Photocatalytic degradation of ciprofloxacin using a novel carbohydrate-based nanocomposite from aqueous solutions

Synergistic adsorption of methylene blue using ternary composite of phosphoric acid geopolymer, calcium alginate, and sodium lauryl sulfate

The removal of dyes from the aquatic ecosystem is necessary being a major threat to life. For enhanced remediation of methylene blue (MB) dye, a new ternary biopolymer-geopolymer-surfactant composite adsorbent is synthesized by combining phosphoric acid geopolymer (PAGP), calcium alginate (Alg), and sodium lauryl sulfate (SLS). During the synthesis of the composites, PAGP and SLS were mixed with the alginate matrix, producing porous hybrid beads. The PAGP-SLS-alginate (PSA) beads prepared were characterized using different analytical tools, i.e., scanning electron microscopy (SEM), Fourier transform infrared spectrophotometry (FTIR), X-ray diffractometry (XRD), surface area and porosimetery (SAP), and thermogravimetric analysis (TGA). To ascertain the ideal conditions for the adsorption process, a batch reactor procedure was used to investigate the effects of several parameters on MB adsorption, including pH (2, 4, 6, 8, 10), PSA adsorbent dosage (0.06-0.12 g), MB concentration (50-500 mg/L), contact time (15 to 300 min), and temperature (25, 35, and 45 °C). The SEM investigation indicated that ~ 1860 μm-sized PSA beads with 6-8 μm voids are generated. Based on XRD, FTIR, and SAP examinations, the material is amorphous, having numerous functional groups and an average pore size of 6.42 nm. Variation of pH has a little effect on the adsorption process, and the pH of 7.44 was found to be the pHpzc of the PSA beads. According to the findings of the batch study, equilibrium adsorption was obtained in 270-300 min, showing that the adsorption process was moderately slow-moving and effective. The dye adsorption linearly increased with initial dye concentration over concentration range of 50-500 mg/L and reciprocally decreased with rise in temperature. 0.06 g adsorbent dose, 25 °C, pH10, and 270 min were found to be the better conditions for adsorption experiments. Langmuir isotherm fitted well compared to Freundlich, Temkin, and Dubinin-Radushkevich (DR) isotherm models on the experimental data, and the maximum adsorption capacity(qmax) calculated was 1666.6 mg. g-1. Pseudo-second-order (PSO) kinetics model and multi steps (two) intra particle diffusion (IPD) model fitted well on the adsorption kinetics data. The system's entropy, Gibbs free energy, and change in enthalpy were measured and found to be -109.171 J. mol-1. K-1, - 8.198 to - 6.014 kJ. mol-1, and - 40.747 kJ. mol-1. Thermodynamics study revealed that adsorption process is exothermic, energetically favorable and resulting in the decrease in randomness. Chemisorption is found to be the dominant mechanism as confirmed by pH effect, Langmuir isotherm, PSO kinetics, IPD model, and thermodynamics parameters. PSA beads were successfully regenerated using ethanol in a course of 120 min and re-used for five times. To sum up, the PSA adsorbent's impressive adsorption capability of 1666.66 mg/g highlights its potential as a successful solution for methylene blue removal. The results of this study add to the expanding corpus of information on sophisticated adsorption materials and demonstrate PSA's potential for real-world uses in wastewater treatment and environmental clean-up.

Employing a magnetic chitosan/molybdenum disulfide nanocomposite for efficiently removing polycyclic aromatic hydrocarbons from milk samples

This study aimed to develop a highly efficient nanocomposite composed of magnetic chitosan/molybdenum disulfide (CS/MoS2/Fe3O4) for the removal of three polycyclic aromatic hydrocarbons (PAHs)-pyrene, anthracene, and phenanthrene. Novelty was introduced through the innovative synthesis procedure and the utilization of magnetic properties for enhanced adsorption capabilities. Additionally, the greenness of chitosan as a sorbent component was emphasized, highlighting its biodegradability and low environmental impact compared to traditional sorbents. Factors influencing PAH adsorption, such as nanocomposite dosage, initial PAH concentration, pH, and contact time, were systematically investigated and optimized. The results revealed that optimal removal efficiencies were attained at an initial PAH concentration of 150 mg/L, a sorbent dose of 0.045 g, pH 6.0, and a contact time of 150 min. The pseudo-second-order kinetic model exhibited superior fitting to the experimental data, indicating an equilibrium time of approximately 150 min. Moreover, the equilibrium adsorption process followed the Freundlich isotherm model, with kf and n values exceeding 7.91 mg/g and 1.20, respectively. Remarkably, the maximum absorption capacities for phenanthrene, anthracene, and pyrene on the sorbent were determined as 217 mg/g, 204 mg/g, and 222 mg/g, respectively. These findings underscore the significant potential of the CS/MoS2/Fe3O4 nanocomposite for efficiently removing PAHs from milk and other dairy products, thereby contributing to improved food safety and public health.

Cefixime removal via WO3/Co-ZIF nanocomposite using machine learning methods

In this research, an upgraded and environmentally friendly process involving WO3/Co-ZIF nanocomposite was used for the removal of Cefixime from the aqueous solutions. Intelligent decision-making was employed using various models including Support Vector Regression (SVR), Genetic Algorithm (GA), Artificial Neural Network (ANN), Simulation Optimization Language for Visualized Excel Results (SOLVER), and Response Surface Methodology (RSM). SVR, ANN, and RSM models were used for modeling and predicting results, while GA and SOLVER models were employed to achieve the optimal conditions for Cefixime degradation. The primary goal of applying different models was to achieve the best conditions with high accuracy in Cefixime degradation. Based on R analysis, the quadratic factorial model in RSM was selected as the best model, and the regression coefficients obtained from it were used to evaluate the performance of artificial intelligence models. According to the quadratic factorial model, interactions between pH and time, pH and catalyst amount, as well as reaction time and catalyst amount were identified as the most significant factors in predicting results. In a comparison between the different models based on Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R2 Score) indices, the SVR model was selected as the best model for the prediction of the results, with a higher R2 Score (0.98), and lower MAE (1.54) and RMSE (3.91) compared to the ANN model. Both ANN and SVR models identified pH as the most important parameter in the prediction of the results. According to the Genetic Algorithm, interactions between the initial concentration of Cefixime with reaction time, as well as between the initial concentration of Cefixime and catalyst amount, had the greatest impact on selecting the optimal values. Using the Genetic Algorithm and SOLVER models, the optimum values for the initial concentration of Cefixime, pH, time, and catalyst amount were determined to be (6.14 mg L-1, 3.13, 117.65 min, and 0.19 g L-1) and (5 mg L-1, 3, 120 min, and 0.19 g L-1), respectively. Given the presented results, this research can contribute significantly to advancements in intelligent decision-making and optimization of the pollutant removal processes from the environment.

Management of caffeine in wastewater using MOF and perovskite materials: optimization, kinetics, and adsorption isotherm modelling

Pharmaceuticals and personal care products (PPCPs) have been increasingly used all over the world and they have been reported on water cycle and cause contamination. Among these pharmaceuticals is caffeine (CAF). In this work, CAF removal from aqueous samples by metal-organic framework (UIO-66) and perovskite (La0.7Sr0.3FeO3) was achieved. Detailed studies on the preparation of MOFs and perovskite oxides compounds have been presented. Extensive characterizations such as X-Ray diffraction (XRD), field emission scanning electron microscope (FESEM), Fourier transform infrared spectra (FT-IR), N2 adsorption-desorption isotherms were also carried out to assure proper formation and to better understand the physico-chemical behavior of the synthesized samples before and after adsorption. Batch experiments of CAF adsorption onto both MOFs and perovskite were performed to compare the effectiveness of both materials on the removal competence of the CAF residue at different conditions including the effect of pH, initial concentration, and contact time. It was observed that the adsorption capacity of CAF by MOF increased with increasing acidity. On the other hand, the adsorption capacity of perovskite is stable in pH 4-10. The maximum adsorption capacities of UiO-66 and perovskite toward CAF are high as 62.5 mg g-1 and 35.25 mg g-1, respectively. Equilibrium isotherms were investigated by numerous models: Langmuir, Freundlich, Temkin, Redlich-Peterson, Sips, Langmuir-Freundlich, Toth, Kahn, Baudu, and Fritz Schlunder. Moreover, the kinetics of the CAF@MOF and CAF@Perovskite systems have been studied by five kinetic models (Pseudo-1st -order (PFO), Pseudo-2nd -order (PSO), Mixed 1st, 2nd-order, Intraparticle diffusion and Avrami). The best model described the adsorption of CAF onto both of MOF and perovskite was the mixed 1st, 2nd-order model. The metal-organic framework and perovskite were applied to quickly extract CAF from water samples successfully. The maximum removal percentage obtained for MOF and perovskite was 0.89% and 0.94% respectively within 30 min contact time which suggests that these materials are considered as promising adsorbents for CAF.

Solar photocatalytic degradation of ciprofloxacin using biochar supported zinc oxide- tungsten oxide photocatalyst

Ciprofloxacin (CIP) is an antibiotic used to treat bacterial infections. It is not completely broken down during conventional wastewater treatment processes and can persist in the environment, leading to the development of antibiotic-resistant bacteria. This study focuses on the solar photocatalytic degradation CIP using biochar-supported photocatalysts. The photocatalysts developed by combining ZnO and WO3 in different ratios (1:2, 1:1, 2:1) were supported on hemp herd biochar. The photocatalyst made with a ratio of 2:1:1 of ZnO:WO3:biochar (Z2W1H) reported the highest CIP degradation efficiency of 87.3% and TOC removal efficiency of 43.1% at a catalyst dosage of 2 g/L, initial CIP concentration of 3 mg/L, and treatment time of 150 min. Subsequently, the effects of operating parameters on CIP degradation were investigated using central composite design (CCD). About 85.4% degradation efficiency of CIP was obtained at optimum conditions (pH ∼8.4, initial CIP concentration ∼4.4 mg/L, catalytic dosage ∼3.4 g/L) within 90 min. A quadradic model was developed to interpret the linear and interactive effect of operating parameters on the CIP degradation efficiency with 2.24-4.59% error. The adsorption-desorption study showed around 42.21% of adsorbed CIP was desorbed from Z2W1H. Scavenger studies demonstrated that the CIP breakdown was notably done by the superoxide radical (O2•-). The mechanism of CIP degradation was adsorption on biochar and subsequent degradation by photocatalyst. The prevalent degradation reactions such as C-N bond cleavage, decarboxylation, decarbonylation, defluorination, and ring opening lead to formation of various intermediates. The Z2W1H reusability test showed ~ 4.2% decrease in CIP removal efficiency after three cycles.

Novel nanostructure approach for antibiotic decomposition in a spinning disc photocatalytic reactor

Conventional wastewater treatment processes are often unable to remove antibiotics with resistant compounds and low biological degradation. The need for advanced and sustainable technologies to remove antibiotics from water sources seems essential. In this regard, the effectiveness of a spinning disc photocatalytic reactor (SDPR) equipped with a visible light-activated Fe3O4@SiO2-NH2@CuO/ZnO core-shell (FSNCZ CS) thin film photocatalyst was investigated for the decomposition of amoxicillin (AMX), a representative antibiotic. Various characterization techniques, such as TEM, FESEM, EDX, AFM, XRD, and UV-Vis-DRS, were employed to study the surface morphology, optoelectronic properties, and nanostructure of the FSNCZ CS. Key operating parameters such as irradiation time, pH, initial AMX concentration, rotational speed, and solution flow rate were fine-tuned for optimization. The results indicated that the highest AMX decomposition (98.7%) was attained under optimal conditions of 60 min of irradiation time, a rotational speed of 350 rpm, a solution flow rate of 0.9 L/min, pH of 5, and an initial AMX concentration of 20 mg/L. Moreover, during the 60 min irradiation time, more than 69.95% of chemical oxygen demand and 61.2% of total organic carbon were removed. After the photocatalytic decomposition of AMX, there is a substantial increase in the average oxidation state and carbon oxidation state in SDPR from 1.33 to 1.94 and 3.2, respectively. Active species tests confirmed that ·OH and ·O2- played a dominant role in AMX decomposition. The developed SDPR, which incorporates a reusable and robust FSNCZ CS photocatalyst, demonstrates promising potential for the decomposition of organic compounds.

Integration of sequential electrocoagulation and adsorption for effective removal of colour and total organic carbon in textile effluents and its utilization for seed germination and irrigation

Textile effluent discharge can negatively impact the environment and living organisms due to its potential toxicity, higher percentages of total organic carbon (TOC) contents, and so on. The study investigates the extraordinary performance of the electrocoagulation process (ECP) combined with powdered activated carbon (PAC) as a highly effective and environmental friendly method of treating textile effluents. This scientific work mainly includes the focus on removing toxic components in textile effluents, such as high concentrations of colour and TOC using synthesized PAC derived from coconut shells coupled with the ECP (ECP-PAC). Initially, PAC was characterized by using XRD, Raman, BET, FTIR, and TGA studies. Subsequently, the pilot-scale ECP-PAC batch reactor was constructed with iron (Fe) as an anode and copper (Cu) as a cathode. The pilot-scale ECP-PAC batch reactor has achieved higher treatment efficiency in a shorter reaction time with low energy consumption compared to a stand-alone ECP. Further, the optimum conditions for effective ECP-PAC have been optimized, such as pH 7.5, applied current density (0-50 mA/cm2), reaction time (0-30 min), electrode combinations (Fe-Cu) with electrode distances of 5 cm apart, and an optimum dose of 5 g/L of PAC. Specifically, 98% of the colour and 96% of the TOC contents present in the industrial textile effluent were treated in 15 and 30 min, respectively. In quantitative perspectives, the developed batch reactor has sharply decreased TOC (324.1 mg/L), IC (1410 mg/L) and TC (1019 mg/L) to 13.55 mg/L (96%), 31.49 mg/L (97%), and 48.05 mg/L (95%), respectively, in 30 min demonstrating its sensitivity and selectivity with the utmost care. Moreover, the physicochemical properties of the treated water were convincingly assessed. That is, it remains suitable for the seed germination of mung bean and chlorophyll content study. Thus, the developed methodology could effectively reduce freshwater consumption in the agricultural sector, increase freshwater availability in water-scarce regions, and facilitate the increase of the recharging capacity of groundwater tables.

Deep removal of phosphate from electroplating wastewater using novel Fe-MOF loaded chitosan hydrogel beads

Since the electroplating industry is springing up, effective control of phosphate has attracted global concerns. In this study, a novel biosorbent (MIL-88@CS-HDG) was synthesized by loading a kind of Fe-based metal organic framework called MIL-88 into chitosan hydrogel beads and applied in deep treatment of phosphate removal in electroplating wastewater. The adsorption capacities of H2PO4- on MIL-88@CS-HDG could reach 1.1 mmol/g (corresponding to 34.1 mg P/g and 106.7 mg H2PO4-/g), which was 2.65% higher than that on single MOF powders and chitosan hydrogel beads. The H2PO4- adsorption was well described by the Freundlich isotherm model. Over 90% H2PO4- could be adsorbed at contact time of 3 h. It could keep high adsorption capacity in the pH range from 2 to 7, which had a wider pH range of application compared with pure MIL-88. Only NO3- and SO42- limited the adsorption with the reduction rate of 11.42% and 23.23%, proving it tolerated most common co-existing ions. More than 92% of phosphorus could be recovered using NaOH and NaNO3. Electrostatic attraction between Fe core and phosphorus in MIL-88@CS-HDG and ion exchange played the dominant role. The recovered MIL-88@CS-HDG remained stable and applicable in the treatment process of real electroplating wastewater even after six adsorption-regeneration cycles. Based on the removal properties and superb regenerability, MIL-88@CS-HDG is potentially applicable to practical production.

Graphitic-carbon-nitride-hydrophilicity-dependent photocatalytic degradation of antibiotics with different log Kow

The surface hydrophilicity of a photocatalyst is an important factor that directly influences its interactions with organic pollutants and significantly impacts its degradation. In this study, we investigated the impact of increased hydrophilicity of g-C3N4 (CN) by alkaline solvothermal treatment on the degradations of three antibiotics (oxytetracycline (OTC), oxolinic acid (OA), and sulfamethoxazole (SMX)) with different log Kow values. Scanning electron microscopy (SEM), X-ray diffraction analysis (XRD), and Fourier-transform infrared (FT-IR) spectroscopy showed no significant differences in the morphology, crystalline structure, and surface functional groups of CN after alkaline solvothermal treatment (Nv-HPCN). However, contact angle analysis revealed that Nv-HPCN (31.8°) was more hydrophilic than CN (61.1°). To assess the hydrophilicity of the antibiotics, the log Kow values of SMX (0.77), OA (0.43), and OTC (-0.34) were measured. Nv-HPCN showed faster OTC degradation than CN, whereas the opposite pattern was observed for the degradation of OA. Scavenger tests showed that O2•- and h+ mainly contributed to the degradation of these antibiotics. Furthermore, the influences of NOM and coexisting anions on antibiotic degradation were investigated. This study thus offers perspectives on the impact of surface hydrophilicity of photocatalysts on the degradation of antibiotics.

Adsorption of diazinon from aqueous solution using metal organic framework and functionalized graphene: Comparison of BBD, ANN models

In the present study, metal organic frameworks (MOFs) and aminated graphitic carbonaceous structure (ACS-RGO) through chemical synthesis prepared by a simple precipitation method and used for diazinon removal. Several techniques such as XRD , FESEM and FTIR were applied for identification of MOF-5 and ACS-RGO. Also, response surface methodology (RSM) was employed in this work to look at the effectiveness of diazinon adsorption. To forecast pesticide removal, we applied artificial neural network (ANN) and Box-Behnken Design (BBD) models. For the ANN model, a sensitivity analysis was also performed. The effect of independent variables like solution pH, various concentrations of diazinon, MOFs and ACS-RGO adsorbent dose and contact time were assessed to find out the optimum conditions. Based on the model prediction, the optimal condition for adsorption ACS-RGO and MOF-5 were determined to be pH 6.6 and 6.6, adsorbent dose of 0.59 and 0.906 g/L, and mixing time of 52.15 and 36.96 min respectively. These conditions resulted in 96.69% and 80.62% diazinon removal using ACS-RGO and MOF-5, respectively. Isotherm studies proved the adsorption of ACS-RGO and MOF-5 following the Langmuir isotherm model for diazinon removal. Diazinon removal followed by the pseudo-second and Pseudo-first order kinetics model provides a better fit for analyzing the kinetic data associated with pesticide adsorption for ACS-RGO and MOF-5, respectively. Based on the obtained results, the predicted values for the efficiency of diazinon removal with the ANN and BBD were similar (R2=0.98). Therefore, two models were able to predict diazinon removal by ACS-RGO and MOF-5.

Modeling sunset yellow removal from fruit juice samples by a novel chitosan-nickel ferrite nano sorbent

Analysis of food additives is highly significant in the food industry and directly related to human health. This investigation into the removal efficiency of sunset yellow as an azo dye in fruit juices using Chitosan-nickel ferrite nanoparticles (Cs@NiFe2O4 NPs). The nanoparticles were synthesized and characterized using various techniques. The effective parameters for removing sunset yellow were optimized using the response surface methodology (RSM) based on the central composite design (CCD). Under the optimum conditions, the highest removal efficiency (94.90%) was obtained for the initial dye concentration of 26.48 mg L-1 at a pH of 3.87, a reaction time of 67.62 min, and a nanoparticle dose of 0.038 g L-1. The pseudo-second-order kinetic model had a better fit for experimental data (R2 = 0.98) than the other kinetic models. The equilibrium adsorption process followed the Freundlich isotherm model with a maximum adsorption capacity of 212.766 mg g-1. The dye removal efficiency achieved for industrial and traditional fruit juice samples (91.75% and 93.24%), respectively, confirmed the method's performance, feasibility, and efficiency. The dye adsorption efficiency showed no significant decrease after five recycling, indicating that the sorbent has suitable stability in practical applications. variousThe synthesized nanoparticles can be suggested as an efficient sorbent to remove the sunset yellow dye from food products.

Tailoring the topology of ZIF-67 metal-organic frameworks (MOFs) adsorbents to capture humic acids

Chlorination is a versatile technique to combat water-borne pathogens. Over the last years, there has been continued research interest to abate the formation of chlorinated disinfection by-products (DBPs). To prevent hazardous DBPs in drinking water, it is decided to diminish organic precursors, among which humic acids (HA) resulting from the decomposition and transformation of biomass. Metal-organic frameworks (MOFs) such as zeolitic imidazolate frameworks (ZIFs) have recently received tremendous attention in water purification. Herein, customized ZIF-67 MOFs possessing various physicochemical properties were prepared by changing the cobalt source. The HA removal by ZIF-67-Cl, ZIF-67-OAc, ZIF-67-NO3, and ZIF-67-SO4 were 85.6%, 68.9%, 86.1%, and 87.4%, respectively, evidently affected by the specific surface area. HA uptake by ZIF-67-SO4 indicated a removal efficiency beyond 90% in 4  90% after 60 min mixing the solution with 0.3 g L-1 ZIF-67-SO4. Notably, an acceptable removal performance (∼72.3%) was obtained even at HA concentrations up to 100 mg L-1. The equilibrium data fitted well with the isotherm models in the order of Langmuir> Hill > BET> Khan > Redlich-Peterson> Jovanovic> Freundlich > and Temkin. The maximum adsorption capacity qm for HA uptake by ZIF-67-SO4 was 175.89 mg g-1, well above the majority of adsorbents. The pseudo-first-order model described the rate of HA adsorption by time. In conclusion, ZIF-67-SO4 presented promising adsorptive properties against HA. Further studies would be needed to minimize cobalt leaching from the ZIF-67-SO4 structure and improve its reusability safely, to ensure its effectiveness and the economy of adsorption system.