| dc.contributor.author | Hassan Hosseinzadeh asl | |
| dc.contributor.author | Ghasem Tohidi | |
| dc.contributor.author | F. Movahedi | |
| dc.contributor.author | E. Hassannayebi | |
| dc.contributor.other | Department of Industrial Engineering, Faculty of Engineering, Islamic Azad University of Central Tehran Branch, Tehran, Iran | |
| dc.contributor.other | Department of Industrial Engineering, Faculty of Engineering, Islamic Azad University of Central Tehran Branch, Tehran, Iran; Corresponding author. | |
| dc.contributor.other | Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran | |
| dc.contributor.other | Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran | |
| dc.date.accessioned | 2021-11-26T04:24:34Z | |
| dc.date.available | 2025-10-02T04:17:24Z | |
| dc.date.issued | 01-12-2021 | |
| dc.identifier.issn | - | |
| dc.identifier.uri | http://www.sciencedirect.com/science/article/pii/S1319610321001769 | |
| dc.description.abstract | In this paper, the performance of the benzene gas detection sensor in the air is optimized by an experimental design method. So in this work, Nanostructured thin films of ZnO and Zn2SnO4 were prepared in wurtzite form via a facile atmospheric pressure chemical vapor deposition (CVD) method, using metallic zinc and tin precursors. Characterization of the gas sensor was performed by using Powder X-ray diffraction (PXRD), scanning electron microscopy (SEM) and surface area analysis (using BET method). The results show that Zn2SnO4 nanowire network exhibited good sensitivity at 299 °C temperature to low concentrations (100 ppb) of Benzene which can be potentially used as a resistive gas sensor. Ultimately modeling and optimization of Zn2SnO4 sensor performance to detect benzene by surface response method in design expert11 software has been done. Also, the effect of each parameter on the sensitivity of the sensor was analyzed by analysis of variance (ANOVA). Moreover, the performance efficiency of the Zn2SnO4 sensor is estimated with the reliable correlations obtained in the modeling. The two parameters selected to optimize the performance of the gas sensor include the operating temperature of the sensor and the concentration of the sensor. Comparison of the modeling results and the predicted values for the sensor sensitivity to benzene shows 97.60% excellent agreement. | |
| dc.format | - | |
| dc.language.iso | EN | |
| dc.publisher | Elsevier | |
| dc.relation.uri | ['https://www.journals.elsevier.com/the-cell-surface', 'https://www.elsevier.com/journals/the-cell-surface/2468-2330/guide-for-authors', 'https://www.elsevier.com/authors/open-access/choice#waivers'] | |
| dc.rights | ['CC BY', 'CC BY-NC-ND', 'CC BY-NC'] | |
| dc.subject | ['cell surfaces', 'extracellular polymers', 'plasma membranes', 'cell walls', 'Cytology', 'QH573-671'] | |
| dc.subject.lcc | Chemistry | |
| dc.title | Optimization and modeling of Zn2SnO4 sensitivity as gas sensor for detection benzene in the air by using the response surface methodology | |
| dc.type | Article | |
| dc.description.keywords | Zn2SnO4 | |
| dc.description.keywords | Benzene | |
| dc.description.keywords | Gas sensor | |
| dc.description.keywords | Design Expert11 | |
| dc.description.keywords | Optimization | |
| dc.description.pages | - | |
| dc.description.doi | 10.1016/j.jscs.2021.101371 | |
| dc.title.journal | Journal of Saudi Chemical Society | |
| dc.identifier.e-issn | - | |
| dc.identifier.oai | oai:doaj.org/journal:189c8031cce84be9877b0b27ea1dfc09 | |
| dc.journal.info | Volume 25, Issue 12 | |
