ChemistryOpen最新文献

The growing demand for sustainable and efficient photocatalysts has driven extensive research into aluminate-based materials due to their high stability, tunable electronic properties and promising photocatalytic performance. Nanocomposites derived from ZnAl₂O₄, MgAl₂O₄, CaAl₂O₄, and SrAl₂O₄ have shown remarkable potential in environmental remediation, particularly in the degradation of organic pollutants under light irradiation. This review explores the synthesis strategies, structural modifications, and performance enhancements of these aluminate-based nanocomposites. Special emphasis is placed on the role of heterojunction engineering, ion doping, and band structure modulation in optimizing charge carrier dynamics and reducing recombination losses. Furthermore, the photocatalytic mechanisms of these materials are critically analyzed through the lens of energy band theory and interfacial charge transfer. The review also identifies current challenges and outlines future research directions, highlighting the potential of aluminate nanocomposites in advanced photocatalytic applications. By providing a systematic overview of their design principles and functional properties, this work aims to serve as a valuable resource for developing next-generation photocatalysts with superior efficiency and stability.

Polygonum cognatum (Madımak) is a plant traditionally consumed for medicinal purposes in Turkey. Unlike previous studies examining samples from different regions and seasons, this research presents the first comprehensive characterization of P. cognatum collected from the Central Black Sea Region (Tokat, 40°01'02″N, 36°28'15″E; 1210 m altitude) during the vegetative growth phase (June 2024), where geographical origin and collection time significantly influence secondary metabolite profiles. This study evaluates the phytochemical profile and multitarget biological activities of P. cognatum extracts obtained using solvents of different polarities (hexane, ethanol, and water). Advanced analytical techniques (liquid chromatography-tandem mass spectrometry, high-performance liquid chromatography-diode array detector, and gas chromatography-mass spectrometry) identified 28 phenolic compounds, with the ethanol extract showing the highest diversity (24 compounds) and total phenolic content (78.6 ± 2.3 mg GAE/g). Compounds identified for the first time in P. cognatum include isoquercetin-3-O-rhamnoside, apigenin-7-O-glucoside, and luteolin-4'-O-glucoside. The ethanol extract demonstrated superior multitarget bioactivity: potent antioxidant activity ( 2,2-diphenyl-1-picrylhydrazyl (DPPH) IC₅₀: 76.4 ± 2.1 μg/mL), moderate but selective anti-inflammatory effects (COX-2 IC₅₀: 145.3 ± 5.2 μg/mL; selectivity index: 2.06, indicating preferential COX-2 inhibition over COX-1) and significant antidiabetic potential (α-amylase IC₅₀: 89.3 ± 3.1 μg/mL; α-glucosidase IC₅₀: 76.8 ± 2.9 μg/mL), and antimicrobial activity (MIC: 62.5 μg/mL against S. aureus). Notably, this study demonstrates for the first time the histone deacetylase (HDAC) inhibitory activity of P. cognatum (IC₅₀: 92.4 ± 3.8 μg/mL), revealing novel epigenetic modulation properties. Molecular docking studies showed strong correlations between binding affinities and experimental IC₅₀ values (r = -0.87 to -0.91; p < 0.01). Cytotoxicity evaluation showed favorable safety profiles (CC₅₀ > 500 μg/mL). Docking, IC₅₀, and compositional data consistently indicate that quercetin, rutin, chlorogenic acid, and kaempferol are key contributors to the observed antioxidant, antidiabetic, anti-inflammatory, and HDAC inhibitory effects. These findings establish P. cognatum as a promising multitarget therapeutic agent with novel epigenetic regulatory mechanisms, supporting its potential development for inflammatory, metabolic, and epigenetic-related disorders.

Electrochemical CO₂ reduction provides a promising strategy for reducing greenhouse gas emissions by converting CO₂ into chemicals such as ethylene. Integrated CO₂ electrolysis, using CO₂-enriched absorbent solutions, is a cost-effective alternative to gas-fed systems due to reduced process complexity. However, for industrial applications, the process parameters need to be optimized to enhance selectivity and efficiency. Despite advances in catalyst and cell design, the impact of operational factors like catholyte flow rate, pressure, and temperature on C₂₊ product selectivity remains largely unexplored. This study systematically investigates the effects of catholyte flow rate, overpressure, and temperature on ethylene selectivity in integrated CO₂ electrolysis with a potassium carbonate absorbent. Our results show that increasing the catholyte flow rate enhances the Faraday efficiency for ethylene by mitigating mass transport limitations between the flow field and the catalyst layer, whereas increasing pressure or temperature does not yield similar improvements. This insight shifts the focus from stoichiometric availability of physically dissolved CO₂ to mass transport limitations, suggesting that further advances in cell design could unlock higher conversion efficiencies. Our study provides a foundation for scaling up integrated CO₂ electrolysis by highlighting the importance of improving mass transport, a key step toward industrial implementation of sustainable CO₂ conversion technologies.

Although corrosion prevention methods have been studied for many years, they still maintain their relevance and popularity. Today's metal protection methods are desired to be cheap, easy to use, permanent, and effective, as well as environmentally friendly. Organic-based inhibitors are preferred due to their effectiveness and environmental benefits. Among these, organic acids, such as quinic acid, are particularly valued for their corrosion inhibition properties. Quinic acid, an organic acid found in various plants, serves as an effective corrosion inhibitor for mild steel in 0.5 M HCl solutions. This study evaluates its corrosion inhibition efficiency and stability under different storage conditions. Electrochemical techniques, including electrochemical impedance spectroscopy and polarization curve analysis, are employed to assess the inhibition performance. Surface characterization is conducted using scanning electron microscopy, atomic force microscopy, energy-dispersive X-ray spectroscopy, and contact angle measurements. Additionally, density functional theory analysis is performed to elucidate the molecular interactions of quinic acid. Experimental results demonstrate that quinic acid, at a concentration of 80 ppm in 0.5 M HCl, achieves a corrosion inhibition efficiency of 92% and maintains stability for up to 144 h. Environmentally friendly quinic acid has a high potential for use as inhibitors of mild steel corrosion.

Hydrogel adhesives have attracted significant attention for diverse biomedical applications, including tissue engineering, wound dressings, crack propagation prevention, and hemorrhage control. In this study, a tissue adhesive composed of polyethylene glycol, tannic acid, and gelatin, with different concentrations of silk fibroin (SF), was synthesized and systematically evaluated using fourier transform infrared, scanning electron microscopy (SEM), adhesion strength tests, swelling and degradation analysis, cytotoxicity and proliferation studies and antibacterial assays. Structural analysis confirmed the presence of strong hydrogen bonds among the components, while SEM imaging revealed a porous morphology for all samples. Mechanical testing demonstrated that the incorporation of SF additive significantly influenced the adhesion strength of the hydrogels. Furthermore, an increase in SF content led to a significant reduction in swelling capacity and degradation rate. The adhesive samples exhibited excellent biocompatibility, and antibacterial assays indicated that the SF additive maintained antibacterial efficacy comparable to the samples without the additive. These findings highlight the synthesized tissue adhesive as a promising candidate with favorable mechanical and biological properties for potential clinical applications in tissue engineering and wound healing.

Organic synthesis under hydrothermal conditions provides a green and environmentally friendly method that can minimize waste and avoid toxic byproducts. In this study, we investigate ester aminolysis in hydrothermal water at 250°C and P_sat. Among the studied substrates, ethyl acetate with benzylamine yields the highest amide concentration, followed by ethyl acetate with cyclohexylamine and ethyl benzoate with benzylamine. Time-series experiments reveal that a dominating pathway initiates with hydrolysis of ester to form carboxylic acid, followed by the condensation between the acid and amine. The reaction proceeds more efficiently under neutral and basic than acidic conditions, suggesting the protonation of amines at lower pH inhibits the amide formation. The effects of common metal salts, such as NaCl, FeCl₃, FeCl₂, CuCl₂, and ZnCl₂, on amide hydrothermal synthesis are also studied, in which all tested metal salts show an inhibition on the amide yield. In the phosphate-buffered experiments, however, most of the metal salts show an increase in amide formation compared to the non-buffered experiments, suggesting the inhibition from the metal salts is caused by the decrease of pH in dissolved metal solutions. These findings suggest another feasible synthetic pathway of amides under hydrothermal conditions, which is subject to the solution pH and complexation with metal ions.

This work aims to develop an approach for the systematic determination of the formation and sublimation enthalpies of inorganic compounds using the examples of potassium bicarbonate, potassium carbonate, and potassium formate. The standard enthalpies of formation in the solid and gas phases are determined using solution calorimetry and the G4 method, respectively, while the enthalpies of sublimation are calculated from lattice energies. Density functional theory (DFT) calculations at the PBE-D3/projector-augmented-wave level are well-suited to determine sublimation enthalpies based on lattice energies and thus to validate the standard enthalpies of formation of inorganic compounds in the solid and gas phases. The uncertainty associated with the determination of standard formation enthalpies in the solid phase using solution calorimetry is roughly 0.5 kJ·mol^-1, while the uncertainty of sublimation enthalpies from DFT calculations is approximately less than 10 kJ·mol^-1, consistent with recent benchmark studies on representative molecular test sets. Given that the determination of sublimation enthalpies for salts based on vapor pressures is currently not feasible with existing techniques, DFT calculations are a promising approach for determining this quantity. In conclusion, the combination of solution calorimetry and quantum-chemical calculations offers a consistent framework for determining key thermodynamic properties of inorganic salts.

In this work, we study the linear and nonlinear optical properties of a novel quinolinone-chalcone derivative, namely, 4(1H)-quinolinone-(E)-4-chlorobenzylidene-4-chlorophenyl-phenylsulfonyl with formula C₂₈H₁₉Cl₂NO₃S. Theoretical calculations of the electrical properties of the quinolinone-chalcone derivative crystal were performed at density functional theory DFT/CAM-B3LYP/6-311++G(d, p) level, both in the static and dynamic regimes. To simulate the crystalline environment, an electrostatic iterative charge embedding approach was employed, which revealed a redistribution of electronic density arising from crystalline polarization effects. This approach revealed a significant enhancement in the molecular dipole moment ( $\mu \approx 5.95D$ ) due to crystal packing effects. The calculated third-order nonlinear susceptibility at 532 nm was found to be ${\chi }_{Kerr}^{\left(3\right)}\approx 162.52\times {10}^{-22}{\left(m/V\right)}^2$ , with a highest occupied molecular orbital-lowest unoccupied molecular orbital gap of 4.14 eV, indicating a good potential for optical switching applications. Future experimental validations via Z-scan and third-harmonic generation measurements are proposed to corroborate these theoretical predictions.

The conversion of glucose to fructose is an important step for the formation of biofuels, fine chemicals and in the food industries. Mg²⁺ is the most abundant divalent cation in living cells and sea water and could be an environmentally friendly biomimetic catalysts for glucose-to-fructose isomerization in water, while holding relevance to prebiotic chemistry. Here, we demonstrate that the catalytic performance of MgCl₂ can be tuned using strategies that limit the presence of basic oxide. Upon calcination and reaction under N₂, glucose isomerization in water at 120°C approached the thermodynamic equilibrium (≈42% fructose) within 30 minutes. Isotope tracking showed that the isomerization proceeds via competing pathways. Compared to Al³⁺ and Cr³⁺, the stereoselectivity is considerably lower for Mg²⁺ than for Al³⁺ and Cr³⁺. Effects of formic acid on the initial rate of glucose-to-fructose isomerization showed a slowing of the reaction catalyzed both by Mg²⁺, Al³⁺, and Cr³⁺. Inhibition decreased in this order, which resembles decreasing pKa values of the metal ions in aqueous solution. Hydrolysis of aqua ions appears to generate active species for the 1,2-hydride shift in all cases, where the formation of transient and non-specific interactions between Mg²⁺ and carbohydrate results in a moderate stereoselectivity.

In scientific documents, molecule structure information is usually delivered by chemical structure images. Although convenient for human interpretation, the image-based molecule structure depiction is not a machine-readable format, blocking productivity improvements in many fields including chemical data mining and drug discovery. Molecule structures can be modeled as graphs with atoms as nodes and bonds as edges. Following this intuitive modeling, optical chemical structure recognition (OCSR) can be achieved by first detecting individual atoms and bonds and then assembling into a graph. However, the challenges in decision ambiguity due to false positives and spatial proximity during graph assembly is rarely explained and explicitly addressed. In this work, we present a rule-based probabilistic OCSR model to explain and tackle the ambiguity challenges in graph assembly. We developed a novel line detection algorithm for precise bond line identification, and designed a candidate mechanism with probabilistic graph to resolve atom/bond ambiguity. The proposed model is evaluated with popular large image datasets and achieved outperforming recognition accuracy compared to state-of-the-art solutions.