Optimization of Working Conditions for Perovskite-Based Gas Sensor Devices by Multiregression Analysis
Environmental degradation and resource depletion drive scientific research priorities to develop technologies for sustainable productive systems. Among them, chemical sensing technology plays a key role for regulating energetic, ecological, and productive efficiency by monitoring and controlling the...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
|
| Series: | Journal of Nanotechnology |
| Online Access: | http://dx.doi.org/10.1155/2019/4628765 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832554867826098176 |
|---|---|
| author | Fabio Zaza Vanessa Pallozzi Emanuele Serra |
| author_facet | Fabio Zaza Vanessa Pallozzi Emanuele Serra |
| author_sort | Fabio Zaza |
| collection | DOAJ |
| description | Environmental degradation and resource depletion drive scientific research priorities to develop technologies for sustainable productive systems. Among them, chemical sensing technology plays a key role for regulating energetic, ecological, and productive efficiency by monitoring and controlling the industrial processes. Semiconducting metal oxide sensors are particularly attractive technology because of their simplicity in function, small size, and projected low cost. The aim of this work is to synthesize Ti-substituted lanthanum ferrite perovskite, LaFe0.8Ti0.2O3, in order to develop a resistive sensor device for monitoring carbon monoxide. Since sensor performances are affected by experimental factors, such as temperature, target gas concentration, and gas flow rate, the aim of the authors was to define the optimum working condition by performing multiple regression analyses. The investigated ranges of operating conditions were temperature from 300 to 480°C, carbon monoxide concentration from 100 to 200 ppm, and inlet-gas flow rate from 40 to 100 cm3/min. The results confirm that the applied systematic analysis is a powerful method for studying the direct and indirect effects of every experimental factor on sensor performance and for computing mathematical models with predictive ability, that are useful tools for defining the optimum chemiresistors’ operating conditions. In addition, mathematical models are able to be used as multiple-factor surface calibration for restive gas sensor devices. |
| format | Article |
| id | doaj-art-e3f4a2414f184421ad65f1656eac792d |
| institution | Kabale University |
| issn | 1687-9503 1687-9511 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Nanotechnology |
| spelling | doaj-art-e3f4a2414f184421ad65f1656eac792d2025-02-03T05:50:24ZengWileyJournal of Nanotechnology1687-95031687-95112019-01-01201910.1155/2019/46287654628765Optimization of Working Conditions for Perovskite-Based Gas Sensor Devices by Multiregression AnalysisFabio Zaza0Vanessa Pallozzi1Emanuele Serra2ENEA-Casaccia Research Centre, Via Anguillarese 301, 00123 Rome, ItalyTuscia University, Via S. Camillo de Lellis, 01100 Viterbo, ItalyENEA-Casaccia Research Centre, Via Anguillarese 301, 00123 Rome, ItalyEnvironmental degradation and resource depletion drive scientific research priorities to develop technologies for sustainable productive systems. Among them, chemical sensing technology plays a key role for regulating energetic, ecological, and productive efficiency by monitoring and controlling the industrial processes. Semiconducting metal oxide sensors are particularly attractive technology because of their simplicity in function, small size, and projected low cost. The aim of this work is to synthesize Ti-substituted lanthanum ferrite perovskite, LaFe0.8Ti0.2O3, in order to develop a resistive sensor device for monitoring carbon monoxide. Since sensor performances are affected by experimental factors, such as temperature, target gas concentration, and gas flow rate, the aim of the authors was to define the optimum working condition by performing multiple regression analyses. The investigated ranges of operating conditions were temperature from 300 to 480°C, carbon monoxide concentration from 100 to 200 ppm, and inlet-gas flow rate from 40 to 100 cm3/min. The results confirm that the applied systematic analysis is a powerful method for studying the direct and indirect effects of every experimental factor on sensor performance and for computing mathematical models with predictive ability, that are useful tools for defining the optimum chemiresistors’ operating conditions. In addition, mathematical models are able to be used as multiple-factor surface calibration for restive gas sensor devices.http://dx.doi.org/10.1155/2019/4628765 |
| spellingShingle | Fabio Zaza Vanessa Pallozzi Emanuele Serra Optimization of Working Conditions for Perovskite-Based Gas Sensor Devices by Multiregression Analysis Journal of Nanotechnology |
| title | Optimization of Working Conditions for Perovskite-Based Gas Sensor Devices by Multiregression Analysis |
| title_full | Optimization of Working Conditions for Perovskite-Based Gas Sensor Devices by Multiregression Analysis |
| title_fullStr | Optimization of Working Conditions for Perovskite-Based Gas Sensor Devices by Multiregression Analysis |
| title_full_unstemmed | Optimization of Working Conditions for Perovskite-Based Gas Sensor Devices by Multiregression Analysis |
| title_short | Optimization of Working Conditions for Perovskite-Based Gas Sensor Devices by Multiregression Analysis |
| title_sort | optimization of working conditions for perovskite based gas sensor devices by multiregression analysis |
| url | http://dx.doi.org/10.1155/2019/4628765 |
| work_keys_str_mv | AT fabiozaza optimizationofworkingconditionsforperovskitebasedgassensordevicesbymultiregressionanalysis AT vanessapallozzi optimizationofworkingconditionsforperovskitebasedgassensordevicesbymultiregressionanalysis AT emanueleserra optimizationofworkingconditionsforperovskitebasedgassensordevicesbymultiregressionanalysis |