Mechanochemical activation of orange peel waste: enhanced surface reactivity and efficient cationic dye removal from water

Abstract

Dye-contaminated wastewater poses a serious environmental challenge because synthetic dyes are toxic and resistant to biodegradation. Even at minimal concentrations, these pollutants can threaten ecosystems, underscoring the urgent need for efficient adsorbents. In this study, ball-milled orange peel powder (BM-OP) was explored as a sustainable adsorbent for cationic dye removal from aqueous solutions. Ball milling significantly enhanced the physicochemical properties of orange peel, increasing the surface area from 3.5 to 8.5 m² g⁻¹ and expanding the pore diameter from 6.3 to 13.1 nm, thereby facilitating active sites and dye diffusion. Adsorption analysis showed that the equilibrium data were reasonably defined by the Langmuir isotherm model. The fitted Langmuir capacities were 485.05 mg g⁻¹ for methylene blue (MB) and 583.60 mg g⁻¹ for methyl violet (MV). Adsorption kinetics were found to be well aligned with pseudo-second-order model (R² = 0.99), suggesting enhanced accessibility of adsorption sites following the modification process. The results demonstrated that BM-OP could be effectively regenerated using KH₂PO₄, with desorption efficiencies of 92.4% for MB and 94.5% for MV. In addition, the adsorbent showed good reusability over eight successive adsorption–desorption cycles. These results show that BM-OP is an efficient and cost-effective adsorbent for cationic dye removal from wastewater.

Ball milling markedly boosts the dye adsorption performance of waste orange peel powder, enabling enhanced removal of methylene blue and methyl violet from water.

1. Introduction

The rapid growth in industrial activities such as textile, leather, and paper manufacturing has led to massive discharges of wastewater contaminated with dyes into natural water bodies. Synthetic dyes are produced worldwide at an annual rate of 7 × 10⁷ tons, with more than 10 000 tons consumed solely by the textile industry and 5–10% released as effluent into the environment after the dyeing process.^1,2 Typically, dyes are divided into numerous groups based on their application, structure, and source. Synthetic dyes are highly visible, chemically stable, and toxic even at low concentrations.^3,4 In practical scenarios, MB and MV are two common cationic dyes used in the biological, medicinal, and dyeing industries. Long-term exposure to these dyes may cause severe health problems, including anaemia, nausea, and hypertension. In addition, MV can be inhaled, ingested, or absorbed through the skin, leading to respiratory tract irritation, diarrhea, and headaches.^5,6 Therefore, developing effective methods for removing cationic dyes from water is of great importance to sustain environmental and public health.

Various treatment methods have been used for dye removal, including chemical oxidation,⁷ membrane filtration,⁸ ozonation,⁹ coagulation–flocculation,¹⁰ photocatalysis,¹¹ and biological processes.¹² However, these techniques are usually undermined by high operational costs, the production of secondary pollutants, complicated operation, and low efficiency with regard to stable dye molecules. Conversely, adsorption has been one of the most promising strategies for wastewater treatment due to its simplicity, high efficiency, reusability, and adaptability.¹³ However, certain trade-offs exist: commercial adsorbents, such as activated carbon, are expensive, limiting their large-scale application and prompting the search for cost-effective, environmentally friendly alternatives.¹⁴

Over the last few years, materials derived from agricultural waste have attracted significant attention as eco-friendly adsorbents due to their wide availability, biodegradability, low cost, and abundance of surface functional groups. Among these materials, orange peels have emerged as particularly attractive adsorbents due to their porous lignocellulosic structure and functional groups, including hydroxyl and carboxyl groups, which provide numerous active sites for dye adsorption. As a major by-product of the citrus industry, orange peels are generated in large quantities worldwide. They are often discarded as waste, making them a sustainable and value-added material for wastewater treatment applications.^15,16 A few studies have demonstrated the use of orange peel-based materials to remove pollutants, but most focus on chemical adjustments, which can raise costs and undermine the process's eco-friendliness.¹⁷ Mechanical treatments, e.g., crushing and ball milling, provide a less chemical-reagent-intensive yet efficient alternative to chemical treatments aimed at improving adsorption performance.¹⁸ In particular, ball milling is an effective physical activation method that can significantly reduce particle size, increase surface area, expose hidden active sites, and improve surface roughness, thereby enhancing the adsorption potential of the adsorbent.¹⁹ Despite the potential of orange peel-based adsorbents for wastewater treatment, the literature has mainly focused on untreated orange peel for the adsorption of dyes. For example, Eddy et al. developed a chemically modified mesoporous orange peel adsorbent via NaOH and EDTA and demonstrated its effectiveness in removing Trypan Blue from aqueous solution.²⁰ At the same time, Rahman et al. evaluated the feasibility of untreated orange peel for textile wastewater treatment by examining the effects of pH, contact time, and adsorbent dosage on dye removal efficiency.²¹ Similarly, Arami et al. also employed untreated crushed orange peel as a low-cost adsorbent and evaluated its adsorption performance through equilibrium, kinetic, and desorption studies for the removal of dyes from aqueous solutions.²² Although these studies demonstrated the potential of orange peel-based adsorbents for dye removal, they mainly focused on equilibrium and kinetic behaviour or chemical modification approaches. In contrast, analyses of regeneration and structural modification, and a systematic comparison of mechanically treated adsorbents under identical conditions, remained limited. In particular, the influence of ball milling on surface morphology, structural properties, adsorption behaviour, detailed characterization of regenerated adsorbents, and regeneration performance over several cycles has not been comprehensively investigated. Therefore, understanding the role of mechanical activation in modifying the surface characteristics and adsorption performance of orange peel powder is essential for optimizing its application as an efficient adsorbent.

This research involved the preparation and comparative evaluation of crushed orange peel powder (OP) and ball-milled orange peel powder (BM-OP) as sustainable adsorbent for the MB and MV removal from aqueous solutions. The impact of ball milling on surface morphology, surface area, and functional group availability was studied using various characterisation techniques (SEM, EDS, FTIR, and BET). Furthermore, adsorption performance, regeneration behaviour, and adsorption mechanism were systematically analyzed through batch adsorption experiments, and the adsorption mechanism was elucidated based on experimental observations. This work demonstrates the potential of mechanically activated orange peel waste as a cost-effective, environmentally friendly adsorbent for water treatment.

2. Experimental materials and methods

2.1. Materials and reagents

Potassium chloride (KCl, 99.5%), sodium chloride (NaCl, 99.5%), sodium hydroxide (NaOH, 96%), potassium dihydrogen phosphate (KH₂PO₄, 99%), disodium hydrogen phosphate dodecahydrate (Na₂HPO₄·12H₂O, 99%), hydrochloric acid (HCl, 37 wt%), borax (99%), potassium dihydrogen phosphate (KH₂PO₄, 99.5%), potassium hydrogen phthalate (KHP, 99%) and sodium bicarbonate (NaHCO₃, 99%) were purchased from DAMAO, while methyl violet (MV, CAS no. 8004-87-3, purity = 75+%) and methylene blue (MB, analytical grade) were purchased from Sigma-Aldrich. All chemicals were of analytical grade and used as received.

2.2. Preparation of orange peel-based adsorbents

Fresh orange peels were collected locally and washed with deionized water several times to eliminate dust, sugars, and other surface contaminants. The washed peels were air-dried and then oven-dried at 80 °C for 24 h to ensure complete moisture removal. The dried orange peels were subsequently ground and sieved through a 60-mesh sieve (∼300 µm) to obtain a homogeneous particle size before ball milling. The sample was referred to as orange peel powder (OP).

The OP was stored in airtight containers and used directly for further characterization and adsorption experiments. A further particle size reduction and an increase in surface area were achieved by ball-milling a fraction of the prepared OP powder. Ambient-condition ball milling was performed using a planetary ball mill (Shanghai Jingxin Industrial Development Co., Ltd, Shanghai, China) for 4 h at 400 rpm. The ceramic (alumina) balls used were 6.4 mm in diameter, and the ball-to-powder ratio was kept around 8 : 1. Milling was carried out intermittently, with a 6 s rest period between cycles to avoid overheating. The fine powder produced after ball milling was collected and stored in an airtight container. The material obtained was referred to as ball-milled orange peel powder (BM-OP). The overall synthesis process is presented in Fig. 1.

Fig. 1. Flow diagram of OP and BM-OP adsorbents synthesis.

2.3. Characterizations of the material

A scanning electron microscope (HITACHI-SU8220 (Japan)) was employed for surface morphology and particle size. At the same time, energy-dispersive X-ray spectroscopy (EDS) analysis was used to characterize the elemental composition of the synthesized material. For SEM and EDS, the accelerating current and voltage were set to 10 µA, 20 µA and 5 kV, 20 kV, respectively. The stage value was maintained at 8 during SEM imaging and adjusted to 15 for EDS measurements to obtain suitable elemental analysis conditions. The KBr pellet method was used to obtain FTIR analysis of the material using a Thermo Fisher Scientific 6700 FTIR Spectrometer (Waltham, MA, USA) in the range of 4000–400 cm⁻¹. X-ray diffraction (XRD) analysis was conducted using a Smart Lab X-ray diffractometer (Rigaku Corporation) over 2θ angles from 5 to 90° to assess the material's crystalline composition. The Brunauer–Emmett–Teller (BET, JW-BK200A, China) was employed to analyze the pore volume and specific surface area of the samples. BET measurements were carried out at 77 K using N₂ adsorption–desorption. The concentrations of MB and MV after the adsorption experiments were measured using a Carry 100 UV-Vis spectrophotometer (Agilent, Kuala Lumpur, Malaysia). PHS-3C pH meter was used to monitor the pH of the solutions.

2.4. Analysis of point of zero charge (PZC)

The point of zero charge (PZC) of the synthesized OP and BM-OP samples was determined using the salt addition technique. A 0.1 M NaCl solution was employed as the supporting electrolyte throughout the experiment. For each measurement, 30 mL of the electrolyte was transferred into a conical flask, after which 10 mg of the corresponding adsorbent was introduced. All analyses were made with a fixed contact time of 3 h, as this was chosen based on preliminary results demonstrating adequate mixing and equilibrium.^23,24 The pH of each solution was measured before and after 3 h of stirring, and the change in pH (ΔpH) was noted. Special formulations were used to prepare buffer solutions to maintain the pH ranges required between 2 and 10, as listed in Table S1.

2.5. Adsorption analysis

2.5.1. Adsorption experiments

MB (C₁₆H₁₈ClN₃S) and MV (C₂₄H₂₈N₃Cl) dyes served as target adsorbates for the adsorption studies. These dyes were selected for their widespread occurrence in industrial wastewater, high toxicity, and frequent use as representative model cationic dyes in adsorption studies. Their stable structure and strong interaction with negatively charged functional groups (e.g., –OH and –COOH) present on orange peel make them suitable candidates for evaluating adsorption performance and mechanism.

A concentration of 1000 mg L⁻¹ was achieved by dissolving 1 g of each dye in 1 L of deionized water to prepare individual stock solutions of MB and MV. Prior to each adsorption experiment, the stock solutions were appropriately diluted to provide working solutions with the required concentrations. Batch adsorption experiments were carried out under continuous stirring at 500 rpm. The influence of solution pH was investigated over the range of 2–10 while maintaining the optimum adsorbent dosage and initial dye concentrations. Initial dye concentrations of 50 mg L⁻¹ for MB and 250 mg L⁻¹ for MV were employed throughout the pH optimization studies. These concentrations were selected based on their differing optical properties and adsorption behaviour. MB exhibits higher molar absorptivity and stronger absorbance at lower concentrations, whereas MV requires a higher concentration to ensure reliable spectrophotometric measurements and accurate evaluation of adsorption performance. pH buffers were used to prepare the 100 mL dye solutions, with the buffer compositions listed in Table S1. Adsorption experiments were performed to examine the influence of the initial dye concentration. For each test, 50 mL of dye solution at pH 8 was prepared, with the initial concentration ranging from 40 to 450 mg L⁻¹. For the equilibrium isotherm experiments, 25 mg of BM-OP was added to 50 mL of MB solution (solid-to-liquid ratio: 0.5 g L⁻¹), whereas 50 mg of BM-OP was added to 50 mL of MV solution (1.0 g L⁻¹). Based on the temperature optimization results, the MB and MV isotherm experiments were conducted at 293 and 333 K, respectively. The required dosage of adsorbent was subsequently added to each sample. In this manner, the effect of dye concentration on adsorption capacity was investigated. The influence of adsorbent dosage was evaluated by introducing different amounts of adsorbent (10–55 mg) into 50 mL dye solutions maintained at the previously optimized initial concentration and pH. For adsorption capacity calculations, solution volumes (mL) were converted to liters (L) to ensure unit consistency. Temperature- and time-dependent adsorption experiments were then carried out using the optimum adsorbent dosage. The suspensions were maintained at temperatures of 293–333 K and agitated for 90 min before the solid phase was recovered by centrifugation for subsequent measurements. The remaining concentration of dyes was quantified using the UV-Vis spectrophotometer at 668 nm in the case of MB and 590 nm in the case of MV. All the adsorption experiments were carried out in triplicate, and the findings are shown as mean values and respective standard deviations.

2.5.2. Evaluation of data analysis techniques

The adsorption performance was evaluated in terms of equilibrium adsorption capacity (q_e) and removal efficiency (%) by eqn (1). The quantity of the dye adsorbed per unit mass of the synthesized adsorbents and the percentage of the eliminated dye in the solution were evaluated through eqn (2).²⁵

1

2

where C_e means the equilibrium concentration in the form of mg L⁻¹, C₀ is the initial concentration of dye in the form of mg L⁻¹, q_e is the equilibrium adsorption capacity in the form of mg g⁻¹, V is the volume of the solution in L, and M is the dosage of the adsorbent in g.

2.5.3. Adsorption isotherm and kinetic analysis

The experimental data were fitted to the Langmuir and Freundlich isotherm models to understand the equilibrium adsorption process. These models were applied to examine adsorption properties and affinity of the adsorbent toward dye molecules. Below, we provide the nonlinear formulas explaining each isotherm;^26–28

The nonlinear formulation of the Langmuir equation is given by:

3

Also, the equilibrium constant (R_L) is further estimated to examine the viability of the adsorption process.

4

In this case, C₀ (mg L⁻¹) can be ascribed to the initial dye concentration, and K_L denotes the Langmuir constant. The type of adsorption process is determined by the R_L value. R_L = 1 indicates linear adsorption, 0 < R_L < 1 reflects a viable process, and R_L = 0 represents a non-reversible process.

The nonlinear formulation of the Freundlich equation is given by:

q_e = K_fC_e^1/n 5

Here, C_e (mg L⁻¹) is the dye concentration at equilibrium; q_m (mg g⁻¹) is the maximum adsorption capacity; K_L (L mg⁻¹) represents the Langmuir adsorption constant; K_f (mg g⁻¹) (mg L⁻¹)^−1/n is the adsorption capacity associated Freundlich constant, while 1/n describes adsorption intensity.

The kinetic study was applied to experimental data on the adsorption of MB and MV dyes on OP and BM-OP using the kinetic models given in eqn (6)–(8). The experimental adsorption data were studied using several kinetic models to understand the adsorption rate and adsorption process. The acquired adsorption findings were fitted to the equations of pseudo-first order (PFO), pseudo-second order (PSO) and intraparticle diffusion models as follows:

q_t = q_e(1 − e^−k₁t) 6

7

q_t = k_it^½ + I 8

Here, q_e is the equilibrium adsorption capacity in mg g⁻¹, q_t is the adsorption capacity at time t, in mg g⁻¹, t is the reaction time measured in min, k₁ (min⁻¹), k₂ (g (mg min)⁻¹) and k_i (mg g⁻¹ min^−1/2) are the rate constants of adsorption in pseudo-first order, pseudo-second order and intra-particle diffusion models. The parameter I represents the intercept of the intra-particle diffusion plot.

2.5.4. Statistical evaluation of model fitting

Statistical error functions were employed to examine the suitability of the adsorption kinetic and equilibrium models. The fitting performance was determined using the Chi-square (χ²) and normalized standard deviation (Δq%). In general, lower χ² and Δq% values indicate better consistency between the calculated and experimentally measured adsorption data. The equations used for these calculations are given below:^29,30

9

10

In this context, q(exp) and q(cal) correspond to the experimental and calculated capacities of equilibrium adsorption, and N indicates the total number of data points.

2.5.5. Desorption efficiency and adsorbent regeneration

Samples of BM-OP with the dye adsorbed on them were used in desorption experiments. Before the desorption experiments, the dye-loaded BM-OP was carefully washed with deionized water to get rid of the dye molecules loosely bound on the surface. The adsorbent was then filtered off and dried overnight under vacuum to remove moisture. Deionized water, methanol, and 0.1 M phosphate solution were tested as eluents for the purpose of desorbing. Methanol was chosen because of its high affinity for organic compounds, while the phosphate solution was used because hydrogen phosphate species (HPO₄²⁻ and H₂PO⁴⁻) could facilitate dye desorption. Deionized water was used as a reference eluent. The amount of desorbed dye was determined from its concentration in the desorption solution (q_{e(desorption)} = C_desV_des/m). The initially adsorbed amount was calculated from the difference between the initial and equilibrium dye concentrations, using eqn (1) mentioned above and desorption efficiency as given below.³¹

11

In this context, D (%) is the cationic dye desorption efficiency, and q_e, desorption and q_e, sorption are the dye desorption and sorption capacities in mg g⁻¹, respectively.

To further examine the regeneration performance of BM-OP, a 0.1 M KH₂PO₄ solution was used as the desorbing medium. The adsorption was first performed by adding 100 mg of BM-OP to 50 mL of 100 mg L⁻¹ dye solution at 25 °C, using contact times of 60 min for MB and 80 min for MV. Equilibrium was reached, after which the suspension was filtered, and adsorption capacity was measured. Desorption of the obtained dye-loaded adsorbent was done by immersing it in 0.1 M KH₂PO₄ solution for 60 min. After desorption, BM-OP was recovered by filtration, washed with deionized water, vacuum-dried overnight, and reused in the subsequent adsorption cycle without the addition of fresh adsorbent. This adsorption–desorption procedure was repeated for 8 successive cycles to evaluate the regeneration and reusability of BM-OP. Some physical loss of adsorbent may have occurred during filtration, washing, and transfer, which could have contributed to the gradual decrease in removal efficiency over successive cycles.

3. Result and discussion

3.1. Characterization of the synthesized OP and BM-OP adsorbent

In the present work, orange peel powder (OP), a rich agro-waste product, was transformed into a potential adsorbent using a simple crushing and ball-milling procedure. To explore the impact of mechanical treatment on the physicochemical characteristics and adsorption performance, two kinds of adsorbents were prepared: crushed orange peel powder (OP) and ball-milled orange peel powder (BM-OP). Ball-milling was used as an effective mechanical activation technique to reduce particle size, increase surface area, and expose more functional groups on the OP surface. To develop a systematic evaluation of the effect of ball milling on surface morphology, textural properties, and adsorption behaviour, both OP and BM-OP samples were morphologically characterized by SEM, BET analysis of surface area, and adsorption measurements with cationic dyes. These comparative findings reveal the roles of particle size reduction and surface activation in improving dye–adsorbent interactions.

To examine the chemical functional groups on the adsorbent surface before and after dye adsorption, the FTIR spectrum of BM-OP was recorded (Fig. 2(a)). The peak that is visible in the high-energy region at about 2935 cm⁻¹ is the stretching vibration of the C–H bond, which shows that the structure contains aliphatic chains (–CH₂– and –CH₃–). A similar OP peak was also observed, with a minor shift at 2933 cm⁻¹, confirming the presence of these functional groups in both adsorbents. A broad absorption band observed in the range of 3200–3500 cm⁻¹ is attributed to the stretching vibrations of hydroxyl (–OH) groups present in cellulose and lignin structures. The large band at 1749 cm⁻¹ (BM-OP) and 1747 cm⁻¹ (OP) represents the C O band, which may originate from ester or carboxylic functionalities present in the lignocellulosic structure. Further, the peaks at 1613 cm⁻¹ in BM-OP and 1638 cm⁻¹ in OP correspond to aromatic C–C stretching in lignin, confirming the lignocellulosic nature of the material. A characteristic peak at 1441 cm⁻¹ (BM-OP) and 1444 cm⁻¹ (OP) is very likely the bending vibration of –CH₂– groups, further supporting the existence of aliphatic and aromatic structures present in the adsorbent. The absorption bands at 1370 cm⁻¹ and 1363 cm⁻¹ in BM-OP and OP are assigned to C–H bending vibrations from lignin and hemicellulose, reflecting the complex chemical composition of the orange peel powder-derived adsorbent. The characteristic peaks at 1241 cm⁻¹ in BM-OP and 1257 cm⁻¹ in OP are assigned to the C–O bending vibration, which is characteristic of alcohols, esters, and ethers and, therefore, indicates the presence of hydroxyl and ether groups on the adsorbent surface. Finally, the sharp bands at 910 cm⁻¹ and 916 cm⁻¹ are assigned to the out-of-plane bending vibrations of C–H bonds of the aromatic ring in the lignin.^16,32

Fig. 2. (a) FTIR spectra, (b) XRD analysis, (c) SEM micrographs of OP, (d) BM-OP adsorbents, and (e) EDS elemental mapping of OP and BM-OP samples.

Overall, the FTIR spectra of OP and BM-OP exhibited similar major functional groups, indicating that ball milling did not introduce substantial new chemical functionalities. However, slight shifts and variations in peak intensity were observed after ball milling. In particular, the broad O–H stretching band around 3300–3400 cm⁻¹ showed noticeable shifts and broadening, which may be associated with changes in hydrogen bonding and increased exposure of hydroxyl groups. In addition, several peaks in the 1800–1000 cm⁻¹ region became more distinct after ball milling, suggesting improved accessibility of the functional groups due to changes in surface roughness induced by the milling process.

Fig. 2(b) shows the XRD patterns of OP and BM-OP, revealing that both samples exhibit characteristic peaks at about 15.32, 18.5, and 21.85°, which are associated with the amorphous and crystalline regions of cellulose in lignocellulosic biomass.³³ Moreover, the Segal method (1959) was used to evaluate cellulose crystallinity. In the Segal method, the index of crystallinity C_I (%) is obtained by the following equation.³⁴

12

where “I₀₀₂” is the intensity of the crystalline peak around 22°, while “I_am” is the intensity of the valley between the two crystalline peaks (Fig. S1).

The crystallinity index, calculated using the Segal method, decreased from 57.5% for OP to 44.7% for BM-OP after ball milling, indicating partial disruption of the crystalline cellulose structure and an increase in the biomass's amorphous character. The obtained crystallinity values should be regarded as semi-quantitative.

SEM examines the surface morphology of the OP and BM-OP, and the micrographs are presented in Fig. 2. The SEM image of OP consists of relatively large, compact, and irregular particle shapes with fairly smooth and folded surfaces (Fig. 2(c)). These features suggest low surface exposure and a reduced number of available interaction sites for the dye molecules. Contrarily, the SEM image of BM-OP depicts a significant alteration of surface appearance following the ball-milling procedure, as shown in Fig. 2(d). The BM-OP particles are more dispersed with distinct cracks, edges, and layered structures. The surface is rendered more uneven and rough, suggesting that mechanical Milling is effective at revealing pre-existing inaccessible areas. This surface modification increases the availability of active sites, thereby facilitating stronger interaction between the adsorbent and dye molecules.

Fig. 2(e) gives the EDS elemental mapping of OP and BM-OP. The elemental maps clearly confirm the existence of C, O, and Ca in both samples. The prevailing elements are carbon and oxygen, which are in line with the lignocellulosic composition of orange peel powder, comprising mostly cellulose, hemicellulose, pectin, and lignin. The elemental mapping indicated the presence and distribution of these elements throughout the analyzed region. Moreover, the EDS spectra in Fig. S2 further confirm the elemental composition by showing typical peaks for C, O, and Ca. The existence of calcium can be explained by the naturally occurring minerals in orange peel waste. Moreover, the presence of Ca may affect the adsorbent's surface characteristics and facilitate interactions with dye molecules during adsorption. In general, the EDS analysis validates the elemental composition of OP and BM-OP and substantiates the structural characterization of the adsorbents.

The BET analysis results for OP and BM-OP are shown in Fig. 3(a–c), which present the N₂ adsorption–desorption isotherms and the associated pore diameter distribution of the synthesized samples. These graphs provide essential information on the adsorption characteristics of OP and BM-OP. The adsorption isotherms of both materials have a Type IV isotherm with an H3 hysteresis loop, which is characteristic of mesoporous materials with pore sizes between 2 and 50 nm. The hysteresis loop and the shapes of the isotherms indicate that both materials consist of mesopores with slit-shaped pores, and the loop indicates capillary condensation in these pores.³⁵ The adsorption curve of orange peel powder shows a gradual increase in adsorbed gas at lower pressures, with a slower slope, suggesting a smaller surface area and a smaller pore size. However, in the case of ball-milled orange peel powder, the isotherm curve rises more sharply in adsorbed volume at high relative pressures, indicating a large increase in surface area and pore size resulting from ball-milling. The surface area increases from 3.5 m² g⁻¹ to 8.5 m² g⁻¹. At the same time, the pore diameter expands from 6.3 nm to 13.1 nm, and the pore volume increases from 0.012 cm³ g⁻¹ for OP to 0.015 cm³ g⁻¹ for BM-OP, indicating improved pore accessibility and slight structural modification after ball milling (Table S2). Based on the changes in surface area, pore structure, and pore volume, it was suggested that the adsorptive properties of orange peel powder were enhanced due to ball milling. The modest increase in surface properties does not seem to be the only reason for the improved adsorption performance of BM-OP, as it may also reflect better access to active sites and easier diffusion of dye molecules.

Fig. 3. N₂ adsorption–desorption isotherms (a) OP, (b) BM-OP, (c) pore size distribution profiles, and (d) PZC curves of OP (PZC = 3.9) and BM-OP (PZC = 4.07).

The point of zero charge (PZC) of the adsorbents was determined using the salt addition method. The graph of ΔpH vs. initial pH values was plotted (Fig. 3(d)). The PZC corresponds to the point where ΔpH equals zero (intersection with the horizontal dotted line). According to the graph, OP and BM-OP exhibit PZC values at pH 3.9 and 4.07, which are in good agreement with the literature.³⁶ At pH values below 4, the adsorbent surface is positively charged due to protonation of functional groups. On the contrary, when the pH is above 4, deprotonation of surface functional groups occurs, leading to a negatively charged surface. This observation confirms that at pH above 4, the surfaces of both OP and BM-OP are characterized by a net negative charge, which prefers adsorption of cationic dyes such as MB and MV by electrostatic attraction. The comparable PZC values of OP and BM-OP suggest that ball milling did not significantly affect the basic surface charge behaviour, aside from improving adsorption performance, which was primarily due to greater surface area exposure and the availability of more active sites.

3.2. Adsorption characteristics of the OP and BM-OP adsorbents

The adsorption behaviour of the dyes on orange peel powder (OP) and ball-milled orange peel powder (BM-OP) was investigated using UV-Vis spectroscopy, as illustrated in Fig. 4. The spectra in Fig. 4 illustrate the interaction between the adsorbate and the OP and BM-OP adsorbents. These results revealed that there was considerable adsorption of MB on the surface of both OP and BM-OP, and the reduction of the absorbance rate was greater in the case of MB + BM-OP than in the case of MB + OP (Fig. 4(a)). The enhanced adsorption performance of BM-OP can be correlated with the surface and structural changes induced by ball milling. BET analysis revealed an increase in surface area from 3.5 m² g⁻¹ to 8.5 m² g⁻¹ and in pore size from 6.30 nm to 13.1 nm after ball milling, likely providing a greater number of accessible adsorption sites and facilitating the diffusion of dye molecules into the adsorbent structure. In addition, SEM analysis also showed an increase in surface roughness, which may have enhanced the interaction between the adsorbent surface and dye molecules, thereby contributing to the improved adsorption capacity of BM-OP. The significant reduction in absorbance in the MB + BM-OP spectrum indicates a higher MB removal efficiency with BM-OP. In the same case, the adsorption pattern of MV in Fig. 4(b) shows that BM-OP had a stronger absorbance change than that of OP. This enhanced adsorption of MV on BM-OP further enhances the efficiency of the ball-milling process by increasing the interaction between the adsorbent and dye molecules. The results show that BM-OP is more effective at removing cationic dyes, underscoring the potential of ball-milled orange peel powder for efficient dye removal. The distinct absorbance patterns for both dyes suggest a significant difference in adsorption behaviour between OP and BM-OP, with BM-OP exhibiting higher adsorption capacities for both MB and MV. These findings confirm the superior performance of BM-OP as an effective adsorbent for cationic dyes, underscoring its potential for dye removal from aqueous solutions. A quantitative comparison between OP and BM-OP under identical adsorption conditions is provided in the SI (Fig. S3), confirming the enhanced adsorption performance of BM-OP after ball milling. Furthermore, preliminary interaction experiments were conducted using the anionic dye Reactive Yellow 145 (RYD-145) to evaluate the adsorption selectivity of BM-OP toward different dye classes. The results indicated that BM-OP exhibited favourable interactions with the cationic dyes methylene blue (MB) and methyl violet (MV). In contrast, negligible interaction was observed with the anionic dye RYD-145, suggesting a preferential affinity of the adsorbent toward cationic dyes (Fig. S4).

Fig. 4. Interaction of MB (a) and MV (b) dyes with OP and BM-OP adsorbents, effect of pH (c), temperature (d), dosage (e), time (f), and initial concentration (g) and (h) on the adsorption of MB and MV dyes.

3.3. Effect of various parameters on the adsorption of cationic dyes

Following the analysis of the adsorption properties of BM-OP on cationic dyes, further tests were performed to analyze the effects of pH, contact time, adsorbent dosage and temperature on adsorption behaviour. The studies aimed to explain the adsorption mechanism and determine the optimal conditions for the highest dye removal capacity. The MB and MV linearity of response was initially determined, and a plot of absorbance vs. concentration was drawn to demonstrate the conformity of these dyes to the Lambert–Beer law, as shown in Fig. S5 and S6 with R² values of 0.986 for MB and 0.998 for MV, respectively.

3.3.1. Effect of solution pH and temperature

The adsorption performance of BM-OP is strongly dependent on the solution pH, which controls the surface charge characteristics of the adsorbent as well as the ionization behaviour of the dye molecules. The corresponding adsorption efficiencies of MB and MV at different pH values are illustrated in Fig. 4(c). The findings suggest that the removal efficiency of both MB and MV increases with increasing pH, with optimal adsorption at pH 8. The adsorption efficiency of both dyes decreased at lower pH (pH 2–4). This could probably be attributed to the higher saturation of hydrogen ions (H⁺) in the solution, which can compete with the positively charged cationic dyes for adsorption sites on the BM-OP surface. With increasing pH, electrostatic attraction between the positively charged dyes and the BM-OP surface increases, resulting in greater dye removal.³⁷ Similar pH-dependent adsorption behaviour for methylene blue removal was also reported by Amin et al.³⁸ using orange peel- and banana biomass-derived biochar adsorbents. At pH 8 and above, the adsorbent surface gets more negatively charged as a result of the deprotonation of functional groups (e.g., –COOH). This increases electrostatic attraction between the surface and the cationic dyes, thereby improving dye removal. For MB and MV, the optimum pH was 8, and the removal efficiencies were almost 95% and 97%, respectively. These results demonstrate that pH is a significant factor in the adsorption performance of BM-OP adsorbents and that neutral and slightly alkaline environments are conducive to efficient dye removal. The trend is consistent with previous research, which has shown that the adsorption performance of cationic dyes increases with increasing pH, due to the maximization of electrostatic interactions. However, when interpreting these pH-dependent results, it should also be noted that phosphate-containing buffers were used at some pH values; therefore, the observed adsorption behaviour may not be attributed exclusively to pH. Phosphate ions may also affect dye uptake through changes in ionic strength or competitive interactions with the adsorbent surface, particularly because KH₂PO₄ subsequently promoted dye desorption. Thus, the pH-dependent results should be interpreted while considering this possible buffer effect.

Besides pH, another important factor influencing the adsorption process is reaction temperature. The temperature dependence of the adsorption of MB and MV was studied from 293 to 333 K, at the optimum pH of 8. Fig. 4(d) shows that the MB removal efficiency decreases with increasing temperature, indicating that MB adsorption on BM-OP is exothermic. This decrease in efficiency with increasing temperature can be explained by the fact that, at higher temperatures, the solubility of MB in the solution increases, thereby reducing contact between MB molecules and the adsorbent surface.^39,40 In addition, this decrease would be consistent with the exothermic nature of the adsorption process, since higher temperatures would favour the desorption process, which would weaken the physical interactions between the MB molecules and the BM-OP adsorbent surface, decreasing the efficiency of the adsorption process.⁴¹ On the other hand, the efficacy of MV removal increases with temperature, suggesting that MV adsorption on BM-OP is endothermic. As the temperature increases, the dye molecules acquire greater kinetic energy, diffuse more rapidly, and thus interact more readily with the adsorbent surface. The continuous increase in removal efficiency with increasing temperature indicates that higher temperatures enhance MV adsorption.⁴² It is consistent with the findings of a previous study by Zhul-quarnain et al. using orange peel adsorbent for Malachite Green dye removal, where the adsorption efficiency increased with increasing temperature.⁴³

3.3.2. Effect of BM-OP dosage and reaction time on adsorption

The adsorbent amount is another crucial factor in the adsorption process, as it governs the adsorbent–adsorbate equilibrium in the system.^44,45 As observed in Fig. 4(e), an increase in the adsorbent dosage (10 mg to 50 mg) led to a notable increase in the removal efficiency of both MB and MV. This is due to the enhanced surface area and greater number of adsorption sites on BM-OP, enabling more dye molecules to adsorb. However, at some point, the removal efficiency levels off, and additional increases in the adsorbent dosage yield diminishing returns. This plateau of efficiency indicates that when the dosage is increased (above approximately 50 mg), the adsorbent sites are saturated and no additional adsorbent can significantly enhance dye removal. The plateau observed at higher adsorbent dosages could be due to the constant dye concentration in the original solution, despite the increasing number of available dye-removal sites. Most of the dye molecules were now completely removed, leaving some adsorption sites unutilized and thus only a small improvement in removal efficiency.^47–49 At high dosages, the adsorbent particles can also aggregate, thereby decreasing the available active surface area for successful dye binding. Therefore, an optimal adsorbent dosage is identified around 50 mg, beyond which the increase in dye removal efficiency becomes negligible. A similar trend was observed by Naik et al., who reported that the removal efficiency increased with increasing adsorbent dosage when using rice powder and orange peel adsorbents for Cu and Ni removal from wastewater.⁵⁰

Fig. 4(f) shows the influence of contact time on the adsorption of dyes on BM-OP. The graph shows that, at a constant dye concentration, the adsorption process was fast during the first 40 min, after which the rate decreased and finally reached equilibrium. In the case of MB, the equilibrium was reached at approximately 60 min, where the adsorption capacity increased only marginally from 47.74 to 47.88 mg g⁻¹ between 60 and 80 min. In contrast, MV approached equilibrium around 80 min, with negligible change in adsorption capacity thereafter (<1%), indicating equilibrium.

This indicates that the optimal contact times for MB and MV adsorption were 60 min and approximately 80 min, respectively. The rapid initial adsorption could be attributed to the large number of active sites on the BM-OP surface, enabling efficient interaction between the adsorbent and the dyes. However, as adsorption sites become saturated, the adsorption rate decreases, and equilibrium is reached. The reduced adsorption rate of the second phase is probably due to fewer available sites and to the diffusion of dye molecules into the pores of the BM-OP. The same dye removal efficiency as a function of contact time was also reported by Arami et al. for dyes in textile wastewater using an orange peel adsorbent.²²

3.3.3. Effect of initial dye concentration on adsorption

The most important characteristic affecting adsorption is the initial dye concentration, which provides the driving force for the transfer of dye molecules from the solution to the surface of the adsorbent.⁵¹ The corresponding adsorption efficiency of BM-OP for MB and MV at different initial concentrations is depicted in Fig. 4(g) and (h). As observed in Fig. 4(g), the removal efficiency of MB decreased slightly as the initial concentration increased from 40 mg L⁻¹ to 160 mg L⁻¹, from 99.19% to 97.8%. The limited number of adsorption sites relative to the increased number of dye molecules in solution could explain the decrease in removal efficiency at higher initial dye concentrations. At higher dye concentrations, the available adsorption sites will no longer be able to capture all the dye, leading to less than optimal removal efficiency.⁵² In contrast, the MB adsorption capacity (q_e) increased with increasing initial concentration up to roughly 320 mg g⁻¹ at 160 mg L⁻¹. The higher initial concentrations of dye may be due to the rise in concentration gradient between the dye solution and the surface of the adsorbent, which further increases the mass transfer and thus a higher amount of dye adsorption per unit mass of adsorbent.⁵³ A similar performance trend can be observed in the case of MV (Fig. 4(h)). Removal efficiency of MV declined from 97.71% to 90.89% as the initial concentration was increased from 150 mg L⁻¹ to 450 mg L⁻¹, whereas adsorption capacity (q_e) increased from 150 mg g⁻¹ to 400 mg g⁻¹. A greater initial concentration of the MV will result in more collisions between the dye molecule and the adsorbent surface and, consequently, increase adsorption capacity while decreasing overall removal efficiency.

3.4. Analysis of adsorption isotherm and kinetic behaviour

The adsorption behaviour of BM-OP was further explained by analyzing the equilibrium adsorption data of MB and MV using the Langmuir and the Freundlich adsorption isotherms. The Langmuir model predicts that the surface of the adsorbent is homogenous, the adsorption energies are the same, and just one molecule of the adsorbate may be accommodated in an adsorption site.⁵⁴ Conversely, the Freundlich isotherm model is based on a heterogeneous surface, allowing adsorption to occur in multiple layers.⁵⁵ Table S3 summarizes the isotherm parameters obtained from the slopes and intercepts derived from their nonlinear plots, and Fig. 5(a) and (b) present the corresponding graphs. The Langmuir and Freundlich models both described the adsorption behaviour of MB and MV on BM-OP reasonably well, as indicated by their high correlation coefficients (Table S3). Although the Langmuir model showed slightly higher R² values than the Freundlich model, the difference between the two models was relatively small, particularly for MV. Therefore, the adsorption behaviour cannot be attributed exclusively to ideal monolayer adsorption on a perfectly homogeneous surface. The satisfactory fitting of both models suggests that adsorption may involve relatively uniform adsorption sites together with a certain degree of surface heterogeneity, which is expected for lignocellulosic biomass materials. Moreover, in addition to the correlation coefficient (R²) values, error function analyses, including χ² and Δq (%), were performed to further evaluate the fit of the adsorption isotherm models. For MB adsorption, the Langmuir model exhibited better overall fitting performance, with lower χ² (61.11) and Δq (15.75%) values compared with the Freundlich model, indicating better agreement with the experimental data. For MV adsorption, however, the model-selection criteria were not fully consistent. Although the Langmuir model showed a slightly higher R² value and lower Δq (17.42%), the Freundlich model exhibited a lower χ² value (14.22), suggesting comparable fitting capabilities of both models. Therefore, the Langmuir model should be regarded as a statistical fitting preference rather than conclusive evidence of homogeneous monolayer adsorption.

Fig. 5. Adsorption isotherm plots (a) MB at 293 K and (b) MV at 333 K, pseudo-first-order and second-order kinetic plots (c) and (d), and intra-particle diffusion plot (e) and (f) of MB and MV dyes adsorption on BM-OP adsorbent.

It should also be noted that the dry-state N₂-BET surface area of BM-OP (8.5 m² g⁻¹) is relatively low compared with the fitted Langmuir capacities. Therefore, the adsorption capacity cannot be explained solely by external surface area. The high dye uptake may also involve aqueous-accessible domains of the biomass, swelling of the lignocellulosic matrix, ion–exchange interactions, and other bulk sorption processes that are not fully represented by N₂-BET measurements.

The equilibrium constant values were also calculated, and the obtained R_L values indicate that adsorption is favourable, with readings ranging from 0.045–0.012 for MB and from 0.104–0.037 for MV. The adsorption efficiency of BM-OP towards MB and MV was further evaluated through the fitted Langmuir adsorption capacities (q_m) of 485.05 mg g⁻¹ for MB and 583.60 mg g⁻¹ for MV. However, because the experimental adsorption data did not clearly reach a saturation plateau and both Langmuir and Freundlich models provided reasonable fits, these values should be regarded as model-derived estimates rather than directly measured saturation capacities. Therefore, the fitted Langmuir capacities represent the theoretical adsorption capacities obtained from the model fitting. In contrast, the fitting results alone do not provide sufficient evidence to conclude that adsorption occurs exclusively through ideal monolayer formation on a homogeneous surface. The high adsorption capacities may instead result from the combined contributions of surface functional groups, electrostatic interactions, and other surface heterogeneities of BM-OP.

To assess the effectiveness of BM-OP in adsorbing MB and MV, the uptake capacity (q_m, mg g⁻¹) of BM-OP was compared with those of other adsorbents reported to adsorb cationic dyes (Table 1). The findings reveal that BM-OP has a high adsorption capacity for both MB (485.05 mg g⁻¹) and MV (583.60 mg g⁻¹), indicating its high efficiency in removing cationic dyes from aqueous solutions. This comparison highlights the potential of BM-OP as a competitive, effective adsorbent for wastewater treatment.

Table 1. Comparison of the removal efficiency of various adsorbents towards MB and MV.

Adsorbate	Adsorbent	Reported/fitted adsorption capacities qmax (mg g−1)	Ref.
MB	Graphene	153.85	56
	Fig leaf activated carbon (FLAC-3)	24.750	57
	Agro-waste	55.390	58
	NaOH-treated pure kaolin	20.400	59
	Birchwood pellets	91.0	60
	BM-OP	485.05 (at 293 K)	This study
MV	Raw date seeds	59.50	46
	Ti2O3/mAPF MMSs	132.62	61
	Halloysite nanotubes	105.20	62
	Halloysite nanoclay	27.850	63
	Poly(methacrylic acid-co-acrylamide)/bentonite nanocomposite hydrogels	137.03	64
	BM-OP	583.60 (at 333 K)	This study

Thus, according to Table 1, BM-OP exhibits an outstanding adsorption capacity, which can be attributed to the improved accessibility and availability of active adsorption sites facilitated by its porous structure and well-developed pore network. Consequently, the dye molecules are successfully attached to the adsorbent surface. In addition, there are more active sites, leading to a higher overall adsorption efficiency.

The adsorption kinetics were analyzed by employing the pseudo-first-order (PFO) and pseudo-second-order (PSO) kinetic models to explain the whole adsorption process. The PFO model is usually used to study the adsorption kinetics considering the availability of adsorption sites. In contrast, the PSO model implies that the adsorption rate may be dependent on the adsorbent–adsorbate interactions. The MB and MV adsorption kinetics were analyzed by fitting both the PFO and PSO models using nonlinear regression (Fig. 5(c) and (d)), and the corresponding kinetic parameters are included in Table S4. Nonlinear plots were used to obtain different kinetic parameters, the intercept and the slope. The correlation coefficient (R²) obtained from the plots was used to assess the closeness of the experimental data to the theoretical data and the fit of the data to a suitable model. The higher the R² value, the closer the experimental q_e value is to the theoretical value, and the better the kinetic model represents the data. The findings indicate that both dyes adsorbed on BM-OP followed the PSO model more accurately, with R² values of 0.99 for MB and 0.99 for MV, higher than those for the PFO model (R² = 0.793 for MB and 0.775 for MV).

Moreover, the Δq% values for the PSO model were the lowest of both the kinetic models, i.e. 0.430 and 0.530 for MB and MV, respectively, with the least χ² values (0.005 for MB and 0.016 for MV), confirming the best fit of the PSO model for adsorption for both dyes (Table S4). The results indicated that the adsorption process was effectively explained by the PSO model for both MB and MV adsorption onto BM-OP.

To get further insight into the adsorption kinetics, the intra-particle diffusion model was applied to calculate the rate-limiting phase of the adsorption of MB and MV onto BM-OP adsorbent. This model describes the intraparticle diffusion. The adsorption process can be divided into three major steps: (1) external diffusion (or film diffusion) is a step when the dye molecules diffuse from the bulk solution to the BM-OP adsorbent surface, (2) intra-particle diffusion is a step when the dye molecules migrate on the surface of the adsorbent into the inner pores, and (3) the third region is the equilibrium stage, where the adsorption rate decreases due to the decreased availability of active sites and the decrease in the concentration gradient. According to the intra-particle diffusion model, a straight-line graph of q_tversus t^1/2 indicates that adsorption is governed by intra-particle diffusion. Conversely, the presence of multilinear behaviour in the graph suggests that multiple stages are involved in the adsorption process. The intra-particle diffusion model curves for MB and MV adsorption on BM-OP can be plotted as three straight lines, indicating a three-step adsorption process (Fig. 5(e) and (f)). The graphs are nonlinear, and the straight lines are not tangent to the origin, i.e., I ≠ 0. The first stage is rapid dye adsorption at the adsorbent's outer surface. The second stage is intra-particle diffusion, which prevails after the surface is saturated on the outside, and the third stage is the equilibrium stage, where the adsorption rate slows due to reduced availability of active sites. The kinetic profiles indicate three stages of adsorption. The dye molecules were initially quickly captured by the large number of active sites on the outer surface of BM-OP. This was followed by a slower adsorption stage that was controlled by diffusion through the internal pores of the adsorbent. Finally, the adsorption rate stabilized at a nearly constant value, thus reaching equilibrium. The outcomes show that both surface adsorption and intraparticle diffusion are important factors in controlling the efficiency of the dye removal.

3.5. Adsorption mechanism

The adsorption modes of MB and MV on BM-OP were studied by FTIR spectroscopy; the corresponding spectra are shown in Fig. S7 (SI). The post-adsorption FTIR spectra showed slight changes in peak intensity and position, providing insight into the possible interactions between BM-OP and the cationic dyes.

After adsorption, the peak of BM-OP (before adsorption) at around 2935 cm⁻¹ decreased in intensity, indicating that the functional groups of the BM-OP adsorbent interacted with the cationic dye molecules. This is further corroborated by changes in the 1749 cm⁻¹ and 1613 cm⁻¹ regions, which correspond to carbonyl groups and aromatic structures, respectively, indicating their participation in the adsorption process. In addition, the peaks in the region between 1400 cm⁻¹ and 1100 cm⁻¹ showed slight changes, which can be explained by interactions between the functional groups of BM-OP (hydroxyl and carboxyl) and the cationic dyes. The variations in the spectral bands at 1370 cm⁻¹ and 1241 cm⁻¹ suggest that electrostatic interactions and, perhaps, hydrogen bonding between the functional groups of BM-OP and the cationic dyes contribute significantly to the adsorption mechanism.^65,66 The general shape changes in the FTIR spectra, particularly the shifts in the regions of the functional groups, including –OH, –COOH, and C O, justify the fact that the adsorption process may be due to a significant degree of strong electrostatic interactions between the negatively charged functional groups on the adsorbent and the positively charged dye molecules. The post-SEM analysis of dye-adsorbed BM-OP was also performed and is shown in Fig. S8, showing that the layered surface morphology of BM-OP remained visible after adsorption. In contrast, surface agglomeration was observed, which might be due to the attachment and accumulation of dye molecules.

XPS analysis of BM-OP and dye-adsorbed BM-OP was performed further to explore the adsorption mechanism (Fig. 6). The full survey scan is shown in Fig. S9. Prior to adsorption, BM-OP showed distinct C 1s and O 1s peaks, confirming the presence of carbon- and oxygen-containing functional groups on the adsorbent surface. The high-resolution C 1s spectra of BM-OP prior to adsorption were fitted with three components at 284.15, 285.54, and 287.52 eV, corresponding to C–H/C–C, C–O, and C O groups (Fig. 6(a)), respectively. After MB adsorption, the peaks shifted to 284.10, 285.36, and 286.42 eV; after MV adsorption, they shifted to 284.19, 285.43, and 286.59 eV (Fig. 6(c) and (g)).^67,68 The O 1s spectra prior to adsorption exhibited peaks at 531.70 and 532.50 eV, attributed to C O and hydroxyl (–OH) groups, respectively (Fig. 6(b)). After MB adsorption, the peaks shifted to 531.75 and 532.60 eV, whereas after MV adsorption, they shifted to 531.99 and 532.61 eV (Fig. 6(d) and (h)). The alterations in the binding energies of C 1s and O 1s signify the participation of oxygen-containing functional groups in the adsorption process.⁶⁹ Additionally, new N 1s and S 2p signals emerged following dye adsorption. In the MB-loaded BM-OP, the N 1s spectra displayed peaks at 399.36 and 401.41 eV, indicative of C–N and protonated nitrogen (N⁺) species (Fig. 6(e)),⁷⁰ respectively, whilst the S 2p spectrum exhibited a spin–orbit doublet at 164.06 and 165.24 eV, corresponding to the S 2p_3/2 and S 2p_1/2 components of the thiazine sulfur (C–S) in MB, respectively (Fig. 6(f)).⁷¹ The MV-loaded BM-OP exhibited N 1s peaks at 399.33 and 400.73 eV, attributed to C–N and protonated nitrogen species (Fig. 6(i)).⁷⁰ The emergence of these distinctive nitrogen- and sulfur-containing species validates the effective adsorption of MB and MV molecules onto the BM-OP surface.

Fig. 6. XPS spectra of BM-OP before adsorption, C 1s (a) and O 1s (b), after MB adsorption, C 1s (c), O 1s (d), N 1s (e), S 2p (f), and after MV adsorption, C 1s (g), O 1s (h), and N 1s (i).

The schematic diagram illustrating the proposed adsorption process for the removal of MB and MV onto BM-OP is shown in Fig. 7. The adsorption is determined by different bonds between the cationic dye molecules and the functional groups of the lignocellulosic components (cellulose, hemicellulose, pectin, and lignin) present in BM-OP.⁷² Electrostatic interactions are important, in which the positively charged dye molecules are drawn towards the negatively charged functional groups, e.g., the carboxyl (–COOH) groups present in lignin and cellulose.⁷³ Moreover, hydrogen bonding takes place between the hydroxyl (–OH) groups of the cellulose and pectin and the dye molecules, which also contributes further to the adsorption process.⁷⁴ The mechanism also demonstrates π–π interactions between the aromatic rings of MB and MV and the aromatic constituents of lignin, which are involved in adsorption via delocalized π-electrons. Lastly, the contact of carbonyl (C O) groups within hemicellulose and the π-electrons on the benzene rings of the dyes denotes an n–π interaction, which further reinforces the adsorption process.⁷⁵ These interactions (electrostatic, hydrogen bonding, π–π interactions, and C O interactions) facilitate the effective adsorption of both MB and MV onto BM-OP, highlighting the complex, synergistic nature of the adsorption mechanism. The XPS study also corroborated the participation of several adsorption interactions. The emergence and alteration of O-containing functional groups, together with the detection of N- and S-related peaks after dye adsorption, indicated the involvement of electrostatic interactions, hydrogen bonding, and potential π–π interactions during adsorption.

Fig. 7. Proposed mechanism of adsorption of cationic dyes on BM-OP adsorbent.

3.6. Desorption efficiency and adsorbent regeneration

The desorption experiments were conducted to assess the feasibility of regenerating and reusing the BM-OP adsorbent. The concentrations of desorbing agents used in the desorption studies were 0.1 M KH₂PO₄, methanol, and water. Next, 100 mg of dye-loaded BM-OP was added to 50 mL of each eluent solution and stirred for 60 min under ambient conditions at neutral pH. The comparison of the desorption efficiencies of these solvents is given in Fig. 8(a). KH₂PO₄ showed the best desorption efficiency, with MB and MV desorption rates of 92.4% and 94.5%, respectively. On the contrary, the desorption capacities of both methanol and water were very low. Methanol resulted in a desorption of 52% for MB and 51.43% for MV, while water led to desorption rates of 27% for MB and 28.6% for MV. These findings indicate that KH₂PO₄, which is a phosphate buffer with weak acids such as HPO₄²⁻ and H₂PO⁴⁻, is very effective in desorbing both MB and MV from the BM-OP surface.³⁷ As a result, 0.1 M KH₂PO₄ was identified as the most suitable desorbing agent for regenerating the BM-OP adsorbent.

Fig. 8. Desorption of cationic dyes (a) from dye-loaded BM-OP using various eluents, and (b) regeneration efficiency of BM-OP adsorbent for MB and MV dyes.

The graph in Fig. 8(b) shows the recycling efficiency of BM-OP in adsorbing MB and MV over eight consecutive cycles. The findings indicate that adsorption efficiency was high throughout the cycles, with average adsorption efficiencies of 93.09% and 94.94% for MB and MV, respectively, in the first cycle. However, as the cycles progressed, a noticeable reduction in adsorption efficiency was observed. In the case of MB, the adsorption efficiency decreased from 93.09% in the first cycle to 72.3% in the eighth cycle. Similarly, the adsorption efficiency of MV declined to 71.3% after eight cycles, compared with 94.94% at the start of the cycle. The gradual decrease in adsorption efficiency after repeated cycles may be attributed to partial loss of adsorbent material during regeneration or to incomplete desorption of dye molecules from active sites. Such measurements suggest that BM-OP exhibits high adsorption efficiency across numerous cycles and can be regenerated and reused for wastewater dye removal. After regeneration cycles, the adsorption efficiency gradually decreased, but BM-OP still maintained a high adsorption efficiency after eight cycles, indicating good reusability and stability.

Furthermore, the structural integrity of BM-OP after regeneration was assessed using FTIR spectroscopy. A comparison of the spectra obtained before adsorption and after the eighth adsorption–desorption cycle (Fig. S10) showed no appreciable changes in either the characteristic peak positions or their intensities. From these results, it is concluded that the chemical structure and surface functional groups of the adsorbent were retained by repeated re-use.

4. Conclusions

This study demonstrates the potential of ball-milled orange peel powder (BM-OP) as an effective adsorbent for the removal of cationic dyes from aqueous solutions. BM-OP showed high adsorption capacities for MB (485.05 mg g⁻¹) and MV (583.60 mg g⁻¹). The equilibrium data were reasonably described by the Langmuir isotherm model; however, this fit should be considered an empirical representation of the adsorption behaviour rather than definitive evidence of ideal monolayer adsorption on a homogeneous surface. Kinetic experiments were satisfactorily described by the pseudo-second-order model. At the same time, the adsorption mechanism was mainly associated with electrostatic interactions and hydrogen bonding, as supported by FTIR and XPS analyses. In addition, BM-OP showed superior reusability, with desorption efficiencies of 92.4% and 94.5% for MB and MV, respectively, using KH₂PO₄ as the desorbing agent. The material maintained an adsorption efficiency of approximately 70% after eight consecutive cycles, indicating its potential for multiple reuses in dye removal applications. Hence, the ball milling process significantly enhanced the surface properties of BM-OP, increasing the availability of active sites for dye adsorption. The developed BM-OP adsorbent demonstrated promising adsorption performance along with good regeneration ability, highlighting its potential for practical wastewater treatment applications. However, further studies are required to evaluate its performance in real wastewater systems under continuous-flow conditions. Future work should focus on large-scale applications and the long-term stability of the adsorbent.

Author contributions

F. Shafiq: writing – original draft, investigation, formal analysis, data curation. M. Sarfraz: writing – original draft, visualization, data curation. W. Raza: writing – review & editing, visualization. N. Ali: validation, methodology, data curation. N. AlMasoud, T. Alomar: review & editing, validation, investigation, data curation, funding acquisition. M. Azam, N. Raza: visualization, formal analysis, review and editing. M. Riaz: validation, review and editing, funding acquisition, supervision.

Conflicts of interest

The authors declare that there is no conflict of interest.

Data availability

Data supporting the findings of this study are available from the corresponding author upon reasonable request.

Supplementary information (SI) is available. See DOI: https://doi.org/10.1039/d6ra06109e.