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In this study, the photocatalytic degradation of Methylene Blue was investigated using CdSe nanoparticles. CdSe nanoparticles were synthesized via a simple method and were characterized by FTIR, XRD, FESEM, BET, DRS and EDS techniques. The photocatalytic performance of the CdSe nanoparticles was optimized using Response Surface Methodology (RSM) under visible light. The independent variables involved initial pH, MB concentration, photocatalyst dosage, and irradiation time were evaluated and the optimum photodegradation efficiency of MB dye removal was achieved ˜ 92.80% at pH = 8, 20 mgL −1 of MB concentration, 0.02 g 50 mL −1 of CdSe dosage, and 20 min of irradiation time. Also, the photodegradation of MB by CdSe is obeyed pseudo-first-order kinetic model (k = 0.038 min −1 ). The thermodynamic results revealed that the photocatalytic degradation of MB is spontaneous and endothermic. Also, the evaluation of various scavengers confirmed that the MB photodegradation was mainly done by photogenerated holes and hydroxyl radicals.

The primary objective of this study was to evaluate the use of natural compounds as opposed to chemical preservatives. This study employed response methodology to evaluate the synergistic antibacterial effect of Areca nut and Punica granatum L. extract. Independent variables included extract type ( Punica granatum L., Areca nut , and their mixture), solvent (water, ethanol, methanol), bacterial type ( S. aureus , Salmonella , E. coli ), and extract concentration (1, 10, 100 mg/L). The sensitivity was determined using the disk diffusion method, and the diameter of the inhibitory zone was measured. On the specified bacteria, the MIC (minimum inhibitory concentration) and MBC (minimum bactericidal concentration) of each extract were ascertained using the serial dilution method. This study revealed the existence of beneficial synergistic effects between the two extracts. Results indicated that the ethanolic extracts of Punica granatum L. and Areca nut had a synergistic effect on E. coli .

This study presents the preparation of SiO 2 /g-C 3 N 5 @NiFe 2 O 4 nanophotocatalyst for the removal of betamethasone from aqueous solutions. The SiO 2 /g-C 3 N 5 @NiFe 2 O 4 nanophotocatalyst was synthesized using the solvothermal method, and its structure and optical properties were characterized and confirmed through XRD, FESEM, EDX, DRS, BET, VSM and PL analysis. Photocatalytic removal of betamethasone was optimized using a central composite design. The band gap of pure g-C 3 N 5 , NiFe 2 O 4 , and SiO 2 /g-C 3 N 5 @NiFe 2 O 4 was obtained 2.4 eV, 2.7 eV, and 1.4 eV, respectively using the Tauc plot. The F -value of 909.88 and Lack of Fit F -value of 0.41 confirm the obtained model is significant. Also, the value of R 2  = 0.9988 along with R 2 adja = 09977 demonstrates excellent model performance. Maximum removal efficiency of betamethasone was approximately 87.15% under the following optimal conditions: nanophotocatalyst dosage of 0.005 g/50 mL, a betamethasone concentration of 20 mg/L, and an irradiation time of 40 min under visible light. This performance closely aligns with the actual value of 80.65%. In conclusion, the SiO 2 /g-C 3 N 5 @NiFe 2 O 4 nanophotocatalyst demonstrates excellent photocatalytic ability for the removal of betamethasone from aqueous solutions.

Polyvinylidene fluoride (PVDF)/g-C3N4/Chitosan thin film membranes were prepared by immersing of PVDF/g-C3N4 membrane in solution containing various concentrations of chitosan for removal of Direct Blue 14 dye (an anionic dye) from aqueous solutions. The resulting membranes were characterized by XRD, FESEM, TEM and AFM. Also, pure water flux, salt rejection, water content and antifouling properties of prepared membranes were investigated. The resulting demonstrate that pure water flux was decreased (from 70.98 to 14.7%) by increasing of chitosan concentration (2–4%), while water content (42.5–94.78%), salt rejection (from 62.66 to 88.98%) and antifouling properties were increased. It is found that chitosan has major impact on the membrane structural properties due to transform of the PVDF membrane into hydrophilic ones. It is reported that maximum 93% rejection of Direct Blue 14 was obtained by PCC3 (PVDF/g-C3N4-chitosan 4% w/v) membrane. Compared to the PVDF/g-C3N4 membrane, the experimental results showed that PVDF/g-C3N4/Chitosan membranes demonstrated high potential mainly due to greater hydrophilicity and further minimizing membrane fouling.

In this research, the effect of seed halopriming with plasma activated water (PAW) on wheat germination parameters have been studied. Response surface methodology was used to investigate the effect of three factors including: 1) type of water (distilled water, 0.2 and 0.4 min/mL PAW), 2) priming time (1, 3 and 5 h), and 3) salinity of the priming solution (0, 25 and 50 mmol/L NaCl) on wheat germination parameters. The results revealed that increasing PAW levels up to 0.18 min/mL led to an increase in seed germination percentage, seedling weight (both fresh and dry), seedling length, vigor indexes A and B, and water uptake and decreasing mean germination time. Increasing the level of PAW by more than 0.18 min/mL had a negative effect on these parameters. The fresh and dry weight of the seedlings respectively at the 0.18 and 0.2 min/mL levels of PAW, in all salinity levels, had the highest value. The effect of halopriming on enhancing seedling length was more than other characteristics. The optimum ranges of PAW, salinity and priming time were 0.13 min/mL, 10.3 mmol/L and 120.22 min for germination percentage, 0.18 min/mL, 15 mmol/L and 191.24 min for seedling fresh weight, 0.15 min/mL, 13.84 mmol/L and 221.2 min for seedling dry weight, 0.33 min/mL, 24.36 mmol/L and 152.62 min for mean germination time, 0.11 min/mL, 19.03 mmol/L and 177.77 min for vigor indexes A and 0.1 min/mL, 18.1 mmol/L and 178.99 min for vigor indexes B.

In this study, a flower-like SnIn 4 S 8 /SmVO 4 heterostructure was synthesized by applying a hydrothermal approach and used as a visible-light-driven photocatalyst to remove hexavalent chromium (Cr 6+ ) and Rhodamine B (RhB). The process design and optimization were carried out by response surface methodology (RSM). An artificial neural network (ANN) was also used to determine the relative importance of operational factors. Under RSM-based optimal conditions, the Cr 6+ and RhB removal efficiency reached 90.93 and 97.57%, respectively. Process modeling by ANN revealed pH as the most influential factor in Cr 6+ and dye removal. The predominant photocatalytic activity of SnIn 4 S 8 /SmVO 4 was attributed to its Z-scheme structure, leading to the significant separation of charge carriers and conserving the redox capacity of the photogenerated electron-holes. Kinetic studies revealed that the SnIn 4 S 8 /SmVO 4 could achieve considerable rate constants of 0.036 and 0.080 min −1 to remove Cr 6+ and RhB, respectively. Furthermore, the catalyst’s reusability was confirmed under optimal conditions.

In this research, MgO/C 3 N 4 nanocomposite was synthesized via facile and economical method and was characterized by Fourier - transform infrared spectroscopy , X-ray diffraction, Field emission scanning electron microscopy , Energy-dispersive X-ray spectroscopy and Dot mapping. Then efficiency of synthesized MgO/C3N4 nanocomposite was investigated in removal of Reactive Orange 16 (RO16) dye from aqueous solutions under visible light in a batch system. Results obtained from photocatalytic removal showed that removal percentage of RO16 dye decreases by increasing RO16 dye concentration and increasing MgO/C3N4 nanocomposite dosage. The optimum pH for the removal of RO16 was pH 6. As results, maximum removal of RO16 dye was obtained about 82% in following conditions: Visible light radiation = 39.6 w, RO16 dye concentration = 2 mg/L, MgO/C3N4 nanocomposite, dosage = 0.2 g/500 mL, pH 6, time = 30 min. Accordingly, it can be concluded that the synthesized MgO/C3N4 nanocomposite can be used as an efficient photocatalyst under visible light for the removal of RO16 dye.

The present study deals with use of central composite design (CCD) and artificial neural network (ANN) in modeling and optimization of reactive blue 21 (RB21) removal from aqueous media under photo-ozonation process. Four effective operational parameters (including: initial concentration of RB21, O3 concentration, UV light intensity and reaction time) were chosen and the experiments were designed by CCD based on response surface methodology (RSM). The obtained results from the CCD model were used in modeling the process by ANN. Under optimum condition (O3 concentration of 3.95 mg L−1, UV intensity of 20.5 W m−2, reaction time of 7.77 min and initial dye concentration of 40.21 mg L−1), RB21 removal efficiency reached to up 98.88%. A topology of ANN with a three-layer consisting of four input neurons, 14 hidden neurons and one output neuron was designed. The relative significance of each major factor was calculated based on the connection weights of the ANN model. Dye and ozone concentrations were the most important variables in the photo-ozonation of RB21, followed by reaction time and UV light intensity. The comparison of predicted values by CCD and ANN with experimental results showed that both methods were highly efficient in the modeling of the process.

Zinc sulfide nanoparticles (ZnS-NPs) were synthesized via a simple and facile co-precipitation method and were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM) and diffuse reflectance spectroscopy (DRS). Photocatalytic activity of synthesized nanoparticles was evaluated in removal of double azo dye Direct Blue 14 (DB14) from aqueous media. Optimization of photocatalytic removal of DB14 was studied using response surface methodology (RSM). Based on the results, DB14 removal efficiency increased with increasing intensity and duration of UV light irradiation, whereas the higher pH and higher initial dye concentration were unfavorable. Under optimum conditions (initial DB14 concentration =10 mg L−1, ZnS-NPs amount = 0.7 g L−1, pH = 3.5, UV light intensity =16 W m−2, and irradiation time = 48 min), dye removal efficiency reached up to 88.26%. In continuation of our researches, non-linear regression analysis was used to development a kinetics model based on the Langmuir–Hinshelwood model and an empirical equation was obtained for estimation of apparent pseudo-first-order rate constant (kap) as a function of the operational variables. Findings indicated a high similarity was between the model prediction and experimental results.

Today, the tendency to use of natural preservatives to increase food security has expanded. In the present study, antibacterial effects of Areca Nut fruit extracts were evaluated against Staphylococcus aureus, Escherichia coli, Salmonella enterica, and Enterobacter aerogenes bacteria using agar disc diffusion technique. Methanol, ethanol, and water were used as solvents for extraction by maceration method, and extracts were analyzed by GC-MS. The antibacterial activity was evaluated using microtiter broth dilution method to determine minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Results revealed that all ATCC strains were significantly inhibited by ethanolic and methanolic extracts. Escherichia coli produced a significantly larger zone of inhibition for Gentamicin (35±0.65 mm) and Penicillin (25 mm±0.56), while Enterobacter aerogenes produced smaller zone of inhibition for Gentamicin (20 ± 0.87 mm) and Penicillin (15±0.87 mm). Also, methanolic extract had considerable antibacterial activity with MIC value of 1.56 mg/mL against Escherichia coli. All of extracts were used to evaluate antibacterial effects in prepared cake, and as a result, all pathogenies were the most sensitive by methanolic extract in 100 mg/L of concentration except Escherichia coli that were more sensitive by ethanolic extract. In conclusion, the Areca Nut fruit extracts may be used as a natural preservative in food industries. Future studies should focus on the effect of Areca Nut fruit extracts in bakery and drinking industries.