| Download | - View final version: Inkjet-printed paper-based surface enhanced Raman scattering (SERS) sensors for the detection of narcotics (PDF, 1.0 MiB)
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| DOI | Resolve DOI: https://doi.org/10.1557/s43580-022-00257-8 |
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| Author | Search for: Tay, Li-Lin1ORCID identifier: https://orcid.org/0000-0003-3408-3636; Search for: Poirier, Shawn1; Search for: Ghaemi, Ali1; Search for: Hulse, John1 |
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| Affiliation | - National Research Council of Canada. Metrology Research Centre
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| Format | Text, Article |
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| Abstract | Recent advances in inkjet-printing of advanced materials have provided a versatile platform for the rapid development and prototyping of sensor devices. We have recently demonstrated inkjet-printed surface enhanced Raman scattering (SERS) sensors on flexible substrates for the detection of variety of small molecules [Tay et al. in Front Chem 9:680556 (2021); Tay et al. in J Raman Spectrosc 52:563 (2020)]. These flexible SERS sensors have many advantages for performing point-of-sampling testing, among them liquid or aerosol filtration and swabbing capabilities. These simple sampling and separation features make these inkjet-printed paper-based sensors ideal for field applications. SERS detection of molecules with poor binding affinity towards the plasmonic surfaces of the sensors tends to be inefficient. A surface functionalization approach has been applied to SERS sensors to improve the molecule affinity and hence their detection sensitivity. In this paper, we investigate the optimization of SERS sensor fabrication to achieve optimal performance. Three performance criteria: diffuse reflectance, SERS background intensity from the as-printed blank sensors and SERS performance of sensors exposed to the benzenethiol reporter molecule, are characterized carefully to derive the optimal inkjet-printing conditions for producing the best performing SERS sensors. Additionally, we demonstrate the use of a simple potassium iodide functionalization scheme to improve the detection sensitivity for narcotics such as fentanyl by two orders of magnitude. |
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| Publication date | 2022-03-07 |
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| Publisher | Springer Nature |
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| Licence | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | b44a14c8-3458-4aad-bd58-57cdf6ebb3e9 |
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| Record created | 2023-07-28 |
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| Record modified | 2023-07-28 |
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