Iron-Modified Biochar Derived from Poultry Manure for Efficient Removal of Methyl Orange Dye from Aqueous Solution

Abstract

Waste and chemicals generated from industry have been a major source of pollution and a prominent threat to human health via the food chain; hence, an efficient and durable material that can be used to detoxify polluted soil and water bodies is necessary to attain ecosystem equity and security. This study hypothesized that biochar (BC) made from poultry manure (PM) through pyrolysis and fortification with iron (Fe–BC) can be used to remove methyl orange dye from aqueous solution. Furthermore, this study evaluated the effect of solution pH on the sorption of methyl orange through batch sorption studies. The similarity in the modeled data and experimental data was measured by the standard error of estimate, whereas sorption isotherms were examined using nonlinear forms of different sorption equations. With the use of Langmuir models, a maximum sorption capacity of 136.25 mg·g⁻¹ and 98.23 mg·g⁻¹ was recorded for Fe–BC and BC, respectively. Fe–BC possessed a higher adsorption ability in comparison to BC. The pseudo-second-order best described the sorption kinetics of both adsorbents at R² = 0.9973 and 0.9999, indicating a strong interaction between MO and Fe–BC. Furthermore, the efficiency with which MO was removed by the absorbent was highest at lower pH (pH = 4). It is therefore concluded that Fe–BC can be used as an effective and environmentally friendly material for detoxification of wastewater; however, further research on the application and usage of biochar modified techniques for enhancing adsorption efficacy on a large scale should be encouraged.

1. Introduction

In our modern world, where industrial activities flourish, the vibrant colors of synthetic dyes permeate our lives [1]. From the clothes we wear to the products we use daily, these dyes contribute to our aesthetic experiences. However, their journey doesn’t end there. Once discharged into water bodies, they pose a significant threat to environmental health and aquatic ecosystems [2]. Foremost, methyl orange (MO), a commonly used dye in industrial processes, poses significant health risks and environmental concerns [3]. High concentrations of MO can cause skin, eye, and respiratory irritation [4], with chronic exposure potentially leading to more severe health issues. Studies suggest that aromatic amines released from azo dyes like MO are potential carcinogens [5,6,7], increasing the risk of cancer, particularly bladder cancer [8], with prolonged exposure. Additionally, MO and other azo dyes can disrupt the endocrine system, leading to reproductive and developmental abnormalities [9]. The toxicity of MO extends to aquatic ecosystems, where it can harm organisms, disrupt food chains, and reduce biodiversity [10]. Furthermore, MO and its metabolites have the potential to bio-accumulate in organisms, posing health risks for both humans and wildlife.

Addressing the challenge of dye pollution demands innovative and sustainable approaches. Foremost, bioremediation utilizes microorganisms or plants to degrade dye pollutants via enzymatic processes or plant uptake [11]. Phyto-remediation employs specially selected plants to accumulate and store dye pollutants for proper disposal or treatment [12]. Activated carbon filtration physically adsorbs dye molecules using activated carbon’s high surface area and porosity [13]. Advanced oxidation processes (AOPs) break down dye molecules into harmless byproducts through chemical oxidation methods like ozonation, photocatalysis, or Fenton’s reagent [14]. Biochar adsorption utilizes biochar, a carbon-rich material, to physically adsorb dye molecules from water due to its high surface area and adsorption capacity [15,16]. Natural coagulants, such as chitosan or plant-based extracts, aggregate dye particles through coagulation and flocculation processes for removal. Electrocoagulation destabilizes and precipitates dye pollutants from water using electrochemical methods. Constructed wetlands mimic natural ecosystems to treat dye-contaminated water via physical filtration, adsorption, microbial degradation, and plant uptake processes [17,18,19]. Among these, biochar has emerged as a promising solution [20]. Renowned for its high surface area and adsorption capacity, biochar offers a cost-effective and eco-friendly means of removing contaminants from aqueous solutions [21].

However, the quest for more efficient and selective adsorbents continues. In this context, the modification of biochar with iron, coupled with an unconventional source of poultry manure, holds immense potential. Poultry manure, typically viewed as waste, becomes a valuable resource when transformed into biochar [22]. When combined with iron, this modified biochar exhibits enhanced adsorption properties, making it a potent tool for water purification.

The focus of this study lies in exploring the utilization of iron-modified poultry manure biochar for the removal of methyl orange dye from aqueous solution. Methyl orange, a widely used dye in various industries, presents a formidable challenge due to its complex molecular structure and resistance to conventional treatment methods. By investigating the efficiency and adsorption mechanisms of this novel adsorbent, we aim to contribute to the advancement of sustainable solutions for dye pollution mitigation. Through a combination of experimental analysis and theoretical insights, we seek to unravel the intricacies of the adsorption process and pave the way for the development of effective and eco-friendly water treatment technologies.

2. Materials and Methods

2.1. Sorbent Synthesis and Characterization: Biochar, Modified Biochar Preparation, and Characterization

Biochar (BC) was produced by pyrolyzing poultry manure at 650 °C for three hours, following prior drying in an oven at 65 °C until a constant weight was achieved. The resulting biochar was ground, passed through a 53 µm mesh sieve, and stored in an airtight container labeled BC. Iron-modified biochar (Fe–BC) was synthesized using the method described by Dong et al. [23]. Briefly, BC was mixed with an FeSO₄·7H₂O solution at a 10:1 weight ratio (biochar–iron) and stirred vigorously. The mixture was then sonicated at 25 °C for one hour to promote uniform dispersion. To enhance iron loading, the Fe–BC was subsequently heated at 180 °C for six hours, yielding the final iron-modified product.

The percentage yield of the produced biochar was determined using Equation (1).

$$\mathbf{Y}\mathbf{i}\mathbf{e}\mathbf{l}\mathbf{d}\left(\mathbf{\%}\right)={\displaystyle \frac{\mathbf{M}\mathbf{a}\mathbf{s}\mathbf{s} \mathbf{o}\mathbf{f} \mathbf{B}\mathbf{C}}{\mathbf{M}\mathbf{a}\mathbf{s}\mathbf{s} \mathbf{o}\mathbf{f} \mathbf{P}\mathbf{M}}}\times \mathbf{100}$$

(1)

The materials produced were analyzed for: proximate analysis in accordance with ASTM standard procedures from 1989; cation exchange capacity (CEC), measured using the ammonium acetate extraction method as described by Richard in 1954; pH and Electrical Conductivity (EC), assessed in a 1:10 (w/v) suspension of the absorbents in deionized water; elemental composition, determined using a PerkinElmer CHNSO elemental analyzer (PerkinElmer series II, Waltham, MA, USA); and particle size distribution, which was evaluated with a Malvern Mastersizer 2000 laser particle size analyzer (Mastersizer 2000, Malvern Panalytical, Malvern, UK).

Additional physicochemical characterizations, including Brunauer–Emmett–Teller (BET) (TriStar II 3020, Micromeritics, Norcross, GA, USA) specific surface area measurements, scanning electron microscopy (SEM) imaging (model: MAXima XRD-7000, Shimadzu, Tokyo, Japan), and Fourier transform infrared (FTIR) spectroscopy (FTIR, Bruker Alpha-Eco ATR-FTIR, Bruker Optics Inc., Coventry, UK), were conducted following the methodology described by Yang et al. [24]. The point of zero charge (pH_PZC) for both adsorbents was also determined.

2.2. Sorption Experiments

2.2.1. Influence of Solution pH on Dye Sorption

The influence of solution pH on the adsorption of methyl orange (MO) was examined through batch experiments. Solutions with pH values of 3.0, 5.0, 7.0, and 10.0 were prepared using deionized water, each containing an initial MO concentration of 200 mg/L. In polypropylene tubes, 30 mL of each solution was mixed with 21 mg of adsorbent. All treatments, including a control without adsorbent, were conducted in triplicate. The mixtures were agitated at 150 rpm for 24 h at room temperature (23 ± 2 °C). Following agitation, the solutions were separated from the adsorbent by centrifugation and filtered using Whatman No. 42 filter paper (Maidstone, UK).

The amount of MO adsorbed per unit mass of the adsorbent was calculated using Equation (2).

$${\mathit{q}}_{\mathit{e}}=\left[{\displaystyle \frac{{\mathit{C}}_{\mathit{o}}-{\mathit{C}}_{\mathit{e}}}{\mathit{m}}}\right]\times \mathit{v}$$

(2)

where

C_o = initial MO concentration (mg L⁻¹)

C_e = equilibrium MO concentration (mg L⁻¹)

m = mass of absorbent (g)

v = the volume of solution (L)

2.2.2. Kinetic Sorption Batches

A stock solution of methyl orange (MO) dye was prepared in deionized water at an initial concentration of 200 mg/L and a pH of 7. In each experiment, approximately 21 mg of the sorbent was added to 30 mL of the MO solution in a polypropylene tube. Each sorbent sample, along with a blank (without sorbent), was tested in triplicate. The tubes were shaken at 150 rpm and maintained at a temperature of 23 ± 2 °C. Samples were collected at specific time intervals: 0, 2, 5, 15, 30, 60, 180, 300, 600, and 1440 min. After separating the solution from the sorbent, the concentration of MO was analyzed. The amount of MO adsorbed per unit mass of the sorbent was calculated using Equation (2).

Various kinetic models (Equations (2)–(5)) were used to investigate the sorption dynamics:

• Pseudo-second-order

$${\displaystyle \frac{\mathit{t}}{{\mathit{q}}_{\mathit{t}}}}={\displaystyle \frac{1}{{\mathit{k}}_2^{\prime }{\mathit{q}}_{\mathit{e}}^2}}+{\displaystyle \frac{1}{{\mathit{q}}_{\mathit{e}}}}\mathit{t}$$

(3)

2.

Elovich

$${\mathit{q}}_{\mathit{t}}={\displaystyle \frac{1}{\mathit{\beta }}}\mathit{ln}\left(\mathit{\alpha }\mathit{\beta }\right)+{\displaystyle \frac{1}{\mathit{\beta }}}\mathit{ln}\mathit{t}$$

(4)

3.

Power function

$$\mathbf{l}\mathbf{n}{\mathit{q}}_{\mathit{t}}=\mathbf{l}\mathbf{n}\mathit{b}+{\mathit{k}}_{\mathit{f}}\left(\mathit{ln}\mathit{t}\right)$$

(5)

Here, t denotes the time interval, while q_t refers to the quantity of methyl orange (MO) adsorbed at a given time t (in (mg·g⁻¹)⁻¹). Q The symbol q_e defines the equilibrium adsorption capacity (mg·g⁻¹). Additionally, k₂′ signifies the rate constants for the pseudo-second-order model. The parameter α indicates the initial sorption rate (mg·g⁻¹ min⁻¹), and β is the sorption-related constant. Lastly, k_f is the rate coefficient (mg·g⁻¹ min⁻¹), and b denotes another kinetic constant.

The degree of agreement between the modeled and experimental data was evaluated by computing the standard error of estimate (SEE).

$$\mathrm{SEE}={\sum }_{\mathit{i}=1}^{\mathit{n}}({{\mathit{q}}_{\mathit{e}\mathit{m}}-{\mathit{q}}_{\mathit{e}\mathit{c}})}^2$$

(6)

Here, n represents the total number of observations, while q_em and q_ec denote the experimentally measured and model-calculated adsorption capacities (mg·g⁻¹), respectively.

2.2.3. Equilibrium Adsorption Batch Experiments

A stock solution of methyl orange (MO) dye was prepared in deionized water with an initial concentration of 200 mg/L and adjusted to pH 7. This stock solution was then diluted to create a series of solutions with initial MO concentrations ranging from 0 to 200 mg/L, all maintained at pH 7. Each experiment involved adding the sorbent material to 30 mL of the MO solution at a dosage of 0.70 g/L. For each sorbent, as well as a blank (without sorbent), the experiments were conducted in triplicate. The mixtures were agitated at 150 rpm for 24 h at a temperature of 23 ± 2 °C. After separating the sorbent materials from the solutions, the concentration of MO in the solution was determined. Various nonlinear forms of isotherm equations (Equations (7)–(10)), as outlined by Ahmad et al. [25], were employed to analyze the sorption isotherms.

1.

Langmuir

$${\mathit{q}}_{\mathit{e}}={\displaystyle \frac{{\mathit{Q}}_{\mathit{L}}{\mathit{C}}_{\mathit{e}}{\mathit{K}}_{\mathit{L}}}{1+{\mathit{K}}_{\mathit{L}}{\mathit{C}}_{\mathit{e}}}}$$

(7)

2.

Freundlich

$${\mathit{q}}_{\mathit{e}}={\mathit{K}}_{\mathit{F}}{\mathit{C}}_{\mathit{e}}^{1/\mathit{n}}$$

(8)

3.

Temkin

$${\mathit{q}}_{\mathit{e}}={\mathit{q}}_{\mathit{D}}\mathbf{e}\mathbf{x}\mathbf{p}(-{\mathit{B}}_{\mathit{D}}[\mathit{R}\mathit{T}\mathit{l}\mathit{n}\left(1+{\displaystyle \frac{1}{{\mathit{C}}_{\mathit{e}}}}\right){]}^2]$$

(9)

4.

Dubinin–Radushkevich

$${\mathit{q}}_{\mathit{e}}={\mathit{q}}_{\mathit{D}}\mathbf{e}\mathbf{x}\mathbf{p}(-{\mathit{B}}_{\mathit{D}}[\mathit{R}\mathit{T}\mathit{l}\mathit{n}\left(1+{\displaystyle \frac{1}{{\mathit{C}}_{\mathit{e}}}}\right){]}^2)$$

(10)

In this context, Q_L denotes the adsorption capacity (mg·g⁻¹), and K_L refers to the equilibrium constant of sorption (L·mg⁻¹). The term 1/n represents the Freundlich linearity factor, while K_F reflects the Freundlich affinity constant (L·g⁻¹). Additionally, in Equation (12), R stands for the universal gas constant, with a fixed value of 8.314 J·K⁻¹·mol⁻¹, and T indicates the absolute temperature. The parameter A corresponds to the binding constant (L·mg⁻¹), and b indicates the adsorption enthalpy. The variable qD refers to the maximum adsorption capacity (mg·g⁻¹), and BD represents the mean free energy of adsorption.

The BD value derived from Equation 13 was subsequently employed to determine the binding energy (E) using the following relation:

$$\mathit{E}={\displaystyle \frac{1}{\sqrt{2{\mathit{B}}_{\mathit{D}}}}}$$

(11)

2.3. Partition Coefficient

The partition coefficient (KP) serves to assess and contrast the sorption abilities of various adsorbent materials for a particular adsorbate ion subjected to similar experimental circumstances. It is determined using Equation (12), as described by Alloway [26].

$${\mathit{K}}_{\mathit{P}}={\displaystyle \frac{\mathit{M}\mathit{B} \mathit{a}\mathit{d}\mathit{s}\mathit{r}\mathit{o}\mathit{b}\mathit{e}\mathit{d} \mathit{a}\mathit{t} \mathit{e}\mathit{q}\mathit{u}\mathit{i}\mathit{l}\mathit{i}\mathit{b}\mathit{r}\mathit{i}\mathit{u}\mathit{m}}{\mathit{M}\mathit{B} \mathit{c}\mathit{o}\mathit{n}\mathit{c}\mathit{e}\mathit{n}\mathit{t}\mathit{r}\mathit{a}\mathit{t}\mathit{i}\mathit{o}\mathit{n} \mathit{a}\mathit{t} \mathit{e}\mathit{q}\mathit{u}\mathit{i}\mathit{l}\mathit{i}\mathit{b}\mathit{r}\mathit{i}\mathit{u}\mathit{m}}}$$

(12)

3. Results and Discussion

3.1. Properties of the Absorbents

Table 1. Properties of the absorbents.

Sorbents	pH (1:10)	CEC (meq/100 g)	Yield	Moisture	Volatile Matter	Ash	Fixed Carbon	Surface Area (m2/g)	Total Pore Volume (cm3/g)
			%
BC	10.98	45.35	33.46	3.98	22.43	17.86	52.67	99.95	0.09
BC-Fe	8.25	75.59	-	4.93	29.29	13.59	28.65	90.68	0.15

BC = poultry manure biochar, BC-Fe = iron-modified biochar.

summarizes the characterization of iron-modified biochar (Fe–BC) and poultry manure biochar (BC). The results show that BC exhibited a higher pH of 10.98 compared to 8.25 for Fe–BC. This difference in pH may be attributed to the naturally alkaline nature of poultry manure, which contributes to the higher pH of BC. However, the incorporation of iron into the biochar appears to lower the pH, consistent with findings by Pérez et al. [27], who noted that iron modification can reduce biochar pH due to the acidic nature of iron salts. The pH of an adsorbent can significantly influence its performance in environmental applications; for example, a higher pH may be beneficial for neutralizing acidic pollutants, whereas a lower pH may be more suitable for treating acidic waste streams [28].

Additionally, Fe–BC demonstrated a substantially higher cation exchange capacity (CEC) of 75.59 meq 100 g⁻¹ compared to 45.35 meq 100 g⁻¹ for BC. This increase in CEC may result from iron modification, as supported by Gutierrez et al. [29], who reported enhanced CEC in biochar produced from corn straw modified with iron and zinc. The elevated CEC of Fe–BC suggests greater potential for contaminant binding, particularly heavy metals [30,31], making it a promising material for environmental remediation and soil amendment. The observed differences in physicochemical properties between BC and Fe–BC are likely due to variations in feedstock composition, production conditions, and the effects of iron modification.

The moisture content, which reflects the amount of water present in the material, is also reported in Table 1. Poultry manure biochar (BC) exhibited a lower moisture content of 3.98% compared to 4.93% in iron-modified biochar (Fe–BC). This increase may be attributed to the iron modification process, which could introduce additional moisture or alter the biochar’s water retention capacity. Moisture content influences the handling, storage, and application of adsorbents, with lower moisture levels generally preferred for enhanced stability and performance. Volatile matter, which represents compounds released during thermal decomposition, was 22.43% in BC and increased to 29.29% in Fe–BC. This difference could be due to the introduction of organic residues or compounds during the iron modification process. In contrast, the ash content was higher in BC (17.86%) than in Fe–BC (13.59%), suggesting a reduction in mineral content or transformation of ash components during modification. Fixed carbon content was notably lower in Fe–BC (28.65%) compared to BC (52.67%). This reduction may result from carbon loss during heat treatment, possibly due to the decomposition of organic matter or the formation of iron-containing compounds. As reported in previous studies [32], the fixed carbon and organic content of adsorbents can significantly influence their reactivity and stability during adsorption processes.

Furthermore, Fe–BC exhibited a lower surface area (90.68 m²/g) than BC (99.95 m²/g), likely due to pore blockage by iron particles, which reduces the available surface area. However, Fe–BC showed a higher total pore volume (0.15 cm³/g) compared to BC (0.09 cm³/g), indicating that iron modification may alter pore structure. Overall, these results highlight how the physicochemical characteristics of biochar-based adsorbents are significantly affected by iron modification.

The key adsorption peaks corresponding to functional groups present in BC and Fe–BC were identified using FTIR spectroscopy (Figure 1). A prominent peak near 3400 cm⁻¹ corresponds to the O–H stretching vibration of hydroxyl groups, likely originating from surface-bound moisture or hydroxylated structures. Another distinct peak around 1600 cm⁻¹ is attributed to C=O stretching from carboxyl or carbonyl groups formed through oxidation of the biochar surface. These functional groups enhance the ability of biochar to adsorb heavy metals and organic pollutants, making them crucial for environmental remediation applications. Similar findings by Liu et al. [33] reported an increased sorption capacity in iron-modified biochar, attributed to the presence and enhancement of these surface functional groups. Fe–BC exhibited a distinctly different chemical structure compared to unmodified BC, as revealed by FTIR analysis. An additional absorption peak at 570 cm⁻¹ was observed in Fe–BC, corresponding to Fe–O bonds, indicating the successful incorporation of iron oxides onto the biochar surface. The presence of these new spectral features and changes in vibrational bands provide clear evidence of iron integration into the Fe–BC structure.

Figure 2 also presents the X-ray diffraction analysis of BC and Fe–BC showing their crystallographic structure. BC had a wide diffraction peak signifying a predominant amorphous structure, whereas Fe–BC possessed an extra sharp diffraction peak demonstrating the successful incorporation of iron in the modified biochar. The amorphous structure of BC is in line with recent findings that pyrolysis carried out at high temperature destroys the crystalline nature of raw biomass, leaving a reorganized medium of carbon and inorganic minerals. It was reported that a varied peak of 20° to 30° indicates a rearranged structure of carbon found in biomass-derived biochar [34]. The peaks observed for Fe–BC correspond to the fact that iron oxides such as haematite and magnetite have been incorporated into the modified biochar. The XRD pattern of the two adsorbents shows that upon treatment of biochar with iron, an organization or reordering in structure occurs, thus leading to the production of new crystalline phases. The modification of biochar with iron is realistic to improve its stability and reactivity, and hence makes Fe–BC an important tool for environmental applications. It was highlighted that oxides of iron can increase the transfer of electrons in Fe–BC, therefore increasing effectiveness for redox and catalytic reactions [35].

Scanning Electron Microscopy (SEM) images of BC and Fe–BC reveal distinct morphological differences between the two adsorbents (Figure 2). BC exhibited a highly porous structure, characteristic of biochar derived from biomass combustion, aligning with findings from previous studies. The porous and uneven surface of BC, including visible cavities and channels, likely results from thermal decomposition during pyrolysis. These structural features are crucial for pollutant entrapment, enhancing BC’s effectiveness in environmental remediation and soil amendment applications [34]. Upon iron modification, the surface morphology of Fe–BC changed notably. SEM images showed clusters of iron particles dispersed across the biochar surface, suggesting successful loading of iron and the introduction of additional reactive sites. This structural enhancement is supported by Zhang et al. [35], who reported that iron modification increases the availability of redox-active sites, thereby improving the biochar’s applicability in catalytic degradation of organic pollutants. However, the incorporation of iron also appeared to reduce the pore size of Fe–BC, which may slightly decrease its surface area. Thus, the balance between porosity and the formation of functional active sites becomes a critical factor when selecting or engineering biochar for environmental use. Previous studies have emphasized that both the distribution and size of iron particles significantly influence the performance of Fe–BC [36]. In summary, SEM analysis confirms that iron treatment alters the structural and functional characteristics of biochar, enhancing its potential for contaminant removal while partially retaining its original porosity.

3.2. Methyl Orange Sorption Batches

3.2.1. Effects of pH on MB Sorption

The initial pH of a solution containing methyl orange (MO) plays a crucial role in its removal. The results indicated that the removal efficiency of MO by both biochar (BC) and iron-modified biochar (Fe–BC) was significantly influenced by the solution pH. Specifically, lower (acidic) pH conditions enhanced the removal of MO by both adsorbents. This enhancement can be attributed to the protonation of the adsorbent surface under acidic conditions, which promotes electrostatic attraction between the positively charged adsorbent surface and the negatively charged MO molecules, thereby improving adsorption efficacy. This finding aligns with previous studies, which reported that the removal of anionic dyes is more favorable at lower pH due to stronger electrostatic interactions [37]. Conversely, under alkaline conditions (higher pH), a decrease in MO removal efficiency was observed for both BC and Fe–BC. This decline is likely due to surface deprotonation, which reduces the electrostatic attraction between the biochar surface and MO molecules, thereby diminishing adsorption performance.

Furthermore, the efficacy of Fe–BC in removing methyl orange (MO) was higher than that of unmodified biochar (BC) under acidic conditions, highlighting the importance of iron modification in enhancing MO removal. This improved performance can be attributed to the additional active sites introduced during iron treatment, which facilitate stronger interactions between MO molecules and the biochar surface. Moreover, the consistently enhanced performance of Fe–BC across all pH levels indicates that the presence of iron oxides on the Fe–BC surface contributes to additional binding mechanisms and increased adsorption capacity. Wang et al. [38] also reported an increased affinity of Fe–BC for MO, attributed to the formation of complexes or ligand exchange mechanisms.

The point of zero charge (pH_pzc) for BC and Fe–BC was determined to be 3.72 and 4.05, respectively (Figure 3). This indicates that the surface of the adsorbents is positively charged when the solution pH is below 3.72 and 4.05, and negatively charged when the pH exceeds these values [39]. At low pH levels, the positively charged adsorbent surface promotes strong electrostatic attraction with the anionic methyl orange (MO) dye, resulting in high removal efficiency. Conversely, as the pH rises above the pH_pzc, the surface becomes negatively charged, favoring electrostatic interactions with cationic dyes such as methylene blue (MB). These findings are consistent with the results reported by Baloo et al. [40] and Li et al. [41].

3.2.2. Kinetic Sorption

The changes in methyl orange (MO) adsorption over time were examined using kinetic models during sorption experiments conducted at optimal pH and temperature (Figure 4). As presented in

Table 2. Kinetic models parameters for the sorption of MO.

Order	Model	Parameters	Sorbents
			BC	Fe–BC
1	Elovich	A (mg·g−1·min−1)	15.8547	27.0613
		Β (g·mg−1)	−9.8451	18.0115
		r2	0.9452	0.8762
		SEE (J/g)	0.0037	0.0028
2	Power function	kf (mg·g−1·min−1)	0.6281	0.5246
		B	0.8414	2.2908
		r2	0.8833	0.6222
		SEE (J/g)	6.2744 × 10−6	5.8673 × 10−6
3	Pseudo-second-order	H (min−1)	2.3636	23.0312
		qe (mg·g−1)	98.1917	179.1673
		k2 (g·mg−1·min−1)	0.0002	0.0007
		r2	0.9973	0.9999
		SEE (J/g)	0.0210	0.0244

, the kinetic parameters for the two adsorbents (BC and Fe–BC) were evaluated. The first-order kinetic model yielded k¹ values of 0.0019 and 0.0013 for BC and Fe–BC, respectively. However, the low R² values for both adsorbents indicate that the first-order model could not adequately describe the adsorption dynamics of MO.

Similarly, the second-order kinetic model also failed to accurately capture MO adsorption behavior, as evidenced by the low R² values. The k₂ constant in the second-order model was slightly higher for Fe–BC (−7.2916 × 10⁻⁶) than for BC (−8.0000 × 10⁻⁵), though still inadequate to describe the adsorption process.

In contrast, the Elovich kinetic model provided a better fit for the experimental data, as indicated by relatively higher R² values for both BC and Fe–BC. Moreover, both the A and B constants were higher for Fe–BC compared to BC, suggesting faster sorption kinetics with the iron-modified adsorbent. When using the power function model, a higher k_f constant was also observed for Fe–BC, reinforcing its superior sorption performance.

Application of the pseudo-second-order kinetic model further supported these observations. Fe–BC exhibited higher values for H (initial sorption rate), q_e (equilibrium sorption capacity), and k₂ (pseudo-second-order rate constant) compared to BC. The elevated H and k₂ values for Fe–BC imply a more rapid and efficient adsorption process.

The superior performance of Fe–BC over BC, as indicated by the kinetic data, may be attributed to enhanced surface properties and additional active sites resulting from iron modification. This is consistent with previous reports indicating that iron oxides and hydroxides possess high surface areas and are effective in adsorbing dye molecules, thereby improving sorption kinetics and capacity [42,43,44]. Additionally, it has been reported that the Fe–BC surface can facilitate specific adsorption of MO via hydrogen bonding, electrostatic interactions, and π–π interactions, all of which are enhanced by the presence of iron oxides and hydroxides [42].

Iron modification of biochar can alter its surface area, pore volume, and structure, leading to more accessible active sites for MO adsorption and enhanced diffusion of MO molecules into internal pores. Furthermore, solution pH plays a role in modifying the surface charge of the adsorbent, thereby improving the ionization and interaction of MO with Fe–BC. The iron component may also form complexes with MO molecules, contributing to the faster sorption kinetics and higher adsorption capacity observed for Fe–BC compared to BC.

Overall, MO sorption occurred more rapidly with Fe–BC than with BC, as shown by the kinetic models. This improvement is likely due to iron treatment enhancing the adsorptive properties of biochar. The higher equilibrium sorption capacity indicated by the pseudo-second-order model suggests that Fe–BC can adsorb more MO per unit mass than BC. Furthermore, the higher coefficient of determination (R²) values for Fe–BC indicate a better fit to the kinetic models, emphasizing its superior adsorption behavior.

Finally, higher sorption capacities observed for Fe–BC relative to BC in the Langmuir, Freundlich, and Temkin isotherm models support the effectiveness of iron treatment. However, the X-ray diffraction (XRD) patterns presented in Figure 2 show similar frequency and intensity for both BC and Fe–BC, likely due to the shared precursor material used in producing the adsorbents.

3.2.3. Equilibrium Sorption

Sorption isotherms describe the relationship between the concentration of an adsorbate in solution and its accumulation on the surface of an adsorbent at a constant temperature during sorption studies [45]. The effectiveness of an isotherm model depends on its ability to accurately represent the adsorption process using a minimal number of parameters while maintaining mathematical simplicity, thereby enhancing its practical applicability [46]. In this study, the experimental sorption data were fitted to the nonlinear forms of the Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich isotherm models, as shown in Figure 5. The sorption experiments were conducted at an initial solution pH of 4, based on prior optimization studies.

An increase in the initial concentration of methyl orange (MO) led to an increased quantity of dye adsorbed onto the adsorbent, indicating a direct relationship between MO concentration and adsorption capacity. The adsorption process followed three distinct phases: initially, an H-type isotherm—characterized by a steep slope at low concentrations, indicating early saturation—was observed. This was followed by an L-type isotherm, where adsorption energy decreased as active sites became progressively occupied, eventually reaching an equilibrium phase. The H-type isotherm suggests a strong initial affinity between the adsorbent and MO, while the L-type isotherm indicates diminishing affinity as surface sites become saturated. Ahmad et al. [47] similarly reported that higher adsorption at lower concentrations is attributed to the abundance of available active sites, which gradually become occupied as the initial dye concentration increases.

The nonlinear isotherm parameters, presented in

Table 3. Nonlinear parameters of isotherm model for the sorption of methylene dye.

Isotherms	Parameters	BC	Fe–BC
Langmuir	QL (mg·g−1)	98.23	136.25
	KL (L·g−1)	0.13	1.67
	R2	0.98	0.97
Freundlich	KF (L·g−1)	24.98	72.54
	1/n	0.30	0.16
	R2	0.94	0.75
Temkin	A (L·g−1)	2.27	65.31
	B (J·mol−1)	129.30	129.65
	R2	0.95	0.78
Dubinin–Radushkevich	QD (mg·g−1)	83.49	126.90
	BD (kJ·g−1)	0.01	0.00
	R2	0.91	0.96

Biochar (BC), iron-modified biochar (Fe–BC).

, indicate that the adsorption data best fit the Langmuir model, followed by the Temkin, Freundlich, and Dubinin–Radushkevich models. According to the Langmuir model, the maximum adsorption capacity (Q_L) for MO was higher for Fe–BC (136.25 mg/g) than for BC (98.23 mg/g). Similarly, the Langmuir equilibrium constant (K_L) was greater for Fe–BC (1.67 L/g) than BC (0.13 L/g), indicating a stronger binding affinity of MO to the iron-modified biochar. The high coefficient of determination (R²) values for the Langmuir model for both BC and Fe–BC confirm that monolayer adsorption is the predominant mechanism.

For the Freundlich model, the R² value was higher for BC (0.94) compared to Fe–BC (0.75), suggesting that MO adsorption onto BC conformed more closely to the Freundlich model, which assumes a heterogeneous surface. The Freundlich constant (K_F), representing adsorption capacity, was higher for Fe–BC (72.54 L/g) than for BC (24.98 L/g), reflecting a greater sorptive potential. The adsorption intensity parameter (1/n), which indicates favorability and surface heterogeneity, was lower for Fe–BC (0.16) than BC (0.30), suggesting more favorable adsorption on Fe–BC.

Regarding the Temkin model, the equilibrium binding constant (A), which reflects the heat of sorption, was significantly higher for Fe–BC (65.31 L/g) than for BC (2.27 L/g), implying greater interaction energy during MO sorption onto Fe–BC. The Temkin constant (B), which is related to adsorbate–adsorbent interaction energy, was similar for both materials. The model showed a better fit for BC (R² = 0.95) than for Fe–BC (R² = 0.78), indicating a more accurate description of MO sorption onto BC by the Temkin model.

Finally, the Dubinin–Radushkevich (D–R) model indicated a higher sorption capacity (Q_D) for Fe–BC (126.90 mg/g) than BC (83.49 mg/g), further corroborating the enhanced sorptive performance of the iron-modified biochar.

3.3. Mechanism of Methyl Orange Removal

The removal of methyl orange (MO) from aqueous solutions using biochar (BC) or iron-modified biochar (Fe–BC) likely occurs through multiple adsorption mechanisms. These include surface complexation, pore filling, hydrogen bonding, π–π interactions, and electrostatic attraction. At lower pH values, protonation of surface functional groups on BC and Fe–BC enhances electrostatic attraction between the positively charged adsorbent surfaces and the anionic MO molecules.

Hydrogen bonding plays a particularly important role in MO adsorption by Fe–BC. The hydroxyl (–OH) and carboxyl (–COOH) functional groups present on the biochar surface facilitate interaction with the azo (–N=N–) and sulfonic (–SO₃H) groups of MO [40]. This interaction contributes to the formation of stable adsorbate–adsorbent complexes on the surface. Liu et al. [33] also reported that iron oxides can form stable inner-sphere complexes with the sulfonic and azo components of MO.

Furthermore, the predominantly aromatic structure of biochar enables π–π stacking interactions with MO molecules. As highlighted by [39], the delocalized π-electrons in the graphene-like layers of biochar can interact with the aromatic rings of MO, enhancing adsorption. Chen et al. [36] similarly demonstrated that iron oxide modification of biochar can enhance such interactions and introduce additional active sites through ligand exchange and surface complexation mechanisms.

Smith et al. [48] reported that iron modification significantly increases the number of active adsorption sites on biochar, thereby improving the efficiency of MO removal compared to unmodified biochar. Additionally, the porous structure of biochar contributes to the physical entrapment of MO molecules within its internal pores. A related study by Zhang et al. [35] showed that the high surface area and increased porosity of iron-modified biochar can enhance dye adsorption, particularly at higher MO concentrations.

4. Conclusions

The research findings demonstrated the effectiveness of both pristine biochar (BC) and iron-modified biochar (Fe–BC) in the removal of methyl orange (MO) dye from aqueous solutions. Fe–BC exhibited a significantly higher adsorption capacity than unmodified BC, which can be attributed to its enhanced surface characteristics, increased number of active sites, and the presence of functional groups that facilitate hydrogen bonding, π–π interactions, electrostatic attractions, and complexation reactions. The adsorption process was strongly influenced by solution pH, with maximum MO uptake observed under acidic conditions (pH 4).

Adsorption isotherm analysis revealed that the Langmuir model best described the experimental data for both BC and Fe–BC, indicating monolayer adsorption behavior. Fe–BC exhibited the highest maximum adsorption capacity among the tested materials. Kinetic modeling showed that the adsorption process followed the pseudo-second-order model, suggesting chemisorption as the rate-limiting step. Furthermore, Fe–BC achieved a higher removal efficiency (90%) compared to BC (84%) for MO dye.

Overall, these results highlight the superior performance of iron-modified biochar as a promising, cost-effective, and environmentally friendly adsorbent for the efficient removal of dye contaminants from aqueous environments.