Determination of nicotine in e-liquids by electrochemical generation of surface-enhanced Raman scattering substrates

Quantitative methods using surface-enhanced Raman scattering (SERS) for analysis in complex matrices are very attractive due to the high sensitivity and selectivity of this technique. In this work, a novel time-resolved elec trochemical surface-enhanced Raman scattering (TR-EC-SERS) analytical metho...

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Detalles Bibliográficos
Autores: Romay García, Luis, Pérez Estébanez, Martín, Heras Vidaurre, Aránzazu, Colina Santamaría, Álvaro
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Universidad de Burgos (UBU)
Repositorio:Repositorio Institucional de la Universidad de Burgos (RIUBU)
OAI Identifier:oai:riubu.ubu.es:10259/10194
Acceso en línea:http://hdl.handle.net/10259/10194
Access Level:acceso abierto
Palabra clave:SERS
Spectroelectrochemistry
PARAFAC
Nicotine
E-liquid
Química analítica
Electroquímica
Chemistry, Analytic
Electrochemistry
Descripción
Sumario:Quantitative methods using surface-enhanced Raman scattering (SERS) for analysis in complex matrices are very attractive due to the high sensitivity and selectivity of this technique. In this work, a novel time-resolved elec trochemical surface-enhanced Raman scattering (TR-EC-SERS) analytical method has been developed for the determination of nicotine in e-liquids of electronic cigarettes. One of the main challenges of SERS is its inherent lack of reproducibility. Here, this limitation was mitigated by employing an electrochemical pre-treatment step to generate a homogeneous distribution of silver nanoparticles (Ag-NPs) on a silver screen-printed electrode. The enhanced Raman scattering induced by the Ag-NPs enabled the detection of nicotine at nanomolar levels. The high sensitivity of the method allowed the quantitative analysis of diluted e-liquid samples, mitigating potential interferences from other components present in these complex matrices. Moreover, TR-EC-SERS, coupled with parallel factor analysis (PARAFAC), demonstrated the capability of trilinear spectroelectrochemistry data not only to detect nicotine but also to identify potential interfering compounds without prior knowledge of their spectral signatures. This multivariate approach offers significant potential for the detection of outliers in complex samples.