ChemNanoMat

Single‐Atom Iron Nanozyme‐based Colorimetric and Photothermal Dual‐Mode Sensor Array for Sulfur‐containing Metal Salts Identification

Can Wang 1, 2
Lifeng Wang 1, 2, 3
Wendong Liu 1, 2
Zhipeng Xu 4, 5
Yizhong Lu 2
1
 
University of Jinan School of Materials Science and Engineering CHINA
2
 
School of Materials Science and Engineering University of Jinan Jinan 250022 China
3
 
SICC Co., Ltd. Jinan 250000 China
4
 
University of Jinan Information Management Office CHINA
5
 
Information Management Office University of Jinan Jinan 250022 China
Publication typeJournal Article
Publication date2025-03-20
Journal: ChemNanoMat
scimago Q2
wos Q3
SJR0.743
CiteScore6.1
Impact factor2.6
ISSN2199692X
Abstract

The simultaneous detection and effective identification of various sulfur‐containing metal salts (SCMs) is essential for food safety and public health, but it continues to pose significant challenges. In this study, we introduced an innovative iron‐based single‐atom nanozyme (Fe−N/C) sensor array. This sensor array integrates both colorimetric and photothermal dual modes and is aimed at accurately distinguishing various SCMs. Fe−N/C catalyst is capable of facilitating the conversion of 3,3′,5,5′‐tetramethylbenzidine (TMB) into oxidized TMB (oxTMB) by activating O2, which can turn the colorimetric signal into a photothermal signal under external infrared laser irradiation, allowing for the quantitative detection of SCMs. By leveraging this dual‐mode detection technology, the detection range for SCMs extends from 5 to 150 μM. The limits of detection (LODs) are 0.688–0.887 μM for the colorimetric method and 0.011–8.5 μM for the photothermal method. Different SCMs can suppress oxTMB to varying extents, generating distinct colorimetric and photothermal dual‐mode response changes on the sensor array, successfully identifying five types of SCMs. Additionally, it has been utilized for detecting and distinguishing real food samples, including grape wine, pure milk, and raw egg. This innovative design offers new ideas and methods for efficient detection.

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