2026-10-13T07:55:37Z https://www.scidb.cn/oai

10.57760/sciencedb.07450 2023-02-16T10:07:17Z

2023-02-16 Multifunctional Fe3O4@mTiO(2)@noble metal composite NPs as ultrasensitive SERS substrates for trace detection doi:10.57760/sciencedb.07450 en Multifunctional materials have become the development trend of current material preparation. We reported a typical layer-by-layer method for the fabrication of multifunctional Fe3O4@mTiO2@noble metal triplex core-shell composite nanoparticle (NP), which is composed of a magnetic Fe3O4 particle as the core, a mesoporous TiO2 interlayer and a layer of Ag nanoparticles or Au nanorods as the shell. The obtained Fe3O4@mTiO2@noble metal composite NPs have shown excellent surface enhanced Raman scattering (SERS) sensitivity. Raman results present that the limit of detection (LOD) for crystal violet (CV), p-aminothiophnol (p-ATP) and p-mercaptobenzoic acid (p-MBA) of the Fe3O4@mTiO2@noble metal composite NPs substrates are as low as 1.0 × 10−9 M, 1.0 × 10−12 M and 1.0 × 10−9 M, respectively. In addition, the composite NPs also show high reproducibility and stability across the entire area with relative standard deviations (RSD) less than 15.00%. These highly sensitivity with good reproducibility can be attributed to the presence of plentiful “hot spots” produced by magnetic aggregation and target molecules enrichment by mesoporous TiO2 adsorption for practical application. Fe3O4@mTiO2@Ag composite NPs were used for thiram detection and the detection limit can reach to 5.0 × 10−8 M (about 0.012 ppm), which is lower than the maximal residue limit of 7 ppm in fruit prescribed by the U.S. Environmental Protection Agency. These multifunctional composite NPs provide easy separation, enrichment and trace detection of the analyte, exhibiting a great prospect as a potential SERS sensor in complex environments. Surface enhanced Raman scattering; Fe3O4@mTiO2@Ag; Fe3O4@mTiO2@Au NR; Thiram; Trace detection Hongyan Guo Aiwu Zhao Rujing Wang Qinye He Ping Chen Yuanyuan Wei Xiangyu Chen Haiying Hu Min Wang He Huang PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.1016/j.arabjc.2019.01.007 Science Data Bank