Green synthesis of Ag2O nanoparticles using Punica granatum leaf extract for sulfamethoxazole antibiotic adsorption: characterization, experimental study, modeling, and DFT calculation.

Silver oxide (Ag2O) nanoparticles (NPs) were generated by synthesizing green leaf extract of Punica granatum, and afterwards they were used as adsorbent to remove the antibiotic additive sulfamethoxazole (SMX) from aqueous solutions. Prior of their use as adsorbent, the Ag2O NPs were characterized by various methods such as X-ray diffraction, Fourier transform infrared spectroscopy (FTIR), Brunauer-Emmett-Teller (BET), scanning electron microscopy/energy-dispersive X-ray (SEM-EDX), and transmission electron microscopy (TEM). The Ag2O NPs were found to be spherically shaped and stabilized by the constituents of the extract. Further, at SMX antibiotic concentration of 100 mg L-1, the Ag2O NPs achieved almost complete removal of 98.93% within 90 min, and by using 0.8 g L-1 of adsorbent dose at pH=4 and temperature T=308 K. In addition, the experimental data were well fitted with the theoretical Langmuir model indicating homogeneous adsorbed layer of the SMX antibiotic on the Ag2O NPs surface. The maximum uptake capacity was 277.85 mg g-1. A good agreement was also found between the kinetic adsorption data and the theoretical pseudo-second-order model. Regarding the thermodynamic adsorption aspects, the data revealed an endothermic nature and confirmed the feasibility and the spontaneity of the adsorption reaction. Furthermore, the regeneration study has shown that the Ag2O NPs could be efficiently reused for up to five cycles. The geometric structures have been optimized and quantum chemical parameters were calculated for the SMX unprotonated (SMX+/-) and protonated (SMX+) using density functional theory (DFT) calculation. The DFT results indicated that the unprotonated SMX+/- reacts more favorably on the Ag2O surface, as compared to the protonated SMX+. The SMX binding mechanism was predominantly controlled by the electrostatic attraction, hydrogen bond, hydrophobic, and π-π interactions. The overall data suggest that the Ag2O NPs have promising potential for antibiotic removal from wastewater.

Kinetics and thermodynamics evaluation of oxidative stability in Oleum hyperici: A comparative study.

In this study, Oleum hyperici (St. John's Wort oil) was investigated according to its oxidative stability and antioxidant activity parameters. A homemade and two different brands of oils were used for comparative reasons. Oxidation process regarding kinetics and thermodynamics studies achieved by accelerated Rancimat conditions (100-140 °C). The quality parameters of the oil samples were compared depending on phenolic and flavonoid contents, antioxidant activity, free fatty acid quantity and shelf-life. Principal component analysis (PCA) has been also applied to comprehend the relationship between these three groups and their quality parameters. The homemade oil has been predicted to have almost twice longer shelf-life than that of the commercial ones (119 days versus 66/69 days). Additionally, lipid oxidation in the St. John's Wort oils has been found to be endothermic and non-spontaneous depending on the thermodynamic indexes.

Optimization of ultrasound-assisted extraction of phenolic compounds from grapefruit (Citrus paradisi Macf.) leaves via D-optimal design and artificial neural network design with categorical and quantitative variables.

BACKGROUND: The extraction of phenolic compounds from grapefruit leaves assisted by ultrasound-assisted extraction (UAE) was optimized using response surface methodology (RSM) by means of D-optimal experimental design and artificial neural network (ANN). For this purpose, five numerical factors were selected: ethanol concentration (0-50%), extraction time (15-60 min), extraction temperature (25-50 °C), solid:liquid ratio (50-100 g L-1 ) and calorimetric energy density of ultrasound (0.25-0.50 kW L-1 ), whereas ultrasound probe horn diameter (13 or 19 mm) was chosen as categorical factor. RESULTS: The optimized experimental conditions yielded by RSM were: 10.80% for ethanol concentration; 58.52 min for extraction time; 30.37 °C for extraction temperature; 52.33 g L-1 for solid:liquid ratio; 0.457 kW L-1 for ultrasonic power density, with thick probe type. Under these conditions total phenolics content was found to be 19.04 mg gallic acid equivalents g-1 dried leaf. CONCLUSION: The same dataset was used to train multilayer feed-forward networks using different approaches via MATLAB, with ANN exhibiting superior performance to RSM (differences included categorical factor in one model and higher regression coefficients), while close values were obtained for the extraction variables under study, except for ethanol concentration and extraction time. © 2018 Society of Chemical Industry.