Machine learning for rapid quantification of trace analyte molecules using SERS and flexible plasmonic paper substrates
Reshma Beeram, Dipanjan Banerjee, Linga Murthy Narlagiri, S. Venugopal Rao
Abstract
error of 0.9629 for CV and 0.9472 for PA. In conjunction with a portable Raman spectrometer and a computation time of less than <10 s, we believe that this is an affordable and rapid method for quantification of analytes using the SERS technique.
Topics & Concepts
AnalytePlasmonTRACE (psycholinguistics)Substrate (aquarium)MoleculeNanotechnologyChemistryMaterials scienceComputer scienceChromatographyOptoelectronicsOrganic chemistryLinguisticsOceanographyPhilosophyGeologyGold and Silver Nanoparticles Synthesis and ApplicationsBiosensors and Analytical DetectionAdvanced biosensing and bioanalysis techniques