Digital Protocol for Chemical Analysis at Ultralow Concentrations by Surface-Enhanced Raman Scattering.
Carlos Diego L de AlbuquerqueRegivaldo G Sobral-FilhoRonei J PoppiAlexandre Guimarães BroloPublished in: Analytical chemistry (2017)
Single molecule surface-enhanced Raman spectroscopy (SM-SERS) has the potential to revolutionize quantitative analysis at ultralow concentrations (less than 1 nM). However, there are no established protocols to generalize the application of this technique in analytical chemistry. Here, a protocol for quantification at ultralow concentrations using SM-SERS is proposed. The approach aims to take advantage of the stochastic nature of the single-molecule regime to achieved lower limits of quantification (LOQ). Two emerging contaminants commonly found in aquatic environments, enrofloxacin (ENRO) and ciprofloxacin (CIPRO), were chosen as nonresonant molecular probes. The methodology involves a multivariate resolution curve fitting known as non-negative matrix factorization with alternating least-squares algorithm (NMF-ALS) to solve spectral overlaps. The key element of the quantification is to realize that, under SM-SERS conditions, the Raman intensity generated by a molecule adsorbed on a "hotspot" can be digitalized. Therefore, the number of SERS event counts (rather than SERS intensities) was shown to be proportional to the solution concentration. This allowed the determination of both ENRO and CIPRO with high accuracy and precision even at ultralow concentrations regime. The LOQ for both ENRO and CIPRO were achieved at 2.8 pM. The digital SERS protocol, suggested here, is a roadmap for the implementation of SM-SERS as a routine tool for quantification at ultralow concentrations.
Keyphrases
- raman spectroscopy
- single molecule
- gold nanoparticles
- sensitive detection
- living cells
- atomic force microscopy
- randomized controlled trial
- label free
- healthcare
- primary care
- machine learning
- quantum dots
- optical coherence tomography
- risk assessment
- small molecule
- particulate matter
- air pollution
- drinking water
- mass spectrometry
- computed tomography
- pseudomonas aeruginosa
- deep learning
- liquid chromatography
- climate change
- molecularly imprinted
- dual energy