Aggregation-aided SERS: Selective detection of arsenic by surface-enhanced Raman spectroscopy facilitated by colloid cross-linking

Green synthesis of thiazole bis-imines as fluorometric sensor for determination of lead in environmental, biological, and food samples

In this work, we describe for the first time the synthesis of a thiazole bis-imine fluorometric sensor for the selective determination of Pb2+ in environmental, biological, and food samples. The novel molecules were obtained through a multicomponent reaction using a green and environmentally sustainable methodology. Synthesized chemical sensors were characterized using spectroscopic techniques to structural elucidation, including UV-Vis, FTIR-ATR, 1H and 13C NMR. One of these sensors exhibited remarkable selectivity for the Pb2+ ion at pH 3, forming a stable 1:1 (metal:ligand) complex. Additionally, the reaction conditions for complex formation were optimized, resulting in a method with a linear range of 0.667-10  μg L-1 and a detection limit of 0.18  μg L-1. Furthermore, method validation reinforced its reliability, showing low relative standard deviation in both intra-day and inter-day analyses. Recovery experiments ranged from 83.53 % to 119.10 %. This study represents a significant and innovative advancement in the development of rapid, sensitive, and alternative methods for the detection of potentially toxic metals in a wide range of samples employing a green multicomponent reaction of thiazole bis-imines.

Ultrafast Detection of Arsenic Using Carbon-Fiber Microelectrodes and Fast-Scan Cyclic Voltammetry

Arsenic contamination poses a significant public health risk worldwide, with chronic exposure leading to various health issues. Detecting and monitoring arsenic exposure accurately remains challenging, necessitating the development of sensitive detection methods. In this study, we introduce a novel approach using fast-scan cyclic voltammetry (FSCV) coupled with carbon-fiber microelectrodes (CFMs) for the electrochemical detection of As3+. Through an in-depth pH study using tris buffer, we optimized the electrochemical parameters for both acidic and basic media. Our sensor demonstrated high selectivity, distinguishing the As3+ signal from those of As5+ and other potential interferents under ambient conditions. We achieved a limit of detection (LOD) of 0.5 μM (37.46 ppb) and a sensitivity of 2.292 nA/μM for bare CFMs. Microscopic data confirmed the sensor's stability at lower, physiologically relevant concentrations. Additionally, using our previously reported double-bore CFMs, we simultaneously detected As3+-Cu2+ and As3+-Cd2+ in tris buffer, enhancing the LOD of As3+ to 0.2 μM (14.98 ppb). To our knowledge, this is the first study to use CFMs for the rapid and selective detection of As3+ via FSCV. Our sensor's ability to distinguish As3+ from As5+ in a physiologically relevant pH environment showcases its potential for future in vivo studies.

Portable SERS-Based POCT Kit for Ultrafast and Sensitive Determining Paraquat in Human Gastric Juice and Urine

Paraquat (PQ) poisoning poses a significant public health concern. Unfortunately, point-of-care testing (POCT) of PQ in biofluids remains challenging. This study developed a portable kit that enables swift and reliable identification and quantification of PQ in human urine and gastric juice. The approach employed the surface-enhanced Raman scattering (SERS) technique, leveraging gold-silver core-shell nanoparticles (Au@Ag NPs) as the substrate. The kit comprised a portable Raman spectrometer and three sealed tubes containing Au@Ag NPs colloid, KI solution, and MgSO4 solution. A discernible correlation was observed between signal intensity and the logarithmic concentration, spanning from 5 to 500 μg/L in urine and 10 μg/L to 1 mg/L in gastric juice. The detection limits, calculated from the characteristic peak at 1648 cm -1, were 1.36 and 4.05 μg/L in human urine and gastric juice, respectively. Notably, this POCT kit obviated the need for pretreatment procedures, and the detection process was accomplished within 1 min, yielding satisfactory recoveries. This expeditious time frame is crucial for clinical diagnosis and rescue operations. Compared to conventional methods, this kit demonstrated real-time determinations in nonlaboratory settings. The simplicity and practicality of this POCT assay suggest its significant potential as an innovative alternative for poisoning detection applications.

A facile approach for selective detection of arsenite ions using plasmonic behaviour of silver nanoparticles

A specific reagent/aptamer-free easy redox strategy between silver(I) moieties present in a citrate-stabilized colloidal silver nanoparticle (NP) system and arsenite ions is described that enables plasmonic change of AgNPs for the selective quantification of arsenite ions in the range of 0 to 30 μM with a low limit of quantification value of 50 nM (5.3 ppb).

Application of surface-enhanced Raman scattering to qualitative and quantitative analysis of arsenic species

Given the toxicity of arsenic, there is an urgent need for the development of efficient and reliable detection systems. Raman spectroscopy, a powerful tool for material characterization and analysis, can be used to explore the properties of a wide range of different materials. Surface-enhanced Raman spectroscopy (SERS) can detect low concentrations of chemicals. This review focuses on the progress of qualitative and quantitative studies of the adsorption processes of inorganic arsenic and organic arsenic in aqueous media using Raman spectroscopy in recent years and discusses the application of Raman spectroscopy theory simulations to arsenic adsorption processes. Sliver nanoparticles are generally used as the SERS substrate to detect arsenic. Inorganic arsenic is chemisorbed onto the silver surface by forming As-O-Ag bonds, and the Raman shift difference in the As-O stretching (∼60 cm-1) between As(V) and As(III) allows SERS to detect and distinguish between As(V) and As(III) in groundwater samples. For organic arsenicals, specific compounds can be identified based on spectral differences in the vibration modes of the chemical bonds. Under the same laser excitation, the intensity of the Raman spectra for different arsenic concentrations is linearly related to the concentration, thus allowing quantitative analysis of arsenic. Molecular modeling of adsorbed analytes via density functional theory calculation (DFT) can predict the Raman shifts of analytes in different laser wavelengths.