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BY 4.0 license Open Access Published by De Gruyter Open Access August 15, 2022

Chemically modified Teucrium polium (Lamiaceae) plant act as an effective adsorbent tool for potassium permanganate (KMnO4) in wastewater remediation

  • Hatem A. AL-Aoh EMAIL logo and Nasser A. Alamrani
From the journal Open Chemistry


Powdered Teucrium polium leaves (S1) were modified with zinc chloride (ZnCl2) (S2), a mixture of copper sulfide (CuS) and ZnCl2 (S3), and oxalic acid (H2C2O4) (S4). The porosity, surface area, and functional groups of these four samples, along with their ability to uptake KMnO4 from solutions, were inspected to identify the optimal adsorbent. For KMnO4 adsorption by the ideal adsorbent (S2), the pHZPC (pH value at which the adsorbent surface is uncharged), influences of experimental circumstances, and dynamic, isotherm, and thermodynamic parameters were examined. According to the results, the surface area, pore size, pore volume, and pHZPC of the optimum adsorbent (S2) are 3.689 m2/g, 570.20 Å, 0.01776 cm3/g, and 6.4, respectively. The optimal S2 dose, the ideal value of pH solution, and equilibrium time are 0.05 g, 5.5, and 192 min, respectively. The Langmuir and second-order models are appropriate for modeling this adsorption. Furthermore, increasing the temperature from 27 to 57°C increases the maximum adsorption capacity (q max) from 833.33 to 1000.00 mg/g. According to the thermodynamic data, this adsorption is both endothermic and spontaneous.

Graphical abstract

1 Introduction

Potassium permanganate (KMnO4) is mainly utilized as an oxidant agent to control plant growth, the taste, and odor of industrial products, and to disinfect industrial waste [1]. KMnO4 is also applied for the removal of cyanide, hazardous metals, dyes, phenols, and other organic contaminants from polluted wastewaters [2,3]. Furthermore, this chemical agent is used to oxidize and break organic molecules with longer chains [2,4]. KMnO4 is now widely employed as a potent oxidant for removing the solvents of chlorinated groundwater and soil [5] and preventing the growth of some aquatic organisms [1]. Unfortunately, the National Institute for Occupational Safety and Health (NIOSH) has designated KMnO4 as a toxic and harmful material to the health of humans. Whereas direct exposure to permanganate produces skin burns, shortness of breath, and eye pain, it may also cause nervous system damage since it causes shock and neurological collapse, while long-term exposure causes long-term harmful effects [6]. Because of these risks, technologies such as fluidized-bed crystallization [7] and adsorption [1,6] have been utilized to remove KMnO4 from industrial wastewaters before release. Adsorption has been claimed to be one of the best and most utilized methods due to its ease of use, high performance, nontoxicity, ecological friendliness, and a wide range of sorbents [1,8,9,10]. Therefore, the method of adsorption in this work was chosen. Adsorption performance of KMnO4 by activated carbon prepared from different natural raw materials was examined earlier [1,2,11,12]. Nanoparticles of zinc oxide (ZnO) [13], nickel ferrite [14], and copper sulfide (CuS) [15] were utilized for the elimination of KMnO4 and other pollutants from aqueous solutions. Although these nanoparticles have elevated adsorptive capacity, their applications are unwanted due to their expensive production costs. As a result, a variety of low-cost or no-cost materials have been used as effective adsorbents for removing some pollutants from water [16]. For example, modified palm oil fuel ash [17,18] and powdered Neem leaves [19,20,21] have been used to eliminate a variety of organic and inorganic contaminants from water. The modified leaf powder of Neem [22], Nitraria retusa [23], and Ocimum basilicum [24] have recently been utilized to remove KMnO4 from aqueous solutions. The adsorption performance of these low-cost adsorbents toward KMnO4 is significantly disparate. As a result, more research into the adsorption of KMnO4 by other sorbents at a cheap cost is needed.

Teucrium polium L., also known as germander, is a plant that has been used in traditional herbal remedies for more than 2,000 years for its antifungal, carminative, antispasmodic, antipyretic, anti-inflammatory, and antifungal qualities, as well as its capability to reduce high blood pressure [25]. This herbal plant is a member of the Lamiaceae family, which includes roughly 300 types, and blooms between June and August. These types can be found in abundance on hills and mountains all over the world, including the Mediterranean, Southwest Asia, Europe, and North Africa [26,27]. This plant, known in Saudi Arabia as Ja’adeh, is high in flavonoids [26].

T. polium L. has previously been employed for the synthesis of Fe2O3 nanoparticles, which are utilized as a catalyst for methyl orange degradation [26] and as a sorbent for eliminating As(iii) from solutions [28].

Despite its low cost and widespread availability in many countries, particularly in Saudi Arabia, no attempt has been made to date to employ T. polium L. leaf powder as a novel sorbent for the elimination of KMnO4 from polluted waters.

As a result, the goals of this study are to improve the adsorption ability of this herb by modifying its leaf powder with zinc chloride (ZnCl2), copper sulfide (CuS), and oxalic acid (H2C2O4) and to determine the adsorption effectiveness of KMnO4 using the prepared adsorbents. The produced samples will be characterized, and the performance of KMnO4 adsorption by these samples will be compared. In addition, the factors controlling this adsorption, as well as kinetics, isotherms, and thermodynamic constants, will be investigated in this study.

2 Methodology

2.1 Adsorbent preparation and modification

The T. polium leaves were obtained from a market for medicinal herbs in Tabuk, Kingdom of Saudi Arabia. These leaves were washed twice with distilled water, dehydrated in an oven overnight, ground into powder with an electric grinder, and labeled as S1. A specific amount of S1 (100 g) was mixed with 1,000 mL of ZnCl2 (20% w/w) and refluxed for 180 min at the boiling point, after which the mixture was allowed to cool at ambient temperature. After cooling, the mixture was filtered through a Buchner funnel connected to a vacuum bump. The residual solid was then treated with 250 mL of 2 M hydrochloric acid solution and heated for one and a half hours to eliminate any remaining ZnCl2. The solid part of the resultant mixture was then filtered out and washed several times with distilled water. The clean solid was then dehydrated in a 130°C oven for 30 h. In the end, the dry solid was ground and sieved to obtain similar particles, after which it was designated as S2.

The same weight of S1 (100 g) was mixed with copper sulfide (50 g). This mixture was also refluxed with 1,000 mL of ZnCl2 (20% w/w) using the same method and conditions mentioned earlier. In this case, the resulting adsorbent was designated as S3.

Using the same experimental settings and procedures as described earlier, the same quantity of S1 (100 g) was mixed and refluxed with 1,000 mL of H2C2O4 solution (20% w/w), and the resulting sample was labeled S4.

2.2 Adsorbent characterization

The groups that are chemically effective on the surface of the prepared four adsorbents (S1, S2, S3, and S4) were detected using a Fourier-transform infrared spectrometer (FT-IR; Nicolet iS5; Thermo Fisher Scientific, USA). These samples were also scanned by SEM apparatus at 10 kV accelerating power to determine the surface morphology of these adsorbents. Additionally, BET (NOVA-2200 Ver.6.11) technology was used for 22 h at 77.38 K to identify the textural characteristics (porosity and surface area) of these four adsorbents.

Moreover, five 0.05 M Na2CO3 solutions with varied pH starting values (2, 4, 6, 8, and 10) (pHi) were prepared. In a 150 mL plastic container, a given volume of each solution (40 mL) was combined with a fixed mass (0.1 g) of the optimum adsorbent (S2). The filled containers were sealed and shaken for 26 h at 27°C and 180 rpm in shaker incubators. After each solution was separated by filtering, the final pH (pHf) of each of these solutions was quantified by means of a pH meter. Finally, to determine the pHZPC value of this adsorbent, the values of pHi–pHf were assessed and graphed against pHi values.

2.3 Experiments of adsorption

2.3.1 Identifying the best adsorbent

In a 50 mL amber bottle, 30 mL of 200 mg/L KMnO4 solution was integrated separately with 0.03 g of each of the four samples developed in this work (S1, S2, S3, and S4) to find the best active adsorbent toward KMnO4. A shaker incubator was used to agitate the sealed amber bottles for 24 h at 27°C and 180 rpm. The mixtures were then filtered, and the residual concentration of KMnO4 in the filtrate was assessed at 525 nm using a Jenway 6800 UV-vis spectrophotometer. The percentage removal (%R) and amount of KMnO4 adsorbed (q e, mg/g) by each of these adsorbents were calculated using the following equations:

(1) % R = ( C 0 C e ) C 0 × 100 ,

(2) q e = V m ( C 0 C e ) ,

where V is the volume of KMnO4 solution (L); m is the adsorbent mass (g); C 0 is the adsorbate initial concentration; and C e is the adsorbate final concentration.

2.3.2 Effect of experimental parameters

The adsorption experiments of KMnO4 by the best effective adsorbent (S2) were carried out in a batch system to find out how the most important factors, such as dose of S2, KMnO4 concentration, temperature, contact time, and pH, influence the adsorption and to identify the optimal values of these factors. In all these experiments, 50 mL of KMnO4 solution and the required amount of S2 were added to the 100 mL amber bottles. The filled bottles were then placed in a shaker incubator at 180 rpm. The suspensions were filtered after the requested time for every experiment, and the residual concentrations of KMnO4 were measured as described earlier (Section 2.3.1). Table 1 contains a list of the experimental conditions that were used in this study.

Table 1

Summary of the empirical conditions for adsorption of KMnO4 by S2

Experiment Adsorbate concentration (mg/g) Time of adsorption Adsorbent dose (g) pH Temperature (°C)
Dose impact 60 24 h 0.01–0.07 8.11 27
pH impact 500 24 h 0.05 1.5–11.5 27
Time impact 100, 200, 300 0–320 min 0.05 5.5 27
Temp. and KMnO4 conc. impact 10–1,400 360 min 0.05 5.5 27–57

The %R and q e (KMnO4 adsorbed at time t, mg/g) were calculated using equations (1) and (2), respectively, and q t was calculated using the following equation:

(3) q t = V m ( C 0 C t ) ,

where C t is the concentration of KMnO4 at time t.

2.3.3 Isotherm studies

The linear equations of the Temkin, Freundlich, and Langmuir isotherm models (Table 2) were used to analyze the outcomes of Section 2.3.2 for the adsorption of 10–1,400 (mg/L) KMnO4 solutions by S2 (0.05 g) at an interaction time of 360 min, pH 5.5, and temperatures ranging from 27 to 57°C. The values of R L (equilibrium parameter) associated with the Langmuir model’s essential characteristics were calculated using the following equation:

(4) R L = 1 1 + K L C 0 ,

where C 0 is the highest concentration of KMnO4 and K L is the Langmuir constant.

Table 2

Isotherm and kinetic models used in this work

Model name Linear equation Plot Constants
Isotherm models
Langmuir isotherm C e q e = 1 q max K L + C e q max C e q e vs C e q max = (slope)−1
K L = slope/intercept
Freundlich isotherm ln ( q e ) = ln ( K F ) + 1 n ln ( C e ) ln ( q e ) vs ln ( C e ) K F = exp(intercept)
n = (slope)−1
Temkin isotherm q e = B 1 ln ( K T ) + B 1 ln ( C e ) q e vs ln ( C e ) B 1 = slope
K T = exp (intercept/slope)
Kinetic models
Pseudo first order log ( q e q t ) = log ( q e ) K 1 t 2.303 log ( q e q t ) vs t k 1 = −slope
q e = exp(intercept)
Pseudo second order t q t = 1 K 2 ( q e ) 2 + t q e t q t vs t k 2 = (slope)2/intercept
q e = (slope)−1
Intraparticle diffusion q t = K dif t + C q t vs t K dif = slope
C = intercept

q max (mg/g): maximum adsorption capacity; K T, K F, and K L: constants of Temkin, Freundlich, and Langmuir, respectively; n: constants associated to intensity of adsorption; B 1: constants associated to the adsorption heat; q t and q e (mg/g): amount of CR adsorbed at time t and equilibrium (min), K 1 (1/min) and K 2 (g mg−1 min−1) rate constants of the kinetic models for first and second order, respectively; K dif (mg/g min−1)1/2: intra-particle diffusion rate constants; and C: another kinetic constant.

2.3.4 Kinetic studies

To determine the dynamic constants of this adsorption, the linear forms of the kinetic models listed in Table 2 were used to analyze the obtained data for the adsorption of 100, 200, and 300 mg/L of KMnO4 solutions by S2 at 27°C, pH 5.5, and different times (0–320 min) (Section 2.3.2). Hence, the kinetic constants can be used to determine the mechanism and rate of this adsorption.

2.3.5 Thermodynamic studies

The values of ∆G° (change in free energy), ∆S° (change in entropy), and ∆H° (change in enthalpy) for the adsorption of three KMnO4 solutions (50, 100, 200 mg/L) by S2 at the same empirical conditions of Section 2.3.3 were calculated by applying the following equations:

(5) ln q e C e = H ° RT + S ° R ,

(6) G ° = H ° T S ° ,

where T is the surrounding temperature (K) and R is the universal constant of gases.

3 Results and discussion

3.1 Structural characteristics of adsorbents

3.1.1 Analysis of FT-IR

The technique of FT-IR was used to reveal the influence of each chemical agent used in this work on the surface effective groups of T. polium L. (S1). The functional groups and corresponding FT-IR absorption bands for these four adsorbents (S1, S2, S3, and S4) are shown in Figure 1. This figure reveals that the T. polium L. (S1) has seven absorption bands at 3335.93, 2923.91, 2854.17, 1727.26, 1513.56, 1158.35, and 1025.46 (cm−1). These bands are related to stretching the hydrogen band of O–H, C–H (alkyl), C–H, C═O (aliphatic aldehydes), N–H (2°-amide), C–O, and C–H bending (in-plane), respectively. In the case of the modified samples (S2, S3, and S4), similar bands with minor shifts may be seen (Figure 1). Moreover, stretching of the N–H (1°-amide) II band at 1616.92 cm−1, C–H scissoring at 1454.89 cm−1, and C–H bending in out-of-plane at 780.67 cm−1 were detected only in the case of the sample modified by oxalic acid (S4). The outcomes of this part confirm that the chemical properties of the T. polium surface were slightly affected after modification by ZnCl2 as well as by a mixture of ZnCl2 and CuS, whereas these properties were significantly influenced by oxalic acid. Similar outcomes were reported in our previous research [29].

Figure 1 
                     Spectra of FT-IR for the adsorbents prepared in this work, the raw powdered T. polium leaves (S1), raw powder modified by ZnCl2 (S2), raw powder modified by a mixture of CuS and ZnCl2 (S3), and raw powder modified by H2C2O4 (S4).
Figure 1

Spectra of FT-IR for the adsorbents prepared in this work, the raw powdered T. polium leaves (S1), raw powder modified by ZnCl2 (S2), raw powder modified by a mixture of CuS and ZnCl2 (S3), and raw powder modified by H2C2O4 (S4).

3.1.2 Analysis of SEM

The SEM pictures of the adsorbent materials (S1, S2, S3, and S4) are shown in Figure 2. This figure shows that the picture of S1 (T. polium before modification) differs considerably from that of the chemically revised samples (S2, S3, and S4), whereas most pleats in the new adsorbents collapsed and their construction was disrupted. Furthermore, many different pores and holes that are beneficial to the adsorption process appeared on the adsorbent surface after the chemical modification processes.

Figure 2 
                     SEM images of the adsorbents prepared in this work.
Figure 2

SEM images of the adsorbents prepared in this work.

3.1.3 Analysis of BET and pHZPC

The results of the BET surface analyzer obtained in this work indicate that the surface area of S2 (3.689 m2/g) is greater than that of S1 (0.381 m2/g), S3 (2.644 m2/g), and S4 (0.768 m2/g). The findings of this section also showed that the pore size and pore volume of S1, S2, S3, and S4 are 151.07 Å and 0.00147 cm3/g; 570.20 Å and 0.01776 cm3/g; 527.40 Å and 0.01332 cm3/g; and 157.28 Å and 0.00667 cm3/g, respectively. This also implies that the pore properties of S2 are higher than those of S1, S3, and S4. This demonstrates that the modifications of S1 with ZnCl2 are successful in increasing the surface area and porosity of this raw material.

According to the plot of pHi–pHf against pHi (Figure 3), the solution pH at which the net charge on the surface of the optimal adsorbent (S2) will be zero is 6.4.

Figure 3 
                     pHZPC of the adsorbent of S2.
Figure 3

pHZPC of the adsorbent of S2.

3.2 Adsorption results

3.2.1 Performance of adsorbents

The percentages of KMnO4 removed from the solution and the quantities of this adsorbate adsorbed by S1, S2, S3, and S4 are shown in Table 3. This table demonstrates that S2 is the best and most effective adsorbent due to its high porosity and larger surface area, as shown in Section 3.1.3. Therefore, S2 was selected for the adsorption of KMnO4 in this study.

Table 3

Adsorption performance of the synthesized adsorbent

Adsorbent q e (mg/g) % R
S1 15.60 7.80
S2 141.85 70.92
S3 111.78 55.89
S4 122.15 61.07

3.2.2 Influence of the experimental circumstances

The values of % R (percentage of KMnO4 eliminated from solution) were plotted versus values of S2 doses (Figure 4a) to determine the optimum mass of S2 that can be used for KMnO4 adsorption. As demonstrated in Figure 4a, increasing the mass of S2 from 0.01 to 0.05 g increases % P values, which remain constant above 0.05 g. The augmenting of % R when the mass of S2 was raised in the first range of 0.01–0.05 g was due to increasing the adsorbent active sites [30]. The consistent % R values that were found when the mass of S2 increased over 0.05 g were due to the adsorbent particles forming a cluster assembly [31]. Thus, 0.05 g of S2 was chosen as the ideal dosage in this study.

Figure 4 
                     Impact of the experimental circumstances, adsorbent dose (a), solution pH (b), agitations time (c), and temperature and KMnO4 concentration (d).
Figure 4

Impact of the experimental circumstances, adsorbent dose (a), solution pH (b), agitations time (c), and temperature and KMnO4 concentration (d).

According to Wu et al. [32], if the pH of the adsorbate solution is less than, equal to, or greater than the pHZPC of this adsorbent, then the adsorbent surface will be positively charged, uncharged, and negatively charged, respectively. This indicates that the pH of the adsorbate solution affects the adsorption process. As a result, the impact of this component has been investigated in this study. The experimental results associated with the influence of solution pH on this adsorption are represented in Figure 4b. As shown in this figure, the values of q e are somewhat and abruptly lowered when the pH of the KMnO4 solution is raised in the ranges of 1.5–5.5 and 5.5–11.5, respectively. The first lowering resulted from a decrease in the electrostatic attraction between the permanganate anions and the positive charges that appear on the surface of S2 (pHZPC > pH) and are reduced as pH increases in the first range (1.5–5.5) [32], whereas the rapid decrease in the q e values observed in the second range (5.5–11.5) was due to the electrostatic repulsion between the negatively charged S2 surface (pHZPC < pH) and the anions of permanganate [32]. Adsorption of KMnO4 by leaf powder of N. retusa [23] and O. basilicum [24] and copper sulfide nanoparticles [15] produced almost similar outcomes.

The influence of agitation time was examined for the adsorption of 100, 200, and 300 mg/L of KMnO4 solutions by 0.05 g of S2 under the experimental conditions listed in Table 1. Figure 4c depicts the results of this section. This figure shows that increasing the adsorption duration from 0 to 192 min steadily enhances the quantity of q t (amount of KMnO4 adsorbed at time t) for each solution, and no variation can be noted in the amount of q t beyond this time (192 min). This is because all of the effective adsorption sites were initially empty before gradually filling up with MnO 4 anions throughout the adsorption period, which spanned from 0 to 192 min. After that, none of the sites were free to adsorb further anions of MnO 4 . The findings revealed that the equilibrium time is 192 min. The adsorption of KMnO4 on neem leaf powder yielded similar findings [22].

Figure 3d represents the outcomes of the tests that were conducted to evaluate the influence of temperature and concentration on this adsorption. Based on this figure, the temperature has a positive influence on adsorption in this study, indicating that adsorption is an endothermic process. This may be expounded by the fact that when the temperature rises, the KMnO4 solution viscosity decreases, and the kinetic energy of the KMnO4 particles increases [33]. Figure 4d further shows that as the KMnO4 concentration is raised from 10 to 1,200 (mg/L), q e (amount of KMnO4 adsorbed at equilibrium) increases and becomes practically invariable at 1,200 mg/L. This could be explained by the fact that increasing the KMnO4 concentration in the range of 10–1,200 mg/g reduced the resistance to mass transfer of KMnO4 particles between the solid (S2 surface) and liquid (KMnO4 solution) [34], while there is no available operative site to adsorb additional molecules of KMnO4 when the concentration is augmented above 1,200 mg/L. In addition, following each of the adsorptions indicated earlier, the supernatant solutions of KMnO4 were crystal clear and no solid objects could be observed in the solution with the naked eye, demonstrating the stability of the synthesized adsorbent in KMnO4 solutions [35].

3.2.3 Isotherm constants

The empirical isotherm data were analyzed using the linear equations of the Temkin, Freundlich, and Langmuir isotherm models to describe the interaction between MnO 4 ions and the surface of S2 and to determine whether these ions are adsorbed as a monolayer on a homogeneous surface or as a multilayer on a heterogeneous surface. Figure 5a–c represents the isotherm curves produced in this investigation for Temkin, Freundlich, and Langmuir, respectively. The values of the isotherm factors given in Table 4 were calculated using the intercepts and slopes of the curves of these figures. According to Figure 5 and the correlation coefficient of these three models (Table 4), the Langmuir is appropriate for modeling the adsorption of KMnO4 by the S2. As a result, a monolayer of KMnO4 adsorption on the homogenous surface of the adsorbent S2 is proposed [36]. Furthermore, values of dimensionless constant (n) greater than 1 and R L (Langmuir equilibrium parameter) smaller than 1 and higher than zero (Table 4) prove that KMnO4 is preferentially adsorbed by this adsorbent under the conditions used in this study [36]. The increasing temperature from 27 to 57°C enhances the maximum adsorption capacity (q max) from 833.33 to 1000.00 mg/g and the values of the Freundlich constant (K F) (Table 4) from 6.256 to 13.615 mg/g (L/mg)1/n , revealing that this adsorption is an endothermic process. The easy and clean separation of this adsorbent from the aqueous solutions after adsorption along with the great adsorption capabilities of 833.33, 909.09, and 1000.00 mg/g (Table 4) observed in this investigation demonstrate that S2 as a cheap and novel adsorbent would be of particular importance in the decontamination of wastewater and water from KMnO4.

Figure 5 
                     Temkin (a), Freundlich (b), and Langmuir (c) isotherm models for adsorption of KMnO4 by S2 (temperature = 27, 42, and 57°C; C
                        0 = 10–1,400 mg/L; m = 0.05 g; and time = 6 h).
Figure 5

Temkin (a), Freundlich (b), and Langmuir (c) isotherm models for adsorption of KMnO4 by S2 (temperature = 27, 42, and 57°C; C 0 = 10–1,400 mg/L; m = 0.05 g; and time = 6 h).

Table 4

Isotherm constants for adsorption of KMnO4 by S2

Name of the isotherm model Parameter Temperature (°C) Value
Temkin K T (L/mg) 27 0.171
42 0.243
57 0.339
B 1 27 120.00
42 128.85
57 137.64
R 2 27 0.896
42 0.894
57 0.922
Freundlich K F (mg/g) (L/mg)1/n 27 6.256
42 9.574
57 13.615
n 27 1.326
42 1.387
57 1.426
1/n 27 0.754
42 0.721
57 0.701
R 2 27 0.980
42 0.980
57 0.964
Langmuir q max (mg/g) 27 833.33
42 909.09
57 1000.00
K L (L/mg) 27 0.0045
42 0.0061
57 0.0087
R L 27 0.1370
42 0.1044
57 0.0763
R 2 27 0.994
42 0.991
57 0.996

3.2.4 Kinetic modeling

The linearized forms of the kinetic models applied in this research are shown in Figure 6. The values of the dynamic factors given in Table 5 were computed using the intercepts and slopes of the curves of the first- (Figure 6a) and second-order (Figure 6b) kinetic models. Table 6 shows the dynamic constants of the intraparticle diffusion model (Figure 6c). Based on the kinetic constants of the first- and second-order models (Table 5), the model of second order described the whole experimental data extremely well, with R 2 values higher than that of the first order. The settlement between the empirical values of q e and the values of q e estimated by the second-order model (Table 5) is the second indicator that confirms that the second-order model adequately describes the empirical kinetic data [37]. This shows that a chemisorption mechanism, which involves electron sharing, electrostatic attraction between the permanganate anions and the cations that appear on the surface of S2, or exchange between the functional groups on the S2 surface and MnO 4 anions, was controlling the rate of this adsorption [37].

Figure 6 
                     Kinetic models of the first order (a), second order (b), and intra-particle diffusion (c) for KMnO4 adsorption by S2 (temperature = 27°C; C
                        0 = 100, 200, and 300 mg/L; m = 0.05 g; and time = 0–320 min).
Figure 6

Kinetic models of the first order (a), second order (b), and intra-particle diffusion (c) for KMnO4 adsorption by S2 (temperature = 27°C; C 0 = 100, 200, and 300 mg/L; m = 0.05 g; and time = 0–320 min).

Table 5

Parameters of the first- and second-order kinetic models for adsorption of KMnO4 by S2

C 0 (mg/L) q e,exp (mg/g) Kinetic model
First order Second order
q e1,cal (mg/g) K 1 (h−1) R 2 q e2,cal (mg/g) K 2 (g/mg h) R 2 Rate
100 73.00 58.13 0.0177 0.992 78.74 0.00053 0.999 0.0417
200 150.83 126.44 0.0221 0.976 161.29 0.00032 0.999 0.0518
300 221.86 174.70 0.0196 0.973 238.10 0.00022 0.999 0.0516
Table 6

Parameters of the intra-particle-diffusion kinetic model for adsorption of KMnO4 by S2

C 0 (mg/L) First region Second region
K dif (mg/h1/2g) C R 2 K dif (mg/h1/2g) C R 2
100 7.938 –3.3252 0.992 1.0151 55.67 0.868
200 16.478 –1.6496 0.982 1.4782 125.68 0.905
300 24.659 –4.3888 0.991 2.9582 171.46 0.908

Figure 6c shows that the three plots are not linear over the entire time period; none of them passed from zero and have two linear regions with significant R 2 values (Table 6). This shows that there is some control over the boundary layer and that intraparticle diffusion is not the only rate-limiting process [38]. Identical results were found for MnO 4 sorption by Neem leaf powder [22] and for sorption of some dyes by activated carbons prepared from some agricultural wastes [39].

3.2.5 Outcomes of thermodynamic

The calculated ln(q e/C e) values for the adsorption of 50, 100, and 200 mg/L KMnO4 solutions by 0.05 g of S2 were plotted versus 1/T (equation 5) as illustrated in Figure 7. The values of ∆H° (change in enthalpy) and ∆S° (change in entropy) were estimated from the slopes and intercepts of the plots in this figure, respectively. The estimated ∆S° and ∆H° values (Table 7) were then inserted into equation (7) to get the ∆G° (change in free energy) values at each temperature (Table 7). The adsorption of KMnO4 is a chemical and exothermic process, based on the positive and high values of ∆H° (all >20.9 kJ mol−1) (Table 6) [40]. The adsorption of KMnO4 is a chemical and endothermic process, based on the positive and high values of ∆H° (all >20.9 kJ mol−1) (Table 7). The negative values of ∆G° (Table 7) prove that this adsorption is a spontaneous process [41]. Moreover, positive ∆S° values demonstrate that ∆S° rather than ∆H° is the driving factor for this adsorption [42]. The results discussed in this section are consistent with the temperature effect (Section 3.2.2) and kinetic results (Section 3.2.4).

Figure 7 
                     Thermodynamic parameters for KMnO4 adsorption by S2 (temperature = 27, 42, and 57°C; C
                        0 = 50, 100, and 200 mg/L; m = 0.05 g; and time = 6 h).
Figure 7

Thermodynamic parameters for KMnO4 adsorption by S2 (temperature = 27, 42, and 57°C; C 0 = 50, 100, and 200 mg/L; m = 0.05 g; and time = 6 h).

Table 7

Thermodynamic constants for KMnO4 adsorption by S2

Initial concentration (mg/L) H° (kJ mol−1) S° (kJ mol−1) G° (kJ mol−1) R 2
300 K 315 K 330 K
50 38.424 0.1381 –3.0147 –5.0866 –7.1585 0.932
100 35.325 0.1269 –2.7494 –4.6531 –6.5568 0.991
200 24.245 0.0891 –2.5100 –3.8478 –5.1855 0.999

4 Comparative evaluation of low-cost adsorbents

Table 8 summarizes the uptake capabilities of T. polium leaf powder modified by ZnCl2 (S2) and the adsorbents earlier employed to eliminate KMnO4 from aqueous solutions. Based on this table, the adsorbent utilized in this study (S2) has the highest uptake capacity. The obtained uptake performance of this adsorbent, its stability, and its cheapness demonstrate that T. polium leaf powder modified by ZnCl2 will be given important consideration in the treatment of water and wastewater.

Table 8

Adsorbents used for adsorption of KMnO4

Adsorbents q max (mg/g) Sources
Modified T. polium L. (S2) 833.33 27°C This work
909.09 42°C
1000.00 57°C
N. retusa leaf powder 312.50 30°C [23]
333.33 50°C
344.83 60°C
O. basilicum leaf powder 588.24 25°C [24]
625.00 30°C
666.67 45°C
714.29 45°C
Modified Lamiaceae leaves 333.33 25°C [43]
384.62 35°C
434.78 45°C
476.19 60°C
Corn cob powder 46.28 [44]
Teak tree bark 333.00 [45]
Leaves of Neem 60.60 [46]
Sugar beet pulp 250.02 [47]
Orange peel modified by phosphoric acid 307.64 [48]
Sunflower seed husk 45.26 [49]
Mushroom waste as a substrate 63.50 [50]
Powder of mango leaves 156.00 [51]

5 Conclusions

The highest percentage of KMnO4 removed from the solution (70.92%) and the maximum amount of this adsorbate adsorbed (141.85 mg/g) were obtained when the sample was modified by zinc chloride (S2). As a result, S2 was chosen as the unique adsorbent discovered in this study. It was found that increasing the mass of S2 from 0.01 to 0.05 g, the adsorption duration from 0 to 192 min, and the KMnO4 concentration from 10 to 1,200 mg/L, increases the adsorption amounts, which thereafter remain constant above 0.05 g, 192 min, and 1,200 mg/L, respectively. When the pH of the KMnO4 solution is elevated in the ranges of 1.5–5.5 and 5.5–11.5, in that sequence, the values of q e are slightly and suddenly dropped. Langmuir and second-order models are the most suitable for modeling the experimental data of this adsorption. Kinetics and thermodynamics data validated the endothermic, spontaneous, and chemical processes of this adsorption. The cheapness of T. polium leaves and ZnCl2, its stability in the chemical solutions, the easy and clean post-adsorption separation of this adsorbent from the aqueous solutions, and the high adsorption capacities (833.33, 909.09, and 1000.00 mg/g) obtained demonstrate that S2 will receive special attention in the field of treating contaminated water.

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The authors are grateful to the Nanotechnology Research Unit, Faculty of Science, University of Tabuk, for providing us with the devices we needed to complete this research.

  1. Funding information: The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

  2. Author contributions: H.A.A. and N.A.A. designed the research plan and drafted, revised, and formatted the manuscript. H.A.A. performed the experimental work and data compilation. N.A.A. coordinated the work and discussed the results. All authors have read and agreed to the published version of the manuscript.

  3. Conflict of interest: The authors have no relevant financial or non-financial interests to disclose.

  4. Ethical approval: The conducted research is not related to either human or animal use.

  5. Data availability statement: All data generated or analyzed during this study are included in this published article.


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Received: 2022-06-06
Revised: 2022-07-16
Accepted: 2022-07-27
Published Online: 2022-08-15

© 2022 Hatem A. AL-Aoh and Nasser A. Alamrani, published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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