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

• TR-EC-SERS determination of nicotine in e-liquids. • Sensitivity and reproducibility are improved by pretreatment of the electrode. • Study of different electrolytic media for electrosynthesis of SERS substrates. • Trilinear data allow the detection of interfering compounds using PARAFAC analysis. 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 electrochemical 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.

Authors

Publication Details

Journal
Microchemical Journal
Published
2024-12-21
DOI
https://doi.org/10.1016/j.microc.2024.112551
Citations
4
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
Field-Weighted Citation Impact
0.74

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article

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

Álvaro Colina, Aránzazu Heras, Martin Perez-Estebañez, Luis Romay
4 citations
Microchemical Journal
Advanced Chemical Sensor Technologies
0.74
article

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

Álvaro Colina, Aránzazu Heras, Martin Perez-Estebañez, Luis Romay
article en
4 citations

Abstract

• TR-EC-SERS determination of nicotine in e-liquids. • Sensitivity and reproducibility are improved by pretreatment of the electrode. • Study of different electrolytic media for electrosynthesis of SERS substrates. • Trilinear data allow the detection of interfering compounds using PARAFAC analysis. 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 electrochemical 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.

Microchemical JournalVol. 208
Ministerio de Ciencia, Innovación y Universidades, Ministerio de Ciencia e Innovación, Consejería de Educación, Junta de Castilla y León, European Regional Development Fund, Agencia Estatal de Investigación
Openalex Percentile: Top 31%
Advanced Chemical Sensor Technologies
0.74
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