Cited 4 time in
Unraveling the highly sensitive-selective NO2 sensing characteristics of perfect and agglomerated Zn2SnO4 octahedrons
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim, Deasung | - |
| dc.contributor.author | Tran, Thanh Thao | - |
| dc.contributor.author | Bhatt, Vishwa | - |
| dc.contributor.author | Nguyen, Ha Trang | - |
| dc.contributor.author | Kim, Joondong | - |
| dc.contributor.author | Kumar, Manjeet | - |
| dc.contributor.author | Yun, Ju-Hyung | - |
| dc.date.accessioned | 2024-08-08T08:31:03Z | - |
| dc.date.available | 2024-08-08T08:31:03Z | - |
| dc.date.issued | 2023-10 | - |
| dc.identifier.issn | 2213-2929 | - |
| dc.identifier.issn | 2213-3437 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/20491 | - |
| dc.description.abstract | The increasing fears over the worsening condition of the environment due to pollution caused by urbanization and modernization have turned our attention toward the field of gas sensors. Highly selective, stable, and sensitive gas sensors are getting huge attention due to their applicability to monitoring environmental conditions continuously as well as protecting humans, and other lives from the hazardous effect of air pollutants on this planet. In this work, we synthesized Zn2SnO4 octahedrons by a simple hydrothermal method with various reaction times (6 h, 12 h, and 18 h). The gas sensors based on three kinds of Zn2SnO4 samples are fabricated and the effect of synthesis conditions (reaction time) on their sensing performance is studied. In the results, the Zn2SnO4 sample synthesized in 12 h exhibits the most perfect and smoothed octahedral shape with a size of around 500 nm. Additionally, it shows the highest sensor response value of ∼150 at 250ºC with a gas pumping concentration of 40 ppm, followed by the third and first samples with the value of ∼124 and ∼24, respectively. Such improved NO2 gas sensing characteristics may be ascribed to the octahedral morphology of the synthesized Zn2SnO4 as well as the increased contact area between Zn2SnO4 and target chemical input which might be a promising candidate for selectively detecting the traces of NO2 gas. © 2023 Elsevier Ltd | - |
| dc.format.extent | 11 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | Elsevier Ltd | - |
| dc.title | Unraveling the highly sensitive-selective NO2 sensing characteristics of perfect and agglomerated Zn2SnO4 octahedrons | - |
| dc.type | Article | - |
| dc.publisher.location | 네델란드 | - |
| dc.identifier.doi | 10.1016/j.jece.2023.110648 | - |
| dc.identifier.scopusid | 2-s2.0-85167833565 | - |
| dc.identifier.wosid | 001091663800001 | - |
| dc.identifier.bibliographicCitation | Journal of Environmental Chemical Engineering, v.11, no.5, pp 1 - 11 | - |
| dc.citation.title | Journal of Environmental Chemical Engineering | - |
| dc.citation.volume | 11 | - |
| dc.citation.number | 5 | - |
| dc.citation.startPage | 1 | - |
| dc.citation.endPage | 11 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Engineering | - |
| dc.relation.journalWebOfScienceCategory | Engineering, Environmental | - |
| dc.relation.journalWebOfScienceCategory | Engineering, Chemical | - |
| dc.subject.keywordPlus | GRAPHENE OXIDE | - |
| dc.subject.keywordPlus | GAS SENSORS | - |
| dc.subject.keywordPlus | PERFORMANCE | - |
| dc.subject.keywordPlus | NANOPARTICLES | - |
| dc.subject.keywordPlus | ZNO | - |
| dc.subject.keywordAuthor | Hydrothermal method | - |
| dc.subject.keywordAuthor | NO<sub>2</sub> gas sensor | - |
| dc.subject.keywordAuthor | Zn<sub>2</sub>SnO<sub>4</sub> octahedron | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
30, Pildong-ro 1-gil, Jung-gu, Seoul, 04620, Republic of Korea+82-2-2260-3114
Copyright(c) 2023 DONGGUK UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
