RESEARCH ARTICLE

 

Synthesis and characterization of magnetic chitosan-polypyrrole composite for adsorption of tetracyclines from contaminated water

 

 

Mpho C. Lefatle^{I, II}; Lawrence M. Madikizela^III; Vusumzi E. Pakade^IV; Philiswa N. Nomngongo^{I, II, *}

^IDepartment of Chemical Sciences, University of Johannesburg, Doornfontein, South Africa
^IIDepartment of Science and Innovation-National Research Foundation South Africa Research Chair Initiative (DSI-NRF SARChI) in Nanotechnology for Water, University of Johannesburg, Doornfontein, South Africa
^IIIInstitute for Nanotechnology and Water Sustainability, College of Science, Engineering and Technology, University of South Africa, Roodepoort, South Africa
^IVDepartment of Chemistry, College of Science, Engineering and Technology, University of South Africa, Roodepoort, South Africa

 

 

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ABSTRACT

The extensive consumption of tetracyclines (TCs) has gained attention due to their toxic effect. The current study reports the synthesis and characterization of magnetic chitosan-polypyrrole (Cs-PPy-Fe₃O₄) composite, which was then used for the adsorption of TCs from aqueous solutions. The synthesized adsorbent had a surface area, pore volume, and pore size diameter of 129 m² g^-1, 0.32 cm³ g^-1, and 9.9 nm, respectively. Furthermore, the adsorbent had an elemental composition of C (53.6%), O (18.0%), N (12.4%), Fe (12.4%) and O (18.0%). Box-Behnken design (BBD) was used to investigate the effects of various parameters affecting the adsorption of TCs onto Cs-PPy-Fe₃O₄ composite. The results displayed that the sorption of the TCs onto Cs-PPy-Fe₃O₄ composite followed pseudo-first-order and best fitted the Langmuir isotherm model with adsorption capacities of 112, 95, 94, and 93 mg g^-1 for oxytetracycline, tetracycline, chlortetracycline, and doxycycline, respectively. Thermodynamic studies revealed that the adsorption of the analytes onto the Cs-PPy-Fe₃O₄ composite was physical with exothermic and increasing entropy. Furthermore, as the eluting solvent, the adsorbent could be regenerated using methanol and 0.01 oxalic acid (20:80 v/v). Therefore, the Cs-PPy-Fe₃O₄ composite could be a promising adsorbent for the simultaneous removal of TCs in water.

Keywords: tetracyclines; box-behnken design; adsoption isotherms; kinetics; regeneration

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INTRODUCTION

Drinking water is becoming extremely limited worldwide.¹ In 2017, the World Health Organization (WHO) reported that 10.5% of the global population (785 million) were deprived of clean drinking water, while 297,000 children under the age of 5 and 828,000 people die every year from diarrhoea-related diseases because of unsafe drinking water, poor sanitation and poor hygiene.² Furthermore, the world's population is continuing to rise, and it has been estimated that the world's population rose from 1 billion to nearly 7.6 billion in 2017. Additionally, it is estimated that by 2030 and 2050, the global population will increase to approximately 8.6 billion and 9.8 billion, respectively.³ This increase in population will further result in increased water demand. It is further estimated that half of the world's population will be living in severe water stress by the year 2030.⁴ The severe water stress is caused by, among other things, contamination of water by macro pollutants, inorganic chemicals (such as heavy metals), polycyclic aromatic hydrocarbons, microorganism and micropollutants (such as parabens, fragrances, and pharmaceuticals).⁵ Tetracyclines (TCs) are antibiotics frequently used as animal food additives and medicine for treating diseases. However, excessive use and lack of proper disposal and management of tetracyclines have resulted in their introduction into water resources, soil pollution, and bacteria gaining resistance.⁶ The residues of antibiotics found in water bodies can be life-threatening to exposed humans due to their health effects as they can affect the development of teeth and bones, with an ability to cause hepatotoxicity.⁷ Therefore, it is essential to monitor the occurrence of TCs in water bodies and develop their removal strategies in contaminated water. This is important considering that TCs are becoming prevalent in water bodies with recent data showing the presence of TC in groundwater with a concentration of 184 ng L^-1.⁷ Amongst the treatment technologies developed for the remediation of TCs in water, adsorption has emerged as a method of choice due to its simple operation, cost-effectiveness, and high removal efficiencies.⁸

One of the mainstays of adsorption techniques in water treatment is the choice of adsorbent material, and various sorbents have been used. These adsorbent materials include zeolites,⁹ activated carbon,¹⁰ carbon nanotubes,¹¹ clays,¹² metal-organic frameworks¹³ and polymers.¹⁴ Among these adsorbents, activated carbon is the most frequently investigated sorbent in water and wastewater purification/treatment.¹⁵ However, activated carbon has drawbacks, such as reduced selectivity and modification flexibility.¹⁶ In recent years, the application of composite materials in treating water contaminated with antibiotics has emerged.^17-19 Composite materials can be produced from carefully selected chemicals and materials. Each contributes certain characteristics desired to complete the whole composite while enhancing the adsorption and removal of the targeted pollutants. For instance, in the preparation of a polypyrrole-iron oxide nanocomposite for the treatment of pharmaceuticals in water, the incorporation of iron oxide nanoparticles²⁰ was found to enhance the processability of polypyrrole (PPy) substrates²¹ because PPy is an insoluble granular material made of intractable brittle thin films.²² Although the incorporation of iron oxide nanoparticles may improve the processability of the PPy conducting polymer and thus its adsorption performance and removal of pollutants, PPy-Fe₃O₄ nanocomposites have low adsorption capacity.²³ This could be due to the tendency of Fe₃O₄ to form aggregation owing to their high surface energy.²⁴ Iron oxide nanoparticles are encapsulated inside a polymer to mitigate this drawback. Recently studies reported the application of chitosan-polypyrrole-iron oxide (Cs-PPy-Fe3O4) nanocomposite adsorbent in removing carbamazepine, chromium, and naproxen from water. ^25-27 In these studies, including chitosan aided the encapsulation of Fe₃O₄ and thus mitigating the agglomeration while enhancing the removal performance.^25-27

However, to our knowledge, no work has been published on employing Cs-PPy-Fe₃O₄ composite to remove tetracyclines (TCs) from wastewater. Furthermore, even though the adsorbent has been used for the removal of other contaminants,^25-27 it is important to demonstrate that the proposed adsorbent can be used for a wide range of pollutants that have multiple acid dissociation constants, thus making it a versatile adsorbent. Therefore, in this study, the Cs-PPy-Fe₃O₄ composite was synthesized via the facile co-precipitation method and applied as a suitable adsorbent for the removal of TCs in water. The adsorbent was characterized using various analytical techniques. The prepared composite was investigated for simultaneous adsorptive removal of oxytetracycline (OT), tetracycline (TC), chlortetracycline (CT), and doxycycline (DC) from aqueous environments. The effects of the most important parameters on the adsorption of TCs (mass of adsorbent, sample pH, contact time, initial concentration, and temperature) were investigated and optimized using response surface methodology (RSM) based on Box-Behnken design (BBD). The sorption data were examined using isotherms, kinetics, and thermodynamic models. The reusability of the adsorbent was investigated by performing several adsorption-desorption cycles.

 

EXPERIMENTAL

Materials

All chemicals in this study were analytical-grade reagents, and they were used as they were obtained. The analytes; tetracycline (purity = 98-102%), oxytetracycline dehydrate (purity = 95-102%), chlortetracycline (purity > 91%), doxycycline monohydrate (purity = not given) were purchased from Merck, Johannesburg, South Africa. Acetonitrile (ACN) and methanol (MeOH)) were HPLC-grade solvents purchased from Merck, Johannesburg, South Africa. Chemical reagents such as hydrochloric acid (HCl), iron (III) chloride hexahydrate (FeCl₃.6H₂O), ammonium persulfate (APS), iron (II) tetrahydrate (FeCl₂.4H₂O), pyrrole, chitosan, sodium hydroxide (NaOH), oxalic acid dihydrate (OA), acetic acid (purity = 99%) were purchased from Merck, Johannesburg, South Africa. All aqueous solutions were prepared using 18 ΜΩ cm^-1 resistivity ultrapure water (type 1, (Millipore, Bedford, MA, USA).

Preparation of adsorbents

Synthesis of chitosan-Fe₃O₄ composite

The synthesis of the chitosan-Fe₃O₄ composite was prepared by a co-precipitation method modified from Liao et al.²⁸ Briefly, 1.0 g chitosan was dissolved in 400 mL of 0.25% (v/v) acetic acid, followed by adding 30 mM FeCl₃.6H₂O and 15 mM FeCl₂.4H₂O. The mixture was stirred for 1 h at 40 °C under inert conditions. Thereafter, 10% NaOH was added dropwise to adjust the pH of the solution to 10 under vigorous stirring. The solution was left to stir for an additional 1 h to form a black precipitate, which was collected using an external magnet. The residue was washed with ultrapure water and methanol several times and oven-dried at 60 °C overnight. The same procedure prepared iron oxide nanoparticles without the addition of Cs.

Synthesis of chitosan-polypyrrole-fe₃O₄ composite

The synthesis of chitosan-polypyrrole-Fe₃O₄ (Cs-PPy-Fe₃O₄) composite was carried out as follows; 2.5 mL pyrrole monomer and 4 g of magnetic chitosan were added to a round flask containing 100 mL Milli-Q water. The mixture was stirred for 1 h at room temperature under a nitrogen atmosphere, then added 20 mL APS. The mixture was stirred for 4 h at room temperature. The black precipitate was collected with an external magnet and washed several times with Milli-Q water and methanol until the filtrate became colorless. The Cs-PPy-Fe₃O₄ composite was dried at 60 °C for 24 h. Synthesis of PPy followed the same procedure without adding the magnetic chitosan.

Instrumentation

The microscopic morphology, size, shape, and elemental analysis were evaluated using scanning electron microscopy (SEM, TESCAN VEGA 3 XMU, LMH instrument, Czech Republic) coupled with the energy dispersive X-ray spectroscopy (EDS) at a voltage of 20 kV. The internal structure of the composite was investigated by transmission electron microscopy (TEM JOELJEM 2100, Japan) at a voltage of 120 kV. The functional groups present in the materials were determined by using FTIR (KBr disk technique), model, and 100 FTIR spectrometer procured at PerkinElmer (Waltham, MA, USA) in the range 400 - 4000 cm^-1). The X-ray diffraction (XRD) analyses were performed on a PANalytical X'Pert X-ray Diffractometer (PANalytical BV, Netherlands) using a Cu K α radiation (λ = 0.15406 nm) in the 2θ range of 4-90° at room temperature to investigate the crystalline nature of the composite. Brunauer-Emmett-Teller (BET) was used to investigate the surface porosity of the individual components (Cs and Fe₃O₄ particles) and the composite by the multipoint method using the surface area and porosity analyzer (ASAP2020 V3, 00H, Micromeritics Instrument Corporation, Norcross, USA). The pH of the samples was adjusted using an OHAUS starter 2,100 pH meter (Pine Brook, NJ, USA). The concentrations of TCs were quantified using Agilent HPLC 1200 infinity series coupled with a diode array detector (Agilent Technologies, Waldbronn, Germany). The analytes were detected at two wavelengths (351 and 365 nm). The choice was based on the fact that TCs are being recorded in the range of 350-365.²⁹An Agilent Zorbax Eclipse Plus C18 column (3.5 μm χ 150 mm χ 4.6 mm) (Agilent, Newport, CA, USA) was used to separate the analytes. The column temperature was kept at 25 °C, and the elution flow rate was 1.00 mL min^-1. The gradient elution using methanol (A), acetonitrile (B), and 0.03 M oxalic acid solution (C) was applied starting with 0:8:92(v/v/v) (A:B: C), which changed to 0:18:82 in 2 min and to 5:20:75 in 0.1 min which stayed isocratic for 4.9 min, and then changed to 10:25:65 for 3 min, then changed to 15:20:65 in 1 min and lastly to 15:25:60 in 3 min and stayed isocratic for 2 min then returning to the initial conditions in 3 min.³³ Origin 2018 Software was used for fitting and plotting data for isotherms and kinetic studies.

Adsorption experiments

To determine the adsorption capacity, the synthesized Cs-PPy-Fe3O4 composite was used as the adsorbent to remove TCs in water. The pH of aqueous solutions was adjusted with either diluted HCl or NaOH. Box-Behnken design (BBD) was used to optimize the batch adsorption process. The investigated parameters and their levels are shown in Table 1. Briefly, 15-30 mg of Cs-PPy-Fe₃O₄ samples were added into conical flasks with the desired TCs concentration (2 mg L^-1 for each compound), sample pH (4-10), and volume (100 mL) of the solution. The solution was sonicated (5-60 min), followed by separating the supernatant from the adsorbent with an external magnet. After that, 1 mL of the supernatant was filtered through a 0.22 μm PVDF filter and analyzed using HPLC-DAD. The adsorption removal efficiency (%RE) was evaluated as follows:

where C₀ and C_e (mg L^-1) are the initial and equilibrium concentrations, respectively.³⁰

Post optimisation, the optimum experimental conditions were used to study the equilibrium isotherms and adsorption kinetics. Model solutions containing OT, TC, CT and DC at concentration levels ranging from 3-50 mg L^-1 were used to perform equilibrium studies. The experiments were carried out in duplicate, and the adsorption capacities for OT, TC, CT and DC were determined by equation 2:

where Cq and C_e (mg L^-1) are the initial and equilibrium concentration, respectively; V (L) is the volume of the solution and m (g) is the mass of Cs-PPy-Fe₃O₄ composite.³¹

Kinetic studies were carried out by adding 1qq mL of a mixture of TCs (7 mg L^-1 for each TC) into conical flasks and sonicated for 5 to 6Q min. This was followed by the separation of the supernatant from the adsorbent by an external magnet. The supernatant was filtered and analysed by HPLC-DAD. The adsorption capacity was calculated at the time, t, (qt).

Regeneration and reusability

The reusability and regeneration capabilities of the Cs-PPy-Fe₃O₄ composite were investigated by performing five adsorption/desorption experimental cycles of the TCs. A desorption solvent containing a mixture of MeOH and Q.QI OA (20:80 v/v) was used to desorb TCs from the TC-loaded Cs-PPy-Fe₃O₄ adsorbent. The desorption experiments were done at room temperature through sonication of the adsorbent for 5 min. An external magnet separated the eluent and adsorbent. The eluent was then filtered and analysed using HLPC-DAD. After desorption, the composite was washed several times with Milli-Q water and dried at 60 °C for 2 h.

Collection of real samples

The composite prepared in this study was evaluated for its ability to adsorb the four TCs in wastewater. Both wastewater influent and effluent samples were collected from a local wastewater treatment plant, and preserved through keeping in coolerbox packed with ice during the transportation to the laboratory. The samples were filtered and the presence of TCs was monitored using HPLC. All the analytes were not detected in the samples. Therefore, spiking of both the influent and effluent samples with the TCs was performed prior to performing the adsorption studies.

 

RESULTS AND DISCUSSION

Characterisation

FTIR analysis

The FTIR spectra of Cs-Neat, Fe₃O₄-Neat and Cs-PPy-Fe₃O₄ are presented in Figure 1. Figure 1A shows chitosan characteristics peaks at 3423 cm^-1, 2850 cm^-1 and 1053 cm^-1 assigned to O-H/N-H, C-H and C-O-C stretching vibrations, while 1633 cm^-1 and 1385 cm^-1were ascribed to N-H and C-H bending vibrations.³² Iron oxide had characteristic peaks (Figure 1B) at 3352 cm^-1 corresponding to O-H stretching vibration and 592 and 458 cm^-1 corresponding to Fe-O stretching vibration.^33,34 The spectrum of PPy (Figure 1C) showed a broad peak at 3417 cm^-1 due to the N-H stretching vibrations, while the peak at 2922 cm^-1 was attributed to the C-H stretching vibrations.³⁵ The peaks at 1554 and 1470 cm^-1 were ascribed to the C=C stretching vibrations of the PPy ring.³⁶ The peak at 1386 cm^-1 corresponded to the C-N stretching vibrations.^37,38 The peak at 1198 cm^-1 was due to C-N stretching vibrations.³⁹ The peak observed at 1045 corresponds to C-H in-plane bending vibrations.³⁹ The 919 and 793 cm^-1 peaks are ascribed to C-H out-of-plane vibrations.^40,41 The peak at 611 cm^-1 was due to the in-plane deformation of the ring.⁴² The spectrum of the Cs-PPy-Fe₃O₄ composite (Figure 1D) showed a peak at 3430 cm^-1, which resulted from O-H and N-H stretching vibrations of both Cs and PPy. Characteristic peaks of Cs observed at 1633 and 1053 cm^-1 in the Cs spectrum shifted to 1625 and 1095 cm^-1, respectively, in the Cs-PPy-Fe₃O₄ spectrum. The 2922 and 2850 cm^-1 peaks for PPy and Cs disappeared in the Cs-PPy-Fe₃O₄ spectrum. The peaks at 1569 and 1463 cm^-1 are due to PPy. Finally, the peaks 599 and 458 cm^-1 are ascribed to Fe-O stretching vibration, confirming the presence of iron oxide nanoparticles in the composite. Therefore, the results suggested that the Cs-PPy-Fe₃O₄ composite was successfully synthesised.

XRD analysis

Figure 2 illustrates the XRD patterns of Cs, Fe₃O₄ (JCPDS card number 04-013-9809), PPy and Cs-PPy-Fe₃O₄ composite. The XRD pattern of Cs (Figure 2A) showed sharp narrow peaks at 2θ angles 10.2° and 20.0°, characteristic of crystallinity in Cs biopolymer.⁴³ The broad peak at 2θ angle 41.1°characterised the amorphousness of the Cs biopolymer.⁴⁴ Characteristic peaks associated with Fe₃O₄ in Figure 2B agreed with previous studies.^45,46 A broad peak for PPy (Figure 2C) was observed at an angle of 24.7°, corresponding to the amorphous region of PPy,⁴⁷ while the peak at 43.5° was possibly due to impurities. From the Cs-PPy-Fe₃O₄ composite (Figure 2D), the characteristic peaks associated with the crystalline Fe₃O₄ phase can be seen. Furthermore, the peak at 24.7° corresponds to PPy.

TEM, SEM and EDS analysis

The morphologies of the Fe₃O₄ particles and Cs-PPy-Fe₃O₄ composite were investigated by TEM and SEM (Figure 3). The TEM image in Figure 3(A) showed that the Fe₃O₄ particles were semi-spherical and aggregated, which agreed with the results of a difierent study.⁴⁸ The TEM image in Figure 3(B) showed that the Fe₃O₄ particles were dispersed in the polymer matrix.⁴⁹ However, aggregation was still visible.

Scanning electron microscopy images in Figure 4 (A and C) showed that chitosan and iron oxide displayed a lamellar structure. The polypyrrole and the composite were composed of nodular structures (Figures 4B and 4D).⁵⁰ The composite was more porous than the individual components (Cs and Fe₃O₄), which could be attributed to PPy chain agglomerates covering the Cs and Fe3O4 particles, increasing the porosity.⁵¹ The EDS analysis of the individual components (chitosan, polypyrrole and iron oxide) is presented in Figure S1. The EDS analysis of the composite (Figure 4E) confirmed the presence of chitosan and polypyrrole due to the detection of C (53.6%), O (18.0%) and N (12.4%) peaks. The Fe (12.4%) and O (18.0%) peaks further confirmed the incorporation of iron oxide. The S and Cl peaks in the composite were due to the ammonium persulfate and iron salts during the synthesis step.

BET analysis

To investigate the surface area and porosity of the composites, N₂ adsorption/desorption experiments were carried out, and the results are illustrated in Table 2. From the results, Cs, Fe₃O₄ particles and Cs-PPy-Fe₃O₄ composites had surface areas of 0.3276, 13.8 and 129.4 m² g^-1, respectively. Iron oxide and the Cs-PPy-Fe₃O₄ composite had pore volumes of 0.03 and 0.32 cm³ g^-1, respectively, while the pore sizes were 7.6 and 9.9 nm, respectively. The results show that the BET surface area, pore volume and pore size of the Cs-PPy-Fe3O4 composite were higher than those of Cs and Fe₃O₄ particles. This means the synthesis of the composite improved these features, which could be beneficial for the application of the resulting material as an adsorbent.

Optimisation of adsorption parameters

Optimisation Box-Behnken design

The batch adsorption optimisations were carried out using the Box-Behnken design; the results are shown in Table S1. The analysis of variance (ANOVA) was used to analyse the statistical significance of the investigated independent factors on removal efficiency at the 95% confidence level. The ANOVA results were reproduced as Pareto charts. Only the linear factors (indexed L) were considered during the Pareto charts' analysis, while quadratic factors (indexed Q) were excluded (Figure 5). This is due to the ANOVA being a linear model. The results in Figure 4 showed that the factors with significant effects were sample pH for all analytes of interest and mass of adsorbent (MA) for OT. This suggests that these independent factors were more influential on the analytical response.

Response surface methodology (RSM)

The 3D response surface plots were used to study the combined effects of the factors on the removal of OT, TC, CT and DC from water. The results from Figure 6 (A and B) show that maximum concentration was observed when the sample pH was between 3.5 and 7.5 and with any amount of MA and cT. This might be attributed to the sample pH affecting the TCs' ionisation and the adsorbent's surface charge.⁵² The point of zero charges for Cs-PPy-Fe₃O₄ composite was determined to be 7.50 (Figure S2), suggesting that when the pH was below the pH_pzc, the adsorbent surface was positive and conversely, when the sample pH was above the pH_pzc the surface of the adsorbent was negative. All TCs have three disassociation constants; namely, pKa₁ = 3.2, pKa₂ = 7.5 and pKa₃ = 8.9 for OT, pKa₁ = 3.3, pKa₂ = 7.8 and pKa₃ = 9.6 for TC, pKa1 = 3.3, pKa2 = 7.6 and pKa3 = 9.3 for CT and pKa1 = 3.0, pKa₂ = 7.9 and pKa₃ = 9.2 for DC.⁵³ TCs are cationic when pH < pKa₁, zwitterionic when pKa₁ < pH < pKa₂ and anionic when pH > pKa2.⁵⁴ The maximum concentration was seen when the sample pH was between 3.5 and 7.5 was due to the electrostatic interactions between the zwitterionic species of the TCs and positively charged Cs-PPy-Fe₃O₄ surface. Figure 6C shows the interaction between MA and cT. In this case, maximum concentration was observed when MA was below 19 mg and cT was between 1 and 70 min. The opposite effect was observed when the MA was above 19 mg. This could be attributed to the increase in the number of analyte binding sites. However, increasing the mass of the adsorbent may have resulted in the agglomeration of particles and thus decreased the surface area.⁵⁵

Desirability function

Using the desirability function permits estimating the optimum values for the investigated factors. The results are illustrated in Figure 7. The optimum conditions for the removal process were 4, 15 mg and 5 min for sample pH, mass of adsorbent and contact time, respectively. Under optimal conditions, the predicted concentration for the adsorption of OT, TC, CT and DC were 917.01, 1211.2, 2661.7 and 1855.3 μg L^-1, respectively (Figure S3). These predicted optimal conditions were confirmed experimentally by performing the adsorption process five times. The experimental results gave concentrations of 913.9 ± 2.3, 1210.8 ± 3.7, 2634.9 ± 39.6 and 1857.4 ± 28.6μg L^-1 for OT, TC, CT and DC, respectively.

Adsorption isotherms

Isotherm studies were conducted to determine the relationship between the remaining concentration of TCs after reaching equilibrium and the amount adsorbed onto the Cs-PPy-Fe₃O₄. This was achieved by fitting the data into five nonlinear isotherm models: Langmuir, Freundlich, Dubinin-Radushkevich, Hill and Sips. The Langmuir isotherm model indicates monolayer adsorption onto a homogenous surface.⁵⁶ The nonlinear equation of the Langmuir isotherm model is shown in equation (3):

where qe (mg g^-1) is the amount of TCs adsorbed at equilibrium, Ce (mg L^-1) is the concentration of TCs at equilibrium and q_max (mg g^-1) and K_L (L mg^-1) are model parameters related to maximum adsorption capacity and free adsorption energy, respectively.⁵⁷ The adsorption equilibrium is favourable when K_L is greater than zero but less than one. When K_L is greater than one, the adsorption equilibrium is not favourable.

The Freundlich isotherm model indicates heterogeneous adsorption on the adsorbent's surface and that the adsorption heat is not uniform.⁵⁸ The nonlinear equation of the Freundlich isotherm model is given in equation (4):

where n shows the adsorption intensity and K_F (mg g^-1)(L mg^-1)^1/n is the Freundlich constant, respectively. When n is greater than one, adsorption is favourable.⁵⁸

Dubinin-Radushkevich (D-R) isotherm model assumes that the adsorption process is related to micropore volume filling rather than layer-by-layer adsorption on the pore walls. This model accounts for the effects of the porous structure of the adsorbent.⁵⁹ The nonlinear equation of the D-R isotherm model is given in equation (5):

where β (mol² kJ^-2) is the D-R isotherm constant associated with the adsorption energy and ε (kJ mol^-1) is the adsorption potential.⁶⁰

Hill isotherm model assumes that the adsorption process is a cooperative phenomenon of analytes on the adsorbent site affecting different adsorbent sites.⁶¹ The nonlinear equation of the Hill isotherm model is given in equation (6):

where n_H is the binding interaction coefficient, and K_D is the Hill isotherm constant.⁶²

Sips isotherm model combines both Langmuir and Freundlich isotherms. The heterogeneity factor nS associated with this isotherm model is typically less than one, indicating a heterogeneous surface. When nS equals one, the equation reduces to Langmuir, indicating a homogeneous surface.⁶³ The nonlinear equation for the Sips isotherm model is shown in equation (7):

where q_s (mg g^-1)is the maximum adsorption capacity, nS is the heterogeneity factor and K_s (L mg^-1) is the affinity constant.⁶⁴

The nonlinear isothermal parameters and the correlation coefficients (R²) for Langmuir, Freundlich, Dubinin-Radushkevich, Hill and Sips isotherms are shown in Table 3. From the results, the correlation coefficients for OT, TC, CT and DC for the Freundlich isotherm model were 0.9603, 0.9521, 0.9467 and 0.9649, respectively, with n_F of 2.56, 3.40, 2.21 and 2.53 for OT, TC, CT and DC, respectively. Since the values of n_F > 1, this suggested that adsorption was favourable.⁶⁵ The Langmuir isotherm model R² values were 0.9971, 0.9961, 0.9831 and 0.9877 for OT, TC, CT and DC, respectively, with maximum adsorption capacity of 112, 95, 94 and 93 mg g^-1 for OT, TC, CT and DC, respectively. However, the results showed that the Langmuir isotherm model best fitted the experimental data since its R² value was higher than that of the Freundlich isotherm model. The results suggested a monolayer and homogenous adsorption of the TCs onto the Cs-PPy-Fe₃O₄ surface. The Sips isotherm model agreed with the results observed. As mentioned earlier, when ns equals 1, the model reduces to Langmuir, suggesting homogeneous adsorption. Furthermore, the Hill cooperativity coefficient constant (ns) was greater than 1, suggesting positive cooperativity in binding.

Adsorption kinetics

Kinetic studies are important since they provide useful information, such as a better understanding of the adsorption mechanism and the interaction between the adsorbent and the analytes.⁶⁶ The effects of time on the adsorption of TCs on Cs-PPy-Fe₃O₄ were investigated. This was accomplished by fitting the data into four kinetic models: pseudo first order, pseudo-second order, Elovich and intra-particle diffusion kinetic models. Pseudo-first order (PFO) assumes that the adsorption process is determined by diffusion from one layer to another.⁵⁶ The nonlinear equation for the PFO model is shown in equation (8):

where qe (mg g^-1) is the amount of TCs adsorbed at equilibrium, qt (mg g^-1) is the amount of TCs at time t, k₁ (min^-1) is the first order rate constant, and t (min) is the adsorption time.⁶⁷

Pseudo-second order (PSO) assumes the adsorption process is determined by chemical uptake.⁵⁶ The nonlinear equation for the PSO model is presented in equation (9):

where k₂ (g mg^-1 min^-1) is the second-order rate constant.⁶⁸

Elovich model assumes that adsorption occurs in two steps, a quick initial reaction based on the movement of the analytes to available external sites followed by a slow diffusion of the analytes in and out of the adsorbent's micropores.⁶⁹ The nonlinear equation for the Elovich model is shown in equation (10):

where α (g mg^-1) is the desorption coefficient, and β (mg g^-1 min^-1) is the adsorption rate.⁷⁰

Intra-particle diffusion model assumes that the interaction of the adsorbate and the adsorbent is instantaneous relative to the diffusion steps, and therefore, these diffusion steps determine the overall rate.⁷¹ The equation for the intra-particle diffusion model is shown in equation (11):

where K_id (mg g^-1 min^1/2) is the rate coefficient and C (mg g^-1) is the diffusion constant representing the thickness of the boundary layer.⁷² The results of the nonlinear fit for the pseudo-first order, pseudo-second order, Elovich and linear intra-particle diffusion kinetic models are shown in Table 4. From the results, the R² values for pseudo first order were 0.9978, 0.9988, 0.9967 and 0.9978 for OT, TC, CT and DC, respectively. While for the pseudo-second order, the R² values were 0.9960, 0.9972, 0.9944 and 0.9971 for OT, TC, CT and DC, respectively. The results from the models revealed that the adsorption of the analytes onto the adsorbent followed a pseudo first-order kinetic model since the R² values were greater than those of the other three models (pseudo-second order, Elovich model and intra-particle diffusion). This suggests that the adso rption of TCs onto Cs-PPy-Fe₃O₄ adsorbent may have been physical.⁷³ Elovich kinetics model did not fit better with the data due to lower R² values. This further validates that chemisorption was not the rate-determining step. To determine the rate-determining step, different intra-particle diffusion models were used. From the results in Table 4, a two-step adsorption process occurred, the first being film diffusion and the second being intra-particle diffusion. Since the plots for all the analytes did not go through the origin, this suggested that intra-particle diffusion was not the rate-determining step. K_id1 for the film diffusion was greater than K_id2 for intra-particle diffusion, suggesting that intra-particle diffusion was slow.

Adsorption thermodynamics

Thermodynamic studies became useful in determining the dominant adsorption mechanism. To evaluate thermodynamic factors such as the standard enthalpy (∆H°), free energy (∆G°) and entropy (∆S°), adsorption experiments were carried out at three temperatures (298.15, 308.15 and 318.15 K). The Van't Hoffs equation (equation 12) was used to calculate the change in enthalpy and entropy, while the Gibbs free energy was determined using equation (13):

where T (K) is the temperature of the solution, R (J mol^-1 K) is the universal gas constant, and K is the thermodynamic equilibrium constant of the adsorbent equal to q_e/C_e.⁷⁴

The slope and intercept of the Van't Hoff plot of ln K versus 1/T were used to calculate ΔΗ° and ∆S° respectively, and equation 13 was used to calculate ∆G° and the results are presented in Table 5. The negative values of ∆G° reveal that the adsorption of the TCs onto the Cs-PPy-Fe₃O4 composite was spontaneous and thermodynamically favourable. Furthermore, when the values of ∆G° are between -20 and 0 kJ mol^-1, this suggests a physical adsorption process.⁷⁵ Since ∆G° values for all four analytes were between -20 and 0 kJ mol^-1, a physical process governed the removal of TCs in water. These results agree with kinetic studies (Section 3.4) that showed that the experimental data best fitted the pseudo-first order model. The negative values of ∆H° indicate that the adsorption process was exothermic. The positive values of ∆S° suggested an increase in the randomness at the solid-solution interface during the adsorption process.

Possible adsorption mechanism

To gain insight into the adsorption mechanism of OT, TC, CT, and DC onto the Cs-PPy-Fe₃O₄ composite, the composite was characterised by FTIR before and after adsorption, and the results are presented in Figure 8 A and B, respectively. The possible adsorption mechanism is depicted in Figure 9. The adsorption of the TCs could be attributed to cationic-π bonds, hydrogen bonding, π-π interactions and electrostatic interactions. Cationic-π bonds could have occurred between the electron-rich benzene ring of the TCs and the protonated amino groups of the adsorbent and vice versa. This is evident in the FTIR spectrum of Cs-PPy-Fe₃O₄ after adsorption; the peaks at 3430 and 1625 cm^-1 shifted to 3493 and 1613 cm^-1, respectively. At the same time, hydrogen bonding could have occurred between the OH from the adsorbent with the OH from the TCs. This can be seen by the peak shift from 3430 to 3493 cm^-1. Another possible contribution of TCs adsorption was due to π-π interactions between the benzene ring of the TCs and that of the adsorbent. The disappearance can see of the peaks at 1569 and 1463 cm^-1 after adsorption. Finally, electrostatic interactions between the analytes' oxygen-rich functional groups and the adsorbent's protonated amino groups might have occurred. The overall results suggest that the adsorption process was physical adsorption.

 

 

Comparison of proposed adsorbent with other adsorbents for TCs removal

The performance of the Cs-PPy-Fe₃O₄ composite was compared with other reported adsorbents for the removal of TCs by looking at the adsorption capacity and the isotherm model followed, and the results are presented in Table 6. The Cs-PPy-Fe₃O₄ composite performed better than magnetic graphene, MIP composite and the EGA_NaCl. However, the activated carbon and biochar performed better than the Cs-PPy-Fe₃O₄ composite. These results indicate that the Cs-PPy-Fe₃O₄ composite can serve as a promising adsorbent for the removal of TCs.

Regeneration and reusability

It was essential to evaluate the regeneration of the adsorbent to investigate the stability and reusability of the adsorbent. The use of Cs-PPy-Fe₃O₄ composite using a mixture of MeOH and 0.01 OA (20:80 v/v) was repeated five times. It was evident that the removal efficiency of the TCs decreased by approximately 2% with the increase in the number of recycles. However, the removal efficiency still was above 65% after five cycles. These results showed that the Cs-PPy-Fe₃O₄ composite could be regenerated and recycled and maintain good adsorption properties.

Application to real samples

The prepared composite's feasibility was evaluated for removing OT, TC, CT and DC from wastewater samples (influent and effluent wastewater). The samples were filtered before analysis followed by determination of TCs before and after adsorption and the results are summarised in Table 7. From the results, none of the analytes were detected in the wastewater samples prior to analysis. However, different concentrations spiked the wastewater samples with the target compounds. This was essential to determine if the developed analytical method could remove and detect the investigated compounds in real water samples. The removal efficiencies of OT, TC, CT and DC in spiked wastewater samples ranged between 88.7-98.5%. The results illustrated that good removal efficiencies were obtained, indicating a good performance by the Cs-PPy-Fe₃O₄ composite in removing TCs. This suggested that the composite has great potential for application in water treatment.

 

CONCLUSION

The current study prepared and characterised the Cs-PPy-Fe₃O₄ composite using FTIR, XRD, TEM, SEM and EDS techniques. The adsorption capabilities of the Cs-PPy-Fe₃O₄ composite were investigated for removing TCs in aqueous solutions.. The results revealed that the Langmuir isotherm model with an adsorption capacity of 112, 95, 95 and 93 mg g^-1 for OT, TC, CT and DC, respectively, fitted the experimental data best. Thermodynamic studies revealed that adsorption was spontaneous, favourable, exothermic, and physisorption-driven. Kinetic studies that adsorption was well described by the pseudo-first order, further confirming that adsorption was driven by physical adsorption. The overall results suggested that the adsorption of TCs was through physical adsorption. The proposed adsorption mechanism was through cationic-π bonds, hydrogen bonding and π-π interactions. The removal efficiency of the TCs remained above 65% after five cycles.

 

ACKNOWLEDGEMENTS

This research was supported by the National Research Foundation (NRF, grant no. 91230) and the University of Johannesburg for making this research possible by providing laboratory facilities.

 

SUPPLEMENTARY MATERIAL

Supplementary material for this article can be found in the online supplemental pdf.

 

CONFLICT OF INTEREST

The authors declare no conflict of interest.

 

ORCID IDS

Mpho C. Lefatle: https://orcid.org/0000-0003-2251-4486

Lawrence M. Madikizela: https://orcid.org/0000-0001-6096-2701

Vusumzi E. Pakade: https://orcid.org/0000-0003-4228-6417

Philiswa N. Nomngongo: https://orcid.org/0000-0001-7615-0548

 

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Received: 28 June 2023
Revised: 5 March 2024
Accepted: 23 April 2024

 

 

* To whom correspondence should be addressed Email: pnnomngongo@uj.ac.za