Bibliographic Details
| Title: |
Chemical sensor systems for emission control from combustions. |
| Authors: |
Lloyd Spetz, A.1,2 spetz@ifm.liu.se, Huotari, J.2 joni.huotari@ee.oulu.fi, Bur, C.1,3 c.bur@LMT.uni-saarland.de, Bjorklund, R.1 robbj@ifm.liu.se, Lappalainen, J.2 jyla@ee.oulu.fi, Jantunen, H.2 heja@ee.oulu.fi, Schütze, A.3 schuetze@lmt.uni-saarland.de, Andersson, M.1 mikan@ifm.liu.se |
| Source: |
Sensors & Actuators B: Chemical. Oct2013, Vol. 187, p184-190. 7p. |
| Subjects: |
Electrochemical sensors, Emission control, Combustion, Environmental health, Silicon carbide, Field-effect transistors, Diesel motor exhaust gas, Power plants |
| Abstract: |
Abstract: Environmental and health concern has increased the importance to monitor and control emissions like toxic gases and particulate matter from combustion processes. The silicon carbide-field effect transistor (SiC-FET) technology offers versatile and powerful sensors for gas detection also in combination with combustion of particles. Emission control has been demonstrated e.g. for small and medium sized power plants and diesel exhausts. The potential danger of nanoparticles makes such detectors interesting not only for detection of concentration and size of particles but also detection of the content of particles. Due to the possibility of operating the sensor devices in different independent modes (e.g. temperature- and bias-modulated) the SiC-FET technology also lends itself for the future development of sensor adaptation, self-diagnosis and auto calibration, which is expected to improve the performance of such a combined gas/particle sensor system. Here we report progress on the sensor technology itself, the application of a sensor system as an alarm for ammonia emission and preliminary results of particle detection in diesel exhausts and particles from a power plant and a steel plant. [Copyright &y& Elsevier] |
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Copyright of Sensors & Actuators B: Chemical is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |
