Evidence map›Paper›PMID 35696111›Full record

ArticleJournal of food and drug analysis2020

Rapid identification of nicotine in electronic cigarette liquids based on surface-enhanced Raman scattering.

Jun-Yi Chien, Yong-Chun Gu, Hsin-Mei Tsai, Chun-Hao Liu, Chia-Yuan Yen, Yuh-Lin Wang, Juen-Kai Wang, Chi-Hung Lin

Abstract read
In one paragraph

Article in Journal of food and drug analysis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Emerging trends in functional materials for electrochemical sensors in nicotine determination.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jun-Yi ChienInstitute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan.
Yong-Chun GuInstitute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan.
Hsin-Mei TsaiInstitute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan.
Chun-Hao LiuDepartment of Health, New Taipei City Government, New Taipei City, Taiwan.
Chia-Yuan YenDepartment of Health, New Taipei City Government, New Taipei City, Taiwan.
Yuh-Lin WangInstitute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan.
Juen-Kai WangInstitute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan.
Chi-Hung LinDepartment of Health, New Taipei City Government, New Taipei City, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nicotine-containing electronic cigarette liquid (e-liquid) is prohibited in many countries, creating requirements for rapid detection approaches for on-site inspection or screening for large amounts of samples. Here, we demonstrate a simple way to identify nicotine using surface-enhanced Raman scattering (SERS) with substrates made of silver nanoparticle arrays imbedded in anodic aluminum oxide nanochannels (Ag/AAO). Compared with the reported colloidal nanoparticle-based SERS, that required serial dilutions to enable colloid aggregation in the viscous e-liquid, a small amount of undiluted e-liquid sample can be directly added onto our solid-phase Ag/AAO substrate without any pre-treatment. The sensitivity of our SERS measurements is 2-3 orders of magnitude higher than that required for identification of nicotine in e-liquid, which is typically around 1000-18,000 ppm. Using such nanoparticle array-based SERS, we have tested 22 commercially available e-liquid products, using the corresponding gas chromatography-mass spectrometry (GC-MS) reports as the reference. The SERS measurements were done within one hour and successfully identified 20 samples. Only 2 samples showed SERS interference from ingredients that were not suitable for SERS analysis.

Identifiers

PMID35696111
PMCPMC9261865

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.