Adsorptive Dephenolization of Aqueous Solutions Using Thermally Modified Corn Cob: Mechanisms,Point of Zero Charge,and Isosteric Heat Studies

Abstract

The sorption mechanisms, point of zero charge, and isosteric heats involved in the adsorptive dephenolization of aqueous solutions using thermally modified corn cob (TMCC) were studied at different initial phenol concentrations (100–500 mg/l), TMCC dosage (0.4–2.0 g), contact time (5–60 min), pH (2–10), and temperature (30–60°C). Analysis of the adsorbent material showed that it possessed the properties typical of a good adsorbent. The adsorption experiments revealed that phenol uptake is favored by an increase in TMCC dosage and contact time and a decrease in temperature and concentration of phenol in the solution. The experimental data were well-fitted to the Sips, Langmuir, Toth, and Redlich–Peterson isotherm models. Thermodynamic studies suggested that the sorption of phenol onto TMCC is feasible, spontaneous, and endothermic. The isosteric heats of adsorption obtained are in the range 47.43-79.38 kJ/mol, confirming that the adsorption process is predominantly a physical process depicting the van der Waals interactions, and it is inversely proportional to surface loading. The analysis of the adsorption mechanisms showed that the intraparticle, film, and pore diffusion mechanisms were significantly involved in the phenol adsorption process. The involvement of electrostatic attraction, $\pi ‐\pi$ electron-donor interaction, and hydrogen bonding was also demonstrated. The point of zero charge ( $\text{p}{\text{H}}_{\text{pzc}}$ ) was obtained at a pH of 5.83; being slightly lower than the optimum pH of 6 indicates that the sorbent surface is obviously not negatively charged at $\text{p}{\text{H}}_{\text{pzc}}$ . The discoveries of this study have shown that the dephenolization process is feasible, spontaneous, endothermic, dominated by a physical process, and governed by intraparticle, film, and pore diffusion mechanisms.

1. Introduction

The release of phenol-contaminated effluents into aquatic environments calls for serious environmental concern. Phenols are very soluble in water; therefore, they can easily contaminate potable water of natural sources when they come in contact with them, thereby posing a danger to human health. The noxious effects of drinking phenol-contaminated water include sore throat, difficulty in swallowing, fainting, vomiting, headache, and liver and kidney damage as well as other mental illnesses [1–3]. The range of toxicity for both aquatic organisms and humans has been reported as 9-25 mg/l [4, 5]. Thus, the removal of phenols from phenol-contaminated effluents is statutorily obligatory so that their residual concentrations pose no serious environmental threat [6].

The most adapted technique for the decontamination of phenol-contaminated aqueous solutions is adsorption [7–12]. Lower design, development, and operating costs, operating ease, and high pollutant elimination efficiency are top of the reasons for the preference of adsorption over other alternative processes [1, 13–16]. The most widely used adsorbent for the removal of pollutants from wastewater is activated carbon (AC), mostly owing to its strong affinity for wastewater contaminants essentially because of its microporous structure, large surface area, enhanced surface reactivity, etc. [2]. However, the high cost of commercial AC made it obligatory for tailored research on the production of AC from renewable sources such as agro-waste products. Some of the agro-waste products that have been considered for the removal of phenol from aqueous solutions include palm kernel shell [17], onion dry scales [18], rice husk [19], wheat bran [20], and eggshell [21]. The source/type of material used in the production of AC greatly impacts the reactivity of the produced AC and the overall performance of the adsorption process.

Corn cob (CC) is an agro-waste product that is generated in the course of corn processing. In Nigeria, CC is typically considered a useless material because there is no developed use for it. Annually, several million tonnes of corn cobs are disposed of in the environment as waste, posing serious environmental pollution concerns. In 2016/2017, Nigeria produced approximately 10.5 million tonnes of corn [22]. Hence, it is pertinent to develop a research-based utilization channel for this widely available agro-waste product. According to reports, AC produced from CC can effectively be used to remove some wastewater contaminants such as arsenic [23], uranium [24], oil and grease [25], and mercury [26]. The findings of the studies showed that CC meets the criteria of good adsorbent source material, and it is on the heels of this revelation that thermally modified corn cob (TMCC) was considered for the removal of noxious phenol from aqueous solutions in this study.

Until now, the focus of most adsorption studies is on pollutants’ removal efficiency, adsorption kinetics, equilibrium isotherms, and thermodynamics. However, the essential parameters necessary for the development and characterization of sorbents and the optimization of the sorption process are the equilibrium isotherms and the isosteric heat of adsorption [27, 28]. While equilibrium adsorption isotherms have been widely studied, studies of the isosteric heats are scarce in the literature. The isosteric heat of adsorption is defined as the heat of adsorption calculated at a fixed amount of the adsorbed compound [28]. It is an essential design parameter in estimating the performance of a sorption process. Information about adsorbent-adsorbate interaction as well as the surface energetic heterogeneity is also obtained from the isosteric heat study [27]. It tells if the adsorption is dominated by a physical process or a chemical process. The complexity of the sorption process taking place at the liquid-solid interfaces necessitates an in-depth study of the isosteric heats.

Other parameters that are important for a comprehensive analysis of an adsorption process and the adsorbent’s characteristics whose information is not sufficient in literature for specific adsorption processes like that of phenol uptake onto TMCC are the adsorption mechanism and the point of zero charge of the adsorbent ( $\text{p}{\text{H}}_{\text{pzc}}$ ). The study of the adsorption mechanism provides information regarding the sequential steps involved in the removal of pollutants in an adsorption process as well as the rate-determining step. On the other hand, the $\text{p}{\text{H}}_{\text{pzc}}$ of an adsorbent depicts the pH for which its surface charge is zero [29]. The net surface charge of an adsorbent in wastewater solution can be affected by the existence of H⁺ or OH^- in the solution [30]; the analysis of the $\text{p}{\text{H}}_{\text{pzc}}$ helps us to know how it is affected. It also helps to gain insight on the ionization of functional groups and the way they interact with adsorbate species in solution.

To this end, the focus of this work is to study the IHA, adsorption mechanism, and the $\text{p}{\text{H}}_{\text{pzc}}$ of TMCC adsorbent for the uptake of phenol from aqueous solutions. To further obtain insight into the adsorption process and intrinsic characteristics connected to the process, the adsorption equilibrium isotherms, thermodynamics, and adsorbent regeneration and reutilization studies were equally carried out. Most of the available reports on the analysis of adsorption equilibrium isotherms focused on the application of the traditional linear transform technique [3]. Due to the reported shortcomings of the linear transform technique [21, 31], the analysis of adsorption equilibrium isotherms was accomplished in this work following the nonlinear regression technique using the solver add-in function available in the Microsoft Excel software.

2. Materials and Methods

2.1. Materials

The CCs (Figure 1) used for the adsorption process were obtained from a neighborhood maize farm in Awka, Nigeria. The chemical reagents (analytical grade) such as phenol, tetraoxophosphoric acid (H₃PO4), and distilled water used were supplied by a Laboratory Chemical dealer at Bridgehead Market, Onitsha, Nigeria.

Figure 1

Raw corn cob samples: (a) before crushing and grinding and (b) after grinding.

(b)

2.2. Synthesis and Characterization of the Adsorbent

The synthesis and characterization methods of the adsorbent followed a procedure already described in our recent work [2]. Scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) analyses were carried out on the raw and the thermally modified CC samples to gain insight into the samples’ surface morphology and functional groups, respectively. The analysis of the physicochemical properties of the produced adsorbent was also performed following the standard methods of the Association of Official Analytical Chemists [32]. The surface area (m²/g) was determined according to the Brunauer-Emmett-Teller (BET) method as described [2].

2.3. Adsorption Experiments

The efficiency of phenol uptake onto TMCC was carried out using the standard batch adsorption mode. The process parameters were pH (2–10), initial phenol concentration (100–500 mg/l), contact time (3–60 min), TMCC dosage (0.4–2.0 g), and temperature (30–60°C). The contacting of the adsorbate and the adsorbent was realized by agitating the solution from 5–60 min at 200 rpm. Phenol removal (in percentage) was calculated using $\begin{array}{}\text{(1)}& \text{Phenol}\text{removal}\left(\%\right)=\left(\frac{C_0-C_{\text{e}}}{C_o}\right)\times 100,\end{array}$

while the adsorption capacity $\left(q_e\right)$ of phenol by TMCC was estimated according to $\begin{array}{}\text{(2)}& q_e=\frac{\left(C_0-C_e\right)V}{m},\end{array}$

where $C_0$ and $C_e$ (mg/l) are the initial and equilibrium concentrations of phenol in the liquid phase, respectively. The volume of the phenol solution (l) and the mass of TMCC used (g) are depicted by $V$ and $m$ , respectively, and $q_e$ is the adsorption capacity (mg/g). The equations used for the analyses of the experimental data are summarized in Table 1.

Table 1

Equations of the isotherm models, mechanism models, thermodynamics, isosteric heat of adsorption, and error functions [33–43].

	Equations	Plot parameters	Equation no.	Source
Equilibrium isotherm models
Langmuir Toth Redlich–Peterson Sips	$q_e=\frac{q_m{K}_L{C}_e}{1+K_L{C}_e}$ $R_L=\frac{1}{1+K_L{C}_o}$ $q_e=\frac{q_{m{K}_T{C}_e}}{\left[1+{\left.{\left(K_T{C}_e\right)}^n\right]}^{1/n}\right]}$ $q_e=\frac{\text{A}{\text{C}}_e}{1+\text{B}{\text{C}}_e^{\beta }}$ $q_e=\frac{K_s{C}_e^{{\beta }_s}}{1-a_s{C}_e^{{\beta }_s}}$	$q_e$ =adsorption capacity at equilibrium (mg/g) $K_L$ =Langmuir’s constant (l/mg) $q_m$ =maximum adsorption capacity (mg/g) $R_L$ =the separation factor $K_T$ =Toth’s constant (mg/g) $n$ =Toth’s isotherm exponent (mg/g) $A$ =Redlich–Peterson’s constant (l/g) $B$ =constant (l/mg) β=exponent $K_s$ =Sips’ constant (l/g) $a_s$ =monolayer adsorption capacity (mg/g)	(3) (4) (5) (6) (7)	[33] [34, 35] [36, 37] [36]
Adsorption mechanism models
Intraparticle diffusion Boyd Bangham	$q_t=K_d{t}^{1/2}+C$ $B_t=-0.4977-\ln \left(1-F\right)$ $F=1-\left(6/{\pi }^2\right)\exp \left(-B_t\right)$ ; $F=q_t/q_e$ $\log \left[\log \left(\frac{C_o}{C_o-q_{t}m}\right)\right]=\log \left(\frac{k_{o}m}{2.30V}\right)+\alpha \log t$	$q_t$ =adsorption capacity at time, $t$ (mg/g) $K_d$ =intraparticle diffusion constant (mg/g min0.5) $F$ =fraction of solute adsorbed at any time $B_t$ =Boyd’s number (rate parameter) $k_o$ =Bangham’s constant $\alpha$ =Bangham’s constant (l2/g) $V$ =volume of solution (l)	(8) (10) (11) (9)	[38] [39–41] [39, 41]
Thermodynamics
Gibbs free energy Van’t Hoff’s equation	${\Delta G}_{\text{ads}}^o=-\text{RTln}K$	${\Delta G}_{\text{ads}}^o$ =Gibbs free energy (kJ/mol) $R$ =ideal gas constant ( $R=8.314$  J/mol.K) $K$ =equilibrium constant (l/g) $\left({\Delta H}_{\text{ads}}^o\right)$ =enthalpy (kJ/mol) $\left({\Delta S}_{\text{ads}}^o\right)$ =entropy (J/mol.K) $T$ =temperature (K)	(12) (13)	[42] [42]
	$\ln K=\frac{{\Delta S}_{\text{ads}}^o}{R}-\frac{{\Delta H}_{\text{ads}}^o}{\text{RT}}$
Isosteric heat of adsorption
	$d\left(\text{Ln}{\text{C}}_e\right)=-\frac{{\Delta H}_x}{{\text{RT}}^2}\times dT$ $\text{Ln}{\text{C}}_e=-\frac{{\Delta H}_x}{\text{RT}}+C$	$C_e$ =equilibrium concentration at constant amount of the adsorbate (mg/l) ${\Delta H}_x$ =isosteric heat of adsorption (kJ/mol)	(14)(15)	[28][28]
Error functions
Root-mean-square error (RMSE)	$\sqrt{\frac{1}{N-2}\sum _{i=1}^N{\left(q_{e,\exp }-q_{e,\text{pred}}\right)}^2}$ $\sum _{\text{i}=1}^N\left[\frac{{\left(q_{e,\exp }-q_{e,\text{pred}}\right)}^2}{q_{e,\exp }}\right]$	$q_{e,\exp }$ =experimental $q_e$ value $q_{e,\text{pred}}$ =model predicted $q_e$ value $N$ =number of observations in the experimental data	(12)(13)	[43][44]
Chi-squared function ( ${\chi }^2$ )

2.4. Determination of the Point of Zero Charge ( $\text{p}{\text{H}}_{\text{pzc}}$ ) of the Adsorbent

The $\text{p}{\text{H}}_{\text{pzc}}$ of TMCC is the pH where its surface potential charge is zero. It was calculated using a method similar to the one described by Harrache et al. [29] and Putra et al. [30]. About 50 ml of NaCl solutions (0.01 M) was put into several Erlenmeyer flasks. The pH of each solution was adjusted with HCl and NaOH to a specified value between 2 and 10. Thereafter, 0.15 g of TMCC was introduced into the flasks. After 24 hours of agitation at room temperature, the final pH of the ensuing solution was determined. The $\text{p}{\text{H}}_{\text{pzc}}$ is the point at which the curve $\text{p}{\text{H}}_{\text{final}}$ vs. $\text{p}{\text{H}}_{\text{initial}}$ crosses the line at $\text{p}{\text{H}}_{\text{final}}=\text{p}{\text{H}}_{\text{initial}}$ [30].

3. Results and Discussion

3.1. Characterization of the Adsorbent

Detailed results and interpretation of the physicochemical properties, surface area, and pore size distribution characterization as well as the instrumental analyses (SEM and FTIR) of the TMCC are reported in our recent work [2]. Summarily, the analysis of the physicochemical properties disclosed that TMCC contained fixed carbon (33.47%), moisture content (5.50%), volatile matter (18.01%), bulk density (0.63 g/ml), ash content (5.82%), porosity (0.24), iodine number (888.35 mg/g), and pH (6.30). The thermal modification of the CC provided the AC with enhanced surface area, average pore width, micropore volume, and pore radius of 903.7 m²/g, 5.55 nm, 0.389 cm³/g, and 16.20 Å, respectively. SEM images revealed that interspatial pores exist within the matrix of the TMCC, while the result of the FTIR analysis indicated that the key functional groups present in the TMCC were alkyls, alkanes, alkanol, carboxylic acids, esters, ethers, and nitro compounds.

3.2. Effects of Operating Variables on Phenol Adsorption

3.2.1. Effect of Contact Time and Initial Phenol Concentration

The time needed to attain equilibrium is a critical factor in batch adsorption system design. The impact of the contact period on phenol percentage adsorption was investigated at various initial phenol concentrations, as shown in Figure 2(a). The result showed that the adsorption of phenol increased as the contact time increased up to 30 min. After 30 min, increasing the contact time further did not improve phenol adsorption significantly. At the initial stage, the adsorption rate was rapid owing to the adsorption of phenol molecules onto the exterior surface of the adsorbent; thereafter, the molecules entered the interior surface of the adsorbent, a slow process relatively. The initial quicker rates of adsorption can also be attributed to the huge number of adsorption binding sites, and the slower rates at the final moment are due to adsorption site saturation and the realization of equilibrium [45]. Similar results have been reported by Abdelkreem [46] for phenol adsorption using olive mill waste. Generally, an increase in the initial phenol concentration resulted to a decrease in the adsorption efficiency. This is a result of the buildup of phenol molecules on the adsorbent’s surface [47].

Figure 2

Effects of operating variables on phenol adsorption: (a) effect of contact time and initial phenol concentration, (b) effect of solution pH, (c) effect of adsorbent dosage, and (d) effect of solution temperature.

(b) (c) (d)

3.2.2. Effect of Solution pH

One of the most significant variables affecting the output of an adsorption process is the pH of the aqueous solution [45, 48, 49]. The impact of pH level on phenol uptake was investigated at pH levels ranging from 2 to 10, as shown in Figure 2(b). The results show that as the pH increased from 2 to 6, the adsorption efficiency increased and thereafter decreased. The optimum percentage of phenol removal was achieved at a pH of 6. Some researchers proposed that the pH range of 6 to 8 is optimal for phenol adsorption [47, 50]. At low levels of pH, phenol removal was minimal, because of the existence of hydrogen ions (H+), which are liable for suppressing phenol ionization and, as a result, reducing its sorption on polar solvents [47]. The observed decrease in phenol removal at elevated pH levels (that is at pH levels higher than 6) could be explained by a rise in hydroxide ion (OH-) concentration, which induces a repulse with the negative active sites on the adsorbent, thus lowering phenol uptake [50]. Equally, at high pH, phenolic ions form salts that readily ionize, releasing negative charges on the phenolic group which subsequently inhibit the sorption of phenol ions [47].

3.2.3. Effect of TMCC Dosage

The impact of TMCC dosage on phenol removal efficiency was studied at a dosage range of 0.4 to 2.0 g as shown in Figure 2(c). The efficiency of phenol removal was observed to be directly proportional to TMCC dosage. This is a consequence of the increase in the available active sorption sites as a result of the increased number of sorbents available for the uptake of an equal number of phenolic ions. This result is in concurrence with the works reported by Abdelkreem [46], Uddin et al. [51], and Saravanakumar and Kumar [52] in comparable studies.

3.2.4. Effect of Solution Temperature

Figure 2(d) illustrates the influence of solution temperature on phenol adsorption efficiency. This was studied in a temperature range of 30 to 60°C. From the figure, it can be seen that the efficiency of phenol uptake varies significantly with temperature. The adsorption of phenol increased with a decrease in temperature indicating that a low temperature favors phenol adsorption. This is because as temperature increases, the adsorptive force between the adsorbent’s active vacant sites and the adsorbate (phenol ions) is weakened, ultimately leading to a decrease in phenol adsorption efficiency. It has been also suggested that higher temperature enhances the thermal energies of the adsorbate, hence making the attractive force between the phenol species and the adsorbent insufficient to retain the adsorbed molecules at the binding sites [53]. A similar result has been reported by Bazrafshan et al. [54].

3.3. Equilibrium Isotherm Study

The data generated from the experiments were analyzed using the Langmuir, Toth, Sips, and Redlich–Peterson isotherm models. To minimize error distribution, the parameters of the isotherm models were evaluated by the nonlinear regression method using the solver add-in function available in Microsoft Excel software.

The Langmuir model is a simple, semiempirical model that is founded on a kinetic principle. It assumes the following: a homogenous adsorbent surface, adsorbed molecules do not interact, adsorptions follow the same mechanism in all cases, and only a monolayer is formed at the maximum adsorption [33]. The nonlinear representation of the Langmuir model is written as equation (3). The parameters obtained from the nonlinear regression of the Langmuir model are presented in Table 2. As can be seen from the table, both $q_m$ and $K_L$ values increased with a decrease in temperature. The coefficient of determination ( $R^2$ ) is in the range of 0.9983-0.9991 at different temperature conditions, indicating a good fit. In the validation of the fitness of the Langmuir model in analyzing the adsorption process, the calculated error functions are very low, indicating minimal error distribution. The parameters of the Langmuir model were further expressed with respect to the dimensionless separation factor, $R_L$ represented by equation (4). The value of $R_L$ shows whether the adsorption is favorable ( $0<R_L<1$ ), unfavorable ( $R_L>1$ ), linear ( $R_L=1$ ), or irreversible ( $R_L=0$ ). The $R_L$ values obtained at different temperatures and initial concentrations were between 0 and 1, depicting favorable adsorption of phenol onto TMCC. One of the key shortcomings of the Langmuir model is that it does not explain the material’s heterogeneity [34].

Table 2

Isotherm parameters for the uptake of phenol onto TMCC.

Isotherm	Parameters	Temperature (°C)
Langmuir		30	35	40	50	60
	$q_m$ (mg/g)	20.4	20.1	16.6	16.6	12.7
	$K_L$ (l/mg)	0.001	0.001	0.001	0.00093	0.00093
	$R^2$	0.9986	0.9990	0.9983	0.9991	0.9989
	RMSE	0.01823	0.01773	0.01025	0.01262	0.00767
	${\chi }^2$	0.00011	0.00011	0.00004	0.00007	0.00003
Toth	$q_m$ (mg/g)	7.9	7.7	6.6	6.3	4.8
	$K_T$ (mg/g)	0.030	0.030	0.027	0.028	0.034
	$n$ (mg/g)	0.638	0.642	0.645	0.645	0.630
	$R^2$	0.9969	0.9976	0.9986	0.9989	0.9976
	RMSE	0.01929	0.01943	0.00645	0.00973	0.00799
	${\chi }^2$	0.00025	0.00026	0.00003	0.00008	0.00007
Redlich–Peterson	$A$ (l/g)	0.030	0.030	0.025	0.024	0.021
	$B$ (l/mg)	0.23	0.25	0.26	0.26	0.30
	$\beta$	0.26	0.25	0.25	0.25	0.27
	$R^2$	0.9803	0.9989	0.9683	0.9961	0.9751
	RMSE	0.04850	0.01310	0.0311	0.01827	0.02594
	${\chi }^2$	1.68798	1.60939	1.55561	0.94391	0.31061
Sips	$K_s$ (l/g)	3.70	3.55	3.10	2.90	2.20
	${\beta }_s$	0.0098	0.0099	0.0094	0.0091	0.0092
	$a_s$ (mg/g)	0.32	0.34	0.32	0.34	0.35
	$R^2$	0.9990	0.9957	0.9970	0.9968	0.9993
	RMSE	0.01089	0.02622	0.00960	0.01640	0.00433
	${\chi }^2$	0.00008	0.00047	0.00008	0.00023	0.00002

The Toth isotherm model was established to enhance and remediate the limitations of the Langmuir model [34]. The model provides an adequate description of the heterogeneity of the adsorbent. It is fitting for modeling an assortment of multilayers and heterogeneous adsorption systems [35]. The Toth model is represented by equation (5). The parametric constants evaluated are summarized in Table 2. The $R^2$ obtained from the model analysis was quite high, varying from 0.9976 to 0.9989, an indication of a good correlation with the adsorption data. The low values of the error parameters affirm that Toth’s predicted and actual adsorption capacities were quite comparable. The factor “ $n$ ” typifies the adsorption system’s heterogeneity; if $n=1$ , the model reduces to the Langmuir isotherm; however, if it departs further from unity (1), the system is considered heterogeneous [55]. The “ $n$ ” values as deduced ranged between 0.630 and 0.645, depicting a heterogeneous surface.

The Redlich–Peterson (R-P) model is an empirical model that incorporates three parameters ( $A$ , $B$ , and $\beta$ ). It features elements from both the Freundlich and Langmuir models. The numerator of the model depicts a linear dependence on concentration, while an exponential function at the denominator represents adsorption equilibria over a broad spectrum of concentrations [36, 56, 57]. At high concentration (that is, as the exponent $\beta$ tends to zero), it tends towards the Freundlich isotherm model, and at low concentration (that is, as the $\beta$ values are all close to one), it approaches the ideal Langmuir condition [37]. The Redlich–Peterson model is represented by equation (6). The derived parameters of the Redlich-Peterson isotherm are presented in Table 2. The R-P isotherm constant $A$ was observed to decrease as the temperature increased. The coefficient of determination is in the range of 0.9683 to 0.9989, indicating a good fit.

The Sips model is a hybrid of the Langmuir and Freundlich models devised for estimating heterogeneous adsorption systems and surmounting the Freundlich model’s limitation associated with rising adsorbate concentration [36]. When adsorbate concentrations are low, it tends towards the Freundlich isotherm; and when the concentrations are high, a monolayer adsorption capacity typical of the Langmuir isotherm is predicted [36, 56, 57]. The Sips model is described by equation (7). Table 2 displays the values of various parameters of the Sips isotherm estimated at different temperature values. The $K_s$ values decreased as temperature increased, in the range of 2.2 to 3.7 l/g. The isotherm exponent, ${\beta }_s$ , and the monolayer adsorption capacity, $a_s$ , showed no linear relationship with temperature. High $R^2$ values (ranging from 0.9957 to 0.9993) and low error parameter values indicate a good correlation between the actual and Sips model data. A direct comparison of the suitability of the models in the analysis of the adsorption data has been provided in terms of the regression coefficient ( $R^2$ ), root-mean-square error (RSME), and Chi-squared test ( ${\chi }^2$ ) (see Table 3). The decreasing order of the fitness of the models is the Sips, Langmuir, Toth, and Redlich–Peterson models. Furthermore, comparison of this work’s maximum adsorption capacity and those reported for other bioadsorbents is presented in Table 4.

Table 3

Comparison of the regression coefficient ( $R^2$ ), root-mean-square error (RSME), and Chi-squared test ( ${\chi }^2$ ) isotherm models.

Regression coefficient/error functions	Isotherm	Temperature (°C)
		30	35	40	50	60
$R^2$	Langmuir	0.9986	0.9990	0.9983	0.9991	0.9989
	Toth	0.9969	0.9976	0.9986	0.9989	0.9976
	Redlich–Peterson	0.9803	0.9989	0.9683	0.9961	0.9751
	Sips	0.9990	0.9957	0.9970	0.9968	0.9993
RMSE	Langmuir	0.01823	0.01773	0.01025	0.01262	0.00767
	Toth	0.01929	0.01943	0.00645	0.00973	0.00799
	Redlich–Peterson	0.04850	0.01310	0.0311	0.01827	0.02594
	Sips	0.01089	0.02622	0.00960	0.01640	0.00433
${\chi }^2$	Langmuir	0.00011	0.00011	0.00004	0.00007	0.00003
	Toth	0.00025	0.00026	0.00003	0.00008	0.00007
	Redlich–Peterson	1.68798	1.60939	1.55561	0.94391	0.31061
	Sips	0.00008	0.00047	0.00008	0.00023	0.00002

Table 4

Comparison of adsorption capacities of various bioadsorbents for phenol removal from aqueous solutions.

Adsorbent	Adsorption capacity (mg/g)	Reference
TMCC	20.40	Present study
Al-pillared bentonite	1.81	[58]
Thermal bentonite	1.30	[58]
Coal	13.23	[59]
Coke breeze	0.172	[59]
Rice husk	4.508	[59]
Rice husk	0.002	[60]
Rice husk ash	0.886	[60]
Petroleum coke	6.01	[59]
Neutralized red mud	4.127	[61]
Aged-refuse in biofilter	0.597	[62]
Luffa cylindrica	9.25	[63]
Peanut shells	21.00	[64]
Lantana camara (KOH treated)	91.07	[65]

3.4. Point of Zero Charge ( $\text{p}{\text{H}}_{\text{pzc}}$ )

The $\text{p}{\text{H}}_{\text{pzc}}$ of an adsorbent is the pH at the point where its surface charge is zero [29]. The existence of H⁺ or OH^- in wastewater solutions may change the net surface charge of adsorbents [30]. The analysis of the $\text{p}{\text{H}}_{\text{pzc}}$ helps to gain information on the ionization of functional groups and the way they interact with adsorbate species in solution. If a solution’s pH is higher than its $\text{p}{\text{H}}_{\text{pzc}}$ , the surface functional groups on adsorbents will be protonated by the excess H⁺ ions; if it is lower than its $\text{p}{\text{H}}_{\text{pzc}}$ , the surface functional groups will be deprotonated by the OH^- ions present in the solution [30]. In other words, if the solution pH is above the $\text{p}{\text{H}}_{\text{pzc}}$ , the sorbent surface interacts with the positive species since this indicates that its surface charge at that condition is negative, whereas at pH lower than $\text{p}{\text{H}}_{\text{pzc}}$ , the interaction will be with the negative species because it is possessing a positive charge. The point of zero charge of phenol uptake onto TMCC is 5.83, and the plot is illustrated in Figure 3. In this study, optimum phenol uptake onto TMCC was obtained at a pH of 6 which is slightly higher than the $\text{p}{\text{H}}_{\text{pzc}}$ . This is an indication that the TMCC surface is not negatively charged at this pH.

Figure 3

Point of zero charge for phenol adsorption onto TMCC.

3.5. Adsorption Thermodynamics

For an enhanced understanding of the adsorption process and the influence of temperature on it, the following thermodynamic properties, such as changes in standard Gibbs free energy $\left({\Delta G}_{\text{ads}}^o\right)$ , enthalpy $\left({\Delta H}_{\text{ads}}^o\right)$ , and entropy $\left({\Delta S}_{\text{ads}}^o\right)$ , were estimated using equations (12) and (13). The values of ${\Delta H}_{\text{ads}}^o$ and ${\Delta S}_{\text{ads}}^o$ were deduced from the plots of $\ln K$ versus $1/T$ (Figure 4) and presented in Table 5. The ${\Delta G}_{\text{ads}}^o$ values ranged from -8.792 to -11.157 kJ/mol at 303 to 333 K. The ${\Delta H}_{\text{ads}}^o$ and ${\Delta S}_{\text{ads}}^o$ values are 14.834 kJ/mol and 78.154 J/mol.K, respectively. The negative values of ${\Delta G}_{\text{ads}}^o$ at varying temperatures depict a spontaneous adsorption process. The adsorption process with ${\Delta G}_{\text{ads}}^o$ in the range of -80 to -400 kJ/mol depicts a chemisorption process [42], but, since the ${\Delta G}_{\text{ads}}^o$ obtained in this work is in the range of -8.792 to -11.157 kJ/mol, it indicates a physisorption-dominated mechanism, in agreement with the experimental result which suggested that adsorption is rapid and is inversely proportional with temperature. The positive value of ${\Delta H}_{\text{ads}}^o$ indicates the endothermic nature of the adsorption process. Also, since ${\Delta H}_{\text{ads}}^o$ is <40 kJ/mol, a physical adsorption process is further suggested [42]. The positive value of ${\Delta S}_{\text{ads}}^o$ reflects the favorable affinity phenol has for TMCC and the increasing degree of randomness at the solid-solution interface during the adsorption of phenol ions onto TMCC adsorbent.

Figure 4

Van’t Hoff’s plot for thermodynamic analysis.

Table 5

Adsorption thermodynamic parameters.

$T$ (°C)	$T$ (K)	${\Delta G}_{\text{ads}}^o$ (kJ/mol)	${\Delta H}_{\text{ads}}^o$ (kJ/mol)	${\Delta S}_{\text{ads}}^o$ (J/mol.K)
30	303	-8.792	14.834	78.154
35	308	-9.246
40	313	-9.702
50	323	-10.417
60	333	-11.157

3.6. Isosteric Heat of Adsorption

The isosteric heat of adsorption ( ${\Delta H}_x$ , kJ/mol) is the heat of adsorption deduced at a fixed amount of the adsorbed compound [28, 66]. Information about isosteric heat of adsorption is critical for the adsorption plant and process design. The isosteric heats at fixed surface coverage ( $q_e=4,6,8,10,12$  mg/g) were estimated using the Clausius–Clapeyron equation, equation (14), expanded as equation (15). The equilibrium concentration ( $C_e$ ) values at a constant amount of phenol adsorbed were deduced from the isotherm data at varying temperatures. The ${\Delta H}_x$ values were calculated from the slope of the linear plot of $\text{Ln}{\text{C}}_e$ against $1/T$ (Figure 5(a)). Table 6 presents the linear regression coefficients and the ${\Delta H}_x$ values as calculated. The ${\Delta H}_x$ value should be less than 80 kJ/mol for physical adsorption and between 80 and 400 kJ/mol for chemical adsorption [28, 66]. The ${\Delta H}_x$ values obtained in this study are between 47.43 and 79.38 kJ/mol signifying that phenol adsorption onto TMCC is dominated by a physical process, validating the thermodynamic results.

Figure 5

(a) Plots of $\text{Ln}{\text{C}}_e$ against 1/T for the determination of ${\Delta H}_x$ . (b) Plot of ${\Delta H}_x$ against surface loading.

(b)

Table 6

Isosteric heat of adsorption parameters.

$q_e$ (mg/g)	${\Delta H}_x$ (kJ/Mol)	$R^2$
4	79.38	0.9408
6	52.14	0.8938
8	49.20	0.8654
10	48.05	0.8526
12	47.43	0.8453

Figure 5(b) illustrates how ${\Delta H}_x$ varies with $q_e$ (surface loading). It can be deduced from the figure that ${\Delta H}_x$ decreased as the $q_e$ values increased, indicating that TMCC is associated with energetically heterogeneous surfaces [27, 28]. The nature of the variation of ${\Delta H}_x$ with $q_e$ can be credited to adsorbate-adsorbent interaction proceeded by adsorbate-adsorbate interaction [28, 45]. At low values of surface loading, adsorbent-adsorbate interaction dominates resulting in high ${\Delta H}_x$ , and as the surface loading increases, adsorbate-adsorbate interaction dominates [27].

3.7. Mechanism Studies

The mechanism of adsorption is generally considered to follow three steps, one or any combination of which can be the rate-controlling mechanism [67, 68]: (i) film diffusion, (ii) pore diffusion (i.e., external mass transfer), and (iii) intraparticle transport diffusion. The adsorption mechanism of phenol uptake onto TMCC was studied via the application of the intraparticle diffusion, Bangham, and Boyd models.

The intraparticle diffusion plot is one of the prominent techniques for assessing the mechanism involved in an adsorption process. It expresses the relationship between the adsorption capacity ( $q_t$ ) and time $t^{1/2}$ as depicted by equation (8) [38]. The model parameters are depicted in Table 7. The high $R^2$ values indicated the presence of intraparticle diffusion in the adsorption process. As depicted by the regression coefficients, the plot points were not entirely linear over the whole operational time interval, indicating that the adsorption was influenced by more than one process. Also, if the intraparticle diffusion were the sole rate-controlling step, the plot would pass through the origin [67]; however, because the plot failed to transit through the origin (as depicted by the $C$ values in Table 7), intraparticle diffusion, while implicated in the adsorption process, does not constitute the rate-controlling step. The $C$ values represent the thickness of the boundary layer; a bigger intercept represents a greater involvement of surface adsorption in the rate-controlling step [69].

Table 7

Adsorption mechanism model parameters for phenol uptake onto TMCC.

Mechanism model	Concentration (mg/l)
	100	150	200	300	500
Intraparticle diffusion
$K_d$ (mg/g min-0.5)	0.803	1.033	1.173	1.518	1.092
$C$ (intercept)	0.375	0.483	0.482	0.529	1.092
$R^2$	0.9755	0.9754	0.9591	0.9483	0.9742
Boyd
Intercept	-1.1666	-1.0527	-0.9793	-1.0094	-0.7714
$R^2$	0.8147	0.8879	0.9410	0.9130	0.9566
Bangham
$k_o$	118.79	117.99	117.42	117.19	116.04
$\alpha$ (l2/g)	0.0177	0.0165	0.0147	0.0131	0.0142
$R^2$	0.7192	0.7776	0.8391	0.8465	0.9018

Another important model that helps to gain a better understanding of the adsorption mechanism is Boyd’s model. Boyd’s film-diffusion model was initially suggested for intraparticle diffusion in a spherical particle [40]. Equations (10) and (11) are used for the analysis of Boyd’s model [39–41]. The plot of the calculated rate parameter $B_t$ versus time $t$ depicts Boyd’s model. The plots were observed to be linear with a high coefficient of determination ( $R^2>0.90$ in most cases) indicating the participation of film diffusion in the mechanism [39, 70]. The fact that the plot did not pass through the origin (as illustrated by the intercept values in Table 7) indicates the involvement of a second mass transfer mechanism (external mass transfer) [40]. Similar outcomes have been reported by Martins et al. [70] and Üner et al. [39] in similar studies.

According to Bangham’s model, the diffusion of phenol molecules into the pore spaces of the adsorbent makes a significant contribution to the rate-controlling step [39, 71]. It is described by equation (36) [39, 41]. The plot of $\log \left[\log \left({\text{C}}_o/{\text{C}}_o-q_{t}m\right)\right]$ against time $t$ gave a straight line with $R^2$ in the range of 0.7192 and 0.9018 as shown in Table 7. This indicates the occurrence of pore diffusion and affirmed the presumption of Bangham’s model.

Further, as indicated by the thermodynamics analysis, physisorption as well as the van der Waal and electrostatic interactions are also involved in the phenol uptake. Phenol has a pKa of 9.89 [72], and below this pH, it is protonated to its cationic form. An important mechanism of adsorption is the electrostatic attraction between phenol and the adsorbent’s negatively charged surface (observed from the $\text{p}{\text{H}}_{\text{ZPC}}$ study). Weak hydrogen bonding and pore diffusion also play a role in phenol adsorption (to a lesser extent). Hydrogen bonding allows water molecules to be adsorbed on the surface oxygen groups. Because the adsorbate’s alkyl hydrogens can interact with the molecules on the adsorbent’s functional groups such as oxygen, hydrogen bonding is established (corroborated by the FTIR). Hydrogen bonds are a sort of dipole-dipole moment and a weak partial intermolecular link [73]. The FTIR study verified functional groups such as C-O, C=O, and -OH. Phenol is a benzene-like polycyclic aromatic molecule. The benzene rings cause a donor-acceptor connection and the phenol to stack onto the adsorbent [74]. That is, the carbon surface’s electron acceptors and basic sites serve as donors [72]. As a result, the $\pi ‐\pi$ electron-donor interaction is a contributing factor. The hydrophobic interactions are thought to contribute to phenol adsorption, which is another rationale for the higher adsorption of substituted phenols [75]. Conclusively, electrostatic attraction, hydrophobic interactions, $\pi ‐\pi$ electron-donor interaction, hydrogen bonding, the van der Waal interactions (may be London dispersion and dipole-induced dipole bonds), and pore diffusion played quite a significant part in the phenol adsorption process as illustrated in Figure 6.

Figure 6

Summary of the adsorption mechanism of phenol onto TMCC at optimum pH.

3.8. Adsorbent Regeneration and Reutilization Studies

Adsorbent regeneration tests were carried out to assess the potentiality of reusing the adsorbent for other adsorption activities and also to render the process more economically attractive. The used adsorbents were treated with sodium hydroxide (NaOH) solution. This was accomplished using the batch method of operations employing varying concentrations of sodium hydroxide (NaOH) solution. Sodium hydroxide was selected because it has been reported as the most effective desorbing/regenerating agent [76–78]. The results depicted in Figure 7 indicate that after approximately 300 minutes, the adsorption efficiency for spent TMCC was 56.48%, 66.05%, and 74.99% using 0.05 M, 0.1 M, and 0.2 M NaOH solutions, respectively. The adsorption performance was found to be relatively within these ranges for about three cycles of regeneration before declining significantly to the point where it was no longer economically feasible. This shows that TMCC adsorbent could be retrieved and reused in the aqueous phenol adsorption.

Figure 7

Reuse of regenerated adsorbent using different concentrations of NaOH.

4. Conclusion

The current study demonstrates that CC, which is typically discarded as waste products, can be effectually used as raw material in the production of adsorbents for the uptake of phenol from aqueous solutions. The nonlinear regression technique was used to evaluate the equilibrium isotherms. The fitness of the isotherm models to the experimental data was in this decreasing order—Sips’, Langmuir’s, Toth’s, and Redlich–Peterson’s models. The uptake of phenol onto TMCC is favorably influenced by a decrease in initial phenol concentration and temperature and an increase in TMCC dosage and contact time. Phenol removal increased with pH from 2 to 6 and decreased thereafter. The negative values of ${\Delta G}_{\text{ads}}^o$ at varying temperatures depict a spontaneous adsorption process. The isosteric heats of adsorption were estimated using the Clausius–Clapeyron equation, and it confirmed that the adsorption process is a physical process dominated by the van der Waals interactions. The values of the isosteres decreased with an increase in surface coverage, signifying a heterogeneous surface. The transport mechanisms depicted in the process were intraparticle, film, and pore diffusion mechanisms. Furthermore, the electrostatic attraction, $\pi ‐\pi$ electron-donor interaction, and hydrogen bonding were also involved in the phenol adsorption. The point of zero charge of TMCC was 5.83, slightly lower than the optimum pH of the adsorption process. These results provided detailed information regarding the equilibrium characteristics, adsorption mechanism, energy and surface interactions, and the point of zero charge of TMCC for the uptake of phenol.