Evidence map›Paper›PMID 35270924›Full record

ArticleSensors (Basel, Switzerland)2022

Part-Per-Billion Level Chemical Sensing with a Gold-Based SERS-Active Substrate.

Tingting Zhang, Liyun Wu, Junchang Pei, Xuefeng Li, Haowen Li, Frank Inscore

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 59% of its field
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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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

6 authors at 1 institution in 1 country.

Tingting ZhangMicro Optical Instruments, Shenzhen 518118, China.
Liyun WuMicro Optical Instruments, Shenzhen 518118, China.
Junchang PeiInstitute of Criminal Science and Technology, Taizhou Public Security Bureau, Taizhou 225300, China.
Xuefeng LiInstitute of Criminal Science and Technology, Taizhou Public Security Bureau, Taizhou 225300, China.
Haowen LiMicro Optical Instruments, Shenzhen 518118, China.
Frank InscoreMicro Optical Instruments, Shenzhen 518118, China.ORCID 0000-0001-5143-291X
Shanghai Public Security Bureau · CN

Funding

Shenzhen Science and Technology Program KQTD20190929173954826
6 · The paper itself

Abstract

We used surface-enhanced Raman spectroscopy (SERS) for the rapid and sensitive detection and quantification of caffeine in solution. Such a technique incorporated into a portable device is finding wide applications in trace chemical analysis in various fields, including law enforcement, medicine, environmental monitoring, and food quality control. To realize such applications, we are currently developing portable and handheld trace chemical analyzers based on SERS, which are integrated with a sensor embedded with activated gold nanoparticles in a porous glass matrix. In this study, we used this gold SERS-active substrate to measure aqueous solutions of the drug caffeine as a test chemical to benchmark sensor performance by defining sensitivity (lowest measured concentration (LMC) and estimated limit of detection (LOD)), determining concentration dependence and quantification capabilities by constructing calibration curves; by evaluating the effects of pH values of 3, 7, and 11; and by examining the reproducibility of the SERS measurements. The results demonstrate that the SERS sensor is sensitive, with caffeine detected at an LMC of 50 parts per billion (ppb) with an LOD of 0.63 ppb. The results further show that the sensor is very stable and can be used to make reproducible measurements, even under extremely acidic to basic pH conditions. Vibrational assignments of all observed SERS peaks are made and reported for the first time for caffeine on a gold substrate.

Indexed as

GoldMetal NanoparticlesLimit of DetectionReproducibility of ResultsSpectrum Analysis, RamanGoldAu nanoparticlesSERSsurface-enhanced Raman sensortrace chemical detection

Identifiers

PMID35270924
PMCPMC8915063
OpenAlexW4214731647

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.