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

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.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2025-03-16
DOI
https://doi.org/10.1002/advs.202500430
Citations
41
Primary Topic
Electrochemical sensors and biosensors
Type
article
Field-Weighted Citation Impact
29.95

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Qiuxia Gao, Ying He, Shixiong Wang, Yuhui Liao et al.
41 citations
Advanced Science
Electrochemical sensors and biosensors
29.95
article

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

Qiuxia Gao, Ying He, Shixiong Wang, Yuhui Liao, Zhaofeng Gu, Zhixuan Fan, Meng Li, Ruilin Zhang, Huiping Bai, Anyun Xu
article en
41 citations

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.

Advanced ScienceVol. 12(18)
Yunnan University (CN), Kunming Medical University (CN), Yunnan Institute of Environmental Sciences (CN)
National Natural Science Foundation of China, Natural Science Foundation of Yunnan Province
Good health and well-being
Openalex Percentile: Top 0%
Electrochemical sensors and biosensors
29.95
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.