Chemical Papers最新文献

In this research work, a biobased coating solution was developed based on chitosan (CS) and guar gum (GG) crosslinked with sodium tripolyphosphate (STPP) to introduce water-repellent and functional properties to cotton textiles. The coating blend was developed to contain 1% chitosan, 1.5% guar gum, 0.09% STPP, and 1.5% glycerol. The cotton textiles were treated using a dip-coating technique followed by drying at ambient temperature. FTIR and SEM analysis has affirmed the successful deposition of the coating solution on the textile surface. The coated textile exhibited significant hydrophobicity, as evidenced by a water contact angle values of 130.4 ± 1.3°. Hydrophobic property was retained (with contact angle values of 98.6 ± 0.4˚) after fourteen (14) washing cycle with water. The coating slight reduction in mechanical properties of the coated cotton textile sample was observed compared to the uncoated sample. Furthermore, the treated textiles exhibited inhibition zones of 16.7 ± 1 mm against S. aureus and 10.6 ± 0.1 mm against C. albicans, indicating significant antimicrobial efficacy. These findings underscore the potential of chitosan/guar gum-based composite coatings for the development of advanced cotton textile with enhanced functional properties, suitable for a broad spectrum of applications.

A method for producing high-quality gasoline is through the catalysis of naphtha, which is essential for environmental protection in the industry. Given the high energy consumption, energy optimization is crucial for global development. Therefore, exergoeconomic and sensitivity analyses are necessary to enhance energy efficiency in processes. In this study, the catalytic modification process of naphtha in the refinery is simulated using Aspen Plus software. Subsequently, the exergy degradation parameters, exergoeconomic factor, and relative costs of the devices are calculated using exergoeconomic analysis. According to the results of the exergy analyses, the greatest destruction of exergy occurs in the distillation tower (T-1) with a value of 3,692,123.250 kJ/s. Additionally, the highest exergy efficiency is associated with the distillation tower (T-1), which has a value of 98.784%. The outcomes of the exergy analyses indicate that the distillation tower (T-1) has the largest destruction of exergy cost rate at $31.056/h, while one of the mixers (M-2) has the smallest at zero. Furthermore, the results show that the furnace (B-3) has the greatest exergoeconomic factor at 77.951%, while the mixers (M1 and M2) have the smallest.

The current study investigates the sorptive potential of raw Spirogyra maxima biomass (RSB) and carbonized Spirogyra maxima biomass (CSB) for malachite green dye removal by integrating experimental studies with machine learning-driven optimization. Surface analysis revealed significant morphological changes with enhanced porosity and surface roughness following carbonization. X-Ray diffraction analysis showed a structural shift in CSB with amorphous content to 92.9%. Mechanistic modeling identified Sips isotherm and pseudo-first-order kinetics as best fit models with higher monolayer sorptive capacity of 140.2 mg/g for CSB than RSB which can only adsorb 78.67 mg/g of malachite green. Machine learning modeling demonstrated superior predictive artificial neural network (ANN) model performance configured with 80 neurons achieving R² value of 0.9996. The best performance for the Random Forest (RF) model was observed at 175 trees, achieving an R² of 0.9637, with mean squared error (MSE) of 18.85 and root mean square error (RMSE) of 4.34. The RF model’s out-of-bag (OOB) error stabilized beyond 150 trees, confirming the generalization capability and stability. The ANN model excelled in capturing the complex sorption nature with close relation to experimental results in the comparative analysis. The reusability studies confirmed the superiority of CSB for five reusability cycles retaining more than 70% of adsorptive activity. The research highlights the significance of integrating machine learning models such as Artificial Neural Network and Random Forest models with experimental adsorption studies for achieving efficient dye treatment.

Graphical Abstract

In drug structure research, distance-based parameters are essential as they enable graph representations to accurately identify and characterize chemical structures. This approach provides a more comprehensive understanding of molecular characteristics and behavior. Within graph theory, a resolving set is a subset of vertices where each vertex in the graph is uniquely identified by its distance vector to the vertices in this set. The metric dimension is the minimum size of such a resolving set. In pharmaceutical research, the metric dimension serves as a valuable measure of structural similarity and difference between molecules. This paper discusses the metric dimensions of several classes of oral hypoglycemic medication compounds, including sulfonylureas, meglitinides, biguanides, thiazolidinediones, (alpha)-glucosidase inhibitors, DPP-4 inhibitors, SGLT2 inhibitors, and cycloset. Our analysis confirms that each of these molecular graphs possesses a unique metric dimension, signifying their structural distinctness. While some drugs share the same metric dimension, others exhibit significant differences that distinguish them despite structural similarities. These variations in metric dimension enhance the effectiveness and accuracy of molecular structure identification, establishing it as a powerful parameter in graph-based pharmaceutical research.

Microfluidic technology has seen remarkable advancements in recent years, drawing significant attention in the field of pharmaceutical sciences under the term “Pharm-Lab-on-a-Chip.” Its appeal lies in numerous advantages, including high throughput, rapid detection, minimal reagent usage, efficient analysis, and compact design. Accordingly, the microfluidic platform is a promising pharmaceutical analysis tool. This review covers the advancements and utilization of microfluidic chip technology in pharmaceutical and pharmacological analysis. Firstly, the basic structure of a microfluidic chip was introduced, along with the fabrication of microfluidic chips. Subsequently, the use of the microfluidic chip in pharmaceutical analysis was discussed, with particular attention paid to the separation and analysis of drug molecules on the chip and integrating a microfluidic chip with other techniques. Furthermore, the role of microfluidic chips in pharmacological analysis was explored, mainly focusing on applying chip-based models for assessing the effectiveness and safety of drugs.

Graphical abstract

Recently, significant attention has been given to the development of adsorbents for the removal of lead ion from wastewater due to its toxicity and persistence. This review compiles and assesses 143 adsorbents, all demonstrating high Pb retention capacity. To aid in practical selection, a guideline was developed based on the following primary metrics: (a) uptake capacity (500–2000 mg/g), (b) reusability (5–15 cycles with 80–90% removal efficiency), (c) activity for Pb ions in the presence of common ions in wastewater, and (d) activity for multiple pollutant types. Based on this framework, CuFe₂O₄–sepiolite emerged as an excellent Pb adsorbent, with an uptake capacity of 1285 mg/g, a treatment time of 90 min, reusability for 5 cycles with a final efficiency of 95%, a high anti-interference ability for Ca²⁺, Mg²⁺, K⁺, and Na⁺, and simple isolation from the treated solution via an external magnet. Similarly, chitosan and amino-modified hydrogel were also identified as practical adsorbents, with uptake capacities ranging from 930 to 990 mg/g, reusability over 3–15 cycles with final efficiencies of 87%, high anti-interference ability for wastewater ions like Ca²⁺, Mg²⁺, and K⁺, and activity for removing Cu²⁺ and Fe³⁺. While the focus is on lead ions, the proposed guide is adaptable for identifying practical adsorbents targeting other pollutants, including dyes, phenols, and pesticides. The current review contributes an organized evaluation framework that creates key performance indicators, introducing a broader, more flexible comparison than typically existed in the literature.

Graphical abstract

At the Pardis Petrochemical Complex, the flue gas produced as a byproduct of natural gas reforming functions as a high-temperature thermal energy source. This investigation formulates an integrated trigeneration system that employs this thermal energy source and undertakes a thorough thermodynamic assessment. The flue gas energy facilitates the Kalina cycle and absorption chiller via two heat exchangers, while the residual heat generated by the Kalina cycle is utilized for the production of freshwater via seawater desalination. The simulation of the system was executed utilizing Aspen HYSYS software. The results of the base case demonstrate the generation of 3318 kW of electrical energy, 1119 kW of cooling capacity, and 12,710 kg/h of freshwater. Moreover, the analysis discloses that the total exergy destruction, exergy efficiency, and energy efficiency of the process are quantified at 6844 kW, 33.04%, and 14.94%, respectively. A parametric analysis was performed to optimize the system. The sensitivity analysis suggests that at a working fluid temperature of 195 °C and a pressure of 4500 kPa within the Kalina section, exergy destruction is minimized, while the production of system entropy is augmented. Under these specific conditions, the energy and exergy efficiencies are enhanced to 17.39% and 35%, respectively, accompanied by a total reduction in exergy destruction of 2.92%.

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Ciprofloxacin (CIP) has been detected frequently in aquatic resources at upsetting attentions, which has created a growing concern. The key focus of this study is to examine ciprofloxacin removal using MgO/C nanocomposite. The synthesized magnesium oxide nanoparticle embedded with carbon substrate was employed as a catalyst for ciprofloxacin removal from the water-based solution. The research encompasses a multifaceted analytical approach, for instance, FTIR, BET, XRD, and SEM with EDAX. FTIR confirms the presence of Mg–O stretching bond in the range of 738 cm‾¹. The SEM analysis confirms the formation of agglomerated spherical particles. EDAX confirms the presence of carbon at 64.45 percent, magnesium at 6.02 percent, and oxygen at 26.68 percent. The BET reveals a high surface area of 548 m²/g and 60% total porosity, with a predominantly mesoporous (2–10 nm) structure. XRD indicates the MgO/C nanocomposite as a cubic rock salt structure at the peak range of 29, 41, and 61, corresponding to the nanoparticles. The CIP removal involves optimal constraints such as pH-6, dosage-1.25 g/L, ciprofloxacin concentration-25 mg/L, time-40 min, and temperature of 30 ℃. The study focuses on the isotherm and kinetics model providing supporting technical data for a better understanding of the adsorption behavior. The best-fit model for MgO/C nanocomposite was found to be Langmuir with an R² value of 0.9705 and pseudo-first-order kinetics. The investigation reports the efficiency of MgO/C nanocomposite in treating CIP through a cost-effective approach while promoting ecological sustainability.

The study focuses on the structural and analytical characterization of two newly synthesized molecular salts: flunarizinium picrate (FLUPA) and meclizinium picrate (MECPA). It is confirmed that both FLUPA and MECPA are crystallized in the monoclinic system with (text{P}{2}_{1}/c) and C2/c, respectively. Variations in bond lengths and angles confirm proton transfer from picric acid (PA) to the flunarizine (FLU)/meclizine (MEC) molecules. A bifurcated N−H⋯O intermolecular linkages was observed in between the FLU/MEC cation and picrate anion in both molecular salts. Two adjacent binary heterosynthons are identified, with graph sets ({R}_{2}^{2}left(8right)) and ({R}_{2}^{2}left(9right)) connecting C−H⋯O interactions between FLU and PA. Meanwhile, the FLU molecules are also interconnected through C−H⋯F linkages, as confirmed by the 11.7% contribution of F…H to the 2D fingerprint plot. Each picrate ion in MECPA is connected to neighboring MEC ions via N−H⋯O and C−H⋯O interactions, forming ({R}_{2}^{1})(6) and ({R}_{2}^{2})(8) ring motifs, hence stabilizing the crystal packing. The evidence for the formation of strong hydrogen bonds through N−H⋯O interactions was confirmed by IR and density functional theory analysis. The significant contribution of H∙∙∙H, O∙∙∙H, C∙∙∙H and F…H intercontacts to 2D fingerprint plot confirms the importance of N−H⋯O, C−H⋯O and C−H⋯F (FLUPA) interactions in stabilizing the supramolecular assembly. The bowtie patterns with colored segments (red and blue) observed on the shape index diagram of FLUPA and MECPA suggested the existence of π⋯π stacking interactions which is further supported by the curvedness plots. A detailed analysis of the supramolecular packing of FLUPA and MECPA is presented.

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This study explores the corrosion behavior of cast AZ92 magnesium alloy modified with 0–3.0 wt% Y₂O₃ produced by a stir casting process in 3.5% NaCl solution, both with and without inhibitors 0.01 mg/L AgNO₃, 0.01 mg/L Ce(NO₃)₃, and 0.01 mg/L Mo(NO₃)₂. A novel approach combining gravimetric analysis, electrochemical techniques (EIS, polarization), and response surface methodology (RSM) was used to optimize corrosion resistance (CRST). Results reveal that 2.5 wt% Y₂O₃ provides the lowest corrosion rate (0.80 mm/y) when Ce(NO₃)₃ present, which is attributed to refinement of β-phase. SEM confirmed compact Mg(OH)₂-rich surface films, while RSM identified Y₂O₃ content as the most influential factor (F = 531.18, p = 0.000), followed by time and media. Electrochemical tests showed enhanced polarization resistance (up to 1901.7 Ω) and stable passive films at 1.5–2.5 wt% Y₂O₃. However, higher Y₂O₃ levels reduced protection due to film instability and agglomeration. The synergistic role of Y₂O₃ and Ce(NO₃)₃ was most effective, with optimal conditions predicted by RSM. These findings provide a promising corrosion control strategy using rare earth oxides and multivariate optimization.