Extracting Optical Fiber Background from Surface-Enhanced Raman Spectroscopy Spectra Based on Bi-Objective Optimization Modeling.

Abstract

We propose a bi-objective optimization model for extracting optical fiber background from the measured surface-enhanced Raman spectroscopy (SERS) spectrum of the target sample in the application of fiber optic SERS. The model is built using curve fitting to resolve the SERS spectrum into several individual bands, and simultaneously matching some resolved bands with the measured background spectrum. The Pearson correlation coefficient is selected as the similarity index and its maximum value is pursued during the spectral matching process. An algorithm is proposed, programmed, and demonstrated successfully in extracting optical fiber background or fluorescence background from the measured SERS spectra of rhodamine 6G (R6G) and crystal violet (CV). The proposed model not only can be applied to remove optical fiber background or fluorescence background for SERS spectra, but also can be transferred to conventional Raman spectra recorded using fiber optic instrumentation.