A new model for quantifying nanoparticle concentration using SERS supported by multi-modal mass spectrometry

Aristea Anna Leventi, Kharmen Billimoria, Dorota Bartczak, Stacey Laing, Heidi Goenaga-Infante, Karen Faulds, Duncan Graham

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
10 Downloads (Pure)

Abstract

Elucidation of the underlying mechanisms behind biological processes is of great importance for disease detection and ef-fective therapeutics. Surface enhanced Raman scattering (SERS) has been widely explored as a non-destructive technique for this purpose. The power of this technique originates from the specificity of molecular information acquired by Raman scattering in combination with the high sensitivity obtained due to the surface enhancing properties of plasmonic nanostruc-tures. However, the capability of absolute quantitation of the number of nanoparticles from the SERS response remains a challenge due to the variability of enhancements produced and the lack of well characterized standards for calibration. Here, we show for the first time the development of a new 2D quantitation model to allow calibration of the SERS response against the absolute concentration of SERS nanotags as characterized by single particle inductively coupled plasma mass spectrometry (spICP-MS). A novel printing approach was adopted to prepare gelatin-based calibration standards containing the SERS nanotags, which consisted of gold nanoparticles (AuNPs) and the Raman reporter 1,2-bis(4-pyridyl)ethylene (BPE). spICP-MS was used to characterize the SERS nanotags for their Au mass concentration and particle number concen-tration before preparation of gelatin-printed standards. Results from laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-ToF-MS) imaging at a spatial resolution of 5 μm, demonstrated the homogeneous distribution of BPE-AuNPs (between-line RSD
Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalAnalytical Chemistry
Early online date26 Jan 2023
DOIs
Publication statusE-pub ahead of print - 26 Jan 2023

Keywords

  • nanoparticle concentration
  • SERS
  • multi-modal mass spectrometry

Fingerprint

Dive into the research topics of 'A new model for quantifying nanoparticle concentration using SERS supported by multi-modal mass spectrometry'. Together they form a unique fingerprint.

Cite this