machine learning algorithms to detect and classify VOCs. An in-house circuit was designed with ten metal-oxide sensors and voltage dividers; an STM32 microcontroller was used for data acquisition with 12-bit analog-to-digital conversion. For classification of target samples, a supervised machine learning algorithm such as support vector machine (SVM) was applied to classify the VOCs based on the measurement results. The coefficient of variation (standard deviation divided by mean) of 8 of the 10 sensors stayed below 10%, indicating the excellent repeatability of these sensors. As a proof of concept, four different types of wine samples and three different oil samples were classified, and the training model reported 100% and 98% accuracy based on the confusion matrix analysis, respectively. When the trained model was challenged against new sets of data, sensitivity and specificity of 98.5% and 98.6% were achieved for the wine test and 96.3% and 93.3% for the oil test, respectively, when the SVM classifier was used. These results suggest that the metal-oxide sensors are suitable for usage in food authentication applications.

scholarly journals Sensitive and Low-Power Metal Oxide Gas Sensors with a Low-Cost Microelectromechanical Heater

ACS Omega ◽  
2021 ◽  
Author(s):  
Yulong Chen ◽  
Mingjie Li ◽  
Wenjun Yan ◽  
Xin Zhuang ◽  
Kar Wei Ng ◽  
...  
Keyword(s):  
Metal Oxide ◽  
Low Power ◽  
Gas Sensors ◽  
Low Cost ◽  
Metal Oxide Gas Sensors

scholarly journals P1SM.7 - Investigation of active heated gas filters on metal oxide gas sensors using a microstructured stacked-die setup

2018 ◽  
Author(s):  
T. Graunke ◽  
S. Raible ◽  
K. R. Tarantik ◽  
K. Schmitt ◽  
J. Wöllenstein
Keyword(s):  
Metal Oxide ◽  
Gas Sensors ◽  
Metal Oxide Gas Sensors

scholarly journals GS1.2 - Nanoheterostructure Metal Oxide Gas Sensors: Opportunities and Challenges

2018 ◽  
Author(s):  
S. A. Akbar ◽  
D. R. Miller ◽  
M. A. Al-Hashem ◽  
P. Karnati ◽  
J. Walker ◽  
...  
Keyword(s):  
Metal Oxide ◽  
Gas Sensors ◽  
Metal Oxide Gas Sensors

Investigating Simultaneous Effects of Flow Rate and Chamber Structure on the Performance of Metal Oxide Gas Sensors

2021 ◽  
pp. 1-1
Author(s):  
Hannaneh Mahdavi ◽  
Saeideh Rahbarpour ◽  
Reza Goldoust ◽  
Seyed-Mohsen Hosseini-Golgoo ◽  
Hamidreza Jamaati
Keyword(s):  
Metal Oxide ◽  
Flow Rate ◽  
Gas Sensors ◽  
Metal Oxide Gas Sensors

scholarly journals SPM—SEM Investigations of Semiconductor Nanowires for Integrated Metal Oxide Gas Sensors

Proceedings ◽  
2018 ◽  
Vol 2 (13) ◽  
pp. 701 ◽  
Author(s):  
Verena Leitgeb ◽  
Katrin Fladischer ◽  
Frank Hitzel ◽  
Florentyna Sosada-Ludwikowska ◽  
Johanna Krainer ◽  
...  
Keyword(s):  
Electron Beam ◽  
Metal Oxide ◽  
Gas Sensor ◽  
Gas Sensors ◽  
Semiconductor Nanowires ◽  
Kelvin Probe ◽  
Sensor Applications ◽  
Sensitivity And Selectivity ◽  
Stable Performance ◽  
Metal Oxide Gas Sensors

Integration of metal oxide nanowires in metal oxide gas sensors enables a new generation of gas sensor devices, with increased sensitivity and selectivity. For reproducible and stable performance of next generation sensors, the electric properties of integrated nanowires have to be well understood, since the detection principle of metal oxide gas sensors is based on the change in electrical conductivity during gas exposure. We study two different types of nanowires that show promising properties for gas sensor applications with a Scanning Probe Microscope—Scanning Electron Microscope combination. Electron Beam Induced Current and Kelvin Probe Force Microscopy measurements with a lateral resolution in the nanometer regime are performed. Our work offers new insights into the dependence of the nanowire work function on its composition and size, and into the local interaction between electron beam and semiconductor nanowires.

Extraordinary performance of semiconducting metal oxide gas sensors using dielectric excitation

2020 ◽  
Vol 3 (5) ◽  
pp. 280-289 ◽  
Author(s):  
Radislav A. Potyrailo ◽  
Steven Go ◽  
Daniel Sexton ◽  
Xiaxi Li ◽  
Nasr Alkadi ◽  
...  
Keyword(s):  
Metal Oxide ◽  
Gas Sensors ◽  
Metal Oxide Gas Sensors ◽  
Semiconducting Metal Oxide
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