An efficient and simple SERS approach for trace analysis of tetrahydrocannabinol and cannabinol and multi-cannabinoid detection.

Many countries have legalized cannabis and its derived products for multiple purposes. Consequently, it has become necessary to develop a rapid, effective, and reliable tool for detecting delta-9-tetrahydrocannabinol (THC) and cannabinol (CBN), which are important biologically active compounds in cannabis. Herein, we have fabricated SERS chips by using glancing angle deposition and tuned dimensions of silver nanorods (AgNRs) for detecting THC and CBN at low concentrations. Experimental and computational results showed that the AgNR substrate with film thickness (or nanorod length) of 150 nm, corresponding to nanorod diameter of 79 nm and gap between nanorods of 23 nm, can effectively sense trace THC and CBN with good reproducibility and sensitivity. Due to limited spectral studies of the cannabinoids in previous reports, this work also explored towards identifying characteristic Raman lines of THC and CBN. This information is critical to further reliable data analysis and interpretation. Moreover, multianalyte detection of THC and CBN in a mixture was successfully demonstrated by applying an open-source independent component analysis (ICA) model. The overall method is fast, sensitive, and reliable for sensing trace THC and CBN. The SERS chip-based method and spectral results here are useful for a variety of cannabis testing applications, such as product screening and forensic investigation.

Tuberculosis determination using SERS and chemometric methods.

Nanostructures have been multiplying the advantages of Raman spectroscopy and further amplify the advantages of Raman spectroscopy is a continuous effort focused on the appropriate design of nanostructures. Herein, we designed different shapes of plasmonic nanostructures such as Vertical, Zig Zag, Slant nanorods and Spherical nanoparticles employing the DC magnetron sputtering system as SERS-active substrates for ultrasensitive detection of target molecules. The fabricated plasmonic nanostructures sensitivity and uniformity were exploited by reference dye analyte. These nanostructures were utilized in the label free detection of infectious disease, Tuberculosis (TB). For the first time, TB detection from serum samples using SERS has been demonstrated. Various multivariate statistical methods such as principal component analysis, support vector machine, decision tree and random forest were developed and tested their ability to discriminate the healthy and active TB samples. The results demonstrate the performance of the SERS spectra, chemometric methods and potential of the method in clinical diagnosis.

Surface-enhanced Raman scattering using silver nanocluster on anodic aluminum oxide template sensor toward protein detection.

The affordable surface-enhanced Raman scattering (SERS) substrates, with a structure consisting of densely distributed round-shape silver nanoclusters on anodic aluminum oxide (AAO) template, is fabricated by magnetron sputtering and anodization processes. The physical investigations show that the silver nanoclusters with size distribution ranging from 10 to 30 nm uniformly distributed on the top and in the bottom of the AAO nanochannels. The SERS activities from adsorbed probe molecules, i.e., methylene blue, on the SERS substrate surface indicate a high Raman enhancement factor for trace organic analysis. The SERS substrate is successfully utilized in the detection of a trace amount of three different proteins, bovin serum albumin, immunoglobulin G, and cardiac troponin T, also adsorbed on the substrate surface. Several spectral bands containing important molecular structures of these proteins are clearly observed and identified. The obtained results indicated a step forward to label-free biomolecular detections in chip-based biosensors.