Fig. 1<\/b>![\"Fig.](\"https:\/\/www.europesays.com\/ie\/wp-content\/uploads\/2026\/09\/41598_2026_67881_Fig1_HTML.png\")
<\/p>\n
X-ray diffraction patterns for (NCCF) and NCCF\/BC composites.<\/p>\n
The peak positions are matched to ICDD Card (01-083-6066) of Ni0.5Co0.5Fe2O433<\/a>. The NCCF\/BC composites pattern resembles a hybrid of the (NCCF) and biochar patterns, with humping between 10\u00b0 and 20\u00b0, which is attributed to the amorphous structure of the biochar34<\/a>. The diffraction peaks of NCCF\/BC composites are identical to those of the as-prepared NCCF, showing that the adding biochar does not promote phase transition. Table\u00a01<\/a> shows XRD structure parameters such as average crystallite size (D), lattice parameter (a), volume of unit cell (V), dislocation density (\u03b4), and The Lattice strain (\u025b) for produced samples.<\/p>\n The interplanar spacing (d) was calculated according to Bragg\u2019s equation35<\/a>:<\/p>\n $$\\:n\\lambda\\:=2d\\text{si}\\text{n} \\theta $$<\/p>\n \n (1)\n <\/p>\n The lattice parameter of the cubic spinel structure was evaluated using the relation35<\/a>:<\/p>\n $$\\:a=d\\sqrt{{h}^{2}+{k}^{2}{+l}^{2}}$$<\/p>\n \n (2)\n <\/p>\n where (hkl) represent the Miller indices of the corresponding diffraction plane.<\/p>\n The average crystallite size (D) was estimated from the most intense diffraction peak using the Debye\u2013Scherrer equation36<\/a>:<\/p>\n $$\\:\\text{D}=\\frac{\\text{k}}{{{\\upbeta\\:}}_{\\text{h}\\text{k}\\text{l}}\\text{cos}}$$<\/p>\n \n (3)\n <\/p>\n where k is the shape factor (0.94 for cubic symmetry), \u03bb is the wavelength of the Cu K\u03b1 radiation (0.15406\u00a0nm), \u03b2 is the full width at half maximum (FWHM) of the diffraction peak expressed in radians, and \u03b8 is the Bragg diffraction angle.<\/p>\n The dislocation density (\u03b4), which indicates the amount of crystallographic imperfections within the material, was determined using37<\/a>:<\/p>\n $$\\:{\\updelta\\:}=\\frac{1}{{D}^{2}}$$<\/p>\n \n (4)\n <\/p>\n Furthermore, the lattice strain (\u03b5) arising from structural distortions such as dislocations and stacking faults was calculated using38<\/a>:<\/p>\n $$\\:{\\upvarepsilon\\:}=\\frac{{\\upbeta\\:}}{4\\text{tan}}$$<\/p>\n \n (5)\n <\/p>\n Table 1 The XRD structure parameters: average crystallite size (D), lattice parameter (a), volume of unit cell (V), dislocation density (\u03b4), and lattice strain for NCCF and NCCF\/BC composites.<\/b><\/p>\n Through structural analysis it is confirmed that biochar does not have major impact either on the crystallographic structure of NCCF ferrite as NCCF maintains cubic spinel phase with minor variations in terms of crystallite size (~\u200919\u00a0nm), lattice parameter and unit cell volume. On the other hand, as the biochar concentration increases, A significant decrease in lattice strain suggests reduced internal tensions and better structural ordering. The small variation in dislocation density indicates that biochar mostly forms defects which alter the properties from their normal behavior, rather than modifying crystal structure.<\/p>\n Crystallite size and microstrain both contribute to XRD peak broadening. To investigate the peak broadening in the XRD pattern, the crystallite size and microstrain are measured using two well-known models: the Williamson-Hall (W-H) plot and the Size-Strain Plot (SSP) method. The W-H method divides peak broadening into size and strain contributions using the following equation39<\/a>:<\/p>\n $$ \\beta {\\text{cos}}\\theta {\\text{ }} = {\\text{ }}\\left( {{\\text{k}}\\lambda \/{\\text{D}}} \\right){\\text{ }} + {\\text{ 4}}\\varepsilon {\\text{ sin}}\\theta $$<\/p>\n \n (6)\n <\/p>\n In contrast, the SSP model assumes Gaussian strain broadening and Lorentzian size broadening, which are expressed as:<\/p>\n $$ \\left( {{\\text{d}}_{{{\\text{hkl}}}} \\beta _{{{\\text{hkl}}}} {\\text{cos}}\\theta } \\right)^{{\\text{2}}} = {\\text{ }}\\left( {{\\text{k}}\\lambda \/{\\text{D}}} \\right){\\text{.d}}_{{{\\text{hkl}}}} ^{{\\text{2}}} {\\text{ }}\\beta _{{{\\text{hkl}}}} {\\text{cos}}\\theta {\\text{ }} + {\\text{ }}\\varepsilon ^{2} \/4 $$<\/p>\n \n (7)\n <\/p>\n Fig. 2<\/b> Size-strain plot (SSP) plot for NCCF and NCCF\/BC composites.<\/p>\n Table 2 Crystallite size and microstrain of NCCF and NCCF\/BC composites by the size-strain plot (SSP) method.<\/b><\/p>\n From Table\u00a02<\/a>, SSP results showed larger crystallite sizes (19.05\u201327.32\u00a0nm) and more pronounced positive strain (5.9\u20137.6\u2009\u00d7\u200910\u207b\u00b3). The SSP analysis demonstrates high accuracy compared to the Williamson\u2013Hall method, with R\u00b2 values nearly equal to one, as shown in Fig. 2<\/a>. However, the linearity observed from the Williamson-Hall plots was not good enough to allow extraction of any quantifiable crystallite size or micro-strain data. Williamson-Hall technique was kept only for the purpose of comparison with the SSP technique. The W-H analysis showed poor linearity implying that the required assumptions are not completely met in case of synthesized nanoparticles. The W-H analysis requires the assumption that the broadening of the peaks is attributed to the combined effects of the crystallite size and isotropic lattice strain40<\/a>,41<\/a>. On the other hand, spinel ferrites generally show anisotropic strain because of the cationic rearrangement, lattice imperfections, and structure distortion violating the required assumption of the W-H analysis. On the other hand, the Size-Strain Plot (SSP) method offered a better linear relationship since it gives greater weight to low-angle reflections, thus resulting in reliable estimation of crystallite size and strain in ferrite nanoparticles41<\/a>.<\/p>\n The SSP approach is generally regarded as more accurate when the lattice strain is relatively low, as it reduces the overestimation of size broadening and provides a better separation between size and strain contributions39<\/a>. Therefore, the measured crystallite size and microstrain values obtained in the present study are based on the SSP only. The increase in crystallite size upon biochar incorporation, particularly at higher loading (0.5\u00a0g), suggests that biochar may facilitate crystal growth and partially relieve internal stresses.<\/p>\n Fourier transform infrared (FT-IR)<\/p>\n FT-IR analysis further supported the spinel phase formation by revealing the presence of prominent absorption bands in the low-frequency region, specifically around 600\u00a0cm<\/b>-1<\/b> and 450\u00a0cm<\/b>-1<\/b>. The bands observed in this study correspond to the intrinsic stretching vibrations of metal-oxygen bonds in the tetrahedral and octahedral complexes, respectively42<\/a>, shown in Fig. 3<\/a>. This confirms that the cubic spinel-type NCCF (Ni\u2080.\u2086Co\u2080.\u2081Cu\u2080.\u2083Fe\u2082O\u2084) had been effectively deposited on the biochar surface43<\/a>.<\/p>\n Fig. 3<\/b> FT-IR of NCCF\/BC composites.<\/p>\n Furthermore, the FT-IR measurements provided confirmation of the functional groups found on the surface of the composite materials. The stretching vibration of O-H (from hydroxyl groups or adsorbed moisture) was identified as the cause of the broad peak observed at around 3440\u00a0cm<\/b>-1<\/b>. The absorption band at approximately 1630\u00a0cm<\/b>-1<\/b> corresponds to the stretching vibrations of C\u2009=\u2009C bonds in the aromatic rings of the biochar framework44<\/a>. Additionally, the peaks near 1380\u00a0cm<\/b>-1<\/b> and 1050\u00a0cm<\/b>-1<\/b> are attributed to C-H bending and the stretching vibrations of oxygen-containing functional groups (such as carboxylic or alkoxy C-O groups) on the biochar, respectively45<\/a>. The coexistence of these distinctive biochar peaks alongside the characteristic metal-oxygen bands provides strong evidence of the successful combination of NCCF with BC.<\/p>\n Surface characterizationsBrunauer-Emmett-Teller (BET) surface area measurements<\/p>\n The textural properties of the NCCF and NCCF\/BC composites<\/b> were examined by nitrogen adsorption\u2013desorption measurements at 77\u00a0K, following degassing at 200\u00a0\u00b0C for 8\u00a0h. As illustrated in Fig. 4<\/a>a\u2013c, the adsorption isotherms of all samples can be classified as Type IV according to the IUPAC classification46<\/a>, exhibiting a single-point saturation plateau and an H3-type hysteresis loop47<\/a>.<\/p>\n Fig. 4<\/b> (a<\/b>\u2013c<\/b>) Adsorption\/desorption isotherm, (d<\/b>) pore size distribution using BJH methods & (e<\/b>\u2013g<\/b>) t-plot method for (NCCF) and NCCF\/BC composites.<\/p>\n This behavior is characteristic of mesoporous materials composed of non-rigidly aggregated particles, leading to the formation of slit-shaped pores48<\/a>. The specific surface area, total pore volume, and average pore diameter were determined using the BET method49<\/a>, and the corresponding values are summarized in Table\u00a03<\/a>.<\/p>\n BET surface area and porosity analyses revealed significant changes upon biochar loading. The obtained NCCF that featured a mesoporous structure through interparticle voids of ferrite nanoparticles, had a moderate specific surface area of 20.67\u00a0m\u00b2 g\u207b\u00b9 and total pore volume of 0.26\u00a0cm\u00b3 g\u207b\u00b9. On addition of 0.2\u00a0g biochar (NCCF\/BC\u20130. 2), the surface area and pore volume of BET trends were substantially enhanced to 29.28\u00a0m\u00b2 g\u207b\u00b9 and 0.33\u00a0cm\u00b3 g\u207b\u00b9, respectively. This enhancement can be attributed to the highly porous nature of biochar and its role in preventing ferrite nanoparticle agglomeration, which generates additional pores. However, further increasing the biochar content to 0.5\u00a0g (NCCF\/BC\u20130.5) resulted in a decrease in surface area (17.89\u00a0m\u00b2 g\u207b\u00b9) and pore volume (0.13\u00a0cm\u00b3 g\u207b\u00b9), which is likely due to high amount of biochar allows iron oxides to enter and block some of the biochar pores50<\/a>. From the t-plot method, NCCF\/BC-0.2 was found to have the greatest external surface area (18.68\u00a0m\u00b2 g\u207b\u00b9) and micropore volume (0.0725\u00a0cm\u00b3 g\u207b\u00b9), suggesting that there was greater pore accessibility and dispersal of ferrite nanoparticles after the introduction of biochar. An increase in biochar content to 0.5\u00a0g resulted in lower values of both external surface area and micropore volume, which could be attributed to the blockage of some pores and aggregation of particles50<\/a>. These results, together with BJH analysis, confirmed that all samples possess mesoporous characteristics, making NCCF\/BC\u20130.2 the most favorable candidate for adsorption-based environmental applications.<\/p>\n Table 3 The total pore volume, BET average pore size, BET surface area, external surface area micropore volume of (NCCF) and NCCF\/BC composites.<\/b>Magnetic properties<\/p>\n The magnetic properties were investigated using vibrating sample magnetometer (VSM) at room temperature. Figure 5<\/a> displays the magnetic hysteresis loops of (NCCF) and NCCF\/BC composites at 300\u00a0K, and the derived magnetic parameters are summarized in Table\u00a04<\/a>. The saturation magnetization (Ms), remanent magnetization (Mr) and coercivity (Hc) of the pure NCCF sample were 46.15 emu g\u207b\u00b9, 8.94 emu g\u207b\u00b9 and 131.14 Oe respectively, suggesting that it exhibited typical ferrimagnetic characteristics for a spinel ferrite51<\/a>. by loading of biochar (BC), both Ms and Mr decreased with increasing BC content. The Ms value decreased to 33.48 emu g\u207b\u00b9 for NCCF\/BC\u20130.2 and further to 23.02 emu g\u207b\u00b9 for NCCF\/BC\u20130.5, while Mr decreased from 8.94 to 6.63 and 4.55 emu g\u207b\u00b9, respectively. Such decrease is due to reduction of the magnetic phase by the non-magnetic biochar matrix, which weakens metal ion interactions through superexchange at either tetrahedral (A) or octahedral (B) sites in the spinel structure for a reduced net magnetic moment.<\/p>\n Fig. 5<\/b> Magnetic hysteresis curves of (NCCF) and NCCF\/BC composites at 300\u00a0K.<\/p>\n The remanence ratio (R\u2009=\u2009Mr\/Ms) was approximately constant across all samples (~\u20090.19\u20130.20), indicating that the magnetic domain configuration is largely independent of the addition of BC. In contrast, the coercivity showed a slight decrease from 131.14 Oe for pure NCCF to 123.34 Oe and 117.41 Oe for NCCF\/BC\u20130.2 and NCCF\/BC\u20130.5, respectively. This observed reduction is ascribed to the reduced interparticle magnetic interactions resulting from the presence of carbon matrix, which partially separates the ferrite nanoparticles. Furthermore, surface effects and possible slight differences in particle size may affect magnetic anisotropy. Comparative drops in coercivity and magnetization have been noted for ferrite\u2013biochar composites, attributed to the non-magnetic carbon phase which acts on both magnetic coupling as well as structural properties52<\/a>.<\/p>\n Table 4 Saturation magnetization (Ms), remanent magnetization (Mr), squareness ratio (R), and coercivity (Hc) for (NCCF) and NCCF\/BC composites.<\/b><\/p>\n Overall, the results indicate that incorporating biochar into the NCCF structure effectively changes the magnetic properties by reducing saturation magnetization while maintaining moderate coercivity. Despite the reduction in magnetization, the composites still have sufficient magnetic response, which is advantageous for applications requiring magnetic separation, such as wastewater treatment and catalytic processes.<\/p>\n Application of biochar-based magnetic adsorbents for the Pb(II) ions removalEffect of the solution pH<\/p>\n The solution pH has a vital role in determining the adsorption mechanism and the removal efficiency. Several mechanisms have been reported for the removal of Pb(II) ions by biochar-based adsorbents such as; physical adsorption, surface complexation, electrostatic interactions, ion exchange, and minerals precipitation53<\/a>. Generally, at low pH values, a repulsion between the positively charged functionalized biochar and Pb (II) ions leads to a poor uptake. While, as the pH values increases\u2009>\u20093\u20134, the adsorption efficiency increases54<\/a>,55<\/a>,56<\/a>. On the other hand, the point of zero charge, PZC, for NCCF, as reported in our previous work, is 5.248<\/a>. Figure 6<\/a> shows the variation of the removal efficiency of the bare biochar; BC, and the prepared magnetic nanocomposites; NCCF\/BC-0.2 and NCCF\/BC-0.5 with the solution pH. Based on the above findings, an expected trend is shown in Fig. 6<\/a>, where the removal % is high at high pH values\u2009>\u20095. While, at low pH value of 4, the biochar maintains its excellent performance, PZC\u2009=\u20092\u2013354<\/a>, the decrease in the removal % is related to the magnetic NCCF and it is more pronounced with increasing NCCF content in the composite, sample NCCF\/BC-0.2.<\/p>\n Fig. 6<\/b> Variation of the removal % of Pb(II) ions by BC, and NCCF\/BC composites with the pH, the initial Pb(II) ions concentration\u2009=\u200930 ppm, shaking time\u2009=\u200924\u00a0h, at room temperature.<\/p>\n Kinetic study<\/p>\n The adsorption efficiency % of NCCF and prepared magnetic nanocomposites for the removal of Pb(II) ions, are calculated at different contact times. Figure 7<\/a>A shows the variation of the removal % with the contact time. It is clear that introducing biochar in the nanocomposite facilitates the adsorption, especially at the early stages. The equilibrium is reached within 30\u00a0min. for NCCF while, a much faster uptake, within 10\u00a0min., is observed by introducing the biochar and it is more pronounced with increasing its amount.<\/p>\n Kinetic data are fitted to pseudo first, pseudo second kinetics, and the intra-particle diffusion models, as shown in Fig. 7<\/a>B\u2013D, respectively57<\/a>.<\/p>\n $$\\:\\text{log}\\left({q}_{e}-{q}_{t}\\right)=\\text{log}{q}_{e}-\\frac{{k}_{1}}{2.303}\\:t$$<\/p>\n \n (8)\n <\/p>\n $$\\:\\frac{t}{{q}_{t}}=\\frac{1}{{k}_{2}{q}_{e}}+\\:\\frac{t}{{q}_{e}}$$<\/p>\n \n (9)\n <\/p>\n $$\\:{q}_{t}={k}_{id}\\sqrt{t}+\\:C$$<\/p>\n \n (10)\n <\/p>\n where, qt and qe represent the amounts adsorbed at time\u2009=\u2009t and at equilibrium, respectively. k1 and k2 denote the pseudo first and second order rate constants of adsorption, respectively. kid is the constant for intra-particle diffusion rate.<\/p>\n Fig. 7<\/b> (A<\/b>) Variation of the removal % of Pb(II) ions by NCCF, and NCCF\/BC composites with the contact time, at pH\u2009=\u20096, the initial Pb(II) ions concentration\u2009=\u2009100 ppm, at room temperature, (B<\/b>) 1st, (C<\/b>) 2nd order kinetic, and (D<\/b>) the intra-particle diffusion model for NCCF\/BC-0.2, and NCCF\/BC-0.5.<\/p>\n From calculated kinetic parameters listed in Table\u00a05<\/a>, The values of R2 are closer to unity, and the calculated adsorbed amounts at equilibrium, qe, are closer to the experimental values, in the case of the pseudo second order kinetics. Thus, it can be concluded that the adsorption of Pb(II) ions on magnetic NCCF, and prepared magnetic biochar-based composites follows the pseudo second order kinetics, suggesting a chemisorption mode through a complexation of surface functional groups57<\/a>,58<\/a>. By increasing the amount of the biochar, in the prepared composite, the kinetic of the adsorption is more facilitated, as indicated by the higher k2 values.<\/p>\n Table 5 Calculated kinetic data for the adsorption of Pb2+ ions by NCCF, and NCCF\/BC composites samples for pseudo 1st, pseudo 2nd, and intraparticle diffusion models.<\/b><\/p>\n Two linear sections are observed in the intra-particle diffusion models for NCCF\/BC-0.2, and NCCF\/BC-0.5 samples, as shown in Fig. 7<\/a>D, suggesting that the Pb(II) ions are first adsorbed at the composite surface then, it is diffused into the sorbent pores57<\/a>. Higher intercept values and lower rate constants are observed for the second linear sections related to the pore diffusion; in the case of NCCF, therefore, the pore diffusion is limited with respect to the surface adsorption, and can be considered as the rate-determining step for the adsorption of Pb(II) ions on the magnetic NCCF48<\/a>. It is worth mentioning that in the presence of the biochar, both surface adsorption and pore diffusion can be attributed to the rate-determining step, since the values of surface and diffusion intercepts are comparable. This is due to the increased porosity of biochar-based composites relative to the bare NCCF.<\/p>\n Adsorption isotherms<\/p>\n The Variation of the removal % and the adsorption capacity of Pb(II) ions by NCCF, NCCF\/BC-0.2, and NCCF\/BC-0.5 with the initial metal ions concentration is shown in Fig. 8<\/a>A. The removal % and the adsorption capacity increase by the increasing the initial Pb(II) ions concentration, and this is more pronounced with the increasing the biochar amount in the composite, reflecting the excellent adsorption performance of the prepared magnetic nanocomposites. The observed increase in removal efficiency with increasing of the initial metal ion concentration, within the evaluated concentration window, can be attributed to mass transfer kinetics and synergistic surface phenomena. High initial pollutant concentrations yield a concentration gradient that overcomes liquid film diffusion resistance, forcing pollutant species deeper into the micro\/mesoporous network of the composite. Furthermore, for materials exhibiting cooperative adsorption behavior, the initial ion uptake enhances the affinity of the sorbent for the remaining ions via intermolecular interactions, which in turn outcompetes the background solvent molecules.<\/p>\n Fig. 8<\/b> (A<\/b>) Variation of the removal % and the adsorption capacity of Pb(II) ions by NCCF, and NCCF\/BC composites with the initial metal ions concentration at pH\u2009=\u20096, shaking time\u2009=\u20092\u00a0h, at room temperature. (B<\/b>) Langmuir, (C<\/b>) Freundlich, and (D<\/b>) Temkin adsorption isotherms for adsorption of Pb(II) ions on NCCF\/BC-0.2.<\/p>\n The adsorption data are fitted to Langmuir59<\/a>, Freundlich60<\/a> and Temkin61<\/a> isotherms, as shown in Fig. 8<\/a>B\u2013D, respectively. According to the following Eqs.62<\/a>,63<\/a>,64<\/a>, different isotherms parameters are calculated and listed in Table\u00a06<\/a>.<\/p>\n $$\\:\\frac{{C}_{e}}{{q}_{e}}=\\frac{1}{{K}_{L}{q}_{m}}+\\frac{{C}_{e}}{{q}_{m}}$$<\/p>\n \n (11)\n <\/p>\n $$\\:\\text{ln}{q}_{e}=\\text{ln}{K}_{F}+\\:\\frac{1}{n}\\text{ln}{C}_{e}$$<\/p>\n \n (12)\n <\/p>\n $$\\:{q}_{e}=\\:\\frac{RT}{b}\\text{ln}{K}_{T}+\\:\\frac{RT}{b}\\text{ln}{C}_{e}$$<\/p>\n \n (13)\n <\/p>\n where, KL, KF, and KT are Langmuir, Freundlich, and Temkin constants, respectively. qm is the maximum adsorption capacity (mg.g\u2212\u20091). n and b are Freundlich and Temkin constants.<\/p>\n Table 6 Calculated adsorption isotherms parameters by fitting the adsorption data of Pb(II) ions by the prepared NCCF, and NCCF\/BC composites samples to different isotherms.<\/b><\/p>\n Based on the correlation coefficient, R2, values, the adsorption of Pb(II) on NCCF, NCCF\/BC-0.2, and NCCF\/BC-0.5 fits best Freundlich isotherms, that is to say the adsorption occurs on non-energetically equivalent heterogenous sites. To further evaluate the adsorption isotherms, nonlinear regression was performed. As shown in Fig. 9<\/a>; Table\u00a07<\/a>, samples NCCF and NCCF\/BC-0.5, Freundlich can better describe the adsorption data (which agrees with the linear models). While for sample NCCF\/BC-0.2, Langmuir is better. The calculated qm values for NCCF\/BC-0.2 and NCCF\/BC-0.5, as presented in Table\u00a07<\/a>, were 388.28 and 217.49\u00a0mg.g\u207b\u00b9, respectively, indicating their high adsorption capacities. The same trend is observed which is the decrease in the qm value as the biochar amount increases. For sample NCCF, the Langmuir isotherm failed to yield physically realistic parameters (qm=2.29\u2009\u00d7\u2009107 mg\/g, R2\u2009=\u20090.6723) due to the absence of a saturation plateau within the measured concentration range.<\/p>\n Fig. 9<\/b> Non-linear fits for Langmuir, Freundlich, and Temkin models across (a<\/b>) NCCF, (b<\/b>) NCCF\/BC-0.2, and (c<\/b>) NCCF\/BC-0.5.<\/p>\n Table 7 Non-linear parameters and goodness-of-fit metrics as indicated by regression coefficient, R2, root mean square error (RMSE) and Chi-square (\u03c72).<\/b><\/p>\n The adsorption mechanism, in the presence of biochar, is more complicated and favored by many factors. The presence of more oxygen-containing functional groups; OH and C-O groups, and also aromatic C\u2009=\u2009C groups, which provide \u03c0-electrons required for the surface complexation with the Pb(II) ions, as shown if FT-IR section, Fig. 3<\/a>. Moreover, the enhanced porosity and the surface roughness53<\/a>,54<\/a>,55<\/a>,65<\/a> resulted in effective surface area and promoted adsorption performance. The calculated maximum adsorption capacities for NCCF\/BC-0.2 and NCCF\/BC-0.5 are much higher than that for the bare NCCF, indicting the enhanced adsorption performance by introducing the biochar phase in the magnetic adsorbent. The adsorption capacity values are three-times and nine-times higher than that of the bare NCCF for biochar ratio of 0.5 and 0.2, respectively. Higher biochar ratio in NCCF\/BC-0.5, still performs better than the bare magnetic ferrite NCCF, but the ratio required to be optimized because higher ratio reduce the porosity and the effective surface area. The maximum adsorption capacities reported for biochar materials, prepared by the pyrolysis of different agriculture wastes, range from 20 to 200 mg.g\u2212\u2009153<\/a>. In this study, introducing the magnetic ferrite to the biochar not only added a magnetic character to the adsorbent and thus a practical applicability, but also enhanced the adsorption performance, qm for NCCF\/BC-0.2 is 398.4 mg.g\u2212\u20091.<\/p>\n To evaluate the practical competitiveness of NCCF\/BC-0.2, qm value, 398.4 mg.g\u2212\u20091, is benchmarked against alternative commercial and state-of-the-art sorbents under comparable conditions. As summarized in Table\u00a08<\/a>, NCCF\/BC-0.2 exhibits a capacity nearly double that of standard commercial activated carbons (150\u2013250\u00a0mg\/g) while operating efficiently at a low dosage (\\(\\:1.0\\text{\\:g\/L}\\)) and neutral pH (\\(\\:\\text{pH\\:}6.0\\text{–}7.0\\)). Although pristine metal-organic frameworks (MOFs) can achieve higher raw capacities, their industrial adoption is hindered by high production costs and poor hydrothermal stability. In contrast, the biochar composite developed in this work offers a favorable balance of high uptake capacity, low cost, green synthesis, and operational robustness, confirming its genuine potential for industrial wastewater remediation.<\/p>\n Table 8 A literature benchmarking and comparative sorbent performance.<\/b>Regeneration and interferences study<\/p>\n The possibility of the adsorbent regeneration and the number of its operating adsorption cycles greatly influence the adsorbent applicability. In this work, the prepared NCCF\/BC-0.2 sample is regenerated by being shaken in 1% HNO3 solution for 1\u00a0h. Figure 10<\/a>A shows the variation of the removal % of NCCF, NCCF\/BC-0.2, and NCCF\/BC-0.5 samples for the Pb(II) ion with successive four operation-regeneration cycles. It can be shown that by increasing the biochar amount in the magnetic composite, the adsorbet maintains more its high adsorption performance especially after the third cycle. ICP analysis of the filtrates is performed after four successive regeneration\/reuse of the presented samples. It was shown that no traces of Fe, Ni, Co, or Cu ions are present, indicating the stability of the proposed adsorbents.<\/p>\n![\"Fig.](\"https:\/\/www.europesays.com\/ie\/wp-content\/uploads\/2026\/09\/41598_2026_67881_Fig2_HTML.png\")
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