title: Based on time and spatial-resolved SERS mapping strategies for detection of pesticides.
abstract: For the sensitive and convenient detection of pesticides, several sensing methods and materials have been widely explored. However, it is still a challenge to obtain sensitive, simple detection techniques for pesticides. Here, the simple and sensitive Time-resolved SERS mapping (T-SERS) and Spatial-resolved SERS mapping (S-SERS) are presented for detection of pesticides by using Au@Ag NPs as SERS substrate. The Time-resolved SERS mapping (T-SERS) is based on state translation nanoparticles from the wet state to the dry state to realize SERS measurements. During the SERS measurement, adhesive force drives the particles closer together and then average interparticle gap becomes smaller. Following, air then begins to intersperse into the liquid network and the particles are held together by adhesive forces at the solid-liquid-air interface. In the late stage of water evaporation, all particles are uniformly distributed. Thus, so called hotspots matrix that can hold hotspots between every two adjacent particles in efficient space with minimal polydispersity of particle size are achieved, accompanying the red-shift of surface plasmon peak and appearance of an optimal SPR resonated sharply with excitation wavelength. Here, we found that the T-SERS method exhibits the detection limits of 1-2 orders of magnitude higher than that of S-SERS. On the other hand, the T-SERS is very simple method with high detection sensitivity, better reproducibility (RSD=10.8%) and is beneficial to construction of a calibration curve in comparison with that of Spatial-resolved SERS mapping (S-SERS). Most importantly, as a result of its remarkable sensitivity, T-SERS mapping strategies have been applied to detection of several pesticides and the detect limit can down to 1nM for paraoxon, 0.5nM for sumithion. In short, T-SERS mapping measurement promises to open a market for SERS practical detection with prominent advantages.
authors.affiliation: Department of Chemistry, University of Science & Technology of China, Hefei, Anhui, 230026, China; Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China.
authors.forename: Bingbing
authors.initials: B
authors.lastname: Ma
authors.affiliation: Department of Chemistry, University of Science & Technology of China, Hefei, Anhui, 230026, China; Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China.
authors.forename: Pan
authors.initials: P
authors.lastname: Li
authors.affiliation: Department of Chemistry, University of Science & Technology of China, Hefei, Anhui, 230026, China; Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China. Electronic address: lbyang@iim.ac.cn.
authors.forename: Liangbao
authors.initials: L
authors.lastname: Yang
authors.affiliation: Department of Chemistry, University of Science & Technology of China, Hefei, Anhui, 230026, China; Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China. Electronic address: jhliu@iim.ac.cn.
authors.forename: Jinhuai
authors.initials: J
authors.lastname: Liu
mesh_terms: D032084:Citrus sinensis / Q000737:chemistry; D005278:Fenitrothion / Q000032:analysis; D005504:Food Analysis / Q000379:methods*; D005506:Food Contamination / Q000032:analysis; D006046:Gold; D057927:Hydrophobic and Hydrophilic Interactions; D027845:Malus / Q000737:chemistry; D053768:Metal Nanoparticles / Q000737:chemistry*; D010261:Paraoxon / Q000032:analysis; D010316:Particle Size; D010575:Pesticides / Q000032:analysis*; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D012834:Silver; D062211:Spatio-Temporal Analysis; D013059:Spectrum Analysis, Raman / Q000379:methods*
chemical_list: D010575:Pesticides; D012834:Silver; D006046:Gold; D010261:Paraoxon; D005278:Fenitrothion
keywords: Au@Ag nanoaprticles; Hydrophobic Treatments; SERS; SERS Mapping; pesticides