Metal-organic framework functionalized with deep eutectic solvent for solid-phase extraction of Rhodamine 6G in water and cosmetic products

Fluorescence sensor based on Methionine-Modified silver nanoparticles located on Fe-BTC metal-organic framework (Meth-AgNPs@Fe-BTC) for trace detection of fenitrothion pesticide in aqueous samples

This research introduces a new "turn-on mode" fluorescence sensor for the detection of fenitrothion (FNT) pesticide in various samples. The sensor is constructed using a porous metal-organic framework (Fe-BTC) as a template to locate silver nanoparticles (AgNPs) and methionine amino acid (Meth). Methionine acts as a bridge, facilitating the interaction between FNT and AgNPs, which subsequently results in the release of AgNPs from the composite structure. The physicochemical properties of the synthesized Meth-AgNPs@Fe-BTC composite were analyzed by Fourier-transform infrared spectroscopy (FT-IR), Brunauer-Emmett-Teller (BET), X-ray diffraction (XRD), Field emission scanning electron microscopy (FESEM), Energy-dispersive X-ray spectroscopy (EDAX), Transmission electron microscopy (TEM), and elemental mapping (MAP) analysis. The sensing system is based on tracking the fluorescence of the synthetic composite in such a way that the intensity of the fluorescence of the composite increases in the presence of different concentrations of fenitrothion (FNT). The effective parameters on the sensor signal, including composite dosage, pH, sonication and reaction time were investigated and optimized. The calibration graph, under optimal conditions, exhibited linearity in the concentration range of 2-95 nM for FNT, with a limit of detection of 1.9 nM. The suggested sensor was successfully validated by analyzing FNT in several real water samples and fruit juices. This research presents a significant technical achievement in the development of a fluorescence sensor for the detection of FNT, offering a sensitive and reliable method for environmental monitoring and public health preservation.

Green extraction of prostaglandin analogs in cosmetics using deep eutectic solvents and detection via LC-MS/MS

Prostaglandin analogs (bimatoprost, travoprost, tafluprost, etc.) have similar effects to prostaglandins and are effective drugs for treating glaucoma. These compounds exhibit abnormal reactions such as causing eyelash growth, with several cases being reported of people purchasing them to increase eyelash growth; however, some cases have reported side effects such as pigmentation and dry eyes. In the Republic of Korea, cosmetics are not medicines for treating diseases; therefore, cosmetics cannot contain drugs or have labels that could mislead people. However, there are cases in which products claim to elongate and enrich eyelashes. Concerns about the abnormal reactions of these products are constantly growing, and the absence of analytical methods for illicit compounds (prostaglandins and their analogs) in cosmetics (eyelash growth serums) renders monitoring challenging. Accordingly, in this study, we sought to develop an LC-MS/MS method for facile and fast analysis of compounds illegally mixed into eyelash growth serums. Green analytical chemistry has recently emerged because of environmental concerns. In line with this trend, we developed an optimal method by comparing the methods mainly used in cosmetic pretreatment (solvent extraction, QuEChERS, and solid phase extraction) with a method using deep eutectic solvents (DESs), which is an eco-friendly solvent. As a result of validation according to the International Conference on Harmonization guidelines, the limit of detection was 0.20-9.34 ng/mL, and the limit of quantification was 0.60-28.31 ng/mL. Recovery, linearity, precision, and accuracy were within acceptable ranges. Additionally, using the Analytical GREEnness calculator and complex green analytical procedure index tools, we confirmed that the method using the DES was greener than the other methods. In this study, we developed an analytical method for illicit compounds contained in eyelash growth serums, offering an eco-friendly approach for the prevention of the distribution of illegal cosmetics.

Deep-Eutectic-Solvent-Decorated Metal-Organic Framework for Food and Environmental Sample Preparation

Deep eutectic solvent (DES) is distinguished by its unique solvent properties, chemical stability, and eco-friendly nature, which are pivotal in a spectrum of chemical processes. It enhances the sample preparation process by increasing efficiency and minimizing the environmental impact. Metal-organic frameworks (MOFs), which are porous structures formed through coordination bonds between metal ions and organic ligands, are defined by their adjustable pore dimensions, extensive surface areas, and customizable architectures. The integration of DES within MOF to create DES@MOF capitalizes on the beneficial attributes of both materials, augmenting MOFs' stability and versatility while providing a multifunctional carrier for DES. This composite material is both highly stable and readily tunable, establishing it as a leading contender for applications in sample preparation for food and environmental samples. This comprehensive review explores the application of DES-decorated MOF in food and environmental sample preparation and highlights the expansive potential of DES@MOF in diverse fields. We provide a detailed analysis of the characteristics of DES@MOF and its individual components, methods for decorating MOFs with DES, the advantages of these composite materials in sample pretreatment, and their specific applications in food safety and environmental monitoring. DESs are employed to modify MOFs, offering a multitude of benefits that can substantially improve the overall performance and applicability of MOFs. The review also discusses current challenges and future directions in this field, offering valuable insights for further research and development. The synergistic effects of DES and MOFs offer new opportunities for applications in food safety and other areas, leading to the development of more efficient, sensitive, and environmentally friendly analytical methods. This collaboration paves the way for sustainable technologies and innovative solutions to complex challenges.

Development of dispersive solid phase extraction based on magnetic metal organic framework for the extraction of sunitinib in biological samples and its determination by high performance liquid chromatography-tandem mass spectrometry

Herein, a simple, sensitive, and reliable dispersive solid phase extraction was reported for the efficient extraction of sunitinib from biological samples. To facilitate the extraction of the desired analyte from urine and plasma samples, magnetic MIL-101Cr (NH2) @SiO2 @ NiFe2O4 was synthesized by a hydrothermal method and applied as an effective sorbent during the extraction process. After adsorption of the drug using 10 mg of MIL-101Cr (NH2) @ SiO2 @ NiFe2O4 nanoparticles through vortexing (1 min), the sorbent was separatedfrom the sample solution using a magnet. To eluate the drug, the sorbent containing the sunitinib was contacted with 100 µL dimethylformamide. The eluent was analyzed by high performance liquid chromatography-tandem mass spectrometry. Reasonable validation data consisting of low limits of detection (0.14, 0.35, and 0.70 ng mL-1 in deionized water, plasma, and urine) and quantification (0.48, 1.2, and 2.4 ng mL-1 in deionized water, plasma, and urine, respectively), a wide linear range of the calibration curve (0.48-200, 1.2-200, and 2.4-100 ng mL-1 in deionized water, plasma, and urine, respectively) good extraction recovery (76 %), and low relative standard deviations for inter- and intra-day precisions (6.9 %) were obtained by the method. Eventually, the proposed procedure was effectively implemented on both plasma and urine samples, yielding successful outcomes.

Aluminium fumarate biological metal-organic framework as an emerging tool for isolation and detection trace amounts of sulfadiazine in food and water samples

Owing to negative impacts of sulfadiazine (SDZ) as an important group of synthetic antibiotics on public health and ecological systems, it has been a serious concern in recent years. In this research, aluminium fumarate biological metal-organic framework (AlFum Bio-MOF) was synthesized and applied as the best option in terms of extraction performance for detection and quantification of SDZ in a variety of samples. The chemical/structural properties of as-prepared AlFum Bio-MOF were confirmed by spectroscopy techniques. The influence of pH, amount of adsorbent, ultrasonic time (adsorption time (and ionic strength as the main variables in the extraction process were optimized and inspected with central composite design (CCD). Linear dynamic range (LDR), the limit of detection (LOD), and precision value (expressed as relative standard deviation (RSD)) in selected conditions were 20-580, 5.67 ng mL-1, and 3.40 % (n = 3), respectively. The developed method was successfully applied for the determination of SDZ in different water and food samples at two spiked levels with recoveries between 84 and 104 %. Practically, the dispersive micro-solid phase extraction (Dμ-SPE) based on AlFum Bio-MOFs as sorbent could be used to quantify SDZ in complex matrices at trace amounts with acceptable recoveries.

Direct immersion single-drop microextraction combined with fluorescence detection using an optical probe. Application for highly sensitive determination of rhodamine 6G

The use of an optical probe for fluorescence detection combined with direct immersion single-drop microextraction has been demonstrated as an innovative approach. The optical probe served both as a drop holder for extractant and as a measuring device which made it possible to eliminate the use of cuvettes. A laser and a light emitting diode (LED) were tested as possible light sources. Both of them showed comparable results. However, given the much smaller half-band width of the laser radiation, its use has proven to be preferable since background correction can be eliminated. Direct immersion single-drop microextraction of an ionic association complex of rhodamine 6G with picric acid with subsequent fluorescent detection (λex was 532 nm and 525 nm for laser and LED, respectively; λem was 560 nm for both laser and LED) was used a model system to evaluate the new approach. The extractant phase was a 55 μL amyl acetate microdrop fixed in the optical part of the probe. LOD, LOQ and linear calibration range were found as 0.14, 0.48 and 0.5-10 nmol L-1, and 0.15, 0.50 and 0.5-5 nmol L-1 for laser and LED light sources, respectively. The accuracy of the method was assessed by analyzing real water samples.

Exploring the purity of chitin from crustacean sources using deep eutectic solvents: A machine learning approach

OBJECTIVE

Chitin a natural polymer is abundant in several sources such as shells of crustaceans, mollusks, insects, and fungi. Several possible attempts have been made to recover chitin because of its importance in biomedical applications in various forms such as hydrogel, nanoparticles, nanosheets, nanowires, etc. Among them, deep eutectic solvents have gained much consideration because of their eco-friendly and recyclable nature. However, several factors need to be addressed to obtain a pure form of chitin with a high yield. The development of an innovative system for the production of quality chitin is of prime importance and is still challenging.

METHODS

The present study intended to develop a novel and robust approach to investigate chitin purity from various crustacean shell wastes using deep eutectic solvents. This investigation will assist in envisaging the important influencing parameters to obtain a pure form of chitin via a machine learning approach. Different machine learning algorithms have been proposed to model chitin purity by considering the enormous experimental dataset retrieved from previously conducted experiments. Several input variables have been selected to assess chitin purity as the output variable.

RESULTS

The statistical criteria of the proposed model have been critically investigated and it was observed that the results indicate XGBoost has the maximum predictive accuracy of 0.95 compared with other selected models. The RMSE and MAE values were also minimal in the XGBoost model. In addition, it revealed better input variables to obtain pure chitin with minimal processing time.

CONCLUSION

This study validates that machine learning paves the way for complex problems with substantial datasets and can be an inexpensive and time-saving model for analyzing chitin purity from crustacean shells.

Fe3O4-lignin@Pd-NPs: A highly active, stable and broad-spectrum nanocomposite for water treatment

In this work, we report an environmentally friendly renewable nanocomposite magnetic lignin-based palladium nanoparticles (Fe3O4-lignin@Pd-NPs) for efficient wastewater treatment by decorating palladium nanoparticles without using any toxic reducing agents on the magnetic lignin abstracted from Poplar. The structure of composite Fe3O4-lignin@Pd-NPs was unambiguously confirmed by XRD, SEM, TEM, EDS, FTIR, and Zeta potential. After systematic evaluation of the use and efficiency of the composite to remove toxic organic dyes in wastewater, some promising results were observed as follows: Fe3O4-lignin@Pd-NPs exhibits highly active and efficient performance in the removal of toxic methylene blue (MB) (up to 99.8 %) wastewater in 2 min at different concentrations of MB and different pH values. Moreover, except for toxic MB, the other organic dyes including Rhodamine B (RhB), Rhodamine 6G (Rh6G), and Methyl Orange (MO) can also be removed efficiently by the composite. Finally, the easily recovered composite Fe3O4-lignin@Pd-NPs exhibits well stability and reusability, and catalytic efficiency is maintained well after ten cycles. In conclusion, the lignin-based magnetism Pd composite exhibits powerful potential practical application in industrial wastewater treatment.