Innovative Green Strategy for the Regeneration of Spent Activated Carbon via Ionic Liquid-Based Systems

Abstract

The widespread use of activated carbon (AC) as an adsorbent in diverse applications generates substantial amounts of AC waste, posing environmental and disposal challenges. Therefore, effective AC regeneration is essential to enhance the sustainability of adsorption-based technologies. However, conventional regeneration methods often involve harsh chemicals or energy-intensive processes, limiting environmental and economic feasibility. In this study, the regeneration of commercial AC saturated with synthetic dyes Acid Blue 9 (AB9) and Acid Yellow 23 (AY23) is investigated using aqueous solutions of ionic liquids (ILs) as a green alternative. A set of ILs with varying cation–anion structures was synthesized and screened for regeneration performance, where [TBP][Sal] was identified as the most effective. Process parameters such as IL concentration, temperature, time, and solid-to-liquid ratio were optimized using response surface methodology, achieving regeneration efficiencies of up to 99% for AB9-AC and 80% for AY23. These efficiencies persisted over three cycles, while adsorption capacity remained unchanged for AY23 and decreased by ~40% for AB9. To improve sustainability, a preliminary study was conducted by implementing an aqueous biphasic system for IL and dye concentration from the post-regeneration solution. This integrated strategy presents a promising step toward the development of near-zero waste adsorption–regeneration cycles for AC adsorption applications.

1. Introduction

Activated carbon (AC) is a cornerstone of industrial and municipal water treatment due to its high adsorption capacity for a wide range of pollutants, including various organic substances and heavy metals [1,2,3]. Although significant attention has been directed towards the synthesis of novel carbon materials, future research is anticipated to place greater emphasis on regeneration, acknowledging it as a vital element of innovative adsorption approaches and the advancement of integrated processes [4].

Spent AC disposal poses economic and environmental challenges related to transportation and regulatory compliance. Millions of tons of spent AC are generated annually, classified as solid or hazardous waste. The main treatment methods, such as incineration or landfilling, increase industrial costs, both for purchasing fresh AC and managing waste [5]. Additionally, the environmental impact is considerable, as spent AC contains adsorbed contaminants that can pose hazards if not properly managed [6]. These burdens highlight the need for efficient regeneration strategies to reduce waste and extend AC usability. Conventional regeneration technologies have struggled to offer an effective balance between performance, cost, and sustainability. Among current regeneration techniques, thermal reactivation is the most extensively used due to its ability to restore AC’s adsorption capacity. However, it is highly energy-intensive, requiring between 220 and 250 kWh per kilogram of spent carbon and typically resulting in a 5–15% mass loss per cycle, thereby reducing long-term material efficiency [7]. Electrochemical regeneration has emerged as a promising alternative, providing low energy consumption (0.2–1.8 kWh/kg) and high capacity recovery (85–90%), but is hindered by the need for specialized reactors and high capital costs [8,9], whereas chemical regeneration can be performed with basic mixing tanks and dosing pumps under mild conditions, yet relies on non-biocompatible solvents. Several recent studies [10,11,12,13,14,15,16,17,18,19] have focused on the chemical regeneration of carbon-based materials, including activated carbon, examining key solvent properties such as polarity, hydrophobicity, solubility, molar mass, pH, boiling point, and toxicity with adsorbates like pharmaceuticals, phenols, dyes, or metals [20]. However, these investigations primarily utilized aggressive or toxic solvents such as inorganic acids (HCl, HNO₂, H₃PO₄ etc.) and bases (NaOH) or organic solvents (methanol, ethanol, acetone, etc.). For example, methanol, commonly used in desorption, has a high volatility and is classified as a hazardous air pollutant by the EPA, while acid-based regeneration can generate corrosive waste streams that require additional neutralization and disposal [21,22]. The lack of a regeneration method that is simultaneously efficient, selective, environmentally benign, and economically viable underscores a critical gap in current adsorption-based treatment technologies.

Ionic liquids (ILs) have emerged as promising candidates for addressing this challenge. Their unique physicochemical properties, such as non-volatility, high thermal stability, and tunable solubility [23], position them as “designer solvents” that can be tailored for specific desorption tasks. Structurally, they consist of large organic cations paired with either organic or inorganic anions, which significantly lowers their melting points compared to conventional inorganic salts [24,25]. A vast number of possible cation–anion combinations exist, allowing for the synthesis of a wide range of ILs that can be specifically engineered to be non-toxic and environmentally compatible, aligning with green chemistry principles [26]. Moreover, they can be tailored for selective interactions with specific analytes, enhancing their efficiency in targeted applications [27]. All these properties make ILs highly attractive for various applications, including the regeneration of adsorbents.

Although widely studied for extraction, metal recovery, and biomass processing [28,29,30], ILs have not yet been explored for the regeneration of spent AC, despite their potential to replace conventional organic solvents. In addition to their solvation properties, ILs can form aqueous biphasic systems (ABS) with salts or polymers, enabling selective separation of solutes and facilitating IL recovery, an essential feature for closed-loop operations [31,32].

In this study, we propose a novel regeneration strategy based on IL-assisted desorption of synthetic dyes from spent commercial AC. This adsorbent was saturated with two model molecules, Erioglaucine disodium salt (Acid Blue 9–AB9) and Tartrazine (Acid Yellow 23–AY23). These dyes were selected due to their relatively simple molecular structures and differences in hydrophobicity, which make them suitable as model adsorbates for adsorption and regeneration studies. Moreover, adsorption of synthetic dyes onto AC has been extensively investigated in the literature, providing a solid basis for comparison and validation of regeneration strategies. At the same time, they are among the most prevalent industrial contaminants, with over 10⁵ tons produced annually, up to half of which enter aquatic environments, emphasizing their persistence and the need for effective remediation [33,34,35]. To investigate the regeneration potential of ILs, a screening process was conducted to identify the most effective candidates, and for this purpose we used the following: [TBP][Sal] (tetrabutylphosphonium salicylate), [TBP][HSO₄] (tetrabutylphosphonium hydrogen sulfate), [TBP][Cl] (tetrabutylphosphonium chloride), [Ch][Cl] (choline chloride), [Ch][Sal] (choline salicylate), [bmim][Sal] (1-butyl-3-methylimidazolium salicylate), [bmim][HSO₄] (1-butyl-3-methylimidazolium hydrogen sulfate), [bmim][Cl] (1-butyl-3-methylimidazolium chloride), and [TBA][Cl] (tetrabutylammonium chloride). The IL exhibiting the highest regeneration efficiency was selected for further process optimization. The optimized regeneration procedure was then evaluated over three consecutive cycles to assess adsorbent reusability. Additionally, preliminary tests of subsequent ABS formation were conducted to investigate the potential for component recovery. These findings advance sustainable wastewater treatment and adsorbent recycling by proposing an efficient, eco-friendly process applicable to large-scale dye-contaminated wastewater streams.

2. Materials and Methods

2.1. Materials

Tetrabutylphosphonium hydroxide (40 wt% in water), tetrabutylammonium hydroxide (40 wt% in water), cholinium hydroxide (46 wt% in water), 1-butyl-3-methylimidazolium chloride (purity ≥ 98%), erioglaucine disodium salt (purity ≥ 99%), tartrazine (purity ≥ 99), salicylic acid (purity ≥ 99%), and sodium citrate dihydrate (purity ≥ 99%) were purchased from Sigma-Aldrich (St. Louis, MO, USA). Activated carbon and sodium bisulfate (purity ≥ 98%) were purchased from Centrohem (Stara Pazova, Serbia). Hydrochloric acid (37 wt% in water), absolute ethanol, and HPLC grade acetone were acquired from Honeywell (Offenbach, Germany). Figure 1 shows the chemical structures and abbreviations of the studied synthetic dyes.

2.2. IL Synthesis

The ionic liquids used in this study were synthesized according to literature procedures [36]. Tetrabutylphosphonium salicylate ([TBP][Sal]), tetrabutylphosphonium chloride ([TBP][Cl]), tetrabutylammonium chloride ([TBA][Cl]), and cholinium chloride ([Ch][Cl]) were prepared by neutralization reaction, involving the addition of the appropriate hydroxide carrying the cation of the IL to the corresponding acid carrying the anion of the IL. The mixture was stirred for two hours at room temperature. The solvents were evaporated using a rotary evaporator (R-210 Rotavapor System, BÜCHI Labortechnik AG, Flawil, Switzerland) at 70 °C under vacuum conditions for approximately 4 h. Additionally, hydrogen sulfate-based ILs, including [TBP][HSO₄] and [bmim][HSO₄], as well as [bmim][Sal], were synthesized through metathesis reaction [37], using [bmim][Cl] and appropriate salt. The precipitated salt was removed after centrifugation, and solvents were removed using a rotary evaporator under the previously described conditions. All ILs were characterized using FTIR analysis (Supplementary Material (SM)–Figures S1a–g), and their water content was confirmed by Karl Fischer titration. Figure 2 represents the chemical structures of cations and anions of synthesized ILs.

2.3. AC Properties

2.3.1. Zero Point Charge

The point of zero charge (PZC) was determined using the pH drift method. A series of 10 mL NaCl solutions (0.1 mol/L) were prepared, and their initial pH values were adjusted in the range of 2, 3, 4, 5, 6, 7, 8, 9, 10, and 11 (±0.01) using 0.1 mol/L HCl or NaOH. After adding 0.1 g of the adsorbent to each solution, the suspensions were stirred using a rotary agitator (Stuart SSL1 Lab-Scale Orbital Shaker, Bibby Scientific, Staffordshire, UK) at 200 rpm for 24 h at 25 °C. Each experiment was performed in triplicate, and the average value was used for data analysis. The final pH was measured after filtration, and the difference between the initial and final pH (ΔpH) was plotted against the initial pH (Figure S2a in SM). The PZC was identified as the pH at which ΔpH = 0.

2.3.2. Boehm Titration

An amount of 0.1 g of AC was weighed and placed into a flask, followed by the addition of 10 mL of 0.1 M NaOH or HCl solution. The mixture was stirred at 200 rpm using a rotary agitator (Stuart SSL1 Lab-Scale Orbital Shaker) for 1 h at 25 °C. After mixing, the solution is filtered to separate the liquid phase from the solid carbon material. The filtrate is subsequently titrated with a standard solution of a basic or acidic titrant, with continuous pH monitoring throughout the titration process, in order to determine the amount of unreacted acid or base (Figure S2b in SM). Each experiment was performed in triplicate, and the average value was used to calculate the concentration of functional groups, determined according to the following equation:

$${\mathrm{C}}_{\mathrm{group} }={\displaystyle \frac{({\mathrm{V}}_{0 }- {\mathrm{V}}_{\mathrm{t}})·{\mathrm{C}}_{\mathrm{t}}}{\mathrm{m}}}$$

where C_group is the concentration of functional group, V₀ is initial volume, V_t is the titrant volume, C_t is the titrant concentration, and m is adsorbent mass.

2.3.3. FTIR Analysis

FTIR-ATR spectroscopy was employed to characterize the dyes (Figure S3b in SM) and the adsorbent material before and after dye adsorption (Figure S3c in SM). A Thermo Scientific Nicolet iS10 spectrometer (Waltham, MA, USA) was used, recording spectra in the wavenumber range of 4000 to 400 cm⁻¹ with a resolution of 4 cm⁻¹, averaging 16 scans per sample. Prior to analysis, both the dyes and the adsorbent were dried at 60 °C for 24 h to remove residual moisture. Additionally, activated carbon samples were pre-dried at 100 °C for 24 h to ensure the elimination of any remaining moisture before FTIR measurements.

2.3.4. Methylene Blue Number

For the determination of the methylene blue number (MBN), 1 mg of AC was added to 1 mL of MB solution at different concentrations (2, 4, 5, 10, 20, 40, 100, and 200 mg/L) and allowed to equilibrate for 24 h at room temperature (25 °C). The residual concentration of methylene blue in the supernatant was quantified by UV/VIS spectrophotometry at 644 nm. The MBN, expressed as the maximum amount of dye adsorbed per gram of adsorbent (q_max), was obtained from the Langmuir isotherm model (Figure S2c).

2.4. Adsorption Experiments

2.4.1. Determination of the Optimal Initial Dye Concentration

To identify the optimal initial dye concentration for further adsorption studies, a series of samples containing 1 mg/mL of AC were prepared with final dye concentrations ranging from 2·10⁻⁶ to 10⁻² mol/L for AB9 and from 1 × 10⁻⁵ to 1 × 10⁻³ mol/L for AY23. The mixtures were stirred continuously at 25 °C for 60 min. The adsorption efficiency was calculated as the ratio of adsorbed to initial dye concentration, and the results are presented in Figure S3a in SM. Dye quantification was performed using a UV/VIS spectrophotometer (LLG-uniSPEC2) at 625 nm for AB9 and 430 nm for AY23.

2.4.2. Isotherm Determination

Adsorption experiments were conducted to determine the equilibrium isotherms for AB9 and AY23 dyes. The initial dye solutions were prepared at varying concentrations (10⁻⁶ to 10⁻⁴ mol/L for AB9 and from 10⁻⁵ to 10⁻³ mol/L for AY23) and with AC dosage of 1 mg/mL and pH~7. The adsorption process was performed at a constant temperature (25 °C) under continuous stirring (200 rpm using a rotary agitator) to ensure equilibrium. After equilibrium was reached, the samples were filtered, and the residual dye concentrations were determined by UV/VIS spectrophotometry using the same procedure described in Section 2.4.1. The amount of dye adsorbed per unit mass of adsorbent was calculated based on the following equation:

$$\mathrm{q} = {\displaystyle \frac{{(\mathrm{C}}_0 - {\mathrm{C}}_{\mathrm{supernatant}})·\mathrm{V}·\mathrm{M}}{{\mathrm{m}}_{\mathrm{AC}}}}$$

where q (mg/g) is the mass of the adsorbed dye per g of AC, C₀ is the initial dye concentration, C_supernatant is the dye concentration in the supernatant analytically determined, V is the volume of the solution, M is molar mass, and m_AC is the mass of the AC.

2.5. AC Regeneration

2.5.1. Screening Study

Following the adsorption procedure described in Section 2.4.1, the dye-saturated activated carbon was separated from the supernatant and subsequently subjected to the regeneration process. For the screening study, 1 mL of a 20 wt% IL solution or other solvent (water, ethanol, or acetone) was added to the saturated adsorbent, and the mixture was stirred for 1 h at room temperature at 1000 rpm. The supernatant was then separated and analyzed using UV/VIS spectroscopy to quantify the amount of dye desorbed from the material.

Regeneration efficiency was calculated as follows:

$$\mathrm{RE} (\%) = {\displaystyle \frac{{\mathrm{n}}_{\mathrm{des}}}{{\mathrm{n}}_{\mathrm{ads}}}}· 100\%$$

where n_des is the moles of the dye from the supernatant during regeneration, while n_ads is the moles of the dye adsorbed onto the AC.

2.5.2. Optimization Study

Optimization of the regeneration process was conducted for the most efficient IL identified during the screening study. To achieve this, the Response Surface Methodology (RSM) was employed, implemented using the Design Expert software (version 13). The experiment was based on an optimal (custom) design, where four key factors were varied: ionic liquid concentration (IL, wt%), temperature (°C), process duration (minutes), and the solvent-to-material ratio (S/L, mL/mg). According to the experimental design, the following factor levels were tested: IL (wt%)–5, 12.5, 20; temperature (°C)–15, 20, 25; time (minutes)–15, 30, 60; and S/L (mL of solution/mg of AC)–0.5, 1, and 1.5. The regeneration percentage was determined as the response variable, similar to the screening phase of the research.

2.5.3. Multi-Cycle Adsorption and Regeneration Performance

The adsorbent regeneration and its performance over multiple cycles were studied under the optimal adsorption and regeneration conditions established during the optimization study. In each cycle, AC was used for dye adsorption following the previously described procedure. After adsorption, the adsorbent was regenerated under the optimized conditions, then separated, rinsed with water for several minutes, and subsequently reused for dye adsorption in the next cycle, repeating the same process. Dye quantification was performed, and adsorption efficiencies were calculated using the methods described earlier. Regeneration efficiency during the cycle in i (RE_i) was calculated as follows:

$${\mathrm{R}\mathrm{E}}_{\mathrm{i}} (\%) = {\displaystyle \frac{{\mathrm{n}}_{\mathrm{des}, \mathrm{i}}}{{\mathrm{n}}_{\mathrm{ads}, \mathrm{i}}}}· 100\%$$

where n_{des, i} is the moles of the dye from the supernatant during the cycle i, while n_{ads, i} is the moles of the dye adsorbed onto the AC during the same cycle i.

2.5.4. Preliminary Assessment of Component Recovery via Aqueous Biphasic Systems

The ABSs were formed by adding sodium citrate to the post-regeneration solution obtained during the optimized regeneration process. The compositions of the ABSs were 5 wt% IL + 10 wt% salt + 85 wt% H₂O and 5 wt% IL + 20 wt% salt + 75 wt% H₂O. The systems were thermostated at 25 °C and allowed to equilibrate for one hour, after which they were centrifuged at 10,000 rpm for 5 min and the phases carefully separated. The dye concentrations in each phase were quantified, and extraction efficiencies (EE) were calculated as follows:

$$\mathrm{EE} (\%) = {\displaystyle \frac{{\mathrm{n}}_{\mathrm{IL}-\mathrm{rich} \mathrm{phase}}}{{\mathrm{n}}_{\mathrm{des}}}}· 100\%$$

where n_{IL-rich phase} is the number of moles of dye in the IL-rich phase, and n_des is the number of moles of dye in the post-regeneration solution.

3. Results and Discussion

3.1. AC Properties

The analysis of key surface and chemical properties of the commercial AC provided valuable insights into its surface chemistry, charge properties, and functional group composition, factors that govern its adsorption–desorption performance.

The studied AC exhibited a near-neutral surface charge with a point of zero charge (pH_pzc) of 7.33 ± 0.02 (SM Figure S2a), suggesting a balanced distribution of acidic and basic surface groups. This was confirmed by Boehm titration, which quantified 0.38 ± 0.06 mmol/g of acidic groups and 0.34 ± 0.05 mmol/g of basic groups (SM Figure S2b). A relatively low degree of surface functionalization was further supported by FTIR analysis (Figure 3). The spectrum showed a weak aromatic C=C stretching band at 1600 cm⁻¹ [38], while the peak observed at 1250 cm⁻¹ can be attributed to C–O stretching vibrations typically associated with ester, ether, phenol, or alcohol groups, commonly present in oxidized carbon materials [39,40]. This minimalist surface chemistry, while potentially reducing chemisorptive interactions, still allows for strong adsorption of nonpolar and weak polar molecules due to the material’s π-rich domains. Furthermore, the determined MBN of 105 mg/g (Figure S2c in SM) represents an average but relatively modest capacity compared to commercial ACs [41,42], suggesting a medium level of mesoporosity and indicating a solid adsorption potential toward organic pollutants.

3.2. Dye Adsorption Conditions

To ensure a consistent and representative evaluation of desorption and regeneration performance, the AC was saturated with two model adsorbates, dyes AB9 and AY23, selected for their distinct structural and polarity characteristics (Figure S6a,b).

The effect of initial dye concentration on removal efficiency was investigated to determine optimal saturation conditions for subsequent experiments. Preliminary batch tests confirmed that an equilibration time of 60 min was sufficient to achieve adsorption equilibrium. Adsorption experiments were conducted over a concentration range from 2·10⁻⁶ to 10⁻⁴ mol/L for AB9 and 1 × 10⁻⁵ to 1 × 10⁻³ mol/L for AY23, with an adsorbent dose of 1 mg/mL, contact time of 60 min, and pH~7. As shown in Figure S3a in SM, removal efficiency sharply declines with increasing initial dye concentrations for both dyes. This trend is attributed to the saturation of available adsorption sites on the activated carbon surface. At lower concentrations, dye molecules have greater access to unoccupied active sites, resulting in high removal efficiencies. However, as concentration increases, the competition among dye molecules intensifies, leading to site saturation and reduced adsorption efficiency. Based on these results, an initial dye concentration of 4 × 10⁻⁶ mol/L for AB9 and 2 × 10⁻⁵ mol/L for AY23 was selected for equilibrium studies, yielding removal efficiency of ~100 ± 0.6% and 80 ± 0.5%, respectively. These conditions were considered optimal for further desorption and regeneration experiments.

3.3. Dye Adsorption Isotherms

A clear understanding of the forces governing dye adsorption on AC is essential for designing efficient desorption and regeneration strategies. Physically adsorbed species, held by van der Waals interactions, can usually be released under mild conditions, whereas chemisorbed species form stronger chemical bonds that demand more rigorous treatment to break [43].

To better understand the mechanism of dye adsorption by the studied AC, we fitted our experimental data obtained under equilibrium conditions into several frequently used adsorption isotherms (Langmuir, Freundlich, Langmuir-Freundlich, Temkin, and Dubinin–Radushkevich) [44]. The non-linear forms of these isotherms are given in Table S1 in SM. For all experiments, the AC dose was held constant at 1 mg/mL. The obtained results are summarized in

Table 1. Isotherm models and respective fitting parameters.

Isotherm		AB9	CI Limits (95%)		AY23	CI Limits (95%)
Langmuir	qm (mg/g)	54.75	44.57	64.94	−106.3	−434.10	221.50
	b (L/mg)	0.02	0.01	0.03	−8.82	−2.59 × 10−3	8.25 × 10−4
	R2	0.97			0.98
	red.χ2	18.45			11.01
Freundlich	K (mg/g)	2.02	0.14	3.89	0.04	−0.11	0.18
	n	1.71	1.19	2.23	0.81	0.38	1.25
	R2	0.98			0.98
	red.χ2	7.60			12.05
Langmuir–Freundlich	qm (mg/g)	75.97	59.57	92.38	31,391.69	−64,956.98	127,740.37
	b (L/mg)	0.01	3.87 × 10−3	1.16 × 10−2	1.48 × 10−6	−6.82 × 10−6	9.77 × 10−6
	n	1.01	0.59	1.41	1.19	−8.02	10.41
	R2	0.99			0.98
	red.χ2	1.75			12.18
Temkin	B (J/mol)	12.11	−0.05	0.56	16.25	−0.18	0.43
	A (L/g)	0.25	−7.71	31.94	0.13	−3.57	36.07
	R2	0.68			0.26
	red.χ2	136.10			885.41
Dubinin–Radushkevich	qm (mg/g)	47.04	36.90	57.18	58.2	57.41	58.98
	K (mol2 kJ−2)	1.98 × 10−4	−2.18 × 10−4	6.14 × 10−4	3.21 × 10−4	2.92 × 10−4	3.5 × 10−4
	R2	0.94			0.86
	red.χ2	24.59			35.23

while graphical representations are given in Supplementary Materials (Figure S3b).

In Table 1, the parameters used for the isotherm models are as follows: q_m (mg/g) is the maximum adsorption capacity, b (L/mg) is the Langmuir constant related to adsorption affinity, K (mg/g (mg/L)1/n) and n are Freundlich constants indicating adsorption capacity and intensity, B (J/mol) and A (L/g) are Temkin constants related to adsorption heat and binding equilibrium, and K (mol²/kJ²) in the Dubinin–Radushkevich model is associated with the mean free adsorption energy. The quality of the fit for each model was evaluated using the coefficient of determination (R²) and the reduced chi-square (χ²) values. Confidence intervals for the fitted parameters were also calculated (CI limits), providing additional insight into the reliability of the estimated values.

The adsorption equilibrium data for both dyes were found to fit well to the Langmuir, Freundlich, and Langmuir–Freundlich isotherm model, as indicated by high correlation coefficients (R²) and relatively low reduced chi-square (red.χ²) values. In contrast, the Temkin and Dubinin–Radushkevich models showed relatively poor fitting accuracy, with higher error values and lower correlation coefficients, indicating their limited applicability for these systems.

For AB9, the adsorption equilibrium data were best described by the Langmuir–Freundlich (R² = 0.99, red.χ² = 1.75), with all fitted parameters precisely determined within narrow confidence intervals, suggesting a system that exhibits characteristics of both homogeneous and slightly heterogeneous adsorption surfaces [45]. The heterogeneity index n was close to 1 (n = 1.01), indicating minimal surface heterogeneity and adsorption behavior similar to the Langmuir model. The Freundlich model also fit well (R² = 0.98, red.χ² = 7.60), with an exponent n > 1, confirming favorable adsorption affinity. Although the Langmuir model showed a slightly lower correlation (R² = 0.97, red.χ² = 18.45), the positive value of the Langmuir constant (b > 0) further supports the favorable nature of AB9 adsorption onto the activated carbon. It should be noted that the q_m value predicted by the Langmuir–Freundlich model (75.97 mg/g) was noticeably higher than the experimental maximum adsorption capacity (q_exp ≈ 52 mg/g), indicating that the model may slightly overestimate the adsorption capacity under the tested conditions. This discrepancy is likely due to extrapolation beyond the experimental range and is a known limitation when applying the Langmuir–Freundlich model with n values close to 1 [45]. Additionally, the adsorption capacity (q_m = 54.75 mg/g) obtained from the Langmuir model aligns well with the experimental maximum adsorption capacity (q_exp ≈ 52 mg/g), and there is good agreement between the model and experimental data.

In the case of AY23, the Langmuir model shows a high correlation coefficient (R² = 0.98, red.χ² = 11.01); however, the corresponding maximum adsorption capacity (q_max = −106.3 mg/g) and affinity constant (b = −8.82 L/mg) were both negative and physically implausible. These anomalous values indicate that the Langmuir model assumptions, monolayer adsorption on a homogeneous surface with finite and identical sites, do not hold for this system. The Langmuir–Freundlich model also produced a strong statistical fit (R² = 0.98, red.χ² = 12.18), but the estimated q_m exceeded 31,000 mg/g, which is several orders of magnitude higher than the experimentally observed uptake. This extreme value, together with the very wide confidence intervals for the fitted parameters, suggests either overfitting or extrapolation artifacts and reflects the model’s limitations when applied to complex adsorption systems involving multilayer formation or aggregation. The Freundlich model, characterized by its empirical nature, provided both a good fit to the experimental data (R² = 0.98, red.χ² = 12.05) and a physically reasonable interpretation of the system, with its parameters determined with narrower CIs and comparatively higher precision than those of the other models. The Freundlich exponent n was found to be 0.81, indicating non-favorable and potentially irreversible adsorption [44]. Such behavior is often attributed to strong interactions between the dye molecules and the adsorbent surface, consistent with heterogeneity and possibly multilayer adsorption phenomena.

Both dyes are adsorbed through complex mechanisms that primarily involve physisorption, with contributions from chemisorption, as indicated by the isotherm models. However, AB9 appears to follow relatively simpler adsorption mechanisms, characterized by predominantly monolayer coverage on a fairly homogeneous surface. In contrast, AY23 exhibits more complex adsorption behavior, including multilayer adsorption and surface heterogeneity, suggesting that desorption and the subsequent regeneration of the adsorbent may be more challenging.

3.4. FTIR Analysis of Dye-AC Interactions

FTIR spectroscopy was used to investigate the interactions between the dyes and AC by comparing spectra recorded before and after adsorption (Figure 3). The lack of new absorption bands after dye adsorption indicates that no covalent bonding or chemical modification of the AC surface occurred. However, minor broadening and shifts in the aromatic C=C stretching vibration around 1600 cm⁻¹ were observed following dye adsorption for both AB9 and AY23, suggesting π–π stacking interactions between the conjugated systems of the dyes and the carbon. Additionally, a slight shift in the peak around 1250 cm⁻¹ indicates possible interactions between the polar functional groups of dyes and the oxygen-containing groups on the carbon surface, such as hydrogen bonding or electrostatic interactions. A scheme of the potential interactions between AC and dyes is presented in Figure 4.

Although minor, these spectral changes provide strong evidence that non-covalent interactions dominate the adsorption mechanism. Specifically, the data support that adsorption is mainly governed by physisorption, including van der Waals forces and hydrophobic interactions, with minimal chemisorptive contribution. This interpretation aligns with the initially observed limited surface functionalization of the AC and is consistent with adsorption isotherm modeling results.

3.5. AC Regeneration

3.5.1. Screening Study

The regeneration of dye-saturated AC was investigated using 20 wt% aqueous solutions of ILs with different chemical structures, as well as conventional solvents including acetone, ethanol, and water, to evaluate their effectiveness in regenerating spent AC. Figure 5 presents the regeneration efficiency values obtained for all tested solvents at 25 °C. Consistent with their differing adsorption affinities, AB9-AC exhibited significantly higher regeneration efficiencies compared to AY23-AC. Regeneration of AB9-AC reached up to 100 ± 0.7%, whereas the maximum for AY23-AC was approximately 70.9 ± 0.6%. Moreover, ILs demonstrated superior regeneration performance compared to conventional solvents, which exhibited significantly lower efficiencies. Among them, acetone achieved a maximum regeneration of around 9%, while ethanol and water were completely ineffective in regenerating the AC for both dyes.

Although ILs proved to be more effective regenerating agents than the tested conventional solvents, notable differences in their performance were observed. Several ILs exhibited no regeneration ability and were thus considered completely ineffective. Among those that demonstrated measurable regeneration efficiency, the performance for AB9-AC decreased in the following order: [bmim][Sal] > [TBP][Sal] > [Ch][Sal] > [TBP][Cl] > [bmim][HSO₄] > [TBP][HSO₄]. In the case of AY23-AC, a slightly different trend was observed: [TBP][Sal] > [bmim][Sal] > [Ch][Sal].

The type of IL’s anion and cation was found to play a crucial role in the regeneration efficiency. Salicylate-based ILs as a group showed superior performance compared to their Cl⁻ and HSO₄⁻ counterparts, indicating that the presence of an aromatic ring in the salicylate anion may play a key role in the desorption process. A potentially dominant interaction mechanism could be π-π stacking [46], as both dyes contain aromatic rings in their structure, which can interact with the aromatic ring in the salicylate anion. In addition to the anion effect, the influence of the IL cation also proved to be significant, as evidenced by differences in regeneration efficiency among ILs sharing the same anion but differing in their cationic components. Comparison among salicylate-based ILs revealed the following trend in regeneration efficiency: [TBP][Sal]~[bmim][Sal] > [Ch][Sal], regardless of the dye adsorbed. ILs with butyl groups in the cation, such as [TBP]⁺ and [bmim]⁺, proved to be the most efficient, suggesting the correlation between hydrophobicity of ILs and desorption efficiency. The enhanced hydrophobicity is primarily attributed to the presence of bulky butyl chains [47]. In contrast, cholinium salicylate was significantly less effective, likely due to its more hydrophilic nature arising from hydroxyl-containing side chains around the nitrogen atom [48]. The cations mentioned, when paired with other anionic groups, were not as effective in regeneration; therefore, the anion’s influence was observed to be more significant than the cation’s.

The influence of Kamlet–Taft parameters helps explain the observed differences in regeneration efficiencies of AB9-AC and AY23-AC. α, reflecting hydrogen bond donating ability, is mainly determined by the cation of the IL and is higher for imidazolium compared to phosphonium ILs [49], making [bmim][Sal] a stronger donor. This favors AB9, which has only hydrogen bond acceptor sites, and explains the superior performance of [bmim][Sal] compared to [TBP][Sal]. For the AY23, which has both donor and acceptor sites, a balance between α and β appears important. In this case, the relatively higher β values of [TBP]⁺ compared to [Ch]⁺ and imidazolium-based ILs [50] enhance its hydrogen bond accepting ability, allowing AY23 to interact more effectively through its donor sites, which likely contributes to the better regeneration observed with [TBP][Sal].

The tested IL solutions span a broad pH range, from 0.45 to 8.78 (Figure S4a in SM), enabling a comprehensive evaluation of pH influence on dye desorption and AC regeneration. As expected, the highest regeneration efficiencies were generally observed in basic media, which aligns with previous studies highlighting the importance of alkaline conditions in enhancing desorption of anionic dyes [15,20]. This effect is primarily due to electrostatic repulsion between the negatively charged adsorbent surface and the dye molecules. In our case, the AC had a pH_pzc of 7.33, meaning that at pH values above this, the carbon surface carries a negative charge. Since the dyes remain anionic throughout the entire pH range [51] with varying degrees of negative charge, this results in stronger electrostatic repulsion in basic conditions, facilitating more efficient dye desorption during regeneration. However, certain salicylate-based ILs demonstrated high regeneration efficiency even under acidic conditions. Notably, [bmim][Sal], with a pH of 4.36, achieved complete (100.0 ± 0.7%) regeneration of AB9-AC and significant regeneration efficiency (60.5 ± 0.6%) for AY23-AC. These findings clearly indicate that while pH plays an important role, it is not the dominant factor governing regeneration performance; rather, specific interactions between the ILs and dye molecules are.

Taking into account the regeneration results obtained using different ILs, [bmim][Sal] and [TBP][Sal] emerged as the most effective candidates. However, [TBP][Sal] demonstrated consistently high performance for both dyes tested, making it a more versatile option. In addition, [TBP][Sal] was previously reported as low-toxic in our earlier study [42], and its recovery through ABS is facilitated by the lower amount of salt required to induce phase separation compared to [bmim][Sal]. Furthermore, its unique thermoresponsive behavior provides additional opportunities for process control and fine-tuning. Considering these combined advantages, [TBP][Sal] was selected for subsequent optimization experiments.

3.5.2. Optimization Study

The desorption of both dyes and regeneration of AC was optimized employing Design Expert software (version 13) and optimal design. Investigated factors included [TBP][Sal] mass percentage, temperature, time, and solid-to-liquid (S/L) ratio. The concentration range of the IL (5%, 12.5%, and 20%) was selected to ensure minimal usage. Temperatures (15, 20, and 25 °C) were chosen within a range that preserves the solubility of the IL in water, considering its thermoresponsive nature [52]. Volume of solvent (ml of solution/mg of AC) was varied within the range of 0.5, 1, and 1.5. Therefore, a total of 25 experimental runs (Table S2a in SM) were conducted for each dye, and the obtained data were analyzed using response surface methodology (RSM).

The optimization of desorption and AC regeneration was carried out separately for AB9-AC and AY23-AC, with both processes evaluated using Design-Expert software. For AB9-AC, the software suggested a quadratic model, while a reduced two-factor interaction (2FI) model was proposed for AY23-AC. In both cases, ANOVA confirmed the statistical significance of the models (for AC with AB9: F-value = 9.22, p < 0.0001; for AC with AY23: F-value = 16.31, p < 0.0001), indicating that the results were not due to random variation (Table S2b,c). In combination with ANOVA, Pareto analysis was performed to highlight the relative contributions of each factor to desorption efficiency, identifying the most influential parameters for process optimization. The models demonstrated good overall fit, with R² values of 0.8218 and 0.8446 for AB9-AC and AY23-AC, respectively, and acceptable predicted R² values (0.5173 and 0.6327, respectively), suggesting moderate but reliable predictive power. Adequate precision values (11.81 and 16.17, respectively) confirmed the models’ robustness and signal-to-noise ratios appropriate for navigating the design space.

Diagnostic plots—including normal probability of residuals, residuals vs. predicted values (Figure S5a,b in SM), and Cook’s distance—showed all data points within an acceptable range, while Box–Cox transformation confirmed no transformation was necessary (λ = 1).

Statistical analysis identified IL concentration as a key factor in both systems. For AB9-AC, significant effects also resulted from interactions between IL concentration and temperature (IL, T), IL concentration and time (IL, t), and temperature and S/L ratio (t, S/L). In the case of AY23-AC, the most influential factors besides IL concentration were its interaction with regeneration time (IL, t), the S/L ratio and its interaction with temperature (T, S/L). The response surface plots illustrating the effects of key variables are presented in Figure 6 and Figure 7 for AB9-AC and AY23-AC, respectively, while the regression equations derived from the response surface methodology are represented as follows:

RE_AB9-AC = 176.31 − 6.05IL − 2.91T − 0.25t − 34.10S/L + 0.13(IL, T) + 0.025(IL, t) + 1.53(T, S/L) + 0.09IL²

RE_AY23-AC = 75.91 − 1.76IL + 1.52T + 1.05t − 52.92S/L + 2.72(IL, S/L) − 0.06(T, S/L)

The optimization analysis determined that the optimal regeneration conditions for AB9-AC involved a 5 wt% IL concentration, a temperature of 23 °C, a regeneration time of ~15 min, and an S/L ratio of ~1.22, under which the model predicted a regeneration efficiency of 95.88%, closely matching the experimentally obtained value of 99%, demonstrating the robustness of the proposed model.

For AY23-AC, optimal regeneration conditions included an IL concentration of 5 wt%, a temperature of 24.59 °C, a regeneration time of 15 min, and an S/L ratio of 0.5. Under the selected conditions, the model predicted a regeneration efficiency of 80.45%, which was in close agreement with the experimentally determined value of 79.97%, confirming the reliability of the proposed model.

This systematic approach enabled the successful regeneration of AC saturated with either dye while ensuring efficient use of IL, moderate energy input, and minimal processing time.

3.6. Regenerated AC’s Adsorbent Performance and Reusability Assessment

3.6.1. Adsorption Using Regenerated AC

To assess the method’s practical applicability and sustainability, reusability of AC was tested over three adsorption–regeneration cycles under the previously determined optimal conditions. Adsorption and regeneration efficiencies obtained in each cycle are presented in Figure 8.

The results demonstrated that the adsorption capacity of the AC was generally preserved and even showed slight improvement in the case of AY23–AC, while the regeneration efficiency remained relatively consistent across all cycles. However, for AB9, the adsorption efficiency decreased from 99.0% in the first cycle to 60.0% and 55.8% in the second and third cycles, respectively, representing a total decline of approximately 40%. In contrast, regeneration efficiency remained stable, ranging from 99.9% in the first cycle to 99.8% and 99.9% in subsequent cycles.

For AY23, the adsorption efficiency slightly increased, from 80.0% in the first cycle to 86.2% in the second and 84.1% in the third cycle, while the regeneration efficiency improved from 80.0% to 90.1% and remained at that level in the third cycle.

Considering the differences in the polarity of the two dyes (logK_o/w(AB9) = 0.287; logK_o/w(AY23) = −2.327 [51]), it is plausible that the surface properties of the AC undergo subtle changes during regeneration due to repeated exposure to IL, potentially shifting in a manner that enhances its affinity toward more hydrophilic molecules. This hypothesis is further supported by FTIR analysis of the regenerated AC (Figure 9), which revealed the appearance of new absorption bands that were absent in the original material. Specifically, the band at 1572 cm⁻¹ can be assigned to aromatic C=C and conjugated C=O stretching from the salicylate anion of the IL, the bands at 1473 and 1436 cm⁻¹ can be assigned to CH₂/CH₃ bending of aliphatic chains from the [TBP] cation, and the band at 1369 cm⁻¹ can be associated with C–H bending or C–O stretching, likely from the salicylate anion [40]. Moreover, in AC previously saturated with AB9, two additional bands at 1123 and 1083 cm⁻¹ were detected, likely corresponding to C–O or P–O stretching vibrations introduced by the IL during regeneration [53]. These spectral modifications indicate that the IL interacts with the AC surface, subtly altering its surface polarity. Such changes can, in turn, slightly modify the initial adsorption properties of the material, potentially affecting its affinity toward molecules of different polarities.

3.6.2. Preliminary Assessment of Component Recovery via Aqueous Biphasic Systems

Given the demonstrated stability of the adsorption–regeneration process across multiple cycles, the next step toward developing a fully integrated and sustainable system involves the recovery and reuse of all components employed during treatment.

To evaluate the potential for post-regeneration component recovery and enable the development of a closed-loop process, a preliminary attempt was made to form an aqueous biphasic system (ABS) using the solution collected after the optimized regeneration of spent AC. Sodium citrate, a biocompatible salting-out agent, was added to induce ABS formation with final concentrations of 10 and 20 wt% in the system. In both cases, the formation of an IL-rich phase confirmed the effective preservation of [TBP][Sal], with no significant loss due to possible adsorption onto the AC (Figure 8). The final ABS compositions were approximately 5 wt% [TBP][Sal] + 10 wt% salt + 85 wt% H₂O and 5 wt% [TBP][Sal] + 20 wt% salt + 70 wt% H₂O. The formation of two phases under these conditions using [TBP][Sal] and citrate salt, along with the approximate compositions of the resulting phases, has been previously described in the literature [54].

Dye recovery into the IL-rich phase was notable, with 39.5% for AY23 and 90.0% for AB9 in the system with 10 wt% of salt, increasing to 80.52% and 99.37%, respectively, for the system with 20 wt% of the salt (Figure 10).

These results indicate that such ABS could be used to concentrate both the dye and IL and can be further optimized by adjusting the system composition, temperature, or other parameters [55]. Further dye recovery from the IL-rich phase potentially could be achieved through methods such as antisolvent addition, temperature-induced precipitation, or membrane separation [56]. Notably, [TBP][Sal] exhibits LCST-type thermoresponsive behavior [57], allowing potential temperature-controlled recovery. In this way, the dye can be effectively isolated, allowing the IL to be reused in subsequent cycles, while the salt can also be recovered by water evaporation from the salt-rich phase of ABS. The integration of this step highlights a promising route toward a closed-loop regeneration process, representing a valuable path for further research. Moreover, given the tunable and designer nature of ILs, which can be synthesized with specific properties to interact preferentially with targeted pollutants, this approach could be extended to a broader range of contaminants. Furthermore, a wide variety of ABS has already been reported in the literature, demonstrating the separation and concentration of diverse contaminants such as dyes, pesticides, and metals [28]. These observations suggest that the proposed strategy may be applicable to more complex adsorption systems. A schematic representation of the proposed integrated process is provided in Figure 11.

4. Conclusions

This work demonstrates ILs as a highly effective and sustainable alternative for the regeneration of dye-saturated AC. The screening phase of the investigation revealed that both dye structure and IL composition significantly influence regeneration efficiency, with the anion exerting the most dominant influence. The optimized regeneration conditions (5 wt% IL, t = 15 min, T = 23 °C S/L = 1.22 for AB9-AC and 5 wt% IL, t = 15 min, T = 25 °C S/L = 0.5 for AY23-AC) using [TBP][Sal] achieved high recovery yields (99 and 80% for AB9-AC and AY23-AC, respectively), while sufficiently maintaining adsorbent reusability across three cycles, alongside consistently high regeneration efficiency in each cycle (~100% for AB9-AC and ~80% for AY23-AC). Furthermore, the proposed integration of aqueous biphasic systems for dye and IL concentration achieved maximum extraction efficiencies of up to 99.37% for AB9 and 80.52% for AY23 into the IL-rich phase. This study thus pioneers an IL-based, near-zero-waste strategy for AC regeneration, with implications for circular-economy processes in environmental remediation.