Experimental modelling studies on the removal of dyes and heavy metal ions using ZnFe2O4 nanoparticles

Adsorption of haem by magnetic chitosan microspheres: Optimal conditions, adsorption mechanisms and density functional theory analyses

Magnetic chitosan microspheres (Al@CTS@Fe3O4) were prepared for haem separation via chemical cross-linking of chitosan, Fe3O4 and AlCl3·6H2O. The properties of the Al@CTS@Fe3O4 microspheres were investigated through techniques including XRD, TEM, FTIR, BET analysis, SEM, TG, VSM, XPS and pHpzc analysis. The haem adsorption of Al@CTS@Fe3O4 was optimized via a Box-Behnken design (BBD) with three operating factors: Fe3O4 dose (0.5-1.3 g), AlCl3·6H2O concentration (0.25-1.25 mol/L) and glutaraldehyde dose (2-6 mL). The optimal haem adsorption effect was achieved with 1.1 g of Fe3O4, 0.75 mol/L AlCl3·6H2O, and 3 mL of glutaraldehyde. The adsorption kinetics and isotherms demonstrated that haem adsorption by the Al@CTS@Fe3O4 microspheres was best described by the pseudo-second-order model. The maximum adsorption capacity is 33.875 mg/g at pH 6. After six adsorption-desorption cycles, the removal of haem still reached 53.83 %. The surface adsorption mechanism of haem on Al@CTS@Fe3O4 can be attributed to electrostatic, hydrogen bonding, and n-π interactions. Thermodynamic calculations indicated that the adsorption process is spontaneous, with the microspheres preferentially accepting electrons and haem preferentially providing electrons. Consequently, the Al@CTS@Fe3O4 microspheres exhibit considerable potential as adsorbents for haem separation.

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.

Chitosan anchored nZVI bionanocomposites for treatment of textile wastewater: Optimization, mechanism, and phytotoxic assessment

In recent years, there has been a growing focus on treating textile wastewater due to its escalating threat to aquatic ecosystems and exposed communities. The present study investigates the adsorption efficacy of biopolymer functionalized nanoscale zero-valent iron (CS@nZVI) composite for the treatment of textile wastewater using the RSM-CCD model. The structure and morphology of CS@nZVI were characterized using XRD, FTIR, FESEM, and EDX. CS@nZVI was then evaluated for its adsorption potential in removing COD, color, and other physico-chemical parameters from textile wastewater. The results showed the high efficacy of CS@nZVI for COD and color removal from textile wastewater. Under optimal conditions (pH 6, contact time 60 min, and 1.84 g CS@nZVI), COD removal reached a maximum of 85.53%, and decolorization efficiency was found to be 89.73%. The coefficient of determination R2 (0.98) and AIC (269.75) values suggested quadratic model as the best-fitted model for optimizing the process parameters for COD removal. Additionally, the physico-chemical parameters were found to be within permissible limits after treatment with CS@nZVI. The influence of coexisting ions on COD removal followed the order PO43- > SO42- > Cl- >Na+ > Ca2+. The kinetics data fitted well with the pseudo-first-order reaction, indicating physisorption as the primary mechanism. The thermodynamic study revealed the endothermic nature of the removal process. Reusability tests demonstrated that great regeneration capacity of spent CS@nZVIafter five consecutive cycles. Furthermore, toxicological studies showed reduced toxicity in treated samples, leading to improved growth of Vigna radiata L. These findings suggest that CS@nZVI bionanocomposites could serve as an efficient, cost-effective, and eco-friendly remediation agent for the treatment of textile effluents, presenting significant prospects for commercial applications.

A Novel Recyclable Magnetic Nano-Catalyst for Fenton-Photodegradation of Methyl Orange and Imidazole Derivatives Catalytic Synthesis

A magnetite chlorodeoxycellulose/ferroferric oxide (CDC@Fe3O4) heterogeneous photocatalyst was synthesised via treated and modified cotton in two steps. The designed nanocomposites were characterised by FTIR, TGA, XRD, SEM, and VSM analyses. The Fenton-photocatalytic decomposition efficiency of the synthesised magnetic catalyst was evaluated under visible sunlight using Methyl Orange (MO) as a model organic pollutant. The impacts of several degradation parameters, including the light source, catalyst load, irradiation temperature, oxidant dose, and pH of the dye aqueous solution and its corresponding concentration on the Fenton photodegradation performance, were methodically investigated. The (CDC@Fe3O4) heterogeneous catalyst showed a remarkable MO removal rate of 97.9% at 10 min under visible-light irradiation. (CDC@Fe3O4) nanomaterials were also used in a heterogeneous catalytic optimised protocol for a multicomponent reaction procedure to obtain nine tetra-substituted imidazole derivatives. The green protocol afforded imidazole derivatives in 30 min with good yields (91-97%) at room temperature and under ultrasound irradiation. Generally, a synthesised recyclable heterogeneous nano-catalyst is a good example and is suitable for wastewater treatment and organic synthesis.

Fe3O4-chitosan nanocomposite as a magnetic biosorbent for removal of nickel and cobalt heavy metals from polluted water

Recently, natural polymers like chitosan have gained attention as promising adsorbents for water treatment. By combining chitosan with magnetic nanoparticles, their adsorption capabilities can be enhanced. In this study, chitosan-magnetite nanocomposite (CMNC) was synthesized via coprecipitation method to remove nickel and cobalt from aqueous solutions. The physicochemical properties of the synthesized CMNC were investigated by various techniques, including FESEM, TEM, XPS, FTIR, XRD, and VSM. The electron microscopy results confirmed the uniform dispersion of magnetite nanoparticles within CMNC nanocomposites, while VSM confirmed their significant magnetic properties. The adsorption experiments showed that at optimal conditions (pH = 6, contact time = 2 h, adsorbent dosage = 2 g/l), CMNC has high adsorption capacities of 30.03 mg/g for Ni2+ and 53.19 mg/g for Co2+. Furthermore, the adsorption data fitted best with the Langmuir isotherm, show that the active sites on CMNC are energetically homogenous. According to kinetic analysis, the experimental data were in good agreement with both pseudo-second-order and intra-particle diffusion models, which suggest that chemical sorption, along with mass transfer steps, influence the overall adsorption process. Finally, investigating the thermodynamic parameters (∆Gads, ∆Hads, ∆Sads) showed that the adsorption process on CMNC was endothermic and spontaneous, with stronger interactions observed between CMNC and Co2+ compared to Ni2+.

Optimization of Cd (II) removal from aqueous solution by natural hydroxyapatite/bentonite composite using response surface methodology

Toxic cadmium (Cd) was removed from water using eggshell-based hydroxyapatite (HAp) grafted bentonite (HAp/bentonite) composite through a straightforward chemical synthesis route. The as-prepared adsorbents were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and Brunauer–Emmett–Teller analysis (BET). Optimization of the initial adsorbate concentration, adsorbent dosage, pH, and contact time—all of which affect the adsorption process—was performed using the central composite design (CCD) of the response surface methodology (RSM). 99.3 percent adsorptive removal efficiency was observed at an initial concentration of 61.58 mg/L of Cd (II), with an adsorbent dosage of 1.58 g, a solution pH of 5.88, and a contact time of 49.63 min. The analysis of variance (ANOVA) was performed, and the multiple correlation coefficient (R2) was found to be 0.9915 which confirms the significance of the predicted model. The Langmuir isotherm model best represented the adsorption isotherm data, which also predicted a maximum sorption capacity of 125.47 mg/g. The kinetic data were best described by the pseudo-second order model.

Green Synthesis of CuO-TiO2 Nanoparticles for the Degradation of Organic Pollutants: Physical, Optical and Electrochemical Properties

CuO-TiO2 nanocomposites were successfully synthesized using the C. benghalensis plant extracts. The effect of the composition of CuO to TiO2 on the morphological, optical, electrochemical, and photodegradation efficiency in the composites was studied. SEM, XRD, UV-vis, FTIR, TGA, BET, and CV were used to characterize these materials. The XRD data reported the tenorite structure of the CuO and the anatase phase of the TiO2. SEM showed the spherical morphologies for all the CuO-TiO2 NPs, and these were also mesoporous in nature, as depicted by BET. The voltammogram of the CuO-TiO2 30/70 electrode showed a higher response current density compared to the other two samples, suggesting a higher specific capacitance. Upon testing the photocatalytic efficiencies of the CuO-TiO2 nanocomposites against methylene blue (MB), ciprofloxacin (CIP), and sulfisoxazole (SSX), the highest degradation of 94% was recorded for SSX using the CuO-TiO2 30/70 nanocomposites. Hydroxyl radicals were the primary species responsible for the photodegradation of SSX, and the material could be reused once. The most active species in the photodegradation of SSX has been identified as OH•. From this study, it can be noted that the CuO-TiO2 nanocomposites were more selective toward the degradation of antibiotics (sulfisoxazole and ciproflaxin) as compared to dyes (methylene blue).

Application of Orange Peel Waste as Adsorbent for Methylene Blue and Cd2+ Simultaneous Remediation

Pollution by dyes and heavy metals is one of the main concerns at the environmental level due to their toxicity and inefficient elimination by traditional water treatment. Orange peel (OP) without any treatment was applied to effectively eliminate methylene blue (MB) and cadmium ions (Cd²⁺) in mono- and multicomponent systems. Although the single adsorption processes for MB and Cd²⁺ have been investigated, the effects and mechanisms of interactions among multicomponent systems are still unclear. Batch experiments showed that in monocomponent systems, the maximum adsorption capacities were 0.7824 mmol g⁻¹ for MB and 0.2884 mmol g⁻¹ for Cd²⁺, while in multicomponent systems (Cd²⁺ and MB), both contaminants competed for the adsorption sites on OP. Particularly, a synergic effect was observed since the adsorption capacity of Cd²⁺ increased compared to the monocomponent system. Results of desorption and adsorbent reuse confirmed that the adsorbent presents good regeneration performance. The low cost of this material and its capacity for the individual or simultaneous removal of Cd²⁺ and MB in aqueous solutions makes it a potential adsorbent for polluted water treatment processes.

Effective removal of Pb(II) ions using piperazine-modified magnetic graphene oxide nanocomposite; optimization by response surface methodology

In this research, the piperazine-modified magnetic graphene oxide (Pip@MGO) nanocomposite was synthesized and utilized as a nano-adsorbent for the removal of Pb(II) ions from environmental water and wastewater samples. The physicochemical properties of Pip@MGO nanocomposite was characterized by X-ray diffraction analysis (XRD), Field emission scanning electron microscopy (FESEM), Transmission electron microscopy (TEM), Energy-dispersive X-ray spectroscopy (EDAX), Thermo-gravimetric analysis (TGA), Vibrating Sample Magnetometery (VSM) and Fourier-transform infrared spectroscopy (FT-IR) analysis. In this method, the batch removal process were designed by response surface methodology (RSM) based on a central composite design (CCD) model. The results indicated that the highest efficiency of Pb(II) removal was obtained from the quadratic model under optimum conditions of prominent parameters (initial pH 6.0, adsorbent dosage 7 mg, initial concentration of lead 15 mg L⁻¹ and contact time 27.5 min). Adsorption data showed that lead ions uptake on Pip@MGO nanocomposite followed the Langmuir isotherm model equation and pseudo-second order kinetic model. High adsorption capacity (558.2 mg g⁻¹) and easy magnetic separation capability showed that the synthesized Pip@MGO nanocomposite has great potential for the removal of Pb(II) ions from contaminated wastewaters.