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

Chromatographic and Spectroscopic Analyses of Cannabinoids: A Narrative Review Focused on Cannabis Herbs and Oily Products

Cannabis sativa L. is cultivated nowadays for agricultural, industrial, and medicinal applications and also for recreational use. The latter is due to the presence of delta-9-tetrahydrocannabinol, a psychoactive substance. Recreational cannabis policies vary between different countries, which has led to the lack of a clearly defined legal context for cannabis and also a diversity of products derived from or containing cannabis on the (il)legal market. These cannabis-derived products have regained attention, notably because of their cannabinoid content. This review aims to assess and present analytical methods developed to analyze phytocannabinoids with spectroscopic and chromatographic techniques in specific cannabis matrices: herbs and oily products. Published papers from 2018-November 2024 were searched for with precise criteria, analyzed, and summarized. In the studies, liquid and gas chromatographic techniques (>70% reviewed papers) were the most used and have been widely applied using similar methods, and most papers were focused on cannabis herbs (>75%). Techniques were also compared and future challenges were identified. A comparison of different specificities of chromatographic and spectroscopic techniques discussed in this current review has also been established and summarized.

Detection of low-level fentanyl concentrations in mixtures of cocaine, MDMA, methamphetamine, and caffeine via surface-enhanced Raman spectroscopy

Surface-enhanced Raman spectroscopy (SERS) was utilized to measure low-level fentanyl concentrations mixed in common cutting agents, cocaine, 3,4-methylenedioxymethamphetamine (MDMA), methamphetamine, and caffeine. Mixtures were prepared with a fentanyl concentration range of 0-339 μM. Data was initially analyzed by plotting the area of a diagnostic peak (1026 cm-1) against concentration to generate a calibration model. This method was successful with fentanyl/MDMA samples (LOD 0.04 μM) but not for the other mixtures. A chemometric approach was then employed. The data was evaluated using principal component analysis (PCA), partial least squares (PLS1) regression, and linear discriminant analysis (LDA). The LDA model was used to classify samples into one of three designated concentration ranges, low = 0-0.4 mM, medium = 0.4-14 mM, or high >14 mM, with fentanyl concentrations correctly classified with greater than 85% accuracy. This model was then validated using a series of "blind" fentanyl mixtures and these unknown samples were assigned to the correct concentration range with an accuracy >95%. The PLS1 model failed to provide accurate quantitative assignments for the samples but did provide an accurate prediction for the presence or absence of fentanyl. The combination of the two models enabled accurate quantitative assignment of fentanyl in binary mixtures. This work establishes a proof of concept, indicating a larger sample size could generate a more accurate model. It demonstrates that samples, containing variable, low concentrations of fentanyl, can be accurately quantified, using SERS.

Flexible, scalable and simple-fabricated silver nanorod-decorated bacterial nanocellulose SERS substrates cooperated with portable Raman spectrometer for on-site detection of pesticide residues

Owing to good flexibility, prominent mechanical properties, three-dimensional (3D) nanofibrous structure and low background interference, sustainable bacterial nanocellulose (BNC) is a highly attractive matrix material for surface-enhanced Raman scattering (SERS) sensor. Herein, a highly sensitive, flexible and scalable silver nanorod-decorated BNC (AgNRs@BNC) SERS sensor is developed by a simple vacuum-assisted filtration. The AgNRs were firmly locked in the 3D nanofibrous network of cellulose nanofibers upon vacuum drying process, resulting in the formation of 3D SERS hotspots with a depth of more than 10 μm on the sensor. With 4-aminothiophenol (4-ATP) as a target molecule, a lowest distinguishable level of 10-12 M and a high enhancement factor of 1.1 × 109 were realized by the optimal AgNRs1.5@BNC SERS sensor. Moreover, the AgNRs@BNC SERS sensor exhibits high detectable level of 10-9 M for thiram molecules by integrating with a portable Raman spectrometer. Besides, toxic thiram residues on grape surface could be directly on-site identified by the combination of AgNRs@BNC SERS sensors and a portable Raman spectrometer through a feasible press-and-peel method. The flexible AgNRs@BNC SERS sensor cooperated with portable Raman system demonstrates great potential for on-site detection of pesticide residues on irregular food surfaces.

Cotton swabs wrapped with three-dimensional silver nanoflowers as SERS substrates for the determination of food colorant carmine on irregular surfaces

A lightweight, portable, low-cost, and accessible cotton swab was employed as surface enhanced Raman spectroscopy (SERS) matrix template. The silver nanoflowers were in situ grown on the surface of cotton swabs to form three-dimensional Ag nanoflower@cotton swabs (AgNF@CS) SERS substrate with high-density and multi-level hot spots. The SERS performance of AgNFs@CS substrates with various reaction time was systematically studied. The optimal AgNF-120@CS SERS substrate exhibits superior detection sensitivity of 10-10 M for methylene blue, good signal reproducibility, high enhancement factor of 1.4 × 107, and excellent storage stability (over 30 days). Moreover, the AgNF-120@CS SERS substrate also exhibits prominent detection sensitivity of 10-8 M for food colorant of carmine. Besides, the portable AgNF-120@CS SERS substrate is also capable of detecting food colorant residues on irregular food surfaces.

Molecularly imprinted polymers (MIP) combined with Raman spectroscopy for selective detection of Δ⁹-tetrahydrocannabinol (THC)

A proof-of-concept sensor is developed for the sensitive and selective detection of Trans-Δ⁹-tetrahydrocannabinol (THC) based on a molecularly imprinted polymer (MIP) synthesized with a THC template which was analyzed using Raman spectroscopy to perform label-free monitoring of THC based on a single identifying Raman peak. The MIP sensor produced a peak at 1614 cm-1 in the Raman spectrum originating from the THC target molecule, allowing for the selective quantification of bound THC with the lowest detection limit of 250 ppm. A higher sensitivity of the MIP to the THC target molecule was observed compared to the non-imprinted polymer (NIP) control which confirmed the presence of THC-specific recognition sites within the synthesized MIP sensing material. The selectivity of this MIP-based sensor was determined by measuring the Raman spectrum of MIP exposed to Cannabidiol (CBD), ethanol, and acetone.

Label free detection of multiple trace antibiotics with SERS substrates and independent components analysis

Surface enhanced Raman spectroscopy (SERS) has been widely studied and recognized as a powerful label-free technique for trace chemical analysis. However, its drawback in simultaneously identifying several molecular species has greatly limited its real-world applications. In this work, we reported a combination between SERS and independent component analysis (ICA) to detect several trace antibiotics which are commonly used in aquacultures, including malachite green, furazolidone, furaltadone hydrochloride, nitrofurantoin, and nitrofurazone. The analysis results indicate that the ICA method is highly effective in decomposing the measured SERS spectra. The target antibiotics could be precisely identified when the number of components and the sign of each independent component loading were properly optimized. With SERS substrates, the optimized ICA can identify trace molecules in a mixture at a concentration of 10^-6 M achieving the correlation values to the reference molecular spectra of 71-98%. Furthermore, measurement results obtained from a real-world sample demonstration could also be recognized as an important basis to suggest this method is promising for monitoring antibiotics in a real aquatic environment.

Surface-Enhanced Raman scattering (SERS) filter paper substrates decorated with silver nanoparticles for the detection of molecular vibrations of Acyclovir drug

Acyclovir (ACV) drug, a common antiviral agent, is frequently used as the primary clinical treatment method for treating hepatitis B, herpes simplex, and varicella zoster viruses due to its potent therapeutic effect. In patients with compromised immune systems, this medication can stop cytomegalovirus infections, and high doses of this drug are required; however, such prescription leads to kidney toxicity. Therefore, timely and accurate detection of ACV is crucial in many areas. Surface-Enhanced Raman Scattering (SERS) is a reliable, rapid, and precise approach for the identification of trace biomaterials and chemicals. Filter paper substrates decorated with silver nanoparticles (AgNPs) were applied as SERS biosensors to detect ACV and control its adverse effects. Initially, a chemical reduction procedure was utilized to produce AgNPs. Afterward, UV-Vis, FE-SEM, XRD, TEM, DLS, and AFM were employed to examine the properties of prepared AgNPs. In order to prepare SERS-active filter paper substrates (SERS-FPS) to detect Molecular vibrations of ACV, AgNPs prepared by immersion method were coated on filter paper substrates. Moreover, the UV-Vis DRS analysis was carried out to assess the stability of filter paper substrates and SERS-FPS. The AgNPs reacted with ACV after being coated on SERS-active plasmonic substrates and could sensitively detect ACV in small concentrations. It was discovered that the limit of detection of SERS plasmonic substrates was 10^-12 M. Moreover, the mean RSD for ten repeated tests was calculated as 4.19%. The enhancement factor for detecting ACV using the developed biosensors was calculated to be 3.024 × 10⁵ and 3.058 × 10⁵ experimentally and via simulation, respectively. According to the Raman results, SERS-FPS for the detection of ACV, fabricated by the present methods, showed promising results for SERS-based investigations. Furthermore, these substrates showed significant disposablity, reproducibility, and chemical stability. Therefore, the fabricated substrates are capable to be employed as potential SERS biosensors to detect trace substances.