Green synthesis of magnetic nanocomposite by leave extract for the treatment of Methylene blue contaminated water

Performance Evaluation of Benzyl Alcohol Oxidation with tert-Butyl Hydroperoxide to Benzaldehyde Using the Response Surface Methodology, Artificial Neural Network, and Adaptive Neuro-Fuzzy Inference System Model

The adaptive neuro-fuzzy inference system (ANFIS), central composite experimental design (CCD)-response surface methodology (RSM), and artificial neural network (ANN) are used to model the oxidation of benzyl alcohol using the tert-butyl hydroperoxide (TBHP) oxidant to selectively yield benzaldehyde over a mesoporous ceria-zirconia catalyst. Characterization reveals that the produced catalyst has hysteresis loops, a sponge-like structure, and structurally induced reactivity. Three independent variables were taken into consideration while analyzing the ANN, RSM, and ANFIS models: the amount of catalyst (A), reaction temperature (B), and reaction time (C). With the application of optimum conditions, along with a constant (45 mmol) TBHP oxidant amount, (30 mmol) benzyl alcohol amount, and rigorous refluxing of 450 rpm, a maximum optimal benzaldehyde yield of 98.4% was obtained. To examine the acceptability of the models, further sensitivity studies including statistical error functions, analysis of variance (ANOVA) results, and the lack-of-fit test, among others, were employed. The obtained results show that the ANFIS model is the most suited to predicting benzaldehyde yield, followed by RSM. Green chemistry matrix calculations for the reaction reveal lower values of the E-factor (1.57), mass intensity (MI, 2.57), and mass productivity (MP, 38%), which are highly desirable for green and sustainable reactions. Therefore, utilizing a ceria-zirconia catalyst synthesized via the inverse micelle method for the oxidation of benzyl alcohol provides a green and sustainable methodology for the synthesis of benzaldehyde under mild conditions.

Investigation of Eucalyptus camaldulensis and Tamarix aphylla species' capacities for methylene blue removal in wastewater and heavy metal remediation in soil

In the contemporary landscape, the reuse of wastewater holds paramount significance. Concurrently, wastewater carries an array of pollutants encompassing chemical dyes and heavy metals. This study delves into the potential of Tamarix aphylla (TA) and Eucalyptus camaldulensis (EC) species for mitigating heavy metals in soil and eliminating methylene blue dye (MB) from wastewater. The research begins with assessing the dye adsorption process, considering pivotal factors such as initial pH, adsorbent dosage, initial dye concentration, and contact time. Outcomes reveal EC's superiority in dye removal compared to TA. As a bioremediation agent, EC exhibits a 90.46% removal efficacy for MB within 15 min, with pH 7.0 as the operative condition. Equilibrium analysis employs Temkin (T), Freundlich (F), and Langmuir (L) isotherms, revealing an excellent fit with the L isotherm model. The study delves further by probing surface adsorption kinetics through pseudo-first-order (PFO) and pseudo-second-order (PSO) models. Furthermore, to discern the divergent impacts of EC and TA on soil heavy metal reduction, soil samples were collected from three distinct zones: an untouched control area, alongside areas where EC and TA were cultivated at the Yazd wastewater site in Iran. Heavy metal levels in the soil were meticulously assessed through rigorous measurement and statistical scrutiny. The findings spotlight TA-cultivated soil as having the highest levels across all examined factors. Ultimately, EC emerges as the superior contender, proficiently excelling in both MB eliminations from wastewater and heavy metal amelioration in the soil, positioning it as the preferred phytoremediation agent.

Activated Carbon Prepared from Waste Coffee Grounds: Characterization and Adsorption Properties of Dyes

Spent coffee grounds (SCGs) have great potential as a useful, value-added biological material. In this context, activated carbon (AC) was prepared from SCGs by an activation process using H3PO4 at 600 °C in the air and used as an adsorbent for the azo dye AO7, a model molecule for dye colorants found in textile industry effluents. X-ray diffraction, SEM and BET revealed that the AC was predominantly amorphous, consisting of a powder of 20-100 µm particles with mesopores averaging 5.5 nm in pore size. Adsorption kinetics followed a pseudo-second-order law, while the Langmuir model best fitted the experimental isotherm data (maximum capacity of 119.5 mg AO7 per AC g). The thermodynamic parameters revealed that adsorption was endothermic and spontaneous. All the characterizations indicated that adsorption occurred by physisorption via mainly π-π interactions. The best experimental removal efficiency optimized by means of a Box-Behnken design and response surface methodology was 98% for an initial AO7 concentration of 20 mg·L-1 at pH 7.5 with a dose of 0.285 g·L-1 of AC and a contact time of 40 min. These results clearly show that activated carbon prepared from SCGs can be a useful material for efficiently removing organic matter from aqueous solutions.

Prediction and optimizing of methylene blue sequestration to activated charcoal/magnetic nanocomposites using artificial neutral network and response surface methodology

Green synthesized magnetic nanoparticles (MNPs) linked with activated charcoal (AC) (AC/Fe3O4 NCs) were exploited for methylene blue (MB) confiscation in this study. The AC/Fe3O4 NCs produced were characterized using TEM, FTIR, UV/Vis and XRD spectrometry. The Response-Surface-Methodology (RSM) was utilized to improve the experimental data for the MB sorption to AC/Fe3O4 NCs, with 20 experimental runs implemented through a central composite design (CCD) to assess the effect of sorption factors-initial MB concentration, pH and sorbent dosage effects on the response (removal-effectiveness). The quadratic model was discovered to ideally describe the sorption process, with an R2 value of 0.9857. The theoretical prediction of the experimental data using the Artificial-Neural-Network (ANN) model showed that the Levenberg-Marquardt (LM) had a better performance criterion. Comparison between the modelled experimental and predicted data showed also that the LM algorithm had a high R2 of 0.9922, which showed NN model applicability for defining the sorption of MB to AC/Fe3O4 NCs with practical precision. The results of the non-linear fitting (NLF) of both isotherm and kinetic models, showed that the sorption of MB to AC/Fe3O4 NCs was perfectly described using the pseudo-second-order (PSOM) and Freundlich (FRHM) models. The estimated optimum sorption capacity was 455 mg g-1. Thermodynamically, the sorption of MB to AC/Fe3O4 NCs was shown to be non-spontaneous and endothermic.

Kaolin-Supported Silver Nanoparticles as an Effective Catalyst for the Removal of Methylene Blue Dye from Aqueous Solutions

Water contamination by organic dyes has become a reason for severe environmental pollution and has been threatening the aquatic ecosystem. In this study, kaolin-supported silver nanoparticle (Ag-NP) composites were synthesized by a facile two-step adsorption-reduction method through the reduction of silver ions adsorbed onto locally available, inexpensive, and easily pretreated kaolin surfaces by using sodium borohydride (NaBH₄) for the catalytic degradation of methylene blue (MB) dye in aqueous solution. The morphology, structure, surface area, and interaction of the synthesized materials were investigated by scanning electron microscopy, X-ray diffraction, Brunauer-Emmett-Teller, and Fourier transform infrared spectroscopy, respectively. Characterization results showed the successful growth of Ag-NPs on the kaolin surface. To understand the catalytic degradation performance of the catalyst, batch experiments were carried out using MB dye as a model dye. The catalytic reduction tests confirmed the importance of Ag-NPs and the high catalytic activities of the synthesized Ag-NPs/kaolin composite toward MB dye reduction. The degradation results indicated that the increased Ag-NP content on the kaolin surface through repeating cycles could effectively enhance the removal of MB dye from an aqueous solution. The kinetic analysis of the MB dye degradation of the catalyst has fitted the pseudo-first-order kinetic model. More than 97% removal efficiency was still present after five reuse cycles, demonstrating exceptional stability and reusability of the composite. In conclusion, the Ag-NPs supported kaolin (Ag-NPs/kaolin) composite was found to be a promising catalyst for the excellent catalytic activity to reduce a model dye MB from the aqueous solution in the presence of NaBH₄ with catalytic efficiency higher than 97% and a reduction rate constant, k _red, higher than 0.86 min^-1.

Green Synthesis of Hydroxyapatite Nanoparticles Using Monoon longifolium Leaf Extract for Removal of Fluoride from Aqueous Solution

Hydroxyapatite (Ca10(PO4)6(OH)2) calcium phosphate is a robust and viable magnetic material for the treatment of polluted air, water, and soil. Because of its unique structure and appealing properties such as high adsorption capabilities, acid-base adaptability, ion-exchange capability, and thermal stability, hydroxyapatite (HAp) has a lot of potential in the field of environmental management. An aqueous extract of Monoon longifolium leaves was used for the preparation of hydroxyapatite nonparticles as the adsorbent for fluoride ion removal from aqueous solution in this work, resulting in bio-based hydroxyapatite nanoparticles. The prepared adsorbent was characterized by using instrumental techniques such as TGA/DTA, XRD, AAS, FT-IR, and UV-Vis spectroscopy as well as SEM. The batch adsorption approach was used to determine the optimum adsorption efficiency of HAp NPs under various experimental conditions. As a result, the best removal efficiency corresponds to 0.75 g HAp NPs, 15 mg/L, and pH 7 at 50 minutes (96%). The equilibrium adsorption data were better fitted into the Freundlich isotherms (R2 = 0.99), and the pseudo-second-order kinetic model was found to be suitable (R2 = 0.99) for the kinetic model. Fluoride ion adsorption on HAp NPs is spontaneous, endothermic, and possible at temperatures over 318 K, according to thermodynamic calculations. The results hint at a conclusion that the synthesized HAp NPs were an efficient adsorbent for the removal of fluoride ions and the overall process can be an economical choice for scaled-up water treatment processes.

Environmental assessment of wastewater management via hybrid nanocomposite matrix implications-an organized review

Pollution of water is currently a significant worry for scientific communities all over the world, and it is imperative that this problem be solved as quickly as possible. It is today recognized to be one of the most important foci of research worldwide. The present dilemma of clean, fresh waste is being addressed by the subsequent ejection of impurities from polluted water following recycling. There are several effective solutions that have been promoted as a solution to this problem. Even if the present procedures for wastewater treatment degrade a wide variety of effluents efficiently, these protocols still have some kind of restrictions. The most cutting-edge research in this area is being done on the subject of nanotechnology, which has an astounding number of potential uses, one of which is the treatment of wastewater. One of the value-added alternatives utilized for water purification by eliminating the many types of pollutants found in wastewater is the green synthesis of nanocomposites in adsorbents, magnetic separation, photocatalysts, and other similar processes. Within the scope of this study, the most significant discoveries of nanocomposites to date that have been made towards the remediation of wastewater are highlighted.