scholarly journals A Set of Platforms with Combinatorial and High-Throughput Technique for Gas Sensing, from Material to Device and to System

Micromachines ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 606 ◽  
Author(s):  
Zhenghao Mao ◽  
Jianchao Wang ◽  
Youjin Gong ◽  
Heng Yang ◽  
Shunping Zhang
Keyword(s):  
Gas Sensor ◽  
High Throughput ◽  
System Integration ◽  
Sensor Array ◽  
Gas Sensing ◽  
Parallel Synthesis ◽  
Testing Platform ◽  
Long Time ◽  
Sensitivity And Selectivity ◽  
Array Optimization

In a new E-nose development, the sensor array needs to be optimized to have enough sensitivity and selectivity for gas/odor classification in the application. The development process includes the preparation of gas sensitive materials, gas sensor fabrication, array optimization, sensor array package and E-nose system integration, which would take a long time to complete. A set of platforms including a gas sensing film parallel synthesis platform, high-throughput gas sensing unmanned testing platform and a handheld wireless E-nose system were presented in this paper to improve the efficiency of a new E-nose development. Inkjet printing was used to parallel synthesize sensor libraries (400 sensors can be prepared each time). For gas sensor selection and array optimization, a high-throughput unmanned testing platform was designed and fabricated for gas sensing measurements of more than 1000 materials synchronously. The structures of a handheld wireless E-nose system with low power were presented in detail. Using the proposed hardware platforms, a new E-nose development might only take one week.

High Throughput Screening of Surface Modificated In2O3 for VOC Gas Sensing Array Optimization

2020 ◽  
Vol 20 (13) ◽  
pp. 7318-7325
Author(s):  
Na Zhang ◽  
Feng Xie ◽  
Jianchao Wang ◽  
Qinyi Zhang ◽  
Shunping Zhang ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Gas Sensing ◽  
Array Optimization

scholarly journals 100 nm-Gap Fingers Dielectrophoresis Functionalized MOX Gas Sensor Array for Low Temperature VOCs Detection

Proceedings ◽  
2018 ◽  
Vol 2 (13) ◽  
pp. 1027
Author(s):  
Luca Francioso ◽  
Pasquale Creti ◽  
Maria Concetta Martucci ◽  
Simonetta Capone ◽  
Antonietta Taurino ◽  
...  
Keyword(s):  
Low Temperature ◽  
Gas Sensor ◽  
Sensor Array ◽  
Gas Sensing ◽  
Enhanced Sensitivity ◽  
Sno2 Nanocrystals ◽  
Gas Sensor Array ◽  
Order Of Magnitude ◽  
Nanogap Electrodes ◽  
Average Size

Present work reports the fabrication process and functional gas sensing tests of a 100 nm-gap fingers DiElectroPhoresis (DEP) functionalized MOX (Metal OXide) gas sensor array for VOCs detection at low temperature. The Internet of Things (IoT) scenario applications of the chemical sensing-enabled mobiles or connected devices are many ranging from indoor air quality to novel breath analyser for personal healthcare monitoring. However, the commercial MOX gas sensors operate at moderate temperatures (200–400 °C) [1], and this limits the mobile and wearable gadgets market penetration. Nanogap devices may represent the alternative devices with enhanced sensitivity even at low or room temperature. A nanogap electrodes MOX gas sensor array functionalized with 5 nm average size SnO2 nanocrystals with positive dielectrophoresis technique is presented. The single sensor active area is 4 × 4 µm2. The devices exhibited about 1 order of magnitude response at 100 °C to 150 ppm of acetone.

An Effective Gas Sensor Array Optimization Method Based on Random Forest*

2018 ◽  
Author(s):  
Guangfen Wei ◽  
Jie Zhao ◽  
Zechuan Yu ◽  
Yanli Feng ◽  
Gang Li ◽  
...  
Keyword(s):  
Random Forest ◽  
Gas Sensor ◽  
Sensor Array ◽  
Optimization Method ◽  
Gas Sensor Array ◽  
Array Optimization

Type discrimination and concentration prediction towards ethanol using a machine learning–enhanced gas sensor array with different morphology-tuning characteristics

2021 ◽  
Author(s):  
Tao Wang ◽  
Hongli Ma ◽  
Wenkai Jiang ◽  
Hexin Zhang ◽  
Min Zeng ◽  
...  
Keyword(s):  
Machine Learning ◽  
Gas Sensor ◽  
Sensor Array ◽  
Gas Sensing ◽  
Hierarchical Structures ◽  
Machine Learning Algorithms ◽  
Microwave Assisted ◽  
Gas Sensor Array ◽  
Microwave Assisted Method ◽  
Concentration Prediction

Microwave-assisted method has been developed to synthesize ZnO gas sensing nanomaterials with controllable hierarchical structures. Machine learning algorithms such as PCA, SVM, ELM, and BP further improve the selectivity and quantitation.

Vitreous Chalcogenide Semiconductors for Gas Sensing Application

2004 ◽  
Vol 828 ◽  
Author(s):  
Serghei V. Dmitriev ◽  
Igor V. Dementiev
Keyword(s):  
Thin Films ◽  
Gas Sensor ◽  
Solid Solutions ◽  
Gas Sensing ◽  
Flexible Substrate ◽  
Gas Sensitivity ◽  
New Class ◽  
Long Time ◽  
Chalcogenide Materials ◽  
Level 2

ABSTRACTReport presents results of research aimed the investigation of possibility to use such chalcogenide materials as vitreous As2S3, As2Se3 and their solid solutions for gas sensors applications. For a long time these materials were well-known as materials mostly used for optical information registration. Developed approach allows to widening the sphere of application of given materials and create new class of gas sensitive devices.Thin film gas sensitive elements on the base of solid solutions of (As2S3)x-(As2Se3)1−x (where x=0; 0.3; 0.5; 0.7 and 1.0) were obtained by means of the thermal evaporation under vacuum conditions 10−5 Torr. Thin films can be deposited on both hard and flexible substrate. Formed films had specific resistance on the level 1010–1014 Ohm.cm (on dependence on composition) at the thickness of 1–2 μm.It was established that CGS thin films possess gas sensitivity S, determined as S=(Ggas-Gait)/Gair, on the level 2–3 relative units for CO and 7–8 for hydrogen at the 100 ppm concentration levels of both gases in atmosphere already at the room temperature that allows to excluding the heater from the gas sensor construction decreasing through that both manufacturing and operational cost.It is concluded that chalcogenide semiconductor materials can be considered as perspective materials for gas sensor application, including space exploration application.

scholarly journals Evaluating the Fitness of Combinations of Adsorbents for Quantitative Gas Sensor Arrays

2020 ◽  
Author(s):  
Rachel Sousa ◽  
Cory Simon
Keyword(s):  
Inverse Problem ◽  
Gas Sensor ◽  
Sensor Array ◽  
Gas Sensing ◽  
Sensor Arrays ◽  
Industrial Process ◽  
Gas Composition ◽  
Monitoring And Control ◽  
Security Threat ◽  
Adsorption Model

Robust, high-performance gas sensing technology has applications in industrial process monitoring and control, air quality monitoring, food quality assessment, medical diagnosis, and security threat detection. Nanoporous materials (NPMs) could be utilized as recognition elements in a gas sensor because they selectively adsorb gas. Imitating mammalian olfaction, sensor arrays of NPMs use measurements of the adsorbed mass of gas in a set of distinct NPMs to infer the gas composition. Modular and adjustable NPMs, such as metal-organic frameworks (MOFs), offer a vast materials space to sample for combinations to comprise a sensor array that produces a response pattern rich with information about the gas composition.<br><br>Herein, we frame quantitative gas sensing, using arrays of NPMs, as an inverse problem, which equips us with a method to evaluate the fitness of a proposed combination of NPMs in a sensor array. While the (routine) forward problem is to use an adsorption model to predict the mass of gas adsorbed in the NPMs when immersed in a gas mixture of a given composition, the inverse problem is to predict the gas composition from the observed mass of adsorbed gas in each NPM. The fitness of a given combination of NPMs for gas sensing is then determined by the conditioning of its inverse problem: the prediction of the gas composition provided by a fit (unfit) combination of NPMs is insensitive (sensitive) to inevitable errors in the measurements of the mass of gas adsorbed in the NPMs. For illustration, we use experimentally measured adsorption data to analyze the conditioning of the inverse problem associated with a [IRMOF-1, HKUST-1] CH<sub>4</sub>/CO<sub>2</sub> sensor array.

Feature Selection and Sensor Array Optimization in Machine Olfaction

2011 ◽  
pp. 1-61 ◽  
Author(s):  
Alexander Vergara ◽  
Eduard Llobet
Keyword(s):  
Mass Spectrometry ◽  
Feature Selection ◽  
Variable Selection ◽  
Gas Sensor ◽  
Critical Review ◽  
Sensor Array ◽  
Sensor Selection ◽  
Array Optimization ◽  
Direct Mass Spectrometry ◽  
Machine Olfaction

In this context, the main objective of this chapter is to provide the reader with a thorough review of feature or sensor selection for machine olfaction. The organization of the chapter is as follows. First the ‘curse of dimensionality’ and the need for variable selection in gas sensor and direct mass spectrometry based artificial olfaction is discussed. A critical review of the different techniques employed for reducing dimensionality follows. Then, examples taken from the literature showing how these techniques have actually been employed in machine olfaction applications are reviewed and discussed. This is followed by a section devoted to sensor selection and array optimization. The chapter ends with some conclusions drawn from the results presented and a visionary look toward the future in terms of how the field may evolve.

scholarly journals Ni-CNT Chemical Sensor for SF6 Decomposition Components Detection: A Combined Experimental and Theoretical Study

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3493 ◽  
Author(s):  
Yingang Gui ◽  
Xiaoxing Zhang ◽  
Peigeng Lv ◽  
Shan Wang ◽  
Chao Tang ◽  
...  
Keyword(s):  
Gas Sensor ◽  
Density Functional ◽  
Chemical Sensor ◽  
Theoretical Study ◽  
Gas Sensing ◽  
Limit Of Detection ◽  
Gas Sensitivity ◽  
Sensitivity And Selectivity ◽  
Sf6 Decomposition ◽  
Insulation Status

SF6 decomposition components detection is a key technology to evaluate and diagnose the insulation status of SF6-insulated equipment online, especially when insulation defects-induced discharge occurs in equipment. In order to detect the type and concentration of SF6 decomposition components, a Ni-modified carbon nanotube (Ni-CNT) gas sensor has been prepared to analyze its gas sensitivity and selectivity to SF6 decomposition components based on an experimental and density functional theory (DFT) theoretical study. Experimental results show that a Ni-CNT gas sensor presents an outstanding gas sensing property according to the significant change of conductivity during the gas molecule adsorption. The conductivity increases in the following order: H2S > SOF2 > SO2 > SO2F2. The limit of detection of the Ni-CNT gas sensor reaches 1 ppm. In addition, the excellent recovery property of the Ni-CNT gas sensor makes it easy to be widely used. A DFT theoretical study was applied to analyze the influence mechanism of Ni modification on SF6 decomposition components detection. In summary, the Ni-CNT gas sensor prepared in this study can be an effective way to evaluate and diagnose the insulation status of SF6-insulated equipment online.

Development of a High-Throughput Impedance Spectroscopy Screening System (HT-IS) for Characterisation of Novel Nanoscaled Gas Sensing Materials

2005 ◽  
Vol 876 ◽  
Author(s):  
Daniel Sanders ◽  
Maike Siemons ◽  
Tobias Koplin ◽  
Ulrich Simon
Keyword(s):  
Impedance Spectroscopy ◽  
Metal Oxide ◽  
High Throughput ◽  
Gas Sensing ◽  
Metal Oxide Nanoparticles ◽  
Sensor Arrays ◽  
Material Deposition ◽  
Interdigital Electrodes ◽  
Sensitivity And Selectivity ◽  
Oxide Particles

AbstractA high-throughput work flow for rapid synthesis and testing of metal oxide nanoparticles for the discovery of new gas sensors of improved sensitivity and selectivity has been developed. The material libraries consist of nanoscaled metal oxide particles which are obtained either from pyrolysis of appropriate precursors or from polyol mediated synthesis. The design of a multielectrode array with 8x8 interdigital electrodes allows efficient and automated pipetting robot assisted sample preparation and material deposition. For characterisation of the sensor arrays high throughput impedance spectroscopy has been used. Test gas sequences and sensor temperatures can be varied. As an example, the properties of an In2O3-based library are introduced.

Preparation and Gas Sensing Properties of Microrod ZnO Materials

2014 ◽  
Vol 492 ◽  
pp. 297-300
Author(s):  
Liu Fang Yang ◽  
Yu Lin Wang ◽  
Qin Hui Wang
Keyword(s):  
Gas Sensor ◽  
Gas Sensing ◽  
Operating Temperature ◽  
High Sensitivity ◽  
Raw Material ◽  
Gas Sensing Properties ◽  
Sensitivity And Selectivity ◽  
Static Volumetric Method ◽  
Degree Of Crystallization ◽  
High Degree

Using zinc chloride solution and ammonia (25%) as raw material, with the presence of surfactant (CTAB), the microrod ZnO material was synthesized by the hydrothermal method. The phase composition and microstructure of the prepared ZnO material were characterized with XRD and SEM. The results show that the ZnO material possesses a high degree of crystallization, its diameter below 4 μm, and its length about 35 μm. The gas sensing property of gas sensor fabricated with the prepared ZnO material was evaluated via the static volumetric method. At the operating temperature of 200°C, the gas sensor has high sensitivity and selectivity to CH3COCH3.The gas sensing characterization was also discussed.

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