Chemical Papers最新文献

This work investigates the use of N-(2-(2-pentadecyl-2,5-dihydro-1H-imidazol-1-yl)ethyl)palmitamide palmitate (PIP) in 1 M H₂SO₄ solution as an anti-corrosive agent for Q235 steel. By using a range of methods including electrochemical tests, weight loss, scanning electron microscopy, atomic force microscopy, contact angler, and X-ray photoelectron spectroscopy were used for the analysis of PIP inhibition potential. The extract molecules formed an adherent and homogenous protective film on the MS surface. When the PIP concentration increased, a stronger inhibition effect against corrosive attack was obtained. The highest obtained inhibition efficiency is 97.65% at 100 mg/L PIP alone and 98.04% at 25 mg/L (PIP) + 0.5 mM potassium iodide. Polarization measurements showed the mixed type inhibitive nature of the PIP with cathodic dominancy. The various kinetic and thermodynamic parameters of metal dissolution and PIP adsorption processes were evaluated from the weight loss methods in order to elaborate the adsorption mechanism. Adsorption of inhibitor obeyed Langmuir adsorption isotherm. Furthermore, an active relationship involving PIP and the Q235 steel surface was highlighted by computational studies, such as density functional theory and molecular dynamics simulation that are demonstrating outstanding mitigation properties.

A fluorescent switch based on graphene quantum dots (GQDs) has been synthesized and modified using luminol to detect Fe (III) in human urine selectively. The pyrolysis of anhydrous citric acids produced GQDs abundant in amino groups. The luminol modification shows distinct optical characteristics, improving the fluorescence intensity by approximately 6.41 times compared to GQD alone. The probe employs static quenching to initiate the fluorescence response by utilizing the interaction between Fe (III) and luminol-GQDs, resulting in the suppression of fluorescence. The probe is capable of detecting Fe (III) in both a pure aqueous solution and synthetic urine. Furthermore, it is also able to detect Fe (III) in human urine. The concentration of Fe (III) required to quench the fluorescence intensity of luminol-GQDs exhibits a strong linear relationship. A good linear relationship was obtained for Fe (III) concentrations ranging from 50 to 400 μM. Notably, this sensitivity surpasses that of earlier studies. The detection limit of Fe (III) using luminol-GQDs is approximately 1.5 μM. The real sample detection was conducted using a human urine sample, and satisfactory recoveries of approximately 94.57% were achieved.

The hazards of pollution are highlighted by gas exposure, and creating effective adsorbents is essential for maintaining clean air, the environment, and human health. In our study, employing the DFT/M062x/def2svp level of theory, the potentials of metal-doped (Na, Zn, and Al) fullerene surfaces as efficient adsorbents for CN, CNCl, and NO₂ gases were evaluated. Investigation revealed that the introduction of metal dopants has visible impacts on the structural and electronic properties of fullerene surfaces. Specifically, a slight increase in the bond length of C–C bonds, with protruded bonds forming between the doped atoms and carbon atoms, was observed. The obtained energy gap (Eg) demonstrated a consistent reduction across the doped surfaces, indicative of heightened sensitivity toward the gas analytes. C59Al exhibited a higher Eg (3.876 eV), while C59Zn displayed a lower value (3.103 eV) compared to C59Na. Topology analysis using the quantum theory of atoms in molecules (QTAIM) predicted non-covalent interactions between gas analytes and metal-doped fullerene surfaces, a finding that was further substantiated by the analysis of non-covalent interactions. Focusing on CN gas adsorption, distinct behaviors emerged, where C59Na exhibited strong adsorption (Eads = −2.67 eV), surpassing C59Al (−1.82 eV) and C59Zn (−0.64 eV). A similar trend was observed for CNCl and NO₂ gas adsorption, with C59Na consistently showing higher adsorption energies. This alignment was corroborated by frontier molecular orbital (FMO) and natural bond orbital (NBO) analyses. The results for dipole moment and recovery time emulated those of adsorption energy, emphasizing the stability and uniformity in adsorbed states. This collective evidence highlights the potential of doped surfaces to effectively adsorb specific gas molecules, offering insights into their applicability in gas sensing and environmental remediation.

The presented paper is focused on the analysis of combustion behaviour and solid-state kinetic data of oxidation reactions of Soma-Manisa and Gediz-Kütahya lignite. Oxidation process was carried out with NI-TGA and tube furnace. The samples are heated up at temperature range from 25 to 1100 °C under multiple constant heating rates 10 °C/min, 15 °C/min, 20 °C/min and 30 °C/min in nitrogen atmosphere. Combustion characterizations of coal samples are studied by X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). Kinetic data analysis is based on model-free approaches by Kissinger-Akashiro-Sunose (KAS) and Ozawa-Flynn-Wall (OFW) with the helping of data during experimental study. The estimated kinetic constants are compared with experimental results. Oxidation parameters such as weight loss rate, burn-out temperature and reactivity of coal samples are calculated. Maximum weight loss rates are estimated at 0.54%/min Soma-Manisa lignite and 0.51%/min and Gediz-Kütahya lignite at 30 °C/min heating rate. Activation energies of coal samples are exhibited in the range 37.6—63.7 kJ/mol and 41.5–74.5 kJ/mol using OFW and KAS methods, respectively.

The pH detection helps control food quality, prevent spoilage, determine storage methods, and monitor additive levels. In the previous studies, colorimetric pH detection involved manual capture of target regions and classification of acid–base categories, leading to time-consuming processes. Additionally, some researchers relied solely on R*G*B* or H*S*V* to build regression models, potentially limiting their generalizability and robustness. To address the limitations, this study proposed a colorimetric method that combines pH paper, smartphone, computer vision, and machine learning for fast and precise pH detection. Advantages of the computer vision model YOLOv5 include its ability to quickly capture the target region of the pH paper and automatically categorize it as either acidic or basic. Subsequently, recursive feature elimination was applied to filter out irrelevant features from the R*G*B*, H*S*V*, L*a*b*, Gray, X_R, X_G, and X_B. Finally, the support vector regression was used to develop the regression model for pH value prediction. YOLOv5 demonstrated exceptional performance with mean average precision of 0.995, classification accuracy of 100%, and detection time of 4.9 ms. The pH prediction model achieved a mean absolute error (MAE) of 0.023 for acidity and 0.061 for alkalinity, signifying a notable advancement compared to the MAE range of 0.03–0.46 observed in the previous studies. The proposed approach shows potential in improving the dependability and effectiveness of pH detection, specifically in resource-constrained scenarios.

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Materials having nonlinear optical (NLO) properties have shown hi-tech uses in a variety of modern fields including telecommunications, solid-state physics, laser optics and more recently in quantum computing. The current study offers a comprehensive computational analysis of the chalcone compounds designed through halogens and traditional acceptors. The molecular structure and electronic properties of parent compound (E)-1-(4-aminophenyl)-3-(3-chlorophenyl)prop-2-en-1-one (C1) were quantum chemically simulated and found in good agreement with experimentally reported results. The new chalcone compounds C2–C8 were also proposed by substituting chlorine with acceptors (F, Br, CH₃, CF₃, COOH, CN and NO₂) into a benzene ring with fixed donor (aniline) and a π-bridge (acrolein). DFT and TD-DFT calculations were employed to shed light on charge transfer properties, promising structures, density of states plots and NLO characteristics. The substitution with acceptors effectively modified the structures with halogens and nonhalogen groups, resulting in improved NLO characteristics. A striking NLO response was seen in all proposed compounds. It is interesting to note that the NLO characteristics of C2–C3 and C4–C8 have been significantly improved by the intramolecular charge transfer (ICT) process with β_// value of 18.30 × 10⁻³⁰ esu. However, C7 showed the highest < γ > values of 106.6 × 10⁻³⁶. Among C1–C8 compounds, C8 had a narrower HOMO–LUMO energy gap, facilitating efficient electronic excitations and resonance enhancement which led to an improved NLO response. TDM analysis confirms the intramolecular charge transfer (ICT) in C1–C8 compounds due to the successful migration of charge from donor to acceptor via π-bridge. The current study intrigues scientific interest regarding the formation of chalcone-based appealing NLO compounds that may be useful in recent high-tech applications.

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The objective of the present study is to optimize the extraction of white tea extract (WTE) containing the highest concentration of polyphenolic compounds (TPC) under ultrasound intensity, ultrasound time, and different solvents, and then to investigate the effect of nanoencapsulation using PLGA on the structural characteristics of the optimized extract. The results of the investigation showed the effect of the time and intensity of ultrasound as well as the type of solvent used on the extraction performance of the extract. Thus, the optimal conditions were obtained by using methanol solvent and applying 15 min of time and 70% ultrasound intensity to extract the extract with the highest antioxidant capacity and maximum TPC, respectively, at the rate of 77.65% and 68.38 mg/g. The preparation of white tea extract nanocapsules (WTE-NCs) using PLGA was based on solvent-emulsion evaporation and ultrasound. WTE-NCs were investigated in terms of efficiency and release of WTE micro-coating and structural properties through particle size determination, morphological analysis, and FT-IR. The micro-coating efficiency was 91.89% on the first day, which decreased to 76.16% after 22 days. The particle size analysis results showed that WTE-NCs with a particle size of 68.36 nm increased to 447.23 nm after six months. In terms of morphology, WTE-NCs had a spherical structure. The present study’s findings showed that micro-coating using PLGA can effectively protect and cover WTE.

Herein, DFT studies were carried out of a novel Phenothiazine-based Fluorescent Probe (PFP) for its physio-chemical and thermodynamic properties. Various aspects were investigated including optimized geometry, frontier molecular orbitals, molecular electrostatic potential, density of states, UV-Vis emission spectra and reactivity parameters. DFT studies reveal that molecular modeling, including the optimization of molecular structures like PFP, is crucial for understanding complex molecules and their characteristics. The energy difference (∆E) between the Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) was determined to be 4.48 eV. MEP maps indicate the nitrogen and sulfur atoms in the thiazine ring appear red, indicating high electron density. Similarly, the benzene rings appear blue thereby indicating lower electron density. The DOS spectrum confirmed the HOMO-LUMO gap and provided insights into the availability of electronic states at specific energy levels. High DOS intensity indicated many accessible states, while zero intensity indicated none. Time-Dependent Density Functional Theory (TD-DFT) calculations predicted the absorption maximum at 365 nm and emission spectra for PFP, with a calculated maximum emission at 656 nm. Coordination with water shifts the emission to 690 nm, showing a redshift of 44 nm. Moreover, the theoretically calculated maximum emission of probe PFP was determined to be λ_em = 656 nm, whereas maximum emission spectra of probe PFP with water coordination is calculated as λ_em = 690 nm which is red shifted 44 nm. These theoretically calculated values significantly deviate from experimental value. This deviation occured because the absorption and emission spectra recorded in solvents of different polarity result in different wavenumbers and intensities.

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This study examined the stability and oxidation kinetics of argan oil (AO) in comparison to other reputed culinary oils worldwide, namely virgin olive oil (VOO) and cactus oil (CO). In order to provide a comprehensive comparative analysis, various parameters were assessed, including fatty acid composition, sterol and tocopherol profiles, and the Rancimat test under elevated temperatures to determine kinetic parameters. The results revealed significant variations between argan, olive, and cactus oils in terms of the physicochemical characteristics studied (p < 0.05). In terms of fatty acids, argan oil contains the highest percentage of saturated fatty acids (19.3%), while olive oil has a higher percentage of monounsaturated fatty acids (75.3%) and cactus oil is distinguished by its higher content of polyunsaturated fatty acids (62.6%). Additionally, argan and olive oils contain higher quantities of total sterols (152.5 ± 5.5 and 140.5 ± 2.5 mg/100 g, respectively) compared to cactus oil (112.5 ± 5.5 mg/100 g). Furthermore, argan and cactus oils contain significant amounts of total tocopherols, mainly γ-Tocopherol (65.5–55.4 mg/100 g), whereas olive oil is characterized by a high content of β-Tocopherol (20.5 mg/100 g). The oils were subjected to oxidation at five distinct temperatures (373, 383, 393, 403, and 413 K) using the Rancimat test. A noticeable increase in the oxidation rate was observed as the temperature increased. The natural logarithms of the kinetic rate constants exhibited a linear relationship with temperature, with the temperature coefficient varying between 6.93 × 10⁻² K⁻¹ for virgin olive oil and 7.45 × 10⁻² K⁻¹ for cactus oil. Argan oil demonstrated better oxidative stability and a significantly longer shelf life (20 months) than the other oils. These results were corroborated by kinetic measurements of oxidative stability, including reaction rate constants, the Arrhenius equation, and other thermodynamic indicators.

A simple fabrication route for an all-solid-state carbon paste Cu(II)-selective potentiometric sensor on the basis of composite sensing layer consisting of PbS microparticles, graphite (G), multi-walled carbon nanotube, and paraffin oil has been propounded. Optimization studies for sensing composite layer signified that the composite contained 10 mg PbS, 10 mg MWCNT, 60 mg G, and 20 mg PO exposed the most promising potentiometric performance properties. The sensor displayed a stable and selective linear response to Cu(II) ions in the concentration range of 1.0 × 10⁻⁶–1.0 × 10⁻² M (R² = 0.9992) with an average potential change of 30.2 mV/decade. Detection limit, response time, and life-span of the sensor were determined as 5.0 × 10⁻⁷ M, 15 s, and 3 weeks, respectively. The fabricated sensor was successfully used in practical applications, serving as an indicator electrode to determine the end-point of Cu(II) titrations and to measure Cu(II) content in Cu(II)-spiked tap water samples.

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