Simulation Analysis of Surface Enhanced Raman Scattering Properties for the Detection of Furfural Dissolved in Transformer Oil

Surface-enhanced Raman scattering (SERS) has been proposed for the application in the detection of furfural concentration in transformer oil recently. However, the intensity changes of SERS signals, which generate from various vibration modes of furfural molecule, are still unable to be explained well. In this paper, the simulation analysis of the adsorption mode of furfural on the metal surface and its SERS characteristics has been analyzed based on the density functional theory. Firstly, the simulation model of furfural molecule and silver cluster, whose selections of the silver atomic number and the furfural molecule adsorption position had been optimized, was built by GaussView and Gaussian software. Then, SERS signals from different vibration modes of furfural molecule and silver cluster were calculated and identified. By comparing theoretical calculation results with measured furfural spectra, the mode of furfural molecule adsorbed on metal surface was determined. These results can provide theoretical basis for the in-situ SERS detection of furfural dissolved in transformer oil.