Reactive orange 12 dye adsorption onto magnetically separable CaFe₂O₄ nanoparticles synthesized by simple chemical route: kinetic, isotherm and neural network modeling

Effluents from industries like textile, paper, rubber, food coloring, cosmetics and so on are loaded with large amounts of toxic dyes, which on disposal to water bodies may cause serious water pollution (Gupta et al. 2012; Chen et al. 2014; Asim et al. 2019). Dye-burdened wastewater may increase the chemical oxygen demand of water and reduce light penetration and photosynthesis activity of the water bodies. Some dyes are non-biodegradable owing to their complex aromatic structure, and carcinogenic as well as mutagenic to human beings (Bhowmik et al. 2016; Deb et al. 2017; Bhowmik et al. 2018). The toxic effects of these synthetic dyes have encouraged the environmental scientists to search for novel techniques or materials for their safe and effective removal from water. Therefore, several physical, chemical, and microbiological approaches such as chemical oxidation/precipitation, photo-degradation, coagulation, microbiological degradation and so on have been utilized to treat dye-loaded wastewater (Chafi et al. 2011; Cui et al. 2012; Debnath & Chakraborty 2013; Debnath et al. 2015). Among several dye remediation methods, adsorption is one of the most effective techniques due to the availability of a large number of adsorbents, easy operation, high efficiency, and economic feasibility. A wide variety of adsorbents like activated carbon, industrial waste, agricultural waste, zeolites, clays, and polymers have been testified for removal of dyes from water (Deng et al. 2013; Yao et al. 2014; Zeng et al. 2014; Montoya-suarez et al. 2016; Bhowmik et al. 2017; Bhowmik et al. 2019). But many of them suffer from low adsorption capacity, high cost, poor regeneration ability, slow adsorption rate and so on. Furthermore, separation of adsorbents from heterogeneous systems is another serious drawback that restricts their large-scale industrial wastewater treatment applications (Liu et al. 2012; Hajati et al. 2014).

Magnetic metal ferrite nanoparticles have attracted a lot of interest as an adsorbent for eradicating dyes, heavy metals, and other water contaminants from aqueous systems (Li et al. 2011; Khanna & Verma 2013). Additionally, metal ferrites are also known for their enhanced photo-catalytic properties for degradation of organic water pollutants (Al-Anzari et al. 2018, 2020). Nano adsorbents are normally preferred owing to their small size, high surface area and large pore volume, which provide faster adsorption and high adsorption capacity compared to the traditional adsorbents. Moreover, nano adsorbents with magnetic properties can provide extra nuance owing to their facile separation from water, resulting in easy recyclability and lower operational cost. Several magnetically separable metal ferrite nanoparticles such as ZnFe₂O_4, MnFe₂O₄, MgFe₂O₄, and CoFe₂O₄ have been used as adsorbent for remediation of dyes like Congo red, Crystal violet, and Acid red 88 (Konicki et al. 2013; Liu et al. 2015; He et al. 2017; Singh et al. 2018). Liu et al. (2015) reported the removal of Congo red dye by MnFe₂O₄ with maximum adsorption capacity of 41.99 mg/g. Similarly, Singh et al. (2018) reported the removal of Crystal violet dye by CoFe₂O₄ nanoparticles with maximum adsorption capacity of 105 mg/g. He et al. (2017) described the removal of Congo red dye by MgFe₂O₄ and maximum adsorption capacity was found to be ∼76 mg/g. Konicki et al. (2013) reported the successful application of ZnFe₂O₄ for Acid red 88 dye with maximum adsorption capacity of 111.1 mg/g. However, adsorption studies on reactive dyes by magnetic spinal ferrite nanoparticles have not yet been explored properly. Reactive orange 12 (RO12) is a reactive anionic dye and commonly used for biological staining, coloring cellulosic textiles, dermatology and veterinary medicine. In addition to toxicity towards ecosystems, human toxicity of RO12 includes skin cancer, permanent eye injury and so on, but reports on removal/degradation of RO12 are scanty (Ghaedi et al. 2014; Fraga et al. 2018). Thus in this research, the adsorptive potential of magnetic CaFe₂O₄ nanoparticles was evaluated for removal of RO12, as the CaFe₂O₄ nanoparticles are expected to be more biocompatible compared to other ferrites owing to its non-toxicity and environmentally friendly nature (Khanna & Verma 2014). Furthermore, due to high chemical and mechanical stability, and easy magnetic separation owing to its super paramagnetic behavior, CaFe₂O₄ nanoparticles could be a potential candidate as an adsorbent for large-scale application (Berchmans et al. 2010).

Thus the main objective of this research is to explore the potential of CaFe₂O₄ nanoparticles for adsorptive uptake of RO12 dye from an aqua matrix. The CaFe₂O₄ nanoparticles were fabricated using a facile precipitation method and characterized extensively for its crystalline structure, surface morphology, active chemical bonds on its surface, specific surface area, and magnetic behavior. Effects of various experimental parameters like solution pH, CaFe₂O₄ nanoparticle dose, reaction time, and initial RO12 concentrations onto the RO12 uptake (%) were investigated thoroughly. Kinetic and isotherm modeling studies were performed with adsorption experimental data to find the insights of the adsorption process. Moreover, to explore the effect of reaction temperature on the adsorption process of RO12 onto CaFe₂O₄ nanoparticles, the thermodynamic study was also performed and important thermodynamic parameters were assessed. Finally, a three-layer feed-forward neural network model was established using adsorption experimental data for accurate prediction of RO12 removal (%).

Analytical grade calcium chloride dihydrate (CaCl₂.2H₂O), NaOH pellets and ferric chloride anhydrous (FeCl₃) were bought from Merck, (India). RO12 powder (C₂₀H₂₃C_lN₉O₁₀S₃3Na; 739.98 g/mol) was obtained from Leo chem Pvt. Ltd (India). Ultrapure deionized (DI) water (Millipore) was utilized throughout the experiment.

In a typical experiment, 20.0 g of NaOH pellets was dissolved in 500 mL of DI water and agitated until the solution turned translucent. In the following step, FeCl₃ (12.0 g) and CaCl₂.2H₂O (12.0 g) were dissolved in 250 mL DI water separately in two beakers and stirring was continued till both the solutions became transparent. Thereafter, FeCl₃ and CaCl₂.2H₂O solutions were added gently to the NaOH solution and mixed until a brownish precipitate was achieved. Following the reaction, the precipitate was filtered and dried in an oven at 85 °C for 12 hours. The obtained precursor was then cleaned several times with DI water to eliminate unreacted impurities. The properly washed precursor was then heated at 200 °C for 8 hours in a muffle furnace. Finally, the brown solid materials were ground and CaFe₂O₄ was obtained in powder form and used for RO12 dye adsorption studies (Deb et al. 2017).

In Equation (1), ‘D’ represents the average crystallite domain size perpendicular to the reflecting planes, λ represents the X-ray wavelength, β represents the full width at half maximum (FWHM), and θ is the diffraction angle. Morphological investigation was performed by field emission scanning electron microscope (FESEM, Hitachi, S-4800). The Fourier transform infrared (FTIR) spectrum of CaFe₂O₄ powder was recorded with FTIR spectrometer (Perkin Elmer). The transmission electron microscopy (TEM) measurement were carried out by transmission electron microscope (JEOL, 200 kV HRTEM). The Brunauer-Emmett-Teller (BET) analysis was performed using automated gas sorption system IQ-C nitrogen adsorption apparatus (Quanta-chrome Autosorb). A vibrating sample magnetometer (VSM) (Lakeshore, 7410 series) was used to investigate the magnetic characteristics of CaFe₂O₄ powder. The salt addition method was used to analyze the PZC of CaFe₂O₄ nanoparticles. A succession of 100 mL test tubes holding 20 mL of 0.01 M KCl solution were adjusted to a pH range of 2.0–10.0 in this method. This pH was reported as the initial pH (pHi). Aqueous 0.1 N HCl or 0.1 N NaOH was used to modify the pH of these samples. CaFe₂O₄ nanoparticles in a controlled amount (0.02 g) were introduced to each tube. The solutions were well mixed and kept undisturbed for 48 hours. The filtrates' final pHs (pHf) were then measured after the solutions were separated. The pH change from pHi to pHf (ΔpH) was plotted against pHi, and the pHi value at which the pH is zero shows the adsorbent's PZC (Caner et al. 2015).

A certain amount of adsorbent was added to 50 mL of dye solution, and the mixture was stirred for a fixed time using an overhead stirrer at 200 rpm. The adsorbent was extracted from the dye solution using an external magnetic field after the completion of reaction and the supernatant was analyzed for residual dye concentration using a UV-Vis-NIR spectrophotometer (Shimadzu UV-3101PC) at maximum absorbency of RO12 (⁠⁠).

Experiments were conducted to investigate the consequence of initial solution pH on the RO12 uptake efficiency in the 2.0–7.0 pH range at room temperature. During the above mentioned experiments, the initial RO12 concentration and CaFe₂O₄ nanoparticles dose were maintained at 100 mg/L, and 1.0 g/L, respectively and the reaction was continued up to 80 min. The variation of RO12 removal and adsorption capacity in relation to CaFe₂O₄ nanoparticles dose was explored over the CaFe₂O₄ dose of 0.125–1.5 g/L. This effect of CaFe₂O₄ dose study was performed with initial RO12 concentration of 80 mg/L, contact time of 80 min and solution pH of 2.0. The variation of RO12 dye uptake efficiency (%) and adsorption capacity (mg/g) as a function of initial RO12 dye concentration with fixed CaFe₂O₄ nanoparticles dose (1.0 g/L) was performed for RO12 dye concentration (20.0–150.0 mg/L). The initial RO12 concentration was varied from 20–80 mg/L at a fixed CaFe₂O₄ nanoparticle dose of 1.0 g/L for studying the effect of contact time.

The adsorption kinetic models are used to assess the contribution and inspection of mass transfer mechanisms in any adsorption process. In the adsorption kinetic modeling, the experimental data of RO12 onto CaFe₂O₄ nanoparticles were fitted to the linear form of three kinetics models, namely the pseudo-first-order, pseudo-second-order and intra-particle diffusion models. The correlation coefficient (R²) value was used to designate the favorable kinetic model, which ascertains the adsorption type; that is, physical adsorption or chemisorption process. The intra-particle diffusion model exhibits the mass transfer process as well as the interaction among dye and the active sites of the adsorbent. The experimental data were obtained by varying the initial RO12 concentration (20–80 mg/L) with fixed CaFe₂O₄ nanoparticles dose (1.0 g/L) for adsorption kinetic studies. The adsorption isotherm models provide the information about the maximum adsorption capacity of the adsorbent and the type of adsorption. Thus the adsorption isotherm analysis was conducted by Langmuir and Freundlich isotherm model. Langmuir isotherm describes the chemisorption process with monolayer distribution of adsorbate onto the adsorbent; however, the Freundlich isotherm model defines the heterogeneous adsorption with multilayer physical adsorption process. Adsorption equilibrium experiments were performed at room temperature, varying the initial dye concentration (20–150 mg/L) with fixed CaFe₂O₄ nanoparticles dose of 1.0 g/L for isotherm studies. The effect of temperature on this adsorption process was explored by thermodynamic study. In thermodynamic study, the experiments were conducted at five different temperatures in the range of 27 °C to 55 °C using CaFe₂O₄ dose 1.0 g/L, contact time 80 min, and at the RO12 concentration of 60 mg/L.

In Equation (4), ⁠, ⁠, and are the normalized, maximum, and minimum value of variable X.

XRD pattern of the synthesized CaFe₂O₄ nanoparticles (Figure 1(a)) was analyzed to explore its crystallinity and phase components. The significant peaks occurred in the XRD pattern due to the reflection from (310), (230), (320), (201), (221), (400), (231), (340), (331), and (431) Miller planes of CaFe₂O₄ (Deb et al. 2017). The average crystallite domain size of the synthesized nanoparticles was computed using Figure 1(a) and was found ∼37 nm. A FESEM image was captured to understand the surface morphology of CaFe₂O₄ nanoparticles, which is depicted in Figure 1(b). The FESEM image shows the particle size distribution throughout a range, with the average size being less than 100 nm. Because of the material's paramagnetic properties, some particle aggregation was observed in the FESEM image. The TEM micrograph of synthesized CaFe₂O₄ nanoparticles is shown in Figure 1(c), which also indicates almost similar size distribution of the particles, likewise FESEM. The crystalline phases of the CaFe₂O₄ nanoparticles were established by the selected area diffraction pattern (Figure 1(d)), which correlates with the XRD pattern.

FTIR spectroscopy was accomplished to understand the available surface bonding of CaFe₂O₄ nanoparticles, which is depicted in Figure 2(a). Several active surface bonds were found in the FTIR spectrum in the range of 4,000 − 400 cm⁻¹, which confirmed the availability of active functional groups on the surface the synthesized nanomaterial. The detailed description of all the significant peaks observed in the FTIR spectrum is illustrated in Table 1. The magnetic response of the CaFe₂O₄ nanoparticles was studied by VSM measurements in the magnetic field of −15 K to +15 K Oe. The sample is found to be super-paramagnetic, with a magnetic saturation (Ms) value of 1.82 emu/g (Figure 2(b)). The sample's remanent magnetization (M_R) and squareness value (M_R/M_S ratio) are 0.13emu/g and 0.071, respectively. The super paramagnetic behavior of the sample is confirmed from the squareness value (less than 0.1), which means the synthesized nanoparticles are magnetizable in manifestation of an external magnetic field, permitting faster and simpler separation from aqueous solution (Yang et al. 2014). The photo showing the efficient separation of CaFe₂O₄ nanoparticles using a magnet is shown in Figure 2(b) (inset). The N₂ gas adsorption-desorption isotherm of CaFe₂O₄ nanoparticles is presented in Figure 2(c), which displays a type IV curve and H3 hysteresis. This demonstrates the prepared sample's predominance of mesoporous behavior (2 nm < pore diameter < 50 nm) and the pores' a non-uniform distribution and connectivity. The BET specific surface area and total pore volume of CaFe₂O₄ nanoparticles were found to be 229.83 m²/g and 0.145 cm³/g, respectively. The desorption isotherm was used to determine the pore size distributions of CaFe₂O₄ nanoparticles (Figure 2(c) inset), and the average pore diameter was found to be ∼2.5 nm. The adsorbent's PZC corresponds to the pH at which the adsorbent's net surface charge becomes zero. Figure 3(a) shows the variance of pH as a function of beginning pH, revealing that the PZC value of CaFe₂O₄ nanoparticle is 5.15. It signifies that the surface of the nanoparticle is positively charged when the pH is less than 5.15 and negatively charged when the pH is greater than 5.15.

Figure 3(b) shows the variation in RO12 removal (%) as a function of solution pH with the experimental conditions. At a solution pH of 2.0, the adsorption process was preferred, and the highest removal efficiency of 77% was attained. The removal efficiency decreased consistently with rose of solution pH and only 10.22% removal is observed at solution pH 7.0. Therefore, solution pH 2.0 was considered as the optimum pH for further adsorption studies. The equilibrium solution pH in relation to initial solution pH for this adsorption process is also incorporated in Figure 3(c). It can be observed that for the initial solution pH in the range of 2.0 to 5.0, the equilibrium pH has increased from its initial value, however for the initial solution pH from 6.0 and above, the equilibrium pH has shown declining trend. This could be related to the PZC of CaFe₂O₄ nanoparticles, which is found to be 5.15 (Figure 3(a)).

In the solution, the interaction of RO12 with the CaFe₂O₄ is a complex process as this interaction involves the H⁺, Cl^–, Na⁺ and anionic dye component present in the solution. In the dye and adsorbent mixed solution, when HCl was added to adjust the solution pH at 2.0, the H⁺ interacted with the adsorbent leaving behind a large number of Cl^– present in the solution. The free Cl^– available in the solution help the complex RO12 molecule to be dissociated resulting to liberating Na⁺ in the solution. This creates the opportunity to the anionic RO12 component to interact with the protonated adsorbent present in the solution. The positively charged surface of CaFe₂O₄ nanoparticles at solution pH 2.0 is also supported by the PZC measurement as PZC of CaFe₂O₄ nanoparticles was found to be 5.15. Similar adsorption behavior of RO12 have been reported by different research works (Ghaedi et al. 2011, 2013; Nia et al. 2014) indicating maximum RO12 uptake at highly acidic pH on account of strong electrostatic interaction between anionic component of RO12 and the protonated adsorbent surface. On the contrary, CaFe₂O₄ nanoparticles surface become negative above solution pH 5.15, causing the repulsion between anionic dye and negatively charged adsorbent surface. Furthermore at that pH, escalation of OH^– result to competitive adsorption with the anionic dye species available in the system resulting to significant decrease in removal efficiency (Asim et al. 2019). The electrostatic interaction between the protonated CaFe₂O₄ nanoparticles surface and RO12 at highly acidic condition is graphically exemplified in Figure 4.

The variation of RO12 removal (%) and adsorption capacity in relation to CaFe₂O₄ nanoparticles dose is presented in Figure 5. With the increase in dose from 0.125 g/L to 1.0 g/L, dye removal (%) rose from 24.54% to 95.67%, and subsequent increase in adsorbent dose could not improve dye adsorption efficiency significantly. Quick increase in uptake efficiency with increasing adsorbent dose corresponds to greater surface area with higher adsorption sites at higher CaFe₂O₄ nanoparticles dose. On the contrary, the adsorption capacity (mg/g) decreases from 157.06 mg/g to 52.14 mg/g with the increase in adsorbent dose from 0.125 g/L to 1.5 g/L. This may be due to (i) unsaturated active sites at higher dose, and (ii) overlapping of active adsorption sites on the surface of adsorbent; resulting to reduced adsorption capacity at higher dose (Sheela et al. 2012).

The variation of RO12 uptake efficiency (%) and adsorption capacity (mg/g) in relation to RO12 concentration (20.0–150.0 mg/L) with fixed CaFe₂O₄ nanoparticles dose (1.0 g/L) have been displayed in Figure 6(a). More than 97% of RO12 removal was observed for lower dye concentrations (20–60 mg/L); though increase in dye concentration reduced the removal efficiency gradually. The adsorption capacity was increased from 19.82–73.17 mg/g with enhancement in dye concentration from 20–80 mg/L, thereafter further increases in dye concentration have shown insignificant improvement in adsorption capacity. This may be due to the fact that at lower dye concentrations there were unsaturated active sites instead of high removal efficiency, but at higher dye concentrations all the active sites may get saturated and adsorption capacity reached equilibrium (Maleki et al. 2015).

The variation of RO12 removal (%) as a function of contact time is shown in Figure 6(b), which clearly depicts that initially the rate of adsorption was fast and the dye uptake efficiency increases with increasing contact time. Thereafter the adsorption rate was reduced and finally it reached equilibrium. This may be explained by the fact that, initially, availability of protonated CaFe₂O₄ nanoparticles surface led to rapid adsorption of anionic dye species due to electrostatic attraction in highly acidic conditions. As the time increases, the electrostatic repulsion between the already adsorbed anionic dye species and available adsorbate in the solution reduced the pore diffusion rate of RO12 on to the bulk of the CaFe₂O₄ nanoparticles (Fraga et al. 2018). However, the equilibrium time is different for different initial RO12 concentration. For instance, at lower initial dye concentrations (20 and 40 mg/L) the equilibrium reached after 40 min, whereas for higher initial dye concentrations (60 and 80 mg/L) it takes nearly 80 min to reach equilibrium. Hence, a stirring time of 80 min was taken as the optimal time in this adsorption process.

In Equations (6)–(8), represents the equilibrium adsorption capacity (mg/g), indicates the adsorption capacity (mg/g) at time t, and represent the rate constants of the pseudo-first-order, pseudo-second-order and intra-particle diffusion model, respectively. In the case of the pseudo-second-order kinetic model, the initial adsorption rate is represented by the parameter ‘h’ (mg/g.min), which can be described as ⁠. The constant ‘_’ in the intra-particle diffusion model indicates the thickness of the boundary layer and the higher the value of ‘⁠, the greater the effect of the boundary layer on the adsorption process (Bhowmik et al. 2017). Table 2 lists the key kinetic parameters derived from linear fitting of experimental data using three kinetic models for various initial RO12 concentrations. From Table 2, it can be seen that the R² values (0.993–0.988) for the pseudo-second-order kinetic model are superior to that of the pseudo-first-order kinetic model (0.972–0.904). Moreover the comparison between the experimental (exp) and model-predicted values also clearly indicates the close agreement between the experimental (exp) and model-predicted values for the pseudo-second-order model. Figure 7(a)–7(c) show the linear fitting of experimental data using pseudo-first-order, pseudo-second-order, and intra-particle diffusion kinetic models for varying initial RO12 concentrations (20–80 mg/L). Figure 7(b) shows the perfect fitting of experimental data with the pseudo-second-order kinetic model. The above observations suggest the applicability of the pseudo-second-order kinetic model for this adsorption process and confirm the occurrence of chemisorption between RO12 molecules and CaFe₂O₄ nanoparticles.

In the case of the intra-particle diffusion model, if the experimental data fitting line passes through the origin of the plot, it means that intra-particle diffusion is the only rate controlling step. On the contrary, if the experimental data fitting shows two linear stages, it indicates that the first line represents boundary layer diffusion while the second linear line indicates the intra-particle diffusion, and the intra-particle diffusion is not the only rate limiting step (Tanhaei et al. 2015). Experimental data can be well matched to two stages with strong correlation coefficients (R²: 0.982–0.998) using the linear form of the intra-particle diffusion model and none of them passes through the origin of the plot. This indicates the involvement of macropore diffusion followed by micropore diffusion and the intra-particle diffusion is not the only rate determining step in this process. The intercept ‘_’ is increasing with the increase in initial RO12 concentration, which indicates the involvement of the boundary layer effect. Therefore, it can be concluded that this adsorption process is governed by the boundary layer diffusion predominantly, with the involvement of intra-particle diffusion (Pirouz et al. 2015).

In this adsorption study, the calculated values are between 0.0 to 1.0 and the Freundlich constant ‘n’ is more than 1.0 (Table 3), signifying the favorable adsorption of RO12 onto CaFe₂O₄ nanoparticles. The maximum adsorption capacity of CaFe₂O₄ nanoparticles towards RO12 was calculated from the Langmuir isotherm and found to be 276.92 mg/g. In terms of maximum adsorption capacity, the adsorptive performance of RO12 dye was compared to that of other earlier reported adsorbents in Table 4. It is clear that the fabricated CaFe₂O₄ nanoparticles have exhibited higher or analogous adsorption capacity (276.92 mg/g) for RO12 compared to previously reported adsorbents like tin sulfide nanoparticles loaded on activated carbon (204.08 mg/g), platinum nanoparticles loaded on activated carbon (285.14 mg/g), ZnS:Mn nanoparticles loaded on activated carbon (94.52 mg/g) and copper sulfide nanoparticles-activated carbon (96.9 mg/g). Therefore, the above observation proposes the potential application of CaFe₂O₄ nanoparticles for RO12 adsorption from aqua matrix.

The data from the RO12 adsorption experiments were utilized to train the neural networks so as to determine the optimal network for accurate prediction of RO12 dye removal (%). Efficiency of the ANN model was analyzed in terms of R² value maximization and MSE value minimization while changing the numbers of nodes in hidden layer from 1 to 30. The dependence of MSE, R² values and number of epochs with neuron numbers (1 − 30) at the hidden layer for ANN model development is depicted in Table 6. It is clear from Table 6 that with an increase in the number of neurons, the MSE values have reduced gradually and a network with 7 numbers of neurons at hidden layer shown the minimum MSE of 0.00185 and high R² values of 0.987, 0.985, and 0.981 for the training, testing and validation data set, respectively. Hence, network with 7 neurons in the hidden layer is selected as the optimal one and can be represented as 4–7–1. The optimal network has shown the best validation performance at epoch 246 and thereafter no improvement is seen with increase in numbers of epochs, which is depicted in Figure 8(a). The linear regression analysis between model predicted normalized values and normalized experimental values (Figure 8(b)) has shown very good agreement among them and a very high linear regression coefficient is observed (0.986). The weight and bias values of hidden and output layer as determined from the optimum network are shown in Table 7, which were used for performing the sensitivity analysis to determine the relative importance of four input parameters onto the output parameter (RO12 removal efficiency). The analysis was performed employing Equation (5), and it was observed that the input parameter solution pH has evolved as the most critical parameter with a relative importance of 42%. CaFe₂O₄ nanoparticles dose and initial RO12 concentration have shown the moderate importance of 27 and 22% respectively, whereas the input parameter contact time is the least important input parameter with a relative importance of only 9%. The sensitivity analysis results are in agreement with experimental data as RO12 removal efficiency was very sensitive to solution pH (Figure 3(b)), whereas the dye uptake efficiency was hardly affected by contact time, once the adsorption process reaches equilibrium.

This investigation shows the successful synthesis of magnetically separable crystalline CaFe₂O₄ nanoparticles and its potential use as an adsorbent for removing an anionic dye called RO12 from an aqueous medium. The most efficient dye removal was observed under very acidic condition (pH = 2.0) and electrostatic attraction between anionic RO12 and the protonated surface of CaFe₂O₄ nanoparticles was the main driving force behind this adsorption process. The Langmuir isotherm model is well suited to the experimental data and maximum adsorption capacity of 276.92 mg/g is determined from this model. Kinetic analysis confirmed the applicability of the pseudo-second-order kinetic model in conjunction with the intra-particle diffusion model. The thermodynamic analysis revealed that this adsorption process is spontaneous and exothermic in nature in the considered temperature range. An optimal ANN model (4–7–1) was developed successfully for prediction of RO12 (%) with a high R² value of 0.986 and very low MSE of 0.00185. The developed ANN model could efficiently predict the RO12 dye removal (%) using the adsorption experimental data. Therefore, in the context of high demand for dye-loaded industrial effluent treatment, the fabricated CaFe₂O₄ nanoparticles may find their application owing to their easy magnetic separation, environmentally friendly nature, and high adsorption capacity towards RO12.

All relevant data are included in the paper or its Supplementary Information.