Room Temperature Real Air Highly Sensitive and Selective Detection of Ethanol and Ammonia Molecules Using Tin Nanoparticle-Functionalized Graphene Sensors
{"title":"Room Temperature Real Air Highly Sensitive and Selective Detection of Ethanol and Ammonia Molecules Using Tin Nanoparticle-Functionalized Graphene Sensors","authors":"Manoharan Muruganathan, Md. Zahidul Islam, Afsal Kareekunnan, Yosuke Onda, Masashi Hattori, Hiroshi Mizuta","doi":"10.1021/acsaelm.4c01308","DOIUrl":null,"url":null,"abstract":"Graphene, with its high surface area, is an important sensing material but lacks selectivity. As tin oxide has a higher selectivity for ethanol, we fabricated a graphene field-effect transistor (GFET) sensor functionalized with tin nanoparticles (Sn NPs) to enhance its selectivity and sensitivity for ethanol detection. Among 200 nm, 500 nm, 1 μm, and 2 μm channel sizes, 1 nm thickness Sn NPs functionalized on 200 nm GFET sensors exhibited high sensitivity and selective detection of ethanol and ammonia among five tested gases in a real air environment. Moreover, they demonstrated high sensitivity for ethanol and ammonia, detecting concentrations as low as 100 ppb at room temperature. The postfabrication thermal annealing facilitates the formation of Sn NP clusters and voids within the smaller 200 nm graphene channel, contributing to the sensor’s high sensitivity. Furthermore, the catalytic reaction of ethanol and ammonia molecules with oxygen molecules in the presence of Sn NPs releases electrons, which are reflected in n-doping in the graphene sensor measurements. The potential of this highly sensitive and selective ethanol and ammonia detection of graphene sensors can be utilized with machine learning techniques in the sensor cluster to identify different gases.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1021/acsaelm.4c01308","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Graphene, with its high surface area, is an important sensing material but lacks selectivity. As tin oxide has a higher selectivity for ethanol, we fabricated a graphene field-effect transistor (GFET) sensor functionalized with tin nanoparticles (Sn NPs) to enhance its selectivity and sensitivity for ethanol detection. Among 200 nm, 500 nm, 1 μm, and 2 μm channel sizes, 1 nm thickness Sn NPs functionalized on 200 nm GFET sensors exhibited high sensitivity and selective detection of ethanol and ammonia among five tested gases in a real air environment. Moreover, they demonstrated high sensitivity for ethanol and ammonia, detecting concentrations as low as 100 ppb at room temperature. The postfabrication thermal annealing facilitates the formation of Sn NP clusters and voids within the smaller 200 nm graphene channel, contributing to the sensor’s high sensitivity. Furthermore, the catalytic reaction of ethanol and ammonia molecules with oxygen molecules in the presence of Sn NPs releases electrons, which are reflected in n-doping in the graphene sensor measurements. The potential of this highly sensitive and selective ethanol and ammonia detection of graphene sensors can be utilized with machine learning techniques in the sensor cluster to identify different gases.