Evidence map›Paper›PMID 40091341›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Dual-Atom Catalyst Au@S-rGO for Rapid and Highly Sensitive Electrochemical Detection of Fentanyl in Serum.

Meng Li, ZhiJin Fan, Qiuxia Gao, Ying He, Anyun Xu, Zhaofeng Gu, Shixiong Wang, Huiping Bai, Yuhui Liao, Ruilin Zhang

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Interpol review of forensic drug chemistry, 2022-2025.Forensic science international. Synergy · 2026
    Review
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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

10 authors.

Meng LiSchool of Forensic Medicine, NHC Key Laboratory of Drug Addiction Medicine, Institute for Engineering Medicine, Kunming Medical University, Kunming, Kunming, Yunnan, 650500, China.
ZhiJin FanSchool of Forensic Medicine, NHC Key Laboratory of Drug Addiction Medicine, Institute for Engineering Medicine, Kunming Medical University, Kunming, Kunming, Yunnan, 650500, China.
Qiuxia GaoSchool of Forensic Medicine, NHC Key Laboratory of Drug Addiction Medicine, Institute for Engineering Medicine, Kunming Medical University, Kunming, Kunming, Yunnan, 650500, China.
Ying HeSchool of Material and Energy, Institute of International Rivers and Eco-Security, School of Chemical Science and Technology, Yunnan University, Kunming, Yunnan, 650091, China.
Anyun XuSchool of Material and Energy, Institute of International Rivers and Eco-Security, School of Chemical Science and Technology, Yunnan University, Kunming, Yunnan, 650091, China.
Zhaofeng GuSchool of Material and Energy, Institute of International Rivers and Eco-Security, School of Chemical Science and Technology, Yunnan University, Kunming, Yunnan, 650091, China.
Shixiong WangSchool of Material and Energy, Institute of International Rivers and Eco-Security, School of Chemical Science and Technology, Yunnan University, Kunming, Yunnan, 650091, China.
Huiping BaiSchool of Material and Energy, Institute of International Rivers and Eco-Security, School of Chemical Science and Technology, Yunnan University, Kunming, Yunnan, 650091, China.
Yuhui LiaoSchool of Forensic Medicine, NHC Key Laboratory of Drug Addiction Medicine, Institute for Engineering Medicine, Kunming Medical University, Kunming, Kunming, Yunnan, 650500, China.ORCID https://orcid.org/0000-0003-4702-9516
Ruilin ZhangSchool of Forensic Medicine, NHC Key Laboratory of Drug Addiction Medicine, Institute for Engineering Medicine, Kunming Medical University, Kunming, Kunming, Yunnan, 650500, China.

Funding

First-Class Discipline Team of Kunming Medical University 2024XKTDYS10National Natural Science Foundation of China 22466038National Natural Science Foundation of China 82260654Natural Science Foundation of Yunnan Province 202201AT070256Natural Science Foundation of Yunnan Province 202303AC100021Practice Innovation Fund project of professional degree graduate students of Yunnan University ZC-24249042Yunnan Revitalization Talent Support Program GrantNo.YDYCQNRC-2022-0303
6 · The paper itself

Abstract

Fentanyl is a highly lethal emerging drug that requires urgent rapid trace detection. In this work, high-sensitivity detection of fentanyl is achieved by Au- and S-doped reduced graphene oxide (Au@S-rGO). Spherical electron microscopy revealed that Au and S existed in an atomically dispersed state. The possible configurations of S in Au@S-rGO, as well as the effects of different doping positions on the electron density of Au, are analyzed by Density functional theory (DFT) simulations. The co-modification of metal and nonmetal atoms significantly improves the catalytic activity of the electrode. The optimal electrode delivers a good linear relationship for fentanyl concentrations from 0.0291 to 38.2 µmol L-1, with a detection limit of 9.7 nmol L-1. The recovery rate of fentanyl in human serum ranged from 98.0% to 104%, demonstrating the precision of the sensor in real biological matrices. Furthermore, by employing rats in place of drug addicts, the coincidence rate between the electrochemical test results and the mass spectrometry results was 85.7% ~ 93.6%. Compared with mass spectrometry, the sensor offers faster, simpler, and more cost-effective onsite detection. In summary, the novel diatomic catalyst design looks excellent for fabricating electrochemical sensors for the rapid detection of fentanyl in real samples.

Indexed as

Electrochemical TechniquesFentanylGoldGraphiteAnimalsCatalysisElectrodesHumansLimit of DetectionRatsFentanylGoldgraphene oxideGraphiteanimal experiments on ratsAu@S‐rGOelectrochemicalfentanyl

Identifiers

PMID40091341
PMCPMC12079473

What OpenQuestion holds

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Registered trials

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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.