A novel SERS selective detection sensor for trace trinitrotoluene based on meisenheimer complex of monoethanolamine molecule

Potential of a deep eutectic solvent in silver nanoparticle fabrication for antibiotic residue detection

Deep eutectic solvents (DESs) have recently emerged as an alternative solvent for nanoparticle synthesis. There have been numerous advancements in the fabrication of silver nanoparticles (Ag NPs), but the potential of DESs in Ag NP synthesis was neither considered nor studied carefully. In this study, we present a novel strategy to fabricate Ag NPs in a DES (Ag NPs-DES). The DES composed of ᴅ-glucose, urea, and glycerol does not contain any anions to precipitate with Ag+ cations. Our Ag NPs-DES sample is used in a surface-enhanced Raman scattering (SERS) sensor. The two analytes for SERS quantitation are nitrofurantoin (NFT) and sulfadiazine (SDZ) whose residues can be traced down to 10-8 M. The highest enhancement factors (EFs) are competitive at 6.29 × 107 and 1.69 × 107 for NFT and SDZ, respectively. Besides, the linearity coefficients are extremely close to 1 in the range of 10-8 to 10-3 M of concentration, and the SERS substrate shows remarkable uniformity along with great selectivity. This powerful SERS performance indicates that DESs have tremendous potential in the synthesis of nanomaterials for biosensor substrate construction.

Rapid detection of trace nitrobenzene in water via SERS using a portable Raman spectrometer

Nitrobenzene is currently the most widely used explosive substance, and is known for its high toxicity and mutagenicity. It can cause severe environmental and water pollution, posing a risk to public health. Among various explosives analysis methods, surface-enhanced Raman spectroscopy (SERS) has the advantages of fast analysis speed, low detection cost, and easy operation, and has become one of the most promising analytical detection methods. Here, we present a portable and reliable sol-based SERS method for the detection of trace amounts of 2,4,6-trinitrotoluene (TNT) in different water bodies. The Meisenheimer complex formed by nitrobenzene and hydrazine hydrate can assemble on unmodified Au nanoparticles in a sol via Au-N bonds, enabling rapid detection of TNT in seawater, lake water, and tap water using a portable Raman spectrometer. Experimental results show that this SERS method can complete the detection within a few minutes and the detection sensitivity can reach 0.01 mg L-1, which is far lower than China's national standard of no more than 0.5 mg L-1. Furthermore, this method was also successfully applied to detect trace 2,4-dinitrotoluene (2,4-DNT) and picric acid (2,4,6-trinitrophenol) in water, demonstrating its strong applicability for on-site detection of nitrobenzene explosives.

Nitroaromatic explosives' detection and quantification using an attention-based transformer on surface-enhanced Raman spectroscopy maps

Rapidly and accurately detecting and quantifying the concentrations of nitroaromatic explosives is critical for public health and security. Among existing approaches, explosives' detection with Surface-Enhanced Raman Spectroscopy (SERS) has received considerable attention due to its high sensitivity. Typically, a preprocessed single spectrum that is the average of the entire or a selected subset of a SERS map is used to train various machine learning models for detection and quantification. Designing an appropriate averaging and preprocessing procedure for SERS maps across different concentrations is time-consuming and computationally costly, and the averaging of spectra may lead to the loss of crucial spectral information. We propose an attention-based vision transformer neural network for nitroaromatic explosives' detection and quantification that takes raw SERS maps as the input without any preprocessing. We produce two novel SERS datasets, 2,4-dinitrophenols (DNP) and picric acid (PA), and one benchmark SERS dataset, 4-nitrobenzenethiol (4-NBT), which have repeated measurements down to concentrations of 1 nM to illustrate the detection limit. We experimentally show that our approach outperforms or is on par with the existing methods in terms of detection and concentration prediction accuracy. With the produced attention maps, we can further identify the regions with a higher signal-to-noise ratio in the SERS maps. Based on our findings, the molecule of interest detection and concentration prediction using raw SERS maps is a promising alternative to existing approaches.

Chemical reduction as a facile colorimetric approach for selective TNT detection by spectrophotometry and photothermal lens spectroscopy

In this study, the simple determination of TNT is achieved through the vivid stable red color products generated after chemically reduction by NaBH₄ as a common and accessible reducing/colorimetric reagent. Some other nitroaromatics were impressed under reduction reaction and led to the colorful products. The color of these reduced nitroaromatics were unstable and approximately vanished after some few minutes which ameliorated the selectivity in TNT determination. Utilizing the time-dependent selectivity, the method was applied specifically for discriminating of TNT from other nitroaromatic compounds (NACs). UV-vis spectrophotometry and photothermal lens spectrometry were employed as detection techniques. The former was simpler and more available in various laboratories while the latter provides higher sensitivity. It was revealed that the photothermal lens responses were linear from 2.0 to 55.0 nM with a limit of detection (LOD) of about 0.8 nM. The LOD of the photothermal lens measurement were found to be 241 times lower than that of the UV-vis spectrophotometry in TNT quantification. The evolved method was successfully carried out for TNT vapor determination after trapping into the colorimetric reagent. The recoveries and relative standard deviations (RSD, n = 3) calculated for 3 gas samples were ≥91% and ≤7%, respectively.

Synthetic Approaches, Modification Strategies and the Application of Quantum Dots in the Sensing of Priority Pollutants

Polycyclic aromatic hydrocarbons (PAHs) and nitro-aromatic compounds (NACs) are two classifications of environmental pollutants that have become a source of health concerns. As a result, there have been several efforts towards the development of analytical methods that are efficient and affordable that can sense these pollutants. In recent decades, a wide range of techniques has been developed for the detection of pollutants present in the environment. Among these different techniques, the use of semiconductor nanomaterials, also known as quantum dots, has continued to gain more attention in sensing because of the optical properties that make them useful in the identification and differentiation of pollutants in water bodies. Reported studies have shown great improvement in the sensing of these pollutants. This review article starts with an introduction on two types of organic pollutants, namely polycyclic aromatic hydrocarbons and nitro-aromatic explosives. This is then followed by different quantum dots used in sensing applications. Then, a detailed discussion on different groups of quantum dots, such as carbon-based quantum dots, binary and ternary quantum dots and quantum dot composites, and their application in the sensing of organic pollutants is presented. Different studies on the comparison of water-soluble quantum dots and organic-soluble quantum dots of a fluorescence sensing mechanism are reviewed. Then, different approaches on the improvement of their sensitivity and selectivity in addition to challenges associated with some of these approaches are also discussed. The review is concluded by looking at different mechanisms in the sensing of polycyclic aromatic hydrocarbons and nitro-aromatic compounds.

SERS substrate fabrication for biochemical sensing: towards point-of-care diagnostics

Rapid technology development and economic growth have brought attention to public health issues, such as food safety and environmental pollution, which creates an ever-increasing demand for fast and portable sensing technologies. Portable surface-enhanced Raman spectroscopy (SERS) capable of various analyte detection with low concentration in a convenient manner shows advantages in sensing technology including enhanced diagnostic precision, improved diagnostic efficiency, reduced diagnostic cost, and alleviation of patient pain, which emerges as a promising candidate for point-of-care testing (POCT). SERS detection technology based on different nanostructures made of noble metal-based nanomaterials can increase the sensitivity of Raman scattering by 6-8 orders of magnitude, making Raman based trace detection possible, and greatly promote the application scenarios of portable Raman spectrometers. In this perspective, we provide an overview of fundamental knowledge about the SERS mechanism including chemical and electromagnetic field enhancement mechanisms, the design and fabrication of SERS substrates based on materials, progress of using SERS for POCT in biochemical sensing and its clinical applications. Furthermore, we present the prospective of developing new nanomaterials with different functionalities for advanced SERS substrates, as well as the future advancement of biomedical sensing and clinical potential of SERS technology.

Wireless Tags with Hybrid Nanomaterials for Volatile Amine Detection

Quality control in the production and processing of raw meat is currently one of the biggest concerns for food industry and would benefit from portable and wireless sensors capable of detecting the onset of spoilage. Raw meat is a natural source of biogenic and volatile amines as byproducts of decarboxylation reactions, and the levels of these compounds can be utilized as quality control parameters. We report herein a hybrid chemiresistor sensor based on inorganic nanofibers of SiO₂:ZnO (an n-type material) and single-walled carbon nanotubes functionalized with 3,5-dinitrophenyls (a p-type material) with dosimetric sensitivity ∼40 times higher for amines than for other volatile organic compounds, which also provides excellent selectivity. The hybrid nanomaterial-based chemiresistor sensory material was used to convert radio-frequency identification tags into chemically actuated resonant devices, which constitute wireless sensors that can be potentially employed in packaging to report on the quality of meat. Specifically, the as-developed wireless tags report on cumulative amine exposure inside the meat package, showing a decrease in radio-frequency signals to the point wherein the sensor ceased to be smartphone-readable. These hybrid material-modified wireless tags offer a path to scalable, affordable, portable, and wireless chemical sensor technology for food quality monitoring without the need to open the packaging.

Plasmonic hollow fibers with distributed inner-wall hotspots for direct SERS detection of flowing liquids

Plasmonic hollow fibers are fabricated by coating silver-/ gold-alloyed nanoparticles (Ag-Au-ANPs) onto the inner walls of hollow fibers. In this Letter, the Ag-Au-ANPs were synthesized chemically and dissolved in acetone to prepare a colloidal solution, flowed subsequently through the hollow fiber multiple times so that a thin layer of colloidal Ag-Au-ANPs was produced on the inner wall. Annealing at 400°C enabled melting/aggregation of the metallic nanoparticles and consequent formation of closely arranged plasmonic nanostructures fixed solidly on the inner wall. A surface-enhanced Raman scattering (SERS) mechanism was thus established for the liquids flowing through the hollows. The SERS measurements show an enhancement factor >10⁴ for such plasmonic hollow fibers in the direct detection of R6G/ethanol solutions. Confinement of the excitation laser energy inside the hollow space represents an additional contribution to the enhancement mechanism. This is a promising design for the direct on-site SERS detection of molecules in flowing liquids with low concentrations.