1. Introduction
Lignocellulosic biomass is regarded as a promising alternative feedstock for renewable transportation biofuels and bio-based chemicals [
1,
2]. Depolymerizing cellulose and hemicellulose in a lignocellulosic biorefinery yield hexose (C6-glucose, fructose) and pentose units (C5-xylose). These monosaccharides can be further converted into bio-chemicals and biofuels [
3,
4,
5,
6,
7]. This process involves the formation of significant amounts of a black and uncontrollable material known as humin. Humin is a carbonaceous, heterogeneous, and polydisperse macromolecule [
8]. Several studies have identified humins as diverse polymers consisting of furan rings connected by aliphatic carbon bonds and various oxygen-containing groups. These humins are categorized as furanyl polymers, resulting from the polymerization of sugar, HMF (hydroxymethylfurfural), or FF (furfuryl alcohol), along with active intermediate compounds [
8,
9,
10,
11]. The yield of humin is heavily influenced by feedstock and process parameters such as reaction medium, temperature, reaction time, pH, etc. In the aqueous phase, humin selectivity can reach 50% on a carbon basis. Recently, in the bio-refining process using alkyl-phenol as the organic solvent, humin synthesis has been shown to reach 25–45 wt%. Consequently, the formation of humin reduces the yield of other valuable products such as 5-HMF, FF, levulinic acid (LA), etc. Therefore, it is crucial to valorize the byproduct humin to ensure the economic and environmental viability of the entire biomass conversion process [
1,
3,
4].
Despite humin being a known substance for an extended period, its primary applications have remained confined to energy and heat applications. However, the escalating production of furans platform chemicals has sparked a surge of interest in exploring additional value-added applications for humin beyond combustion [
1]. These applications encompass its potential as a carbonaceous source for gas synthesis [
12], its liquefaction into alkyl phenolics and higher oligomers using a mixture of formic acid/2-propanol with supported ruthenium catalysts [
13], its combination with biomass-derived humin and poly-furfuryl alcohol (PFA) for composite elaboration [
14], its enhancement of the modulus and tensile strength of pure PFA resins [
15], and the synthesis of humin-based iron oxide catalytic nanocomposites etc. [
16]. Moreover, humin extracted from soil or bio-refinery processes has been effectively utilized as an adsorbent to remove heavy metals such as Cd, Cr, Pb, and Al from aqueous media [
17,
18,
19,
20,
21].
Recent developments in unconventional solvents led to deep eutectic solvents (DES) formed by combining a hydrogen-bond donor (HBD) with a hydrogen-bond acceptor (HBA) [
22,
23]. DESs consist of safe, affordable, and biodegradable components such as choline chloride (ChCl), carbohydrates, carboxylic acids, and glycerol [
22,
24]. These DES mixtures have lower melting points than individual components [
25,
26]. DESs share physicochemical traits with ionic liquids (ILs), being non-flammable, low in volatility, and suitable for long-term recycling [
24]. Past experiments aimed at creating glucose-based deep eutectic solvents (DES) using ChCl and the monosaccharide sugar D-glucose anhydrous. Analysis of their physical properties indicated the potential for various industrial applications, including mediums for chemical reactions [
27].
Considerable amounts of organic dyes find applications in industries such as paper, apparel, textiles, dyestuffs, leather, plastics, etc., leading to health problems for humans and animals, along with environmental pollution. These dyes tend to absorb and reflect sunlight, reducing sunlight penetration into water bodies, resulting in reduced algae activity and dissolved oxygen levels [
28,
29,
30,
31]. Among these dyes, Methylene Blue (MB) stands out as a highly consumed cationic dye utilized in biological, chemical, and medical applications [
21]. MB is an aromatic heterocyclic basic dye with a molecular weight of 319.85 g mol
−1 and a λ
max of 664 nm [
32,
33,
34], being highly water-soluble and stable in solution at room temperature [
34]. According to the International Union of Pure and Applied Chemistry (IUPAC), the chemical name of MB is [3,7-bis(dimethylamino) phenothiazine chloride tetramethylthionine chloride], and its color index (CI) is 52,015 [
35,
36]. It exhibits a deep blue color when oxidized and becomes colorless when reduced [
37]. However, MB is toxic, non-biodegradable, and carcinogenic, posing risks to human health and the environment [
38,
39]. Another dye, Methyl Orange (MO), has a molecular weight of 327.33 g mol
−1 and a λ
max of 465 nm. Its IUPAC name is sodium 4-[(4-dimethylamino) phenyldiazenyl] benzenesulfonate. MO is an anionic azo dye that is water-soluble, non-biodegradable, toxic, and considered carcinogenic [
40,
41].
Biodegradable dyes are a category of dyes that can be broken down naturally by microorganisms into simpler, non-toxic substances over time [
42]. Unlike conventional synthetic dyes, which are typically derived from petrochemicals and pose significant environmental concerns due to their non-biodegradable nature and potential toxicity, biodegradable dyes offer a more sustainable and eco-friendlier alternative [
43]. Additionally, advancements in biotechnology have enabled the synthesis of biodegradable dyes through environmentally benign methods, reducing the need for harmful chemicals in their creation [
44,
45]. For example, Lin et al. studied sustainable wool yarn dyeing using blends of madder red (MR), gardenia blue (GB), and gardenia yellow (GY) dyes to create diverse color shades (color triangle) at different dye mass ratios, eliminating the need for mordants (metallic salts) [
46].
Promising technologies have been researched to eliminate synthetic and non-biodegradable dyes from the environment. Among these, adsorption stands out due to its simple design, ease of use, and cost-effectiveness for reusability. Yet, few studies have examined the use of soil-extracted humin as an economical adsorbent for removing dyes from water [
29,
47,
48]. Furthermore, to the best of our knowledge, there is no previous evidence of utilizing glucose-derived humin (GDH), a byproduct from bio-refinery processes, for dye adsorption. GDH, possessing a polymeric furanic-type structure, was synthesized through the reaction of D-glucose with an allylamine catalyst in a DES medium, followed by a carbonization step. Subsequently, its efficacy in adsorbing organic MB dye was tested. The adsorption process was assessed concerning various factors, such as pH, temperature, contact time, initial dye concentrations, adsorbent weight, and comparison with anionic dye MO. Furthermore, isotherm models were employed to understand the adsorption behavior, while reaction kinetics and thermodynamics were also investigated. To optimize the reaction parameters, response surface methodology was employed.
2. Materials and Methods
2.1. Materials
Allylamine (C3H7N, 98%) and choline chloride were [(CH3)3NCH2CH2OH]+Cl− purchased from Alfa Aesar (Heysham, England). D-glucose (C6H12O6, 99.5%), methylene blue (C16H18N3ClS, 95%), and methyl orange (C14H14N3NaO3S, 85%), methanol (CH3OH, 99.9%) were purchased from Sigma-Aldrich (Burghausen, Germany). All chemicals used in this study were of analytical grade and used without further purification. All the solutions were made with high-purity water with 18 MΩ×cm resistance.
2.2. Synthesis and Collection of GDH Byproduct
To prepare GDH, the following procedure was employed: Choline chloride (ChCl), D-glucose, and deionized H2O were mixed in a 1:1:1 (w%) ratio in a round-bottom flask. An allylamine (AA) catalyst was added to D-glucose in a 5:1 (w%) ratio. The flask was placed in an oil bath, and reflux instrumentation was set up at 393 K (120 °C) with a stirring speed of 350 rpm for 12 h. After cooling to room temperature, the black-colored precipitate was separated from the medium, washed thoroughly with 2 L of DI water, and centrifuged at 10,000 rpm for 10 min to collect water-insoluble GDH. The collected GDH was dried at 378 K (105 °C) overnight and then ground into a powder. Subsequently, the pristine GDH was carbonized by heating it at 773 K (500 °C) in an oven for 2 h.
For studying the effect of different synthesis temperatures on pristine GDH’s surface area, pore size, and pore volume while keeping other parameters constant, GDH was synthesized at 353 K (80 °C), 373 K (100 °C), 393 K (120 °C), 413 K (140 °C), and 433 K (160 °C). The analysis was performed using the ASAP 2020 Plus instrument ASAP 2020 Plus instrument (Micromeritics Instrument Corporation, 4356 Communi-cations Drive Norcross, GA 30093, USA).
2.3. Characterization of GDH
The BET surface area and porous volume of the synthesized GDH were assessed using an ASAP 2020 Plus instrument (Micromeritics Instrument Corporation, 4356 Communications Drive, Norcross, GA 30093, USA). Nitrogen adsorption and desorption isotherms were measured at 77 K (350 °C) after degassing the GDH samples in a vacuum at 373 K (100 °C) for 12 h. To examine the GDH’s structure, infrared spectra were obtained using a Thermo Nicolet Is5 Fourier-transform infrared (FT-IR) spectrometer (Thermo Fisher Scientific, 168 Third Avenue, Waltham, MA USA 02451). The absorbance was measured with a resolution of 0.9 cm−1, and the FT-IR wavenumber ranged from 400 to 4000 cm−1. For material structure determination, powder X-ray diffraction (PXRD) measurements were conducted at room temperature using a Bruker D8 instrument; ADVANCE-XRD (Blue Scientific Limited, St. John’s Innovation Centre, Cowley Road, Cambridge, CB4 0WS). Additionally, the morphological features of the synthesized GDH were analyzed using a Schottky Field Emission Scanning Electron Microscope (SEM) SU5000 (Sukehiro Ito, Science & Medical Systems Design Division, Hitachi High Technologies Corporation, Tokyo, Japan).
2.4. Sample Reactor for Dye Adsorption and Analysis
The experiments were carried out using the PCX-50B Discover Multichannel Photochemical Reaction System (purchased from A08, 11/F, Changyin building, No. 88, Yongding Road, Haidian District, Beijing, China). The stirring speed was set at 300 rpm, and no light was applied, while the temperature-control system in the machine ensured that temperature variations did not impact the experimental outcomes. The typical experiments were conducted at 298 K (25 °C).
To quantitatively analyze the dyes, a UV-visible spectrophotometer (Hitachi U-2900/U-2910 UV-Vis Double Beam Spectrophotometer, Hitachi High Technologies America, Inc.) with a 10 × 10 mm cuvette holder and a 10 mm path length was used. The samples for analysis were diluted 300 times, and DI water served as the blank sample. The spectrophotometer scanned within a wavelength range of 200–800 nm. Calibration curves for the UV-visible spectrophotometer were generated using a series of standard dye solutions due to the ring structure and color of the dyes.
2.5. Use GDH as a Dye Adsorbent
To assess the removal efficiency of MB dye using carbonized GDH, a standard experiment was conducted. In this experiment, 0.1 g of GDH was introduced into a glass bottle containing a 25 ppm MB dye solution (initial concentration) and stirred at 300 rpm at room temperature for a duration of 10 h. Afterward, the samples were subjected to centrifugation to separate the supernatant. A UV-visible spectrometric analysis was then carried out to measure the remaining MB dye concentrations following the adsorption process. The following equations [Equations (1) and (2)] were used to calculate the adsorption capacity and removal efficiencies of the GDH adsorbent for MB dye,
where Q
e (mg/g) = equilibrium adsorption capacity of the MB dye onto GDH adsorbent, C
o (mg/L) = initial concentration of aqueous MB dye solution, C
e (mg/L) = concentration of the aqueous MB dye solution after adsorption, V (L) = volume of the aqueous MB dye solution, and W (g) = mass of the GDH adsorbent [
49,
50,
51,
52].
2.6. Effect of Parameters on Dye Adsorption
Initially, MB dye adsorption experiments were conducted using both pristine GDH and carbonized GDH to compare their dye removal efficiencies. Subsequent experiments focused solely on carbonized GDH. Various adsorbent weights (ranging from 0.025 to 0.150 g) and initial concentrations of MB dye (ranging from 5 ppm to 50 ppm-5, 15, 25, 35, and 50 ppm) were utilized to identify the optimized GDH weight and initial concentration of the adsorbate, respectively.
To explore the impact of medium acidity, a series of 10 mL, 25 ppm MB aqueous solutions were prepared at pH levels of 1.00, 2.00, 4.00, 6.00, 8.00, and 10.00 using HCl and NaOH for pH adjustments. Full wavelength scan spectra were obtained using the UV-visible spectrophotometer for each MB dye solution at the specified pH ranges to determine the λ
max of MB dye before analyzing the remaining MB concentrations after the adsorption experiment. In each glass bottle, 0.1 g of GDH was added, and the dye adsorption conditions and analysis methods described in
Section 2.5 were followed. Each sample was accompanied by a blank solution without a sorbent, and both were treated and analyzed in the same manner. Additionally, the same experimental procedure was conducted for MO dye.
2.7. Adsorption Kinetics and Thermodynamics
The adsorption control mechanism and potential rate-controlling steps of MB dye on GDH were assessed using two kinetic models: the pseudo-first order and the pseudo-second order models. The linear forms of the equations can be represented as Equations (3) and (4), respectively,
where Q
t (mg/g) was the amount of adsorbed dye at adsorption time t (min), k
1 (min
−1) and k
2 (g/mg.min) were the rate constants of the pseudo-first-order and the pseudo-second-order, respectively [
53]. The activation energy for dye adsorption onto the GDH was calculated by using the Arrhenius equation, which is indicated as Equation (5) [
49,
54].
The above equation can be linearized by taking logarithms as indicated in Equation (6),
where k
o (g/mg.min) is the frequency factor, R (8.314 J·K
−1·mol
−1) is the universal gas constant, E
a (kJ mol
−1) is the activation energy of the adsorption, and T (K) is the absolute temperature [
51,
54]. Adsorption experiments were conducted at 298, 308, 318, 328, and 338 K to determine the effect of temperature.
The thermodynamic parameters concerning the adsorption of MB dye, which include the standard free energy change (ΔG°), standard enthalpy change (ΔH°), and standard entropy change (ΔS°), were computed using the following method. Equation (7) provides the Gibbs free energy changes of the adsorption process, which are linked to the equilibrium constant [
53].
K
c can be calculated using Equation (8).
The values of ΔH° and ΔS° were obtained by analyzing the slope and intercept of the linear Van’t Hoff plot (Equation (9)).
where K
c is the equilibrium constant (also called adsorption distribution coefficient), C
Ae (mmol) is the amount of adsorbate adsorbed at equilibrium, and C
e is the equilibrium concentration (mmol L
−1) of MB dye in the solution. Different initial concentrations of MB dye solutions were adsorbed by GDH at 3 different temperatures (298, 318, and 338 K) while keeping other parameters constant to draw the plot [ln (C
Ae/C
e) versus C
e] to estimate K
c. From the slope, K
c can be determined [K = e
(slope), where “e” is the mathematical constant approximately equal to 2.718]. The values of ΔH° and ΔS° for adsorption are assumed to be temperature independent and can be calculated from the slope and intercept, respectively, of the plots of lnK
c against 1/T [
50,
53,
55].
2.8. Adsorption Isotherm Models
The interaction between adsorbate molecules and the adsorbent surface was analyzed using two established models, namely the Freundlich and Langmuir isotherms. Experiments were conducted with different concentrations of MB dyes (5, 10, 20, 30, and 50 ppm). The Langmuir isotherm model and its linearized form were represented by Equations (10) and (11), respectively [
49,
56].
where Q
max (mmol g
−1) was the maximum adsorption capacity of dye, and K
L (g mmol
−1), was the Langmuir constant.
Equations (12) and (13) indicate the Freundlich isotherm model and its logarithmic form, respectively,
where K
F (mmol g
−1) was an indicative constant related to the adsorption capacity of the adsorbent, and 1/n (0~1) was the adsorption intensity or surface heterogeneity of the adsorbent (GDH) [
56].
The adsorbent’s appropriateness for the dye was assessed by means of the separation factor constant (R
L), derived from the equation Equation (14) as follows. Here, K
L represents the Langmuir equilibrium constant (expressed in I/mmol). A value of R
L greater than 1.0 indicates unsuitability, R
L equal to 1 indicates a linear relationship, an R
L value between 0 and 1 suggests suitability, while R
L equal to 0 signifies irreversibility [
50,
52].
2.9. Response Surface Methodology
Response surface methodology (RSM) is a technique that establishes a regression model and leverages quantitative data obtained from designed experiments. It is an empirical statistical approach aimed at identifying the most favorable combination of process operational variables. By employing a statistically based experimental design for an adsorption process, RSM can reduce process variability, experimentation time, and costs, all while improving process efficiency. The RSM methodology has found extensive application in chemical engineering and the optimization of sorption processes [
57,
58].
In this experimental section, we employed the 3-level, 3-factor Box–Behnken design (BBD) to ascertain and validate the parameters affecting the efficiencies of MB dye removal. These parameters, referred to as factors, included time (minutes) (A), initial MB dye concentration (ppm) (B), and GDH weight (g) (C), while keeping other input parameters such as the initial pH of the medium, sample temperature (K), and agitation speed (rpm) constant. The response variable (Y) measured in this study was the MB dye removal rate. The three levels of each factor were coded as −1 (low), 0 (central point), and 1 (high). For a clear representation of the variables and their respective levels, please refer to
Table 1, which illustrates the BBD model’s setup. To determine the total number of experimental runs required for this design, the following Equation (15) can be used,
where N is the total number of experimental runs, k is the number of independent variables, and C
o is the number of central points [
59]. In this research endeavor, a total of 18 experiments were conducted to optimize the impact of three key independent parameters on the efficiencies of MB removal. The experimental error was evaluated using the center points. Prior to conducting the experiments, these parameters and their corresponding ranges were carefully chosen based on insights from previous investigations and pilot studies. For statistical analysis, the Design-Expert software (version 13.0.5.0, Stat-Ease, Inc., Minneapolis, MN, USA) was employed. The obtained results were analyzed using the coefficient of determination (R
2), Pareto analysis of variance (ANOVA), as well as statistical and response plots. These analytical tools allowed for a comprehensive examination of the data and the extraction of meaningful insights from the experimental outcomes [
59,
60,
61].
2.10. Regeneration and Reuse
After MB dye adsorption, the spent GDH was collected using centrifugation at 10,000 rpm for 10 min. Next, 0.5 g of GDH was placed into a 50 mL centrifuge tube, and 40 mL of deionized water (DI water) was added to it. The mixture was then subjected to shaking using a digital orbital shaker TS-500D (Yude Technology Co., Ltd., Xinbei City 23558, Taiwan) at 110 rpm for 30 min to wash the GDH and remove any unbound dye. After washing, the GDH was collected again using centrifugation. For desorption, the adsorbent was treated with 30 mL of methanol (MeOH-99.9%) and placed in an an ultrasonic bath (Elma-Ultrasonic Cleaners-Elmasonic, P 30 H, Elma Schmidbauer GmbH, Gottlieb-Daimler-Straße 17, 78,224 Singen, Germany) for 30 min at a frequency of 37 kHz, maintaining the temperature between 313 and 323 K (40–50 °C), and applying a nominal power of 320 W. Following desorption, the adsorbent was collected once more through centrifugation. The desorption step with MeOH was repeated 3-5 times until the color of the MeOH solvent became colorless, indicating successful desorption of the dye.
Next, the collected GDH underwent an additional cleaning step with 40 mL of DI water and was collected using centrifugation. Subsequently, the GDH was dried overnight at 378 K (105 °C), and the regenerated adsorbent was used in the dye adsorption process to determine the adsorption efficiencies with each repeated use.
4. Conclusions
The isomerization of D-glucose into D-fructose is a crucial industrial conversion with various applications in the food industry, such as in high fructose corn syrup, and as a key intermediate step in producing platform chemicals such as 5-HMF, FDCA, and LA. However, this process leads to the formation of a significant byproduct called humin. In this context, it would be advantageous to utilize GDH as an economical and environmentally friendly adsorbent to remove organic dyes from aqueous solutions. GDH was obtained through the reaction of D-glucose with an AA catalyst in a DES medium, followed by carbonization at 500 °C for 2 h. Cationic MB dye and anionic MO dye were selected as adsorbates in the aqueous medium. The morphology of pristine GDH was altered after the carbonization step, resulting in increased surface area and pore volume, transforming it into activated carbon. The experimental results revealed that the MB removal efficiency of carbonized GDH was higher compared to pristine GDH. Various factors, including the amount of adsorbent, initial MB concentration, reaction temperature, reaction time, and pH of the medium, also influenced the dye removal efficiency. GDH exhibited better removal efficiency for the cationic MB dye compared to the anionic MO dye. Temperature measurements indicated that the MB dye adsorption process was exothermic. The process followed a pseudo-first-order kinetic model, while the Langmuir isotherm provided a comprehensive explanation of the adsorption behavior. The calculated Ea value suggested that the rate-determining step of adsorption was diffusion-controlled. To optimize the process, response surface methodology and ANOVA approaches were employed. The significant F-value obtained from the ANOVA technique indicated that the model was meaningful, and P-values less than 0.0500 indicated the significance of model terms. Upon implementing the optimal parameters suggested by the BBD model, the experimental MB dye removal by GDH was found to be in excellent agreement with the predicted value. Notably, GDH demonstrated enhanced removal effectiveness even after regeneration for multiple cycles, particularly after the tenth adsorption cycle, affirming its potential as a green adsorbent for cationic dye removal from wastewater. This highlights the economic and environmental feasibility of utilizing GDH in the entire biomass conversion process.