Statistical analysis for explosives detection system test and evaluation

The verification of trace explosives detection systems is often constrained to small sample sets, so it is important to support the significance of the results with statistical analysis. As binary measurements, the trials are assessed using binomial statistics. A method is described based on the probability confidence interval and expressed in terms of the upper confidence interval bound that reports the probability of successful detection and its level of statistical confidence. These parameters provide useful measures of the system’s performance. The propriety of combining statistics for similar tests—for example in trace detection trials of an explosive on multiple surfaces—is examined by statistical tests. The use of normal statistics is commonly applied to binary testing, but the confidence intervals are known to behave poorly in many circumstances, including small sample numbers. The improvement of the normal approximation with increasing sample number is shown not to be substantial for the typical numbers used in this type of explosives detection system testing, and binary statistics are preferred. The methods and techniques described here for testing trace detection can be applied as well to performance testing of explosives detection systems in general.

Cascaded microsphere-coupled surface-enhanced Raman spectroscopy (CMS-SERS) for ultrasensitive trace-detection

Surface-enhanced Raman spectroscopy (SERS) has been widely investigated and employed as a powerful optical analytical technique providing fingerprint vibrational information of molecules with high sensitivity and resolution. In addition to metallic nanostructure, dielectric micro-/nano-structures with extraordinary optical manipulation properties have demonstrated capability in enhanced Raman scattering with ultralow energy losses. Here we report a facile cascaded structure composed of a large microsphere (LMS) and a small microsphere array with Ag nanoparticles as a novel hybrid SERS substrate, for the first time. The cascaded microsphere-coupled SERS substrate provides a platform to increase the molecular concentration, boost the intensity of localized excitation light, and direct the far-field emission, for giant Raman enhancement. It demonstrates the maximum enhancement factor of Raman intensity greater than 108 for the limit of detection down to 10−11 M of 4-nitrothiphenol molecules in aqueous solution. The present work inspires a novel strategy to fabricate cascaded dielectric/metallic micro-/nano-structures superior to traditional SERS substrates towards practical applications in cost-effective and ultrahigh-sensitive trace-detection.

Off-Resonance Gold Nanobone Films at Liquid Interface for SERS Applications

Extensive effort and research are currently channeled towards the implementation of SERS (Surface Enhanced Raman Spectroscopy) as a standard analytical tool as it has undisputedly demonstrated a great potential for trace detection of various analytes. Novel and improved substrates are continuously reported in this regard. It is generally believed that plasmonic nanostructures with plasmon resonances close to the excitation wavelength (on-resonance) generate stronger SERS enhancements, but this finding is still under debate. In the current paper, we compared off-resonance gold nanobones (GNBs) with on-resonance GNBs and gold nanorods (GNRs) in both colloidal dispersion and as close-packed films self-assembled at liquid-liquid interface. Rhodamine 6G (R6G) was used as a Raman reporter in order to evaluate SERS performances. A 17-, 18-, and 55-fold increase in the Raman signal was observed for nanostructures (off-resonance GNBs, on-resonance GNBs, and on-resonance GNRs, respectively) assembled at liquid-liquid interface compared to the same nanostructures in colloidal dispersion. SERS performances of off-resonance GNBs were superior to on-resonance nanostructures in both cases. Furthermore, when off-resonance GNBs were assembled at the liquid interface, a relative standard deviation of 4.56% of the recorded signal intensity and a limit of detection (LOD) of 5 × 10−9 M could be obtained for R6G, rendering this substrate suitable for analytical applications.

A Novel 3D Hierarchical Plasmonic Functional Cu@Co3O4@Ag Array as Intelligent SERS Sensing Platform with Trace Droplet Rapid Detection Ability for Pesticide Residue Detection on Fruits and Vegetables

Rapid and effective detection of pesticide residues from complex surfaces of fruits and vegetables has important significance. Herein, we report a novel three-dimensional (3D) hierarchical porous functional surface-enhanced Raman scattering (SERS) substrate, which is fabricated by successive two-step hydrothermal synthesis strategy of silver nanoparticles (Ag NPs) and cobalt oxide nanowires (Co3O4 NWs) on the 3D copper foam framework as Cu@Co3O4@Ag-H. The strategy offers a new avenue for localized plasmonic materials distribution and construction, which exhibits better morphology regulation ability and SERS activity (or hotspots engineering) than physical spurring obtained Cu@Co3O4@Ag-S. The developed Cu@Co3O4@Ag-H possesses large surface area and rich hotspots, which contributes to the excellent SERS performance, including homogeneity (RSD of 7.8%), sensitivity (enhancement factor, EF of 2.24 × 108) and stability. The Cu@Co3O4@Ag-H not only provides plenty of Electromagnetic enhancement (EM) hotspots but also the trace detection capability for droplet rapid sensing within 2 s. Cu@Co3O4@Ag-H substrate is further developed as an effective SERS sensing platform for pesticide residues detection on the surfaces of fruits and vegetables with excellent LOD of 0.1 ppm, which is lower than the most similar reported works. This work offers new potential for bioassay, disease POCT diagnosis, national security, wearable flexible devices, energy storage and other related fields.