Analysis & sensing最新文献

Fluorescent sensor arrays address the limitations of a single sensor by leveraging multiple sensing elements to generate unique response patterns for each of the analyte of interest. This approach has emerged as a powerful tool for identifying and analyzing intricate chemical and biological environments using various multivariate analytical tools such as principal component analysis (PCA), linear discriminant analysis (LDA), and hierarchical cluster analysis (HCA). Nevertheless, the extraction of reliable quantitative information from these arrays presents a greater challenge, primarily due to the complexity associated with managing large datasets using conventional regression methods. In recent years, there has been a notable surge in exploring diverse statistical multivariate techniques and deep learning models (including PCA, LDA, HCA, partial least square regression, support vector regression, Gaussian processes regression, and neural networks) as modern regression tools to handle multidimensional data. These analytical tools facilitate the simultaneous acquisition of both qualitative and quantitative information for various analytes using sensor arrays.

Cardiovascular disease (CVD) remains a major cause of mortality worldwide, and there is an urgent need to develop point-of-care (POC) diagnostic tools for rapid, regular, and on-site monitoring of trace levels of cholesterol in human biological fluids. This work presents a new, reliable, selective, and cost-effective POC sensor for salivary examination of CVD. An interdigital device is utilized for electronic (capacitive) detection of cholesterol using nanostructured Ag@MoO₃-enhanced molecularly imprinted poly(styrene-co-divinylbenzene) in real-time salivary analysis. The formulation of cholesterol-imprinted poly(styrene-co-divinylbenzene), molecularly imprinted polymer (MIP), and the operational frequency of the devices are precisely optimized. The Ag@MoO₃-MIP sensors exhibit a low limit of detection of 0.03 μM and a limit of quantification of 0.1 μM with an impressive sensitivity of 409 nF μM⁻¹ in the linear range of cholesterol concentration 0.1–2.0 μM. Furthermore, the sensor exhibits excellent selectivity for cholesterol, effectively distinguishing it from other interfering analytes like ascorbic acid, creatinine, guanine, uric acid, and glucose. The recovery outcomes of real-time spiked saliva samples are within the range of 85.17–98.19%. The sensor's ability to provide reliable, reproducible, and rapid cholesterol analysis in human saliva highlights its potential for early CVD detection and continuous surveillance, leading to improved patient outcomes and more accessible healthcare solutions.

In this study, sulfur-nitrogen-codoped carbon nanodots (N,S-doped CNDs) are synthesized both in their soluble pristine form and incorporated into aminosilica particles. These materials, are utilized for the fluorometric detection of Hg(II) and Cr(VI). Both the soluble N,S-doped CNDs and the aminosilica/N,S-doped CNDs exhibit two distinct emission spectral bands when the excitation wavelength is varied. The fluorescence of soluble N,S-doped CNDs at λ_ex/λ_em = 390 nm/470 nm is quenched in the presence of both Hg(II) and Cr(VI); however, only Hg(II) quenches the fluorescence at λ_ex/λ_em = 450 nm/553 nm. In contrast, only Cr(VI) quenches the fluorescence of aminosilica/N,S-doped CNDs at λ_ex/λ_em = 380 nm/463 nm, while the fluorescence at λ_ex/λ_em = 440 nm/538 nm remains unaffected. By exploiting the fluorescence quenching behavior of free and aminosilica-embedded N,S-doped CNDs, fluorescence-based probes are developed to selectively detect Hg(II) and Cr(VI). The limits of detection, defined as the concentrations corresponding to a signal-to-noise ratio of 3, are determined to be 0.04 and 0.06 μM for Hg(II) and Cr(VI), respectively. Further investigations reveal distinct quenching mechanisms for each system: the fluorescence quenching effect on N,S-doped CNDs by Hg(II) is attributed to a static mechanism, and the quenching of aminosilica/N,S-doped CNDs by Cr(VI) is ascribed to the inner filter effect.

An imidazolium salt (E)-3-(hydroxy-4-(((2-hydroxyphenyl) imino) methyl) benzyl)-1-methyl-1 H-imidazol-3-ium chloride (HBIm) is synthesized and evaluated for its fluorescence behavior toward metal ions. The probe detected Al³⁺ and As³⁺ ions when excited at 326 nm in an aqueous medium. The nonfluorescent HBIm exhibited a “turn-on” fluorescence response upon being treated with Al³⁺ (λ_em = 510 nm) and As³⁺ (λ_em = 499 nm) ions due to the chelation-enhanced fluorescence effect. The detection limits for Al³⁺ and As³⁺ are low and are found to be 0.38 and 2.37 nM, respectively. Furthermore, the binding constants for these ions are significantly high, 1.59 × 10⁵ M⁻¹ for Al³⁺ and 3.54 × 10⁴ M⁻¹ for As³⁺. The binding mechanism between HBIm and Al³⁺ and As³⁺ ions is supported by various techniques, including ESI-MS, Job's plot, ¹H NMR, X-ray photoelectron spectroscopy, SEM-EDS, and density functional theory studies. The reversibility experiments are conducted using EDTA ions to develop the corresponding logic gates. HBIm has the potential to detect Al³⁺ and As³⁺ ions in real samples, such as plant cells, tissues, and water samples.

Industrial wastewater release of dyes poses serious environmental and health risks when introduced into natural water systems. Herein, a cyclodextrin-based polymer sensor (Ech-CDP) is developed for real-time, visible detection of harmful methylene blue (MB) and methyl orange (MO) dyes in distilled and contaminated natural water samples. The sensor works through a competitive host-guest mechanism between sodium dodecyl sulphate (SDS) and Ech-CDP, altering liquid crystal alignment. Initially, SDS induces homeotropic ordering, which shifts to a tilted state upon binding with Ech-CDP. The presence of MB or MO displaces SDS, reverting the alignment and causing a visible bright-to-dark transition under polarizers. The sensor exhibits high selectivity, with detection limits of 0.03 mM for MB and 0.05 mM for MO in aqueous solutions, and 0.08 mM for MB and 0.26 mM for MO in real water samples, remains effective for 3 days, and is unaffected by pH variations between 4.8 and 9.1. Additionally, the sensor demonstrates an on–off switching capability, suggesting potential applications for molecular logic gates and advancing environmental monitoring techniques in dye-polluted waters.

In Brazil, grocery stores and local markets commonly sell handmade cigarettes crafted from cornhusk and treated tobacco. Once a regional tradition, these artisanal cigarettes are now the second most consumed type in the country. Tobacco products contain nicotine (NIC), a highly addictive substance linked to cardiovascular diseases. This study presents an electrochemical synthesis method for a reduced graphene oxide/silver–copper–hexacyanoferrate (rGO/AgCuHCF) composite, optimized for sensitive NIC detection. The optimized material is prepared using a 3:1 Ag:Cu ratio in an initial cyclic voltammetry step, followed by treatment with a pH = 7.0 ferricyanide solution, achieving a sensitivity of 13.0 nA L mol⁻¹ via a 2² factorial design experiment. Microscopic analysis reveals uniformly distributed PBA particles over the wrinkled carbon support, while spectroscopic and diffraction techniques confirm distinct bimetallic PB analogue structural features from monometallic variants. Batch injection analysis-assisted amperometry with the rGO/AgCuHCF-modified electrode exhibits a linear current response for NIC between 5.0 and 2000.0 μmol L⁻¹, achieving a superior sensitivity of 32.9 nA L mol⁻¹ and a low detection limit of 0.9 μmol L⁻¹. This sensor demonstrates viability and reliability for NIC detection in industrial and artisanal cigarettes tobacco samples.

Fluorescent functional materials, particularly luminescent metal–organic frameworks (LMOFs), have been central to material science research over the past decade. Herein, we report a Co-MOF [Co(phen)(5-aipa)]_∞ (phen: 1,10-phenanthroline, 5-aipa: 5-aminoisophthalic acid), synthesized solvothermally, for luminescence-based, recyclable, “turn-on” detection of “tumor biomarker” glutathione (GSH), and industrial pollutant formaldehyde (FA). Sophisticated characterizations, including XRD, XPS, TGA, FESEM, FT-IR, and Hirshfeld analysis, demonstrate high phase purity, thermal stability, robustness, presence of π–π stacking, and weak H-bonding in the framework. The MOF shows low detection limits for GSH (60.37 nM) and FA (9.77 μM) with fast response times (25 s for GSH, <2 min for FA). Biomarker GSH was detected in complex biological samples, including fetal bovine serum, vegetable, and human urine, with recovery rates between 81% and 89%. A smartphone-assisted GSH-sensing platform was proposed via RGB color variations of several sensor-analyte adducts. A 5-input, 4-output molecular logic gate was also demonstrated based on the sensor's spectroscopic response to varying GSH concentrations. FA detection was extended to fish, meat, and wastewater samples, with recoveries of 91–107%. DFT calculations revealed that analyte interactions restricted photo-induced electron transfer in the MOF, enhancing fluorescence phenomenon. These findings open new possibilities for MOF-based sensor technologies.

Xinomavro wine is one of the most renowned Greek varieties, primarily produced in Northern Greece. The Amynteo and Naoussa regions are included in the protected designation of origin (PDO) zones where differences in terroir are evident. These differences occur due to several factors, such as soil conditions of the cultivated vineyards, temperature, altitude, and climatic variations. Herein, 22 Xinomavro wines from Amynteo and Naoussa, produced with an identical vinification procedure are analyzed using ultra high performance liquid chromatography–trapped ion mobility spectrometry–quadrupole time of flight–mass spectrometry (UHPLC–TIMS–QTOF–MS) with reverse phase chromatography and negative ionization mode. The aim is to evaluate the impact of the geographical origin on their phenolic profile. Both target and non-target screening workflows are employed, leading to the identification and quantification of 26 phenolic compounds and the determination of 25 geographical origin biomarkers. Compounds like catechin and hydroxytyrosol are more abundant in samples from Naoussa while Amynteo is characterized by increased concentration of resveratrol and polydatin. All samples are correctly classified based on their geographical origin, achieving satisfactory, Q² = 0.915 and R² = 0.923, prediction ability results, developing a partial least-squares discriminant analysis model.

Electrical noses that mimic the human olfactory system have been developed to detect odors or flavors. Unfortunately, little research on sensing reactions to various odors like a human nose can be found in the literature. Herein, an electronic nose is proposed using a multi-thin film transistor (TFT) sensor array with various polymer selectors and multi-output signal processing to detect various odorants with high selectivity. Through the combination of multi-output produced by eight polymer variables based on indium gallium zinc oxide (IGZO) TFTs, a specific radar pattern and its selectivity are generated for the eight different odor substances. Eight multi-output signal processing reduced the correlation coefficient of similarity from 77.9% to 45% relative to the case of four multi-output processing. Because the polymers have different functional groups, polymers showed specific reactions to various odorants, like the human's system, and multi-output analysis could distinguish various odors, even if polymers did not show single selectivity to a specific odor. And the sensitivity improved when compared to two-terminal structures by using TFTs based on IGZO. The advantage is that it can classify multiple odors with good selectivity and sensitivity. This sensor and signal processing concept can be applied to E-nose systems capable of odor monitoring.