Analytical Methods最新文献

Reuse of treated wastewater in agriculture exposes soils and edible crops to halogenated disinfection byproducts (DBPs), toxic compounds formed during chlorination. While DBPs are well characterized in water, analytical methods for soil and plant matrices remain scarce, limiting risk assessment for food safety and groundwater contamination. This gap hinders the implementation of EU Regulation 2020/741 on safe wastewater reuse. We developed and evaluated two solid-liquid extraction methods for 36 DBPs across 8 families (THMs, HANs, HNMs, HKs, HALs, HAcAms, HAs, and HAAs) in artificial/natural soils and lettuce, combined with pass-through SPE clean-up (ENVI-Carb for lettuce, Florisil for soils), to reduce matrix effects and enhance system stability and sensitivity. Extraction parameters (pH, ionic strength, and agitation/sonication time) were optimized using GC-ECD. HAAs were esterified prior to clean-up to avoid retention. Recovery rates ranged from 54.3-117.4% (29/36 analytes >80% for soil, 28/36 for lettuce), with method detection limits 14 times lower than prior work on lettuce (0.06-11.69 ng g^-1 dry soil or fresh lettuce). The clean-up step was optimized using both GC-ECD (quantitative) and GC-MS (qualitative). Matrix effects were minimized, improving system robustness using the SPE approach. Stability tests revealed rapid degradation of HNMs, HALs, HANs and HKs in moist soils (<24 h) with halohydrins, HAcAms and HAAs identified as degradation products. This work provides sensitive, reliable tools for monitoring halogenated DBPs in agricultural soil/plant systems, supporting compliance with wastewater reuse regulations and addressing critical gaps in food safety risk assessment.

In this work, a novel and environmentally friendly method based on bismuth fire assay (Bi-FA) combined with laser ablation ICP-MS (LA-ICP-MS) was established for the determination of ultra-trace Pt, Pd, and Au in geochemical samples, using a Pt isotope spike (¹⁹⁴Pt) as the internal standard. Due to the low toxicity and low, stable blank values of the Bi₂O₃ collector, Bi-FA could be directly employed for the pre-concentration of Pt, Pd, and Au prior to analysis. The Ag slices prepared by annealing and tableting were analyzed at multiple points by LA-ICP-MS. This approach offered advantages including rapid analysis, good measurement stability, and the elimination of polyatomic ion interference and dilution effects associated with solution-based analysis. As the internal standard, the Pt isotope spike was thoroughly mixed with the target elements (Pt, Pd, and Au in the sample) in each Ag prill, and its distribution was consistent with that of the target elements. This method resolved the issue of uneven distributions of Pt, Pd, and Au in the Ag slices, thereby enabling internal standard correction for LA-ICP-MS by calculating the intensity of ¹⁹⁴Pt from the Pt isotope spike. In addition, optimization experiments were conducted for key parameters, including laser frequency, energy density, ablation spot diameter, and ICP-MS dwell time. The Ag slices prepared from certified reference materials (CRMs) were used as the calibration standards. The standard samples had the same matrix as the real samples, which reduced laser ablation fractionation effects, minimized analytical errors, and improved accuracy. The standard curves were plotted by the empirical coefficient method and showed excellent linearity with correlation coefficients (R²) of 0.9999 (Pt), 0.9998 (Pd), and 0.9995 (Au). The limits of detection (LODs) of the method were 0.066 (Pt), 0.052 (Pd), and 0.090 (Au) ng g^-1. The proposed method was validated by determining the Pt, Pd, and Au in CRMs, showing excellent agreement with certified values. When applied to geochemical samples, the results were consistent with those obtained by lead fire assay combined with graphite furnace atomic absorption spectrometry (Pb-FA-GF-AAS). The recoveries were 2.5-107.8% (Pt), 91.4-108.0% (Pd), and 91.0-109.2% (Au), demonstrating the good accuracy of the proposed method.

Polyurethane (PU) is one of the most versatile polymers used in everyday life. But PU waste management is a major concern for the scientific community and regulatory authorities. The thermoset architecture of PUs makes degradation and recycling/upcycling difficult. This review provides insights into PU, emphasizing its structural chemistry and wide industrial applicability. The global situation highlights the industrial importance of PUs. Using nanomaterial-based catalysts could improve depolymerization and resource recovery. The paper points out future research areas in PU degradation and suggests ways to encourage innovation and deepen knowledge in the PU waste field.

Alkaline phosphatase (ALP) is an essential biomarker for clinical diagnosis and food safety monitoring, and the development of facile, low-cost, and sensitive ALP detection strategies is of great significance. Herein, uniform cobalt-based Prussian blue analogue (CoFe-PBA) nanocubes were successfully synthesized via a simple one-pot coprecipitation method. The prepared CoFe-PBA possesses intrinsic oxidase-like catalytic activity originating from mixed-valence Co²⁺/Co³⁺ and Fe²⁺/Fe³⁺ active sites, which can activate dissolved oxygen to generate superoxide anion radicals (O₂˙^-) for substrate oxidation. Based on this catalytic characteristic, a straightforward colorimetric sensing platform was constructed for ALP detection. The sensing strategy relies on the ALP-triggered hydrolysis of L-ascorbic acid 2-phosphate trisodium salt (AAP) to produce ascorbic acid (AA), which inhibits the 3,3',5,5'-tetramethylbenzidine (TMB) chromogenic reaction and induces dose-dependent absorbance attenuation. Under optimized conditions, the proposed sensor exhibits good linear correlation, high sensitivity, acceptable selectivity and anti-interference capability. Furthermore, spike-and-recovery assays in 50-fold diluted fetal bovine serum demonstrate the potential of the platform for ALP analysis in complex biological matrices. This work provides a simple, low-cost and efficient colorimetric strategy for ALP bioassay, which holds promising potential for clinical biochemical analysis and food safety monitoring.

Cortisol levels provide valuable information regarding physiological stress and abnormalities associated with endocrine and mental health disorders. In this study, an AuNPs/CNT-modified electrochemical aptasensor integrated with machine learning was developed for sensitive cortisol detection and accurate discrimination of cortisol levels. A porous CNT network supported a large specific surface area with high conductivity, and density functional theory (DFT) calculations revealed the AuNPs modified the electronic structures of CNTs and further accelerated the charge transfer efficiency. Once cortisol specifically binds to the aptamer, target-triggered conformational rearrangement could destabilize the aptamer/cDNA duplex and release the aptamer from the electrode surface. The reduced surface nucleic acid density alleviated steric and electrostatic hindrance for the diffusion of the [Fe(CN)₆]^3-/4- probe, which resulted in an accelerated interfacial electron transfer and yielded an enhanced electrochemical signal. The proposed cortisol aptasensor exhibited a good linear relationship between the current variation and the logarithm of cortisol concentration in the range of 10-5000 nM, with a limit of detection of 1.61 nM. Simultaneously, supervised machine learning was applied to classify cortisol concentrations with low, normal, and high levels, thus providing a promising strategy for intelligent stress assessment.

Per- and polyfluoroalkyl substances, known as PFASs, are persistent organic pollutants. Perfluorooctanoic acid and perfluorooctane sulfonate, referred to as PFOA and PFOS, respectively, require selective sample preparation before trace-level LC-MS/MS analysis. Herein, an amino-functionalized magnetic MIL-101(Fe) composite, Fe₃O₄@SiO₂-NH₂@MIL-101(Fe)-NH₂, was synthesized and applied as an MSPE sorbent for PFOA and PFOS in water and dairy matrices. The composite integrates magnetic Fe₃O₄@SiO₂-NH₂ nanoparticles with an amino-functionalized MIL-101(Fe) porous framework, enabling rapid magnetic separation and multiple adsorption interactions. Adsorption equilibrium was reached within 10 min, and the adsorption mechanism was dominated by electrostatic attraction, hydrogen-bonding, and hydrophobic interactions. Under optimized conditions, the method exhibited satisfactory linearity within the ranges of 0.05-50 ng mL^-1 and 0.5-50 ng mL^-1 for PFOA and PFOS, respectively. The limits of detection were 0.25 ng L^-1 for PFOA and 2.5 ng L^-1 for PFOS in water, and 0.005 ng g^-1 for PFOA and 0.020 ng g^-1 for PFOS in dairy samples. Recoveries ranged from 73.86% to 118.30% with RSDs no more than 15%. The sorbent remained stable over five consecutive cycles and was successfully applied to spiked water, milk, and milk powder samples. This work provides a practical strategy for designing amino-functionalized magnetic MOF composites for rapid and sensitive enrichment of PFOA and PFOS in complex environmental and food matrices.

Discriminating analytes with overlapping signals remains a significant challenge for metal oxide gas sensors. This study presents a methodology to decouple the kinetic fingerprints of ammonia and acetone using ZnO-rGO heterojunctions. In situ prepared rGZO_i5 composites, featuring 12 nm ZnO nanoparticles anchored on rGO defect sites, exhibited superior sensitivity compared to physical mixtures. At operating temperatures of 443 K and 453 K, the sensor revealed distinct temporal signatures: acetone follows pseudo-first-order kinetics with a sluggish sigmoidal recovery (up to 1684 s), whereas ammonia follows zero-order kinetics with rapid Elovich-type relaxation. Mechanistic analysis shows that acetone is bottlenecked by a complex redox pathway with an activation energy barrier of 0.58 eV for water desorption. Conversely, ammonia's 3-electron pathway enables near-instantaneous re-oxygenation of the surface. A Continuous Stirred-Tank Reactor (CSTR) dilution model confirms that recovery delays are dictated by surface-limited chemical bottlenecks rather than carrier transport. With theoretical limits of detection of 3.4 ppm for acetone and 14.8 ppm for ammonia at 453 K, this kinetic profiling framework offers a robust path toward high selectivity.

Discriminating structurally similar biophosphates remains challenging for conventional single-channel sensing systems. Here, we develop a ratiometric differential sensing strategy based on a three-channel array of ligand-diversified Fe-MOF nanozymes, Fe-IPA-NH₂, Fe-TPA-NH₂, and Fe-TPA-OH. Each Fe-MOF combines intrinsic fluorescence with peroxidase-like activity and catalyzes the H₂O₂-mediated oxidation of o-phenylenediamine (OPD) to fluorescent 2,3-diaminophenazine (DAP). Phosphate-dependent modulation of the catalytic process produces coupled changes in the DAP emission and the intrinsic Fe-MOF emission. These outputs were converted into an internally referenced ratio (R = F₅₅₀/F_MOF) and then normalized to the phosphate-free response (R/R₀), generating self-referenced cross-reactive fingerprints. Chemometric analysis enabled discrimination of PPi, Pi, ATP, ADP, and AMP at 5 µM and maintained distinct clustering at 3, 1, and 0.5 µM. The array also differentiated PPi concentration levels and resolved binary PPi/Pi mixtures with varying compositions. By integrating ligand-diversified cross-reactivity, ratiometric normalization, and multivariate decoding, this work provides a proof-of-concept strategy for differential sensing of structurally related analytes.

Cluster of differentiation 47 (CD47), a transmembrane glycoprotein overexpressed in various tumor cells, serves as an important immunoregulatory molecule and has emerged as a promising biomarker for disease diagnosis and therapeutic targeting. This research developed a magnetic fluorescent molecularly imprinted polymers (MMIPs)-based sensor for highly selective, sensitive, and rapid detection of CD47. The sensor was constructed by creating imprinted cavities on the surface of magnetic carbon dots (MCDs) through boronate affinity-oriented immobilization of a fructose-modified CD47 epitope, combined with zinc acrylate-assisted metal chelation. This oriented epitope imprinting strategy ensures precise control over template orientation, leading to improved binding site homogeneity and enhanced recognition performance. Under optimized conditions, the performance evaluation indicates that the sensor achieves a detection limit of 4.97 µmol L^-1, coupled with excellent selectivity, a rapid response (20 min), and high accuracy in human serum samples (recovery rates of 96.4-101.6%). This platform thereby provides a reliable tool for CD47 detection in complex biological samples.

This study demonstrates the applicability of time-of-flight secondary ion mass spectrometry (ToF-SIMS) combined with multivariate statistical analysis (MVSA) for the chemical differentiation of fingermarks from eight donors. Multiple ToF-SIMS spectra were measured on a small area of each fingermark sample to assess whether chemical variability between the fingermark samples exceeded chemical variability within each individual one. Principal component analysis (PCA) enabled the separation of fingermark samples from different donors, while multivariate curve resolution (MCR) further resolved individual fingermark-associated MCR factors and revealed characteristic m/z signals contributing to fingermark sample discrimination. Some characteristic signals were confirmed as unique donor-associated signals within the examined dataset, whereas others still enabled donor differentiation because their relative intensities within the ToF-SIMS spectra differed across the spectral dataset obtained from different donors. This work demonstrates that combining ToF-SIMS and MVSA can provide a promising complementary methodology to conventional fingermark morphology analysis, particularly when only small areas of fingermark residue are available.