43 Journal of Multidisciplinary Applied Natural Science Vol. 3 No. 1 (2023) Research Article Chemical Regeneration of A Dye-Laden Activated Carbon: Optimization via The Box-Behnken Experimental Design Enebi Estella Jasper*, Jude Chinedu Onwuka, and Edith Bolanle Agbaji Received : July 23, 2022 Revised : October 10, 2022 Accepted : October 10, 2022 Online : October 22, 2022 Abstract Activated carbon is widely used as an adsorbent to remove numerous pollutants from water and wastewater. The cost-effectiveness of an adsorbent depends upon its ability to be reused. This study focuses on regenerating Millettia thonningii seed pods' activated carbon (MAC) saturated with Methylene Blue (MB) using acetic acid as a regenerating solvent and exploring its potential to be reused. The effects of the variables such as, the concentration of the regenerating solvent, contact time, and volume of regenerating solvent on the regeneration process were ascertained using the Box-Behnken experimental design, which is a sub-set of Response Surface Methodology. The regeneration process was evaluated based on the desorption capacity of the active carbon. Scanning Electron Microscopy (SEM) and Fourier Transform Infrared spectroscopy (FTIR) was used to characterize the surface of the saturated active carbon before and after regeneration. Results revealed that the concentration of the regenerating solvent had the most significant synergistic effect on the regeneration process. The optimum conditions for the maximum regeneration of the spent activated carbon within the range of the variables studied were found to be: 8M acetic acid, 100 min, and 40 mL of acetic acid. The regenerated and pristine MAC when reused to adsorb fresh MB solutions (50 ml of 10mg/L MB: 0.2g adsorbent) had an adsorption capacity of 2.1912mg/g and 2.0977mg/g for MB respectively. Hence, the regenerated carbon outperformed the pristine active carbon. It could therefore be explored further as a recyclable adsorbent for wastewater treatment. Keywords active carbon, regeneration, desorption, reusability, experimental design 1. INTRODUCTION Dye laden active carbons obtained from wastewater treatment processes pose a significant threat when disposed directly into the environment due to the possibility of the dye leaching. A sustainable approach to mitigating the environmental impact of such secondary pollutant is to regenerate the spent active carbon [1]. Regeneration and reuse of spent adsorbents ensures that the entire remediation process is cost-effective [2]. The regeneration process basically shifts the adsorption equilibrium from adsorption to desorption. Several techniques have been used to regenerate spent active carbon, such as the thermal method [3][4], the chemical method [5], and the microwave-assisted regeneration method [6]. Chemical regeneration is a simple technique in which acids, alkalis, and organic solvents with either oxidizing or solubilizing capacity are used to dissolve adsorbates and restore the adsorption ability of the active carbon. The chemical regeneration method has the main advantages of high regeneration efficiency, almost zero carbon loss, quick regeneration, and possible adsorbate recovery. It is useful, especially when adsorbates form strong bonds with the adsorbent's surface [7]. Larasati et al. [8] identified chemical regeneration as a viable alternative to the most commonly used off-site thermal regeneration because it can be performed both in-situ and on-site. Among other adsorbents, the chemical regeneration method has been successfully used in the regeneration of acid green 25 dye saturated waste biomass [9] and methylene blue-saturated bentonite [10]. Ghasemzadeh et al. [4] used hydrofluoric acid to regenerate dye-saturated active carbon and were able to achieve significant regeneration. To regenerate spent activated carbon, Nasiruddin et al. [11] used HCl and hot water. Marion-Peacok et al. [12] demonstrated that chemically regenerated active carbon outperformed thermally regenerated active carbon in a water cleaning system. The chemical regeneration of active carbon saturated with Methylene Blue (MB) dye is the basis for this research. It is cost-effective to regenerate spent active carbon for reuse during the sorptive removal of pollutants from wastewater. The regeneration of methylene blue-saturated Publisher’s Note: Pandawa Institute stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the author(s). Licensee Pandawa Institute, Metro, Indonesia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-ShareAlike (CC BY-SA) license (https://creativecommons.org/licenses/by-sa/4.0/). https://doi.org/10.47352/jmans.2774-3047.144 OPEN ACCESS https://creativecommons.org/licenses/by-sa/4.0/ https://doi.org/10.47352/jmans.2774-3047.144 https://crossmark.crossref.org/dialog/?doi=10.47352/jmans.2774-3047.144&domain=pdf&date_stamp=2022-10-22 https://creativecommons.org/licenses/by-sa/4.0/ J. Multidiscip. Appl. Nat. Sci. 44 Millettia thonningii seed pods active carbon (MB- MAC) is investigated in this paper using the Box- Behnken experimental design (BBD), a subset of the Response Surface Methodology (RSM). RSM is a multivariate statistical experimental approach to systematically solving problems. The primary objectives of using experimental design in analytical processes are to obtain optimal and statistically valid results with minimum effort, time, and resources [13][14]. The Box-Behnken experimental design ensures that the relationship between a response and the factors influencing it is understood. It also aids in determining the values of the operating factors or variables that will ensure response parameter optimization by conducting fewer experiments. It has been used to optimize a variety of analytical systems, including the production of activated carbon from agricultural residues [15]–[18], the adsorption of dyes, heavy metals, and antibiotics from aqueous solutions [19] –[21], chromatographic method optimization [22], and a variety of other physical and chemical processes. When compared to the univariate or one- factor-at-a-time (OFAT) experimental approach and other types of response surface methods, the BBD is usually very efficient in terms of the number of required experiments, making it less expensive to run. It is also preferred over other RSM designs because it does not contain combinations in which all of the factors are at their highest or lowest levels simultaneously thus, avoiding experiments performed under extreme conditions that may result in unsatisfactory results. Despite a large number of studies on chemical regeneration of spent activated carbon, it has been discovered from literature that little work has been done on the statistical optimization of process conditions for the chemical regeneration of dye-saturated activated carbons. The novelty of this study is the attempt to regenerate dye-saturated activated carbon using a 3- factor-3-level Box-Behnken design (BBD). This study will use the BBD to evaluate the effects and interactions of the regenerating solvent concentration, volume of regenerating solvent, and contact time on the regeneration of Methylene blue- saturated M. thonningii seed pods activated carbon, as well as to determine the optimum conditions of these variables that will result in the maximum MB desorption capacity of the spent MAC. Scanning Electron Microscopy (SEM) and Fourier Transform Infrared spectroscopy (FTIR) were used to confirm the regeneration of the activated carbon. The suitability of regenerated carbon for reuse was also assessed based on its adsorption of methylene blue dye. 2. MATERIALS AND METHODS 2.1. Materials The activated carbon used in this study was prepared according to the method described by Jasper et al. [23]. Methylene blue dye, acetic acid and tetraoxo-sulphate (vi) acid were used as reagents. All of the reagents used were of analytical quality. All solutions used in this study were prepared with de-ionized water. 2.2. Methods 2.2.1. Initial Adsorption Experiments 4 g of fresh M. thonningii seed pod activated carbon (MAC) was agitated for 180 minutes with 100 mL of 250 mg/L Methylene blue (MB) dye solution at pH 7. The spent MAC was filtered from the solution, washed with deionized water to remove any unadsorbed dye, and oven-dried for 1 hour at 100 °C. 2.2.2. Screening of suitable regenerating solvents To find the best solvent for desorption of the Table 1. Levels of factors in the BBD for the Regeneration of Spent MAC. Factors Codes Box Behnken levels [Regeneration Solvent](M) A 2 5 8 Contact time(min) B 20 60 100 Solvent volume(mL) C 10 25 40 J. Multidiscip. Appl. Nat. Sci. 45 retained dye on MAC, 0.1 g of dye-saturated MAC was mixed separately in three different Erlenmeyer flasks with 50 mL of 0.1 M H2SO4, 0.1 M CH3COOH, and deionized water . The resulting mixtures were agitated for 60 minutes before being separated and the supernatants concentration determined using UV-Vis spectrophotometry (664nm for MB). Equation 1 was used to compute the desorption efficiency [24]. (1) where, where Cd is the concentration of dye desorbed (mg/L) and Ca is the dye adsorbed amount (mg/ L). For the following experiments, the solvent with the highest dye recovery was used. 2.2.3 Optimization of the Regeneration of Spent MTSPAC using the Box-Behnken Design The BBD was used to investigate the optimization of factors that affect the regeneration of MB-saturated MAC. The parameters investigated were the regenerating solvent concentration (CH3COOH), the volume of regenerating solvent, and the contact time. After screening for suitable solvents, acetic acid was chosen as a regenerating solvent because it provided the highest percent desorption. The levels of experimental parameters used for the optimization study are shown in Table 1. The BBD created 15 randomized experimental runs with three replicated center points for the optimization experiments based on the equation (2). (2) where N represents the total number of experiments, n represents the number of variables or factors, and p represents the number of center points. Centre points are experimental runs in which the factors are set at the medians of their high and low levels. To improve experiment precision, the Table 2. Percent MB desorbed by various solvents from saturated MAC. Solvent %MB Desorbed CH3COOH 1.68 H2SO4 0.27 Deionized H2O 0.24 Figure 1. Effect of (a) contact time and acetic acid concentration on the amount of dye desorbed (b)acetic acid concentration and solvent volume and (c)contact time and solvent volume at holding values of 25 ml solvent volume, 60 min contact time and 5M acetic acid concentration J. Multidiscip. Appl. Nat. Sci. 46 center point is replicated. Table 3 shows the complete design matrix generated by Minitab Software, Version 17.0, based on the range of process variables (Minitab Inc., USA). In each run, different volumes of the desorbing solvent, CH3COOH, were contacted with 0.2 g of MB- saturated MAC at contact times ranging from 20- 100 min in 150 mL stoppered Erlenmeyer flasks at different initial concentrations as specified in Table 3. All samples were centrifuged at 500 rpm for 5 minutes after they were removed from the flasks. The concentrations of residual MB solutions were measured using UV-Vis spectrophotometry at 664 nm, and the amount of dye desorbed qe(mg/g) was calculated using Equation (3). (3) where V = volume of solvent (L); m = mass of adsorbent (g) and Cf = dye concentration in solvent (mg/L). The experimental data obtained was subjected to statistical treatment which included a multiple regression analysis and an analysis of variance (ANOVA) in order to derive suitable second-order polynomial regression model equations which could express each predicted response (Y) as a function of the independent preparation variables (factors) by fitting the quadratic polynomial function (Eq. 4) to the data set. (4) where α0-23, are regression coefficients, α0 is a constant term; α1, α2, and α3 are linear effect terms; α11, α22 and α33 are the square effect terms and α12, α13, and α23 are cross-product or interactive effect terms. A, B, and C are the coded independent variables that represent the important factors affecting the process being carried out and Y is the particular response being evaluated. The data was analyzed with the Minitab 17.0 software, and the optimum conditions for regenerating the spent activated carbon, that is, the settings that could obtain the highest amount of MB desorbed, were obtained using the software's optimization functions. Experiments were carried out in triplicate at the optimal settings to validate the software's predictions. 2.2.4. Evaluation of the Adsorption capacity of MAC Regenerated at Optimum Conditions Adsorption experiments were conducted in separate Erlenmeyer flasks by agitating 10 mg/L of MB with 0.2 g pristine MAC and regenerated MAC Table 3. BBD matrix for the optimization of the regeneration of MB-saturated MTSPAC. Run [CH3COOH] (mol/L) Contact time(min) Solvent volume (mL) MB Desorped (mg/g) 1 5 60 25 0.0665 2 8 20 25 0.1268 3 2 20 25 0.0144 4 5 100 40 0.1575 5 5 60 25 0.0634 6 2 100 25 0.0011 7 5 20 10 0.0260 8 8 60 40 0.2415 9 2 60 40 0.0216 10 8 100 25 0.2250 11 8 60 10 0.0758 12 5 60 25 0.0674 13 5 20 40 0.0766 14 2 60 10 0.0061 15 5 100 10 0.0270 J. Multidiscip. Appl. Nat. Sci. 47 per 50 mL of dye for 120 minutes, and their adsorption capacities for MB were determined using Eq. 5. (5) Where Co, Ct (mg/L) are the liquid phase concentrations of the dye at initial, and any time t, respectively, V is the volume of solution (L) and m is the mass of the dry adsorbent (g). 2.2.5. Surface and Morphological Characterization of the Regenerated MTSPAC The morphology and surface functional groups of the active carbon regenerated under optimal conditions were compared to those of the MB- loaded MAC and the pristine MAC using Scanning Electron Microscopy (Phenom Pro X, Netherlands) and Fourier Transform Infrared Spectroscopy (FTIR -CARY 630, Agilent Technologies). 3. RESULTS AND DISCUSSIONS 3.1. Solvent Selection The regeneration of spent activated carbon assumes paramount importance considering its economic reuse during the sorptive removal of pollutants from wastewater. Of the three solvents tested for their suitability in the regeneration of spent carbon, CH3COOH removed the most dye (Table 2) and was thus chosen as the regenerating solvent for subsequent experiments. Organic solutions with lower molecular weight than adsorbate have been reported to be effective regenerant solutions [25]. 3.2. Experimental Design and Statistical Analysis The regeneration of the spent M. thonningii seed pods' active carbon was evaluated as a function of its the methylene blue desorption capacity. The results of the desorption experiments are shown in Table 3. The amount of MB desorbed per gram of spent MAC ranges from 0.0011 to 0.2415 mg/g, with the lowest value obtained at factor settings of 25 ml of 2 M acetic acid for a contact time of 100 minutes and the highest value obtained at factor settings of 40 ml of 8M acetic acid for a contact time of 60 minutes. The center points are replicate measurements taken on runs 1, 5, and 12 to determine the precision of the experiments. 3.3. Regression Analysis and ANOVA Interpretation Multiple regression analysis was performed on the experimental data (Table 3) to obtain a polynomial equation that correlates the response Source DF Adj SS Adj MS F-Value P-Value Model 7 0.080668 0.011524 198.40 <0.001 A: [Acetic acid] mol/L 1 0.048969 0.048969 843.06 <0.001 B: Contact time(min) 1 0.003478 0.003478 59.87 <0.001 C: Solvent vol (mL) 1 0.016408 0.016408 282.48 <0.001 A 2 1 0.001469 0.001469 25.29 0.002 AB 1 0.003108 0.003108 53.51 <0.001 AC 1 0.005640 0.005640 97.10 <0.001 BC 1 0.001596 0.001596 27.48 0.001 Error 7 0.000407 0.000058 Lack-of-Fit 5 0.000398 0.000080 18.07 0.053 Pure Error 2 0.000009 0.000004 Total 14 0.081074 R-sq 99.50% R-sq(adj) 99.00% R-sq(pred): 96.72% S 0.0076213 Table 4. ANOVA for final response surface quadratic model for the regeneration of MB-saturated MAC J. Multidiscip. Appl. Nat. Sci. 48 variable, Y, that is, the amount of MB desorbed, to the independent variables (regenerating solvent concentration (CH3COOH), volume of regenerating solvent, and contact time). Eq. 6 depicts the final model equation obtained after removing statistically insignificant terms. (6) An analysis of variance (ANOVA) was used to determine the statistical significance of the model equation, which included a Fisher's F-test and its associated probability, p (F), at the 95 % confidence level. The large value of F indicates that the regression equation can explain the majority of the variation in the response, while the associated p- value estimates whether F is large enough to indicate statistical significance. The model is statistically significant if the p-value is less than 0.05. Table 4 showed that the model with an F- value of 198.40 and p< 0.0001 was statistically significant. The model had a high coefficient of determination, R 2 of 99.50, indicating that only 0.50 % of the variability in the response was not explained by the model. The adjusted R 2 value, R 2 (adj), which represents the proportion of the data that the model accounts for, was also high, at 99.00 %. The model's predictive ability was also statistically acceptable, with a high R 2 -pred value of 96.72 %. The R 2 (adj) and R 2 (pred) were in reasonable agreement, falling within about 20% of each other [25][26]. The ANOVA results also show a lack-of-fit (LoF), which was not statistically significant because the p-value was greater than 0.05. The hypothesis is that if the LoF is not statistically significant, the model is adequate; if the LoF is statistically significant, the model is unfit to represent the data [27].The statistical findings support the model's good predictability and adequacy within the reasonable range of the variables studied. The effect of the regenerating solvent (CH3COOH) concentration (A), contact time (B), and solvent volume (C) on the amount of MB desorbed was also investigated. According to the ANOVA results (Table 4), all linear factors (A, B, and C) had a statistically significant influence on methylene blue desorption, as indicated by p-values of < 0.001. With the highest F-value of 843.06, the concentration of the regeneration solvent, A, had the most significant effect on the amount of MB desorbed, followed by solvent volume (F=282.48) and contact time (F=59.87). The positive sign of the coefficients in the regression model Eq. 6 indicates that all linear factors had a synergistic effect on the response variable, which means that as all factors increased, so did the amount of dye desorbed. 3.3.1. Response Surface Plots 3-D response surface plots were constructed to show the effects of the regeneration variables on the response, desorption capacity of methylene blue (Fig 1). Response surface plots explain the nature of the relationship between two factors on the response while holding a third factor constant. Figure 1a shows the response plot for contact time and acetic acid concentration. Within the range of variables, the MB desorption capacity gradually increased with increasing contact time and acetic acid concentration. This finding could be attributed to an increase in the presence of H+ as a result of the acetic acid displacing dye molecules from the adsorbent pores increasing in concentration. With increased regeneration contact time, it appears that more pores were re-opened. Figure 1b shows the Figure 2. Main effects plots for the regeneration of MB-saturated MTSPAC. Adsorption Capacity Pristine MAC (mg/g) Adsorption Capacity Regenerated MAC (mg/g) 2.0977 2.1912 Table 5. Adsorption capacity of the pristine and regenerated MAC J. Multidiscip. Appl. Nat. Sci. 49 response plot with respect to acetic acid concentration and solvent volume, which shows a similar response to Figure 1a. The plot demonstrates that the maximum desorption capacity was obtained at the highest solvent volume and concentration. Fig 1 c shows that at a concentration of 5M, contact time had little effect on the response; however, increasing the solvent volume resulted in a significant increase in the response value. 3.3.2. Main Effects and Interaction Plots The Main effects plots depicted in Fig. 2 show the extent of each factor's individual effects. The main effect plot contains useful information about the relative importance of each factor parameter on the response. Main effect plots compare changes in level means to determine which factors have the greatest influence on the response: when the line is parallel to the x-axis, there is no main effect. The main effect, however, appears when the line is not parallel to the x-axis. The slope of the plot represents the relative strength of the factors' effect [28]. A steeper slope indicates that the process factor has a greater impact on the response. Based on this premise, the acetic acid concentration had the greatest influence on the regeneration process. The increase in MB desorption from spent carbon with increasing acetic acid concentration could be explained by the accumulation of H + in solution, which competes with the dye ions on the adsorbent's surface, resulting in the release of MB + ions from the adsorbent thus favoring the desorption process. The mean was higher than average for CH3COOH concentrations greater than 5M, times greater than 60 minutes, and volumes greater than 25 mL, with a peak value obtained at 8M CH3COOH concentration. Figure 2 clearly shows that the factors influenced the amount of MB desorbed in the following order: acetic acid concentration > solvent volume > contact time. Figure 3 depicts the interaction plots for the response, MB desorbed. Interaction plots show how Figure 3. Interaction effects between (a) acetic acid concentration and contact time (b) acetic acid concentration and solvent volume (c) contact time and solvent volume for the Regeneration of MB- saturated MTSPAC. Figure 4. Optimization plots for the regeneration of MB-saturated MTSPAC. J. Multidiscip. Appl. Nat. Sci. 50 the relationship between one factor and the response is affected by the value of a second factor. When the lines are more non-parallel, there is more interaction. It can be seen that there is an interaction between A and B; A and C and B and C due to the non-parallel lines. The variability in MB desorption is greatest when the acid concentration and solvent volume are both increased. The MB desorption is found to be less sensitive to changes in contact time and solvent volume. Also significant are the interactions between A and B, A and C, and B and C (Table 3). 3.3.3. Optimization and Validation Response optimization with the Minitab software was used to determine the factor settings that could achieve the maximum MB desorption capacity of the spent active carbon. The response optimization plot(Fig. 4) shows that the optimum experimental conditions of 8M acetic acid, 100 min contact time, and 40 mL solvent volume with a predicted response of 0.31881mg MB per gram of activated carbon were obtained with a desirability function of 1.0. The experiments performed to validate these predictions and justify the accuracy of the results yielded an average of 0.3065mg MB per gram of activated carbon. 3.3.3. Adsorption Capacity of Pristine and Regenerated MAC Table 5 shows that the adsorption capacity of the MB-saturated MAC regenerated under optimal conditions was 2.1912mg/g while that of the pristine MAC was 2.0977mg/g. This means the regenerated MAC produced at optimal settings outperformed the pristine MAC. The treatment of spent activated carbon with acetic acid may have resulted in the formation of more active sites on the carbon's surface, enhancing the activated carbon's ability to adsorb greater amounts of methylene blue. 3.4. SEM and FTIR Analysis of Regenerated Spent MAC Fig 5a depicts the surface of MAC before adsorption; it is characterized by a smooth porous surface. After MB adsorption (Fig 5b), the surface appears rough and corroded due to the surface pores being covered by MB dye molecules. The SEM micrograph obtained on regeneration (Fig 5c) shows the reappearance of several pores of different sizes when compared to the saturated MAC (Fig 5 b). This shows evidence of successful regeneration of the carbon when compared to that of the post adsorption micrograph (5b). This indicates that the Figure 5. SEM micrographs of (a) fresh MTSPAC (b) MB-loaded MTSPAC and (c) Regenerated MTSPAC-MB at x 1000 magnification. J. Multidiscip. Appl. Nat. Sci. 51 regeneration of spent active carbon by chemical activation can create a well-developed porous structure. The FTIR spectra of the pristine, MB-saturated, and regenerated MAC are displayed in Fig. 6a, b, and c respectively. Relevant peaks attributable to special functional groups such as peaks at 3906.3 cm -1 , 3824.2 cm -1 , 3652.8 cm -1 ,3593.2 cm -1 (which could be assigned to OH-, NH- and CH- stretching vibrations), 2325.9cm -1 (C=O stretching vibration) and 1994.1 cm -1 (aromatic C=C stretching) disappeared after adsorption, while other peaks were displaced, confirming surface interaction with MB. Attenuation of peak intensity or a displacement of a peak in a spectrum is evidence of a change associated with a bond on the activated carbon [29] [30]. Fewer peaks were observed in the fingerprint region of the spectrum of the regenerated MB– MAC (Fig 6c) compared to the spectrum of the active carbon when saturated with MB (Fig 6b) indicating the decomposition of adsorbed material upon regeneration. A marked observation made upon regeneration is the reappearance in Fig 6c of four peaks (3652.8 cm -1 , 2109.7 cm -1 , 1994.1 cm -1 , 1688.5 cm -1 ) that were present on the spectrum of the active carbon before adsorption, which which is indicative of regeneration of the MTSPAC to a certain extent. The spectrum of the regenerated MB - MTSPAC (Fig 6c) however had a very close semblance with the spectrum of the activated carbon before adsorption (Fig 6a). This observation could be attributed to the long regeneration contact time which might have led to the desorption of almost all dye molecules adhered to it post adsorption, thus restoring the carbon to its near- original state. Figure 6. FTIR Spectra of (a) pristine MTSPAC (b) MB-loaded MTSPAC and (c) Regenerated MB- MTSPAC. J. Multidiscip. Appl. Nat. Sci. 52 4. CONCLUSIONS The regeneration of spent Millettia thonningii seed pods' active carbon has been examined and optimized with respect to dye desorption capacity. Box–Behnken experimental design, a subset of Response Surface Methodology was used to locate the optimum operating variables (the concentration of the regenerating agent, acetic acid, solvent volume, and contact time) to maximizing the dye desorption capacity of the spent MAC. While all the factors and their interactions significantly influenced the regeneration process, the concentration of the regenerating agent, acetic acid, had the most significant influence on the process. The optimum conditions for the operating factors for the maximum regeneration of the spent activated carbon within the range of the variables studied were found to be: 8M acetic acid, 100 min, and 40 mL of acetic acid. The maximum amount of methylene blue desorbed approached 0.3065 mg/g under these experimental conditions.. The results reveal that the regenerated MAC could be reused and as such has a potential application as a recyclable adsorbent for the treatment of wastewater. Its reusability should be explored further. AUTHOR INFORMATION Corresponding Author Enebi Estella Jasper — Department of Applied Chemistry, Kaduna Polytechnic, Kaduna State - 8000014 (Nigeria); orcid.org/0000-0002-6563-822X Email: enebijasper@gmail.com Authors Jude Chinedu Onwuka — Department of Science Laboratory Technology, Federal University Lafia, Nasarawa State - 960107 (Nigeria); orcid.org/0000-0003-2950-8273 Edith Bolanle Agbaji — Department of Chemistry, Ahmadu Bello University, Kaduna State - 8000014 (Nigeria); orcid.org/0000-0002-6934-5360 Author Contributions E. E. J. conceptualized, designed, and performed the experiments, analyzed the results and drafted the manuscript. J. C. 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