Remote Chemical Sensing by SERS with Self-Assembly Plasmonic Nanoparticle Arrays on a Fiber

dc.contributor.authorZhang, Xin
dc.contributor.authorZhang, Kunyi
dc.contributor.authorvon Bredow, Hasso
dc.contributor.authorMetting, Christopher
dc.contributor.authorAtanasoff, George
dc.contributor.authorBriber, Robert M.
dc.contributor.authorRabin, Oded
dc.date.accessioned2023-09-07T19:38:53Z
dc.date.available2023-09-07T19:38:53Z
dc.date.issued2022-01-25
dc.descriptionPartial funding for Open Access provided by the UMD Libraries' Open Access Publishing Fund.
dc.description.abstractAn optical fiber was modified at the tip with a self-assembled plasmonic metamaterial that acts as a miniature surface-enhanced Raman spectroscopy (SERS) substrate. This optical fiber-based device co-localizes the laser probe signal and the chemical analyte at a distance remote from the spectrometer, and returns the scattered light signal to the spectrometer for analysis. Remote SERS chemical detection is possible in liquids and in dried samples. Under laboratory conditions, the analyte SERS signal can be separated from the background signal of the fiber itself and the solvent. An enhancement factor greater than 35,000 is achieved with a monolayer of the SERS marker 4-aminothiophenol.
dc.description.urihttps://doi.org/10.3389/fphy.2021.752943
dc.identifierhttps://doi.org/10.13016/dspace/yzox-mixa
dc.identifier.citationZhang X, Zhang K, et al "Remote Chemical Sensing by SERS with Self-Assembly Plasmonic Nanoparticle Arrays on a Fiber" Frontiers in Physics, 9, 2022.
dc.identifier.urihttp://hdl.handle.net/1903/30431
dc.publisherFrontiers Media
dc.relation.isAvailableAtA. James Clark School of Engineeringen_us
dc.relation.isAvailableAtMaterials Science & Engineeringen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us
dc.titleRemote Chemical Sensing by SERS with Self-Assembly Plasmonic Nanoparticle Arrays on a Fiber
dc.typeArticle
local.equitableAccessSubmissionNo

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Zhang, X et al 2022
Size:
1.45 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.55 KB
Format:
Item-specific license agreed upon to submission
Description: