Biochar (BC) was prepared utilizing residues from three distinct agricultural crops. A comprehensive comparative analysis was conducted to select the most favorable option. Initially, corn, rice, and wheat straw were subjected to deionized water rinsing, followed by drying at 60°C. The dried material was subsequently pulverized and sieved to obtain straw particles with a diameter of 0.15 mm. Finally, employing these different straw powders as raw materials, BC was individually prepared through pyrolysis in a tube furnace under a nitrogen atmosphere. The pyrolysis temperatures employed in this study were 500°C, 600°C, and 700°C, each maintained for 2 hours to ensure consistent thermal condition.

The co-precipitation method was employed to synthesize chromium ferrite-biochar composite (CF-BC), utilizing BC as the carrier material. Firstly, the simulated wastewater containing Cr (VI) in the concentration of 1000 mg/L was prepared by dissolving K₂Cr₂O₇ (Merck-1.04862) in deionized water. According to the designed molar ratio, the theoretical dosage of Fe²⁺ should be 5 times that of Cr⁶⁺ [42], FeSO₄·7H₂O was introduced into 50 mL of chromium-containing wastewater and stirred vigorously. After thorough mixing, 5 mol/L NaOH was added to adjust the pH to 10.5. Subsequently, different masses of BC were separately added, and the reaction mixture was stirred at 100°C. Upon completion of the reaction, the mixture was allowed to cool, followed by filtration using a sand core funnel and rinsing with deionized water until the solution reached neutrality. The resulting material was then dried in an electric constant temperature oven at 80°C for 24 hours. After grinding, the obtained powder was identified as the CF-BC composite. The composites prepared with BC amounts of 0.1 g, 0.2 g, and 0.3 g are respectively denoted as CF-BC1, CF-BC2, and CF-BC3.

To simulate CR organic dye wastewater in the laboratory, 1 gram of Congo Red (CR) was dispersed in 1000 mL of deionized water, resulting in a concentration of 1000 mg/L of CR dye. Pre-measured adsorbents were then added to a specific volume of the CR solution. The entire experimental process was conducted in a constant-temperature shaking incubator at a rotation speed of 200 revolutions per minute (rpm) for adsorption treatment. Post-treatment, the organic wastewater was analyzed using a UV-visible spectrophotometer at the maximum wavelength of CR (λ = 497 nm) to measure the absorbance of the solution. Adsorption capacity and removal efficiency were calculated based on a standard curve [49].

Calculate the adsorption capacity based on the following Eq. (1)

Here, q_e represents the adsorption capacity (mg/g), C₀ and C_e denote the initial concentration and equilibrium concentration of CR, respectively (mg/L). “V” stands for the volume of the CR solution (L), and “m” represents the mass of the adsorbent (g).

The percentage of removal efficiency (R) is determined by Eq. (2):

Specific surface area is a crucial factor affecting the loading and adsorption efficiency of biochar (BC). The pyrolysis temperature of biochar can influence its adsorption capacity [50]. Therefore, the specific surface area of BC prepared from different agricultural crop residues (wheat, rice, corn [51]) at various pyrolysis temperatures was determined, as shown in Fig. S1(a). Under the preparation conditions of 500°C and 600°C, BC prepared from rice straw has a much larger specific surface area compared to that from wheat straw and maize straw. However, at 700°C, the specific surface area of BC prepared from rice straw decreases instead. Since BC prepared from rice straw at lower temperatures possesses a larger specific surface area, it is more suitable for loading and adsorption. As indicated in Fig. S1(b,c,d), BC prepared from wheat straw at 700°C, corn straw at 700°C, and rice straw at 600°C exhibit Type I adsorption isotherms, indicating a relatively abundant microporous structure. Other BC samples exhibit Type III adsorption isotherms, indicating weak monolayer adsorption and making them less suitable as adsorbents. Fig. S2 shows the adsorption effect of different biochar on CR under certain conditions. The adsorption effect of 700°C wheat straw, 700°C corn straw and 600°C rice straw is significantly better than that of other temperatures in biochar prepared from the same kind of straw. Considering the production cost, the energy consumption of biochar produced with straw as raw material at 600°C is lower. Also considering that China is a major producer of grain, with rice production ranking first, followed by wheat and maize, in order to minimize energy consumption, BC prepared from rice straw at 600°C was used for subsequent experiments.

XRD Analysis revealed the crystalline phases of BC, CF and CF-BC composites (Fig. 1(a)). The presence of an amorphous peak around 24° indicates that BC is an amorphous material. The diffraction peak at around 44° corresponds to the graphite crystal structure of BC [52]. The diffraction peaks at 30.3°, 35.2°, 43.2°, 53.9°, 57.4°, and 63.0° correspond to the (220), (311), (400), (422), (511), and (440) hkl planes, respectively. By comparing the XRD data with standard diffraction patterns of spinel, it was confirmed that the characteristic peaks of FeCr₂O₄ were present.

FT-IR analysis was employed to determine the functional group structures in the composites. As shown in Fig. 1(b), it can be observed that the BC obtained from rice straw pyrolyzed at 600°C exhibits stretching vibration peaks of −OH at 3270 cm⁻¹, a C=C vibration peak at 1589 cm⁻¹, and absorption bands at 1419 and 1017 cm⁻¹, which are mainly attributed to the stretching vibrations of −OH in alcohols or phenols and C-O-C in alcohol ethers or esters. The inherent vibrations of tetrahedral coordination (Fe-O) were observed in the range of 500–600 cm⁻¹, while octahedral coordination (Cr-O) vibrations were detected in the range of 500–400 cm⁻¹[53]. Two peaks corresponding to the metal-oxygen bonds of tetrahedral and octahedral sites appeared at 543 cm⁻¹ (ν1) and 441 cm⁻¹ (ν2), respectively, which closely matched the typical vibrations of spinel ferrite. Additionally, a stretching vibration peak of −OH at 3357 cm⁻¹, stretching vibration of C=C in the composite at 1611 cm⁻¹, and stretching vibration of C-O-C in alcohols, ethers, or esters at 1075 cm⁻¹ were observed, confirming the successful deposition of cubic spinel-type CF on the surface of BC.

Table S1 and S2 show the elemental analysis of BC and CF-BC composites with different BC doping amounts. The element content of BC is diverse, and CF-BC composite is mainly composed of C, O, Fe and Cr, of which Fe content is the highest. CF brings a large amount of iron to the complex, making it easier to magnetic separation and recovery. In addition, because the amount of CF is fixed, the available active sites are limited. With the increase of BC content, Fe and Cr contents in CF-BC2 and CF-BC3 decreased significantly compared with CF-BC1. In Fig. 1(c), with the increase of BC content, the saturation magnetization of CF-BC1, CF-BC2 and CF-BC3 is 31.33, 25.59 and 23.45 emu/g, respectively. However, the saturation magnetization of CF is 36emu/g, and this decrease is attributed to the dilution effect of non-magnetic BC on magnetic nanoparticles [45]. Magnetic biochar with superparamagnetization can be quickly recovered and reused under the action of applied magnetic field without loss of active site, which provides a basis for the recovery and reuse of adsorbent [26]. The magnetic hysteresis loop of CF showing S-type is consistent with the typical characteristics of spinel ferrite materials. As BC is non-magnetic, the addition of CF makes the composite nanoparticles easy to be magnetized and demagnetized, thus forming soft magnetic materials. Therefore, the overall composite material still has considerable magnetic properties, which provides favorable conditions for subsequent recycling.

In order to better understand the microstructure of BC, CF and CF-BC composites, SEM tests were performed (Fig. 2 (a–f)). It can be observed that the surface of BC is relatively rough, showing an irregular porous structure, which is typical of agricultural waste-derived carbon materials (Fig. 2 (a)). In addition, the uneven size of pores on the BC surface is consistent with the previously determined large specific surface area. This provides potential for BC as a structural carrier of CF [54]. CF, on the other hand, consists of condensed magnetic nanoparticles. (Fig. 2 (c)) It can be seen that the diameter of CF particles is very small, and the magnetic properties of chromium ferrite make chromium ferrite exist in the form of clusters. For composite materials, SEM images enhance the results of XRD and FT-IR, demonstrating that chromium ferrite particles are successfully attached to the surface of biochar. But as the amount of CF added increases, the number of pores in the complex also decreases, which is more unfavorable to adsorption. Although CF-BC1 has more pores than CF-BC2, too large pores are not conducive to the adsorption of organic matter. However, SEM images of CF-BC2 composites showed that CF nanoparticles were uniformly dispersed in the pores of BC (Fig. 2 (e)), indicating that BC as a carrier could reduce aggregation and enhance the activity of CF particles [55]. This is because the presence of amorphous carbon with a lamellar structure facilitates the efficient separation of nanoparticles. This amorphous carbon inhibits the aggregation of nanoparticles by reducing the binding between particles, thereby increasing the available surface area of nanoparticles and further enhancing their adsorption capacity [56]. In addition, the uniform distribution and coexistence of C, O, Cr and Fe elements were clearly observed on the CF-BC2 surface from the EDS mapping (Fig. 2 (g)). The finding affirmed that ferrite was grown on the surface of BC, in which the low agglomeration phenomenon might make composites possess more active sites and show better adsorption stability.

To further confirm the pore analysis in SEM, the nitrogen adsorption/desorption isotherm and pore size distribution of CF-BC2 composite are shown in Fig. S3(a) and (b), respectively. It can be seen from Fig. S3(a) that the adsorption of CF and CF-BC2 composites follows the Type IV adsorption isotherm classified by IUPAC, which is the adsorption isotherm model for mesoporous materials. However, there is a bulge in the second half of the curve, and there may be an adsorption hysteresis loop in the middle part, corresponding to the system of capillary condensation of the porous adsorbent. From the type of hysteresis loop, it belongs to the H3 type [57], indicating that the adsorbent material is mesoporous material, indicating that the introduction of iron may destroy the micropore wall and increase the proportion of mesoporous biomass in biomaterials [58]. At the same time, the specific surface area of CF-BC2 is 100.93 m²/g, which is smaller than that of BC (141.67m²/g). This may be due to the fact that CF particles are loaded on the surface of BC during the preparation process and block part of the pores, but it is much higher than the surface area of CF 25.55 m²/g. This means that the addition of BC increases the specific surface area of the complex, which is more conducive to adsorption. As shown in Fig. S3(b), the pore size of CF-BC2 is distributed between 2 and 15 nm. The results showed that the pore volume and size increased, and the excellent mesoporous structure was conducive to the diffusion and adsorption of pollutants in biochar [59, 60].

The XPS wide scanning spectra of CF and the three compounds confirm that Fe, Cr, C and O are mainly present (Fig. 3). High-resolution XPS spectra of C-1s, Cr-2p and Fe-2p are further analyzed (Fig. 3(a)). The C-1S spectrum can be deconvolved into three peaks corresponding to C-C, C-O, and C=O(Fig. 3(b)). The highest intensity peaks at CF-BC are attributed to the graphite structure (C-C), indicating that the carbon components in CF-BC have a highly aromatic structure. The more graphite structure of biochar, the more pore structure, the more favorable for adsorption. After binding with biochar, the peak value of C-O in CF-BC1, CF-BC2 and CF-BC3 changed from 286.08 eV to 286.58 eV, 286.2 eV and 286.5 eV, with relative contents of 19%, 22% and 11%, respectively. By comparing the three compounds, It is observed that the C-O content of CF-BC3 is relatively small, and according to the peak area of C=O, the highest relative content of CF-BC1 is 17%, which is 11% more than the C=O content of CF alone. The C=O content of CF-BC complex gradually decreases, which is because the magnetic nanoparticles are doped in the non-magnetic BC. It is caused by the dispersion of BC to CF nanoparticles. In Fig. 3 (c, d), The Fe 2p peaks of CF-BC1, CF-BC2, and CF-BC3 can be attributed to Fe (III) at 711.73 eV, 711.8 eV, and 712.33 eV, and Fe (II) at 709.61 eV, 709.84eV, and 709.58eV. The Cr2p peaks of CF-BC1 are 575.78 eV and 585.51 eV, CF-BC2 are 575.68 eV and 585.93 eV, and CF-BC3 are 576.34 eV and 586.04 eV, which mainly contribute to the binding energy of Cr (III). The results indicated that Cr (III), Fe (III) and Fe (II) existed in the complex.

To examine the relationship between adsorption capacity (q_e) and concentration (C_e) at equilibrium, various adsorption isotherm models were extensively employed for data fitting [62]. Among them, the Langmuir and Freundlich equations are the most widely applied, as shown in Eq. (3) and (5) respectively. The Langmuir model assumes that adsorbate molecules undergo single-layer adsorption on a uniform surface, without interaction between the adsorbed molecules. The Freundlich model is suitable for non-ideal adsorption on heterogeneous surface [63]. This heterogeneity arises from the presence of various functional groups on the surface, as well as interactions between adsorbent and adsorbate species [64]. In order to obtain equilibrium data, adsorption experiments were conducted by varying the initial concentration of CR (200, 400, 500, 600, 800, and 1000 mg/L) on the samples.

In Eq. (3), where q_e represents the amount of CR adsorbed per unit mass of adsorbent at equilibrium (mg/g), C_e is the equilibrium concentration of CR in the solution (mg/L). Q₀ provides the theoretical monolayer adsorption capacity (mg/g), where K_L is the Langmuir constant related to the adsorption energy. Q₀ and K_L can be calculated from the slope and intercept, respectively [65].

In addition, to elucidate the fundamental characteristics of the Langmuir isotherm, a dimensionless constant termed as the separation factor, denoted as R_L, is introduced. It is defined as shown in Eq. (4):

where C₀ stands for the initial concentration of CR (mg/L), and R_L represents the dimensionless constant. When the value of R_L falls between 0 and 1, it indicates favorable adsorption.

In Eq. (5), K_F represents the constant related to the adsorption capacity, C_e represents the concentration of the dye in the solution at equilibrium (mg/L), q_e represents the equilibrium adsorption capacity of the adsorbent (mg/g), and n represents the parameter related to the adsorption intensity. When n is greater than 1, it indicates good adsorption performance [66].

The Langmuir and Freundlich isotherm models for CF are shown in Fig. 5 (a, b), and the specific parameters for the fitted equations are provided in Table S4. As shown in Fig. 5(a, b), the adsorption capacity of CF for CR increases with the initial concentration, indicating that higher concentrations intensify the collision between adsorbent and pollutant. Furthermore, with the rise in temperature, the adsorption capacity of CF for CR steadily increases, suggesting that temperature favors the progress of the reaction, indicating an endothermic process. From Table S4, it is evident that the Langmuir correlation coefficient for CF is higher than that for the Freundlich isotherm. This indicates that the Langmuir model provides a better fit to the experimental data compared to the Freundlich model, suggesting that CF undergoes monolayer adsorption of CR molecules. The adsorption sites on the surface of the adsorbent are evenly distributed, and the energy is equivalent. Additionally, the value of 0 < R_L < 1 indicates that the adsorption process is favorable.

The Langmuir and Freundlich Isotherm models for CF-BC2 are shown in Fig. 5(c, d), and the specific fitting parameters are listed in Table S5. From Fig. 5(c, d), it is observed that the adsorption capacity of CF-BC2 increases with the initial concentration of CR. This is attributed to the fact that higher concentrations can capture more dye molecules. Furthermore, as the temperature rises, the adsorption capacity of CF-BC2 for CR continues to increase, indicating that the process is more favorable for adsorption at higher temperatures, suggesting an endothermic reaction.

According to Table S5, the Freundlich model provides a better fit for the adsorption isotherm of CF-BC2. This suggests that the adsorption of CR onto CF-BC2 follows the coverage principle, occurring on heterogeneous surfaces and non-equivalent sites, which is related to the developed pores within CF-BC2 due to the load on BC. Moreover, the value of n being greater than 1 indicates that the conditions are favorable for the adsorption reaction.

Observing adsorption kinetics is crucial in adsorption studies, as it can predict adsorption rates and potential mechanisms [62]. In this study, pseudo-first-order and pseudo-second-order kinetic models [67] were employed to analyze the adsorption process of CF and CF-BC2 for the dye. The conformity between experimental data and model-predicted values was evaluated using the correlation coefficient (R²). Higher R² values indicate that the model successfully describes the dynamic adsorption process of different materials.

Here, in Eq. (6), q_e and q_t represent the adsorption capacities at equilibrium and time t (mg/g), respectively. k₁ is the first-order adsorption rate constant (min⁻¹). Plotting log(q_e-q_t) against t yields a straight line. The values of k₁ and q_e are obtained from the slope and intercept of this line.

In Eq. (7), q_e and qt represent the adsorption capacities at equilibrium and time t, (mg/g), respectively. k₂ stands for the rate constant (g/(mg ·min)). The values of q_e and k₂ are determined by the slope and intercept of the curve, respectively.

The fitting results of the pseudo-first-order and pseudo-second-order kinetic models for different adsorbents are shown in Fig. 5(e, f). The specific fitting parameters can be found in Table 1.

The degree of fit of the fitted curves in Fig. 5(e, f) indicates that both materials are better described by the pseudo-second-order kinetic model. Table 1 shows that the correlation coefficients of the pseudo-second-order kinetic equations for CF and CF-BC2 composites are 0.9814 and 0.9990, respectively, which are higher than those of the pseudo-first-order kinetic equations. The adsorption capacities calculated by the pseudo-second-order kinetic model are more in line with the experimental results. This suggests that the adsorption of CR by CF and CF-BC2 follows the pseudo-second-order kinetic model. According to the assumption of the pseudo-second-order kinetic model, it can be inferred that chemical adsorption is the main process in this adsorption. The value of k₂ indicates that the chemical adsorption rate of CR on the surface of CF is slower than that of CF-BC2 composite, which is attributed to the increase in active sites due to the addition of BC, thereby facilitating the adsorption process [68].