FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4233190246> ?p ?o ?g. }

• W4233190246 endingPage "193" @default.
• W4233190246 startingPage "181" @default.
• W4233190246 abstract "Purpose Smart sensors based on graphene field effect transistor (GFET) and biological receptors are regarded as a promising nanomaterial that could be the basis for future generation of low-power, faster, selective real-time monitoring of target analytes and smaller electronics. So, the purpose of this paper is to provide details of sensors based on selective nanocoatings by combining trinitrotoluene (TNT) receptors (Trp-His-Trp) bound to conjugated polydiacetylene polymers on a graphene channel in GFET for detecting explosives TNT. Design/methodology/approach Following an introduction, this paper describes the way of manufacturing of the GFET sensor by using investigation methods for transferring graphene sheet from Cu foil to target substrates, which is functionalized by the TNT peptide receptors, to offer a system which has the capability of answering the presence of related target molecules (TNT). Finally, brief conclusions are drawn. Findings In a word, shortly after graphene discovery, it has been explored with a variety of methods gradually. Because of its exceptional electrical properties (e.g. extremely high carrier mobility and capacity), electrochemical properties such as high electron transfer rate and structural properties, graphene has already showed great potential and success in chemical and biological sensing fields. Therefore, the authors used a biological receptor with a field effect transistor (FET) based on graphene to fabricate sensor for achieving high sensitivity and selectivity that can detect explosive substances such as TNT. The transport property changed compared to that of the FET made by intrinsic graphene, that is, the Dirac point position moved from positive Vg to negative Vg, indicating the transition of graphene from p-type to n-type after annealing in TNT, and the results show the bipolar property change of GFET with the TNT concentration and the possibility to develop a robust, easy-to-use and low-cost TNT detection method for performing a sensitive, reliable and semi-quantitative detection in a wide detection range. Originality/value In this timeframe of history, TNT is a common explosive used in both military and industrial settings. Its convenient handling properties and explosive strength make it a common choice in military operations and bioterrorism. TNT and other conventional explosives are the mainstays of terrorist bombs and the anti-personnel mines that kill or injure more than 15,000 people annually in war-torn countries. In large, open-air environments, such as airports, train stations and minefields, concentrations of these explosives can be vanishingly small – a few parts of TNT, for instance, per trillion parts of air. That can make it impossible for conventional bomb and mine detectors to detect the explosives and save lives. So, in this paper, the authors report a potential solution with design and manufacture of a GFET sensor based on a biological receptor for real-time detection of TNT explosives specifically." @default.
• W4233190246 created "2022-05-12" @default.
• W4233190246 creator A5003391107 @default.
• W4233190246 creator A5021511745 @default.
• W4233190246 creator A5028657805 @default.
• W4233190246 creator A5063834771 @default.
• W4233190246 date "2018-03-19" @default.
• W4233190246 modified "2023-09-26" @default.
• W4233190246 title "Design and manufacture of TNT explosives detector sensors based on GFET" @default.
• W4233190246 cites W1967897514 @default.
• W4233190246 cites W1980516378 @default.
• W4233190246 cites W1981430594 @default.
• W4233190246 cites W1998514112 @default.
• W4233190246 cites W2007377252 @default.
• W4233190246 cites W2020378474 @default.
• W4233190246 cites W2021145393 @default.
• W4233190246 cites W2027020123 @default.
• W4233190246 cites W2043177279 @default.
• W4233190246 cites W2049142984 @default.
• W4233190246 cites W2049536015 @default.
• W4233190246 cites W2056562591 @default.
• W4233190246 cites W2058122340 @default.
• W4233190246 cites W2065569053 @default.
• W4233190246 cites W2066569554 @default.
• W4233190246 cites W2071116105 @default.
• W4233190246 cites W2078508078 @default.
• W4233190246 cites W2092188263 @default.
• W4233190246 cites W2097024925 @default.
• W4233190246 cites W2121990892 @default.
• W4233190246 cites W2157563979 @default.
• W4233190246 cites W2327832547 @default.
• W4233190246 cites W2330908373 @default.
• W4233190246 cites W2528447582 @default.
• W4233190246 doi "https://doi.org/10.1108/sr-08-2017-0167" @default.
• W4233190246 hasPublicationYear "2018" @default.
• W4233190246 type Work @default.
• W4233190246 citedByCount "5" @default.
• W4233190246 countsByYear W42331902462019 @default.
• W4233190246 countsByYear W42331902462020 @default.
• W4233190246 crossrefType "journal-article" @default.
• W4233190246 hasAuthorship W4233190246A5003391107 @default.
• W4233190246 hasAuthorship W4233190246A5021511745 @default.
• W4233190246 hasAuthorship W4233190246A5028657805 @default.
• W4233190246 hasAuthorship W4233190246A5063834771 @default.
• W4233190246 hasConcept C112613896 @default.
• W4233190246 hasConcept C119599485 @default.
• W4233190246 hasConcept C127413603 @default.
• W4233190246 hasConcept C138631740 @default.
• W4233190246 hasConcept C145598152 @default.
• W4233190246 hasConcept C154238967 @default.
• W4233190246 hasConcept C159985019 @default.
• W4233190246 hasConcept C165801399 @default.
• W4233190246 hasConcept C171250308 @default.
• W4233190246 hasConcept C172385210 @default.
• W4233190246 hasConcept C178790620 @default.
• W4233190246 hasConcept C185592680 @default.
• W4233190246 hasConcept C192562407 @default.
• W4233190246 hasConcept C30080830 @default.
• W4233190246 hasConcept C521977710 @default.
• W4233190246 hasConceptScore W4233190246C112613896 @default.
• W4233190246 hasConceptScore W4233190246C119599485 @default.
• W4233190246 hasConceptScore W4233190246C127413603 @default.
• W4233190246 hasConceptScore W4233190246C138631740 @default.
• W4233190246 hasConceptScore W4233190246C145598152 @default.
• W4233190246 hasConceptScore W4233190246C154238967 @default.
• W4233190246 hasConceptScore W4233190246C159985019 @default.
• W4233190246 hasConceptScore W4233190246C165801399 @default.
• W4233190246 hasConceptScore W4233190246C171250308 @default.
• W4233190246 hasConceptScore W4233190246C172385210 @default.
• W4233190246 hasConceptScore W4233190246C178790620 @default.
• W4233190246 hasConceptScore W4233190246C185592680 @default.
• W4233190246 hasConceptScore W4233190246C192562407 @default.
• W4233190246 hasConceptScore W4233190246C30080830 @default.
• W4233190246 hasConceptScore W4233190246C521977710 @default.
• W4233190246 hasIssue "2" @default.
• W4233190246 hasLocation W42331902461 @default.
• W4233190246 hasOpenAccess W4233190246 @default.
• W4233190246 hasPrimaryLocation W42331902461 @default.
• W4233190246 hasRelatedWork W2056865455 @default.
• W4233190246 hasRelatedWork W2127658056 @default.
• W4233190246 hasRelatedWork W2284724371 @default.
• W4233190246 hasRelatedWork W2544365440 @default.
• W4233190246 hasRelatedWork W2794369563 @default.
• W4233190246 hasRelatedWork W2885410218 @default.
• W4233190246 hasRelatedWork W2891026875 @default.
• W4233190246 hasRelatedWork W3139655554 @default.
• W4233190246 hasRelatedWork W4283324009 @default.
• W4233190246 hasRelatedWork W2325624096 @default.
• W4233190246 hasVolume "38" @default.
• W4233190246 isParatext "false" @default.
• W4233190246 isRetracted "false" @default.
• W4233190246 workType "article" @default.