Alstrøm, Tommy Sonne

Boisen, Anja

Larsen, Jan

Rindzevicius, Tomas

Schmidt, Mikkel Nørgaard

Raman spectroscopy is a well-known analytical technique for identifying and analyzing chemical species. Since Raman scattering is a weak effect, surface-enhanced Raman spectroscopy (SERS) is often employed to amplify the signal. SERS signal surface mapping is a common method for detecting trace amounts of target molecules. Since the method produce large amounts of data and, in the case of very low concentrations, low signal-to-noise (SNR) ratio, ability to extract relevant spectral features is crucial. We propose a pseudo-Voigt model as a constrained source separation model, that is able to directly and reliably identify the Raman modes, with overall performance similar to the state of the art non-negative matrix factorization approach. However, the model provides better interpretation and is a step towards enabling the use of SERS in detection of trace amounts of molecules in real-life settings

Online Research Database In Technology

A pseudo-Voigt component model for high-resolution recovery of constituent spectra in Raman spectroscopy

Tommy S. Alstrom

Mikkel N. Schmidt

Tomas Rindzevicius

Anja Boisen

Jan Larsen

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http://orbit.dtu.dk/ws/files/130448623/Untitled.pdf

A pseudo-Voigt component model for high-resolution recovery of constituent spectra in Raman spectroscopy

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Online Research Database In Technology

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