Chemical Papers最新文献

Benzenoid hydrocarbons, ubiquitous members of polycyclic aromatic hydrocarbons, are of significant interest because of their applications in various fields, ranging from toxicological to environmental science. The intriguing nature of aromaticity combined with its importance in predictive carcinogenicity models has created a compelling need for the development of quantitative models for predicting its physicochemical properties. This study introduces topological indices that consider the faces of molecular structures, their associated bond degrees, and generalized reverse degrees. By incorporating these parameters, we aim to develop a newer approach for the prediction of molecular properties by taking into peripheral structural features of the molecular structures composed of benzene rings. We have developed QSPR models using the face indices using a dataset of 79 benzenoid hydrocarbons to predict key physicochemical properties, including boiling points, flash points, retention indices, polarizabilities, heat capacities, enthalpies of vaporization, molar refraction indices, and log P. Furthermore, we validated these models using the leave-one-out cross-validation method, demonstrating strong linear correlations with the studied properties. We also point out that the intriguing face index reported in the literature is the same as a particular case of degree-based indices.

The synthesis of sulfur–nitrogen co-doped Fe₂O₃ nanostructures is crucial for enhancing dye removal efficiency in wastewater treatment. However, optimizing the synthesis process to achieve accurate predictions of dye removal performance remains a challenging task due to the complex interactions between parameters. This research presents a new approach for synthesizing sulfur–nitrogen co-doped Fe₂O₃ nanostructures by hybridizing the similarity-navigated graph neural network (SNGNN) with the Namib beetle optimization (NBO) algorithm, hereafter referred to as the SNGNN-NBO method. The main aim of this work is to accurately predict the methylene blue dye removal efficiency. The SNGNN method is employed to predict the dye removal percentage, ensuring that the synthesis process is optimized for enhanced nanostructure properties. The NBO algorithm is used to optimize the weight parameter of the SNGNN method. The proposed technique is evaluated using MATLAB and compared with various existing approaches, such as ant colony optimization (ACO), artificial neural network-genetic algorithm (ANN-GA), and adaptive particle swarm optimization (APSO). The proposed method achieves a low error of 0.1% and a high dye removal percentage of 98%, outperforming the existing methods. This demonstrates the effectiveness of the SNGNN-NBO approach in accurately predicting and optimizing dye removal efficiency, offering a comprehensive solution for the synthesis of sulfur–nitrogen co-doped Fe₂O₃ nanostructures.

Recent environmental issues, such as climate change, air, water, soil pollution, biodiversity loss, and deforestation, take a heavy toll on the natural ecology of many living being including humans. To ease the situation, scientists and environmentalists are working on innovative approaches to purify and clean our surroundings. This study aims to present a sustainable adsorbent material—cross-linked chitosan bentonite composite to remove the harmful malachite green dye from wastewater system. Dyes are an integral part of many industries and find their way to the natural water bodies through drainage systems carrying effluents. A blend of two environment-friendly and efficient materials, namely chitosan and bentonite, are used for removal of dye molecules. The study includes characterization studies of the adsorbent using techniques of FT-IR, SEM-EDAX, XRD, and TG–DTA analysis along with optimization of operational parameters, such as pH, dose, concentration, and time, through batch adsorption experiments. A mathematical model, response surface methodology has been implemented to the data obtained in order to collect information regarding optimization of the process. Apart from this, the kinetic and isothermal analysis was also performed to get insights of the adsorption phenomena. The observed data on adsorption isotherm correlated to Langmuir isotherm model with adsorption capacity of 333.33 mg L⁻¹ and data on kinetics suggested pseudo-second-order mechanics for uptake of dye with R² value greater than 0.999 showing linear relationship. Furthermore, the fixed-bed or column adsorption method was also studied to evaluate column parameters.

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Fatal human diseases arise from a diverse of microbial infections. Among these, Candida species pose significant challenges in healthcare settings due to their ability to transition morphologically from yeast to hyphal forms, form resistant biofilms, and cause co-infections with other bacterial pathogens. The increasing prevalence of drug resistance to commonly used antimicrobial agents, alongside adverse side effects associated with these treatments, has heightened the demand for safe and effective novel therapeutic options. Plant-derived compounds are recognized for their potential therapeutic properties and may offer promising alternatives. This study investigated the phytochemical composition, antioxidant properties, and cytogenetic effects of hydroalcoholic extracts from Lavandula angustifolia (lavender) and Thymus vulgaris (thyme). Treatment with hydroalcoholic extracts of L. angustifolia and T. vulgaris (100 µg/ml) significantly reduced the expression of key virulence genes (SAP4, BCR1, EFG1, ALS3) and inhibited biofilm formation in C. albicans and C. tropicalis. These effects are attributed to the antifungal and antibiofilm activities of bioactive compounds such as polyphenols, flavonoids, tannins, and terpenoids, and other functionalized phytocompounds, which effectively reduce biofilm formation and induce cellular damage in Candida species.

Graphical abstract

Equiatomic FeNiMnSi, FeNiMnCr, and FeNiMnSiCr alloys were fabricated using the powder metallurgy technique. Thermodynamic calculations classified FeNiMnSi and FeNiMnCr as medium-entropy alloys, while FeNiMnSiCr was identified as a high-entropy alloy (HEA). Among these, FeNiMnSiCr exhibited the highest relative density and the most favorable thermodynamic stability (Ω = 5.57, ∆S_mix = 13.38 kJ/mol K). X-ray diffraction, scanning electron microscopy, and energy-dispersive X-ray spectroscopy confirmed a multiphase microstructure with well-dispersed elements. Mechanical testing revealed that FeNiMnSi and FeNiMnSiCr exhibited higher hardness compared with FeNiMnCr. In corrosion studies, FeNiMnSiCr demonstrated the lowest corrosion rates of 0.41 mm/y in 1 M HCl, 0.11 mm/y in 1 M HNO₃, and 0.46 mm/y in 1 M H₂SO₄, confirming its superior chemical resistance. Surface examinations further revealed reduced micro-galvanic attack compared with FeNiMnSi and FeNiMnCr. Overall, these results highlight FeNiMnSiCr as a promising HEA with a balanced combination of mechanical strength and corrosion resistance.

Biomass-derived bioadsorbents represent an advanced and highly promising approach that can be effectively applied in water treatment, particularly for the removal of pharmaceutical waste substances, which pose a significant environmental risk, especially to aquatic ecosystems. In this study, a powdered bioadsorbent derived from Iraqi date palm frond leaves (IDPFL) as was employed to remove cetylpyridinium chloride (CPC) residues from wastewater. Batch adsorption experiments were designed using the Taguchi method. Four parameters were investigated: concentration (50–250 ppm), adsorbent dose (500–2500 mg/L), shaking speed (50–250 rpm), and shaking time (1–5 h), at an average pH of 7. The Taguchi orthogonal array (L25) consisted of four factors at five levels, with a total of 25 experiments conducted. The optimal conditions determined by Taguchi analysis were an adsorbent dose of 500 mg/L, a mixing speed of 200 rpm, a CPC concentration of 200 ppm, and an adsorption duration of 2 h. Under these conditions, the maximum removal percentage achieved was 74.665%. Eight adsorption isotherm models and four kinetic models were evaluated. The results indicated that the Langmuir adsorption isotherm provided the best fit (R² = 0.9347). Additionally, the pseudo-second-order model aligned perfectly with the kinetic results (R² = 1). The adsorption heat energy, calculated using the Dubinin–Radushkevich isotherm model, was found to be 36 kJ/g, indicating that the adsorption process is favorable and follows a chemisorption mechanism. According to the results, the controlling mechanisms of adsorption are electrostatic interaction and ion exchange. The findings demonstrate that date palm frond powder is a suitable bioadsorbent for the removal of CPC from aqueous solutions and can be effectively utilized in pretreatment stages at treatment facilities located near hospitals or clinical establishments.

Study investigates the electrochromic properties of titanium dioxide (TiO₂) films synthesized by anodic oxidation of titanium in alkali nitrate melts with potassium fluoride additives. The optimal synthesis parameters to achieve a high contrast ratio (K = 7–8) were established: potentiostatic mode, temperature of 625 ± 10 K, voltage of 20 ± 5 V, process duration of 5–12 min, and a KF concentration of 0.01–0.04 mol/kg in a NaNO₃–KNO₃ eutectic melt. A comprehensive characterization of the films was performed using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Fourier transform infrared spectroscopy (FT-IR), and transmission electron microscopy (TEM). The results confirm the formation of a nanocrystalline mixed-phase (anatase and rutile) TiO₂ film with a thickness of ~ 578 nm. EDX analysis revealed the incorporation of fluorine into the oxide matrix, which promotes the formation of oxygen vacancies and enhances ionic conductivity. The nanostructured morphology and optimal defect density are identified as key factors contributing to the superior electrochromic performance. The findings highlight the strong potential of the developed TiO₂ electrodes for application in electrochromic devices, such as smart windows and information displays.

A simple chemical method based on pH-induced precipitation was used to prepare the fluorescent nanosensor (CURNPs), and it was thoroughly characterized. The nanosensor showed high sensitivity and selectivity toward the detection of Co (II) and NO₂⁻ ions in aqueous media. The fluorescence of CURNPs was excited with a 450 nm laser from an in-house-made fluorometer, and it exhibited detection limits in the nanogram range (1.842 ng/0.1 mL) within the calibration range of 0.1–18 μM (which represents a broad linear fit from 0.25 to 14 μM for native curcumin). The fluorescence ‘off–on’ mechanism was caused by quenching due to Co (II) ions and the subsequent recovery of fluorescence by NO₂⁻ ions via the formation of a yellow precipitate. This method enables the detection of NO₂⁻ in the range of 0.5–20 μM at the nanomolar level. For Co (II), the linear range of fluorescence quenching was 0.5–10 μM, and good linearity was obtained (R² = 99.84%, 95% confidence level). The LOD (S/N = 3) was 4.712 ng/mL, significantly much better than previously reported detection limits of conventional methods (58.933 ng/0.1 mL). The method showed high precision (RSD < 0.6%, n = 6) and high throughput (40 samples/hour), requiring only 125 μL per sample. Surface characterization via atomic force microscopy (AFM), scanning electron microscopy (SEM), and Fourier-transform infrared spectroscopy (FTIR) confirmed successful nanoparticle formation, highlighting uniform particle size, defined morphology, and active functional groups. No significant interference from competing ions was observed, confirming high specificity. These findings establish CURNPs as a robust and efficient tool for environmental monitoring of Co (II) and NO₂⁻ ions. Statistical validation using a paired t test and the standard addition method showed no significant deviation (α = 0.05), confirming the nanosensor as a robust alternative for environmental and industrial analyses.