Surface-effect on detection ability of fluorescent Eu(btc) metal-organic frameworks to metal ions

Optical detection strategies for Ni(II) ion using metal-organic chemosensors: from molecular design to environmental applications

Nickel is an important element utilized in various industrial/metallurgical processes, such as surgical and dental prostheses, Ni-Cd batteries, paint pigments, electroplating, ceramics, computer magnetic tapes, catalysis, and alloy manufacturing. However, its extensive use and associated waste production have led to increased nickel pollution in soils and water bodies, which adversely affects human health, animals and plants. This issue has prompted researchers to develop various optical probes, hereafter luminescent/colorimetric sensors, for the facile, sensitive and selective detection of nickel, particularly in biological and environmental contexts. In recent years, numerous functionalized chemosensors have been reported for imaging Ni2+, both in vivo and in vitro. In this context, metal-based receptors offer clear advantages over conventional organic sensors (viz., organic ligands, polymers, and membranes) in terms of cost, durability, stability, water solubility, recyclability, chemical flexibility and scope. This review highlights recent advancements in the design and fabrication of hybrid receptors (i.e., metal complexes and MOFs) for the specific detection of Ni2+ ions in complex environmental and biological mixtures.

Packaged europium/fluorescein-based hydrogen bond organic framework as ratiometric fluorescent probe for visual real-time monitoring of seafood freshness

The freshness of sea food has always been the focus of attention from consumers, and food-safety issues are in urgent need of efficient approaches. A HOF-based ratiometric fluorescence probe (HOF-FITC/Eu) featuring superior amine-response, offers the real-time and visual detection of seafood freshness. Via intermolecular hydrogen bond interaction to form hydrogen-bonded organic frameworks (HOFs), which serve as a structural basis for the conjugate loading of pH-sensitive fluorescein (5-FITC) and coordination doping of lanthanide Eu3+. Amine vapors stimulate the dual-wavelength (525 nm and 616 nm) characteristic fluorescence of HOF-FITC/Eu with an inverse trend, resulting in an increase of the ratio of I525 to I616 accompanied by a distinct color transition from red to green. Prepared HOF-FITC/Eu featuring sensitive red-green color change characteristics of amine response are readily dripped into composite films of filter paper through integrated smartphone and 254 nm UV lamp as mobile observation devices to on-site monitor the freshness of raw fish and shrimp samples. The intelligent food probe HOF-FITC/Eu opens a novel material assembly type for fluorescence sensing and a potential pathway for other functional materials in the field of investigational food.

Machine Learning Algorithms for Intelligent Decision Recognition and Quantification of Cr(III) in Chromium Speciation

Cr(III) is a common oxidation state of chromium, and its presence in the environment can occur naturally or as a result of human activities, such as industrial processes, mining, and waste disposal. This article explores the application of machine learning algorithms for the intelligent decision recognition and quantification of Cr(III) in chromium speciation. Three different machine learning models, namely, the Decision Tree (DT) model, the PCA-SVM (Principal Component Analysis-Support Vector Machine) model, and the LDA (Linear Discriminant Analysis) model, were employed and evaluated for accurate and efficient classification of chromium concentrations based on their fluorescence responses. Furthermore, stepwise multiple linear regression analysis was utilized to achieve a more precise quantification of trivalent chromium concentrations through fluorescence visualization. The results demonstrate the potential of machine learning algorithms in accurately detecting and quantifying Cr(III) in chromium speciation with implications for environmental and industrial applications in chromium detection and quantification. The findings from this research pave the way for further exploration and implementation of these models in real-world scenarios, offering valuable insights into various environmental and industrial contexts.

Fluorescence and electrochemical detection of iodine vapor in the presence of high humidity using Ln-based MOFs

Efficient detection of toxic radioiodine species emitted by nuclear-related activities and accidents is crucial for the health of the human body and safety of the environment. Herein we report that a series of stable Ln-based MOFs with BTC linkers (Ln-BTCs) could provide dual fluorescence and electrochemical response of iodine vapor in the presence of humidity. Iodine molecules could be attracted by the oxygen sites of carboxylate linkers and confined in the cavities of Ln-BTCs. Due to the photoinduced electron transfer effect, the fluorescence of Ln-BTCs is quenched drastically in the presence of iodine. Meanwhile, the conductivity of Ln-BTCs could reach an increase of 107 fold in magnitude after iodine trapping. Water molecules could also be trapped in Ln-BTCs, having interacted with the frameworks via hydrogen bonds, and reduce the iodine uptake capacity, but they cannot alter the fluorescence and conductive properties of Ln-BTCs as distinctly as iodine molecules could. Besides, Raman mapping suggests a diffusion coefficient of 1.5 × 10-14 m2 s-1 for iodine transport in the porous Eu-BTC. The dual fluorescence and electrochemical signal outputs show high sensitivity and attractive ability to reduce false positives, which could be useful for potential integration for sensing radioiodine vapor.