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Efficient removal of pharmaceuticals from water using graphene nanoplatelets as adsorbent
Abstract
Recently, pharmaceutical pollutants in water have emerged as a global concern as they give threat to human health and the environment. object_of_studymethod↗concepts↗concepts↗concepts↗concepts↗concept_edgesconcept_edgesIn this study, graphene nanoplatelets (GNPs) were used to efficiently remove antibiotics sulfamethoxazole (SMX) and analgesic acetaminophen (ACM) as pharmaceutical pollutants from water by an adsorption process. GNPs; C750, C300, M15 and M5 were characterized by high-resolution transmission electron microscopy, Raman spectroscopy, X-ray diffraction and Brunauer–Emmett–Teller. The effects of several parameters viz. solution pH, adsorbent amount, initial concentration and contact time were studied. The parameters were optimized by a batch adsorption process and the maximum removal efficiency for both pharmaceuticals was 99%. The adsorption kinetics and isotherms models were employed, and the experimental data were best analysed with pseudo-second kinetic and Langmuir isotherm with maximum adsorption capacity (Q m ) of 210.08 mg g −1 for SMX and 56.21 mg g −1 for ACM. A regeneration study was applied using different eluents; 5% ethanol-deionized water 0.005 M NaOH and HCl. GNP C300 was able to remove most of both pollutants from environmental water samples. Molecular docking was used to simulate the adsorption mechanism of GNP C300 towards SMX and ACM with a free binding energy of −7.54 kcal mol −1 and −5.29 kcal mol −1 , respectively, which revealed adsorption occurred spontaneously.
Introduction
Water pollutants found in the environment can be divided into several categories viz. heavy metals, dyes, pesticides, pharmaceuticals and personal care products, phenolics, and others (hydrocarbons, inorganic anions, etc.) [ 1 ]. The source of these noxious pollutants come from untreated discharges of irresponsible textile, pharmaceutical, agricultural and mining factories. Pharmaceutical pollutants have attracted interest among researchers to solve this problem which can cause serious health effects towards humans and may harm the environment. Research on the fate of pharmaceuticals in water prove that there are still traces found downstream [ 2 ]. Long-term exposure to low concentrations of pharmaceuticals in water and the synergistic effects of mixtures may pose risks to human health, especially to sensitive subpopulations [ 3 – 5 ]. It gains more concern as it is reported most pharmaceuticals are non-biodegradable [ 6 – 8 ]. Sulfamethoxazole (SMX) is regularly prescribed as an antibiotic either as individual medication or combined with other drugs such as trimethoprim, a combination commercially known as Bactrim. Bactrim is used to treat several diseases, for instance, many types of bacterial infection namely urinary tract infection including pneumonia. Known SMX contraindications cause allergy, hypersensitivity to either component, hyperkalaemia, severe hepatic or renal dysfunction [ 9 ]. Acetaminophen (ACM) are used as an analgesic for mild to moderate pain and an anti-pyretic [ 10 ]. The use of ACM is prevalent among surveyed consumers and has the highest consumption levels in Malaysia [ 11 ]. To put it more simply, because the water also contains other unwanted drugs, the incident of unconscious consummation of other drugs causes interaction with other drugs, thus leading to the worst condition in a prolonged period. It is known that not all drugs are completely digested in the human body which are then secreted as urine into wastewater and it is found that several amounts of concentration of SMX are found in water bodies; approximately 15% of the unmetabolized fraction goes into sewage after being ingested and subjected to human metabolism [ 12 ]. Table 1 shows the maximum concentration of SMX and ACM in surface water in Asia-Pacific and globally. Table 1. Maximum concentration of sulfamethoxazole and acetaminophen found in water [ 13 ]. pharmaceutical substance therapeutic group Asia-Pacific (μg l −1 ) global (μg l −1 ) a sulfamethoxazole antibiotics 14.3 29.0 acetaminophen analgesics 9.17 230.0 a Includes Asia-Pacific, Africa, Eastern Europe, Latin America and Caribbean, western Europe and others in United Nations regions.
There are various removal methods that are used to remove pollutants from water such as bioreactors [ 14 ], degradation and photodegradation [ 15 – 18 ], filtration [ 19 ], photocatalysis [ 20 , 21 ], photo-Fenton and Fenton-like [ 22 , 23 ], coagulation [ 24 ] and adsorption [ 25 , 26 ]. concepts↗Among these methods, adsorption is a widely used and most efficient method for wastewater treatment. This technique is superior and considered as powerful alternatives to conventional methods [ 27 ] because of its low cost, ease of operation, great efficiency, high capacity, simplicity, reliability and less energy consumption [ 28 , 29 ]. Graphene has gained interest as an adsorbent owing to its large surface area, accessible surface, high hydrophobicity and high mechanical properties [ 30 , 31 ]. As such, many researchers have explored graphene or graphite-based materials as an adsorbent for different pollutants [ 32 – 34 ] owing to its enormous, delocalized π-π electron system that can form strong bonding with various pollutants [ 35 ]. In previous research, graphene nanoplatelets (GNP) C750 have been studied as an adsorbent with good adsorption capacity, yet are quite expensive and other types of GNPs with different surface areas are unexplained [ 35 , 36 ]. research_questionIn this study, the removal efficiency of SMX and ACM by the adsorption process from water using GNPs was evaluated. Different types of GNPs: C750, C300, M15 and M5, were screened to choose the best adsorbent and further optimized by several parameters: solution pH, GNP amount, initial concentration and contact time. Langmuir and Freundlich isotherms were applied to analyse the adsorption equilibrium. Pseudo-first order and pseudo-second order were also discussed for the kinetic study of removal capacity and to identify the behaviour and mechanism of adsorption. Molecular docking studies were also implemented to give interaction insight of GNP with SMX and ACM.
Materials and methods
Chemicals and materials
GNPs C750, C300, M15 and M5 were purchased from XG Sciences, USA. SMX, 98% was obtained from Alfa Aesar, USA and ACM (4-acetamidophenol), 98% purity was purchased from Acros Organic ( table 2 ). Deionized water was used as a solvent for a stock solution and further dilution. The solution pH was measured using a HI-2002 Edge pH Meter, Hanna Instrument, USA. Table 2. Physicochemical properties of pharmaceuticals. pharmaceutical chemical formula CAS No solubility in water (mg l −1 ) dissociation constant, pKa molecular weight (g mol −1 ) sulfamethoxazole C 10 H 11 N 3 0 3 S 723-46-6 610 1.6 and 5.7 253.28 acetaminophen C 8 H 9 NO 2 103-90-2 14 000 9.5 151.16
Characterization of adsorbents
The compositional and morphological properties of GNPs were determined using a high-resolution transmission electron microscope (HRTEM) JEM-2100F operated at 200 kV (JEOL, Japan). Specimens were prepared by dispersing the GNPs in 100% acetone and adding a drop of dispersed GNP on the copper grid. Raman spectroscopy was performed using WITec Alpha 300R (WITec GmbH, Germany). Brunner–Emmett–Teller (BET) and Barrett–Joyner–Halenda (BJH) for specific surface area, pore volume, pore size and pore width distribution of GNPs were analysed using MicroActive for TriStar II Plus 2.03 (Micromeritics, USA), the samples were degassed with nitrogen gas at about 150°C with saturation pressure of approximately 756 mmHg overnight before analysis. X-ray diffraction analysis used LabX XRD-6000 (Shimadzu, Japan) by scanning the GNPs at 2 θ of 20°–80° at a speed angle of 2° min −1 with Cu K α radiation. Zeta potential and average diameter were measured using Zetasizer Nano (Malvern Panalytical Ltd, UK).
Preparation of solution
The stock solution of SMX was freshly prepared by dissolving 10 mg in a 100 ml volumetric flask to produce 100 mg l −1 of the pharmaceutical solution then further diluted to lower concentration using deionized water. The calibration curve of SMX was plotted by absorbance at 264 nm and ACM at 243 nm. The regression equation from E xcel was used to calculate the concentration after the adsorption process, C e .
Preliminary adsorption study
Different types of GNPs with different surface areas were used towards the removal of SMX and ACM to select the best adsorbent among four types of GNPs: C750, C300, M15 and M5. The study was carried out by preparing a 10 ml of 20 mg l −1 SMX solution and using 20 mg of GNPs as adsorbent. The solution was then sonicated for 20 min which was later centrifuged, and the supernatant was filtered by using a 0.22 µm cellulose acetate (CA) syringe filter. The concentration of the supernatant was obtained by detecting absorbance using a UV-Vis spectrophotometer (Shimadzu UV-1650PC).
Batch adsorption experiments
Batch adsorption experiments were performed by preparing 10 ml of the pharmaceutical solution to investigate the effect of adsorption parameters: solution pH, GNP amount, initial concentration and contact time. The stock solution was prepared then further diluted to set the initial concentration. The solution pH was adjusted using 0.1 M NaOH and 0.1 M HCl and measured using a HI-2002 Edge pH Meter (Hanna Instrument, USA). GNPs were added into the solution and were sonicated continuously for a certain time. Then, the solution was centrifuged to collect the supernatant and was filtered through a 0.22 µm CA syringe filter, to ensure there is no trace of GNP in the solution before running the sample through the UV-Vis spectrophotometer to avoid ambiguous results. The removal efficiency of the solution was acquired from the calculation by using the following equation: 2.1 removal efficiency ( % ) = ( C i − C e ) C i × 100 , where C i is the initial concentration of the pharmaceutical solution (mg l −1 ) and C e is the equilibrium concentration of the solution retrieved after the removal process (mg l −1 ). The adsorption capacity was calculated according to the equation: 2.2 q e = ( C i − C e ) V m ,
concepts↗where q e is the amount of pharmaceutical adsorbed by the GNPs (mg g −1 ) or known as adsorption capacity at equilibrium, V is the volume of pharmaceutical solution (l) and m is the mass of GNPs used (g). The reported values were the means of triplicates. Isotherms and kinetics studies were further studied to understand the adsorption mechanisms of SMX and ACM onto GNP C300. Table 3 exhibits the expressions of both isotherms and kinetics. For the adsorption isotherm, Langmuir type and Freundlich models were chosen while pseudo-first-order, pseudo-second-order and intraparticle diffusion model were applied to understand the kinetics. Table 3. Linearized expressions for each adsorption isotherm and kinetic. isotherms and kinetics expressions linear expression plot Langmuir isotherm q e = q m [ K L C e 1 + K L C e ] 1 q e = [ 1 K L I I q m ] [ 1 C e ] + 1 q m 1 q e V s 1 C e Freundlich isotherm q e = K F C e 1 / n ln q e = ln K F + 1 n ln C e ln q e Vs ln C e pseudo-first-order kinetic q t = q e ( 1 − e − k 1 t ) ln( q e − q t ) = − K 1 t + lnq e ln( q e − q t ) Vs t pseudo-second-order kinetic q t = k 2 t q e k 2 t + 1 t q t = [ 1 q e ] [ t ] + 1 K 2 q e 2 t q t V s t intraparticle diffusion q t = K id t (0.5) q t = K id t (0.5) + C q t Vs t (0.5)
Regeneration
A regeneration study was carried out using the optimized parameters for adsorption. The used adsorbent was dispersed in 10 ml of different eluents: 0.005 M NaOH, 0.005 M HCl and 5% ethanol-deionized water then sonicated for 30 min for desorption process. The washed adsorbent was then centrifuged, and the supernatant was discarded. The adsorbent was dried in the oven around 55°C. The dried adsorbent was reused for the adsorption process and the steps were repeated for several cycles.
Real water application
Three different real water samples: Langat river water, Kuyoh river water and laboratory tap water were collected for environmental application. The samples were filtered using filter paper and kept at 4°C in the dark. The properties of the three real water samples were analysed. Real water samples were spiked with a concentrated solution of ACM and SMX (100 mg l −1 ) were added into the real water samples to obtain a sample with final concentrations of 20 mg l −1 . Twenty milligrams of GNPs was added to the spiked samples and sonicated for 20 min for the removal process. The sample was centrifuged, and the supernatant was filtered with a 0.22 µm CA syringe filter into a vial ready to be analysed. Chemical oxygen demand (COD, mg l −1 ) and biochemical oxygen demand (BOD, mg l −1 ) were measured following the APHA 5220 and APHA 5210 methods, respectively. Total soluble solids (TSS, mg l −1 ) was analysed, a Hach DR 900 (Hach, USA) and a WTW Inolab meter (WTW GmbH, Germany) was used to measure total dissolved solids (TDS, mg l −1 ). The concentration of sodium, magnesium and calcium were analysed using inductively coupled plasma-optical emission spectrometry by referring to the APHA 31110b method ( table 4 ). Table 4. Analysis of the Langat river water, Kuyoh river water and tap water. Langat river water Kuyoh river water tap water chemical oxygen demand, COD (mg l −1 ) 43.63 77.57 14.60 biochemical oxygen demand, BOD (mg l −1 ) 2.15 7.20 1.40 total soluble solids, TSS (mg l −1 ) 35.00 18.00 0 total dissolved solids, TDS (mg l −1 ) 171.00 282.00 150.00 sodium, Na (mg l −1 ) 5.50 10.00 7.58 magnesium, Mg (mg l −1 ) 1.25 1.84 1.27 calcium, Ca (mg l −1 ) 13.32 24.86 14.64
Results and discussion
Characterization of graphene nanoplatelets
By using an HRTEM at 10 000 times magnification, physical features of GNPs were analysed. Figure 1 displayed the structure of GNPs which possessed wrinkle flakes with multiple layers. C750 ( figure 1 a ) has an irregular shape which resembles more like platelets, more wrinkle features and smaller size with greater aggregation compared to C300, M15 and M5. As shown in figure 1 c,d , M5 and M15 exhibit bigger flakes with a less overlapping layer. Figure 1. HRTEM images of ( a ) C750, ( b ) C300, ( c ) M15 and ( d ) M5 at 10 000 times magnification.
The thickness of layer GNPs was evaluated at atomic resolution via Raman spectroscopy which shows vibrational bands of D, G and 2D ( figure 2 ). concepts↗content_tags↗The D band, known as the disorder band appears around 1350 cm −1 because of out of plane vibrations attributed to the presence of structural defects. The presence of this band proved the GNPs have ragged edges [ 37 , 38 ]. This result is also confirmed in the HRTEM images. concepts↗concepts↗concept_edgesThe G band which is a sharp peak that exists around 1587 cm −1 resulted from the in-plane vibration of sp 2 hybridized carbon atoms. The 2D band is the second order of the D band, sometimes denoted as the G’ band that appears around 2700 cm −1 , resulted from a two-phonon lattice vibrational process without defect. The shape of 2D bands was wide and low and the full width at half maximum of the 2D bands for all GNPs greater than 90 cm −1 perfectly categorized as multilayer graphene [ 39 ]. Intensity ratio of 2D and G peaks were used to determine the number of graphene layers. content_tagsThe ratios I 2D / I G of four different GNPs are less than 1, thus confirming the multilayer properties of these adsorbents. Figure 2. Raman spectra of GNPs C750, C300, M15 and M5.
Figure 3 shows the X-ray diffraction patterns of GNP C750, C300, M15 and M5. Peaks shown in the figure correspond with the characteristic peaks of pristine graphite which could be assigned to the (002), (100), (004) and (110) hexagonal planes by referring to the JCPDS Card No (75-1621). C300 ( figure 3 b ) shows more distinct peaks with a higher intensity that resemble graphite compared with the X-ray diffraction pattern of C750 ( figure 3 a ) that only exhibits peaks of (002) and (100) with a broader peak. Figure 3. X-ray diffraction spectra for GNPs ( a ) C750, ( b ) C300, ( c ) M15 and ( d ) M5.
Through BET and BJH analysis, the surface area, micropore area, pore size and pore volume of adsorbent were analysed and summarized in table 5 . content_tagsThe surface area C750 (738.44 m 2 g −1 ) was found to be the highest compared to others followed by C300 (390.30 m 2 g −1 ), M15 (61.51 m 2 g −1 ) and M5 (63.55 m 2 g −1 ). The pore diameter of C750, C300, M15 and M5 can be categorized as mesopores as they fall in the range of (2–50 nm) according to the International Union of Pure and Applied Chemistry classification. Table 5. Summary of BET and BJH analysis for GNP C750, C300, M15 and M5. GNP BET surface area (m 2 g −1 ) micropore area (m 2 g −1 ) total pore volume (cm 3 g −1 ) external surface area (m 2 g −1 ) BJH pore width (nm) C750 738.44 218.71 0.78 519.73 4.96 C300 390.30 83.65 0.41 306.65 4.66 M15 61.51 10.00 0.10 51.51 5.38 M5 63.55 17.96 0.08 45.59 4.94
Figure 4 exhibits adsorption/desorption isotherm type IV which is similar to reported by Al-Khateeb et al . [ 36 ] with an H3 type hysteresis loop that confirms there were aggregates (loose assemblages) of platelet like particles forming slit-shaped mesopores [ 40 ]. The intermediate flat region in the isotherm corresponds to monolayer formation at the lower pressure region of the graph then followed by multilayer [ 41 ]. Figure 4. N 2 adsorption/desorption isotherms for GNP ( a ) C750, ( b ) C300, ( c ) M15 and ( d ) M5.
concepts↗Zeta potential measured the electrostatic repulsion between similarly charged particles and hence indicates a degree of dispersion efficiency thus giving information tendency of agglomeration, and a larger zeta potential may mean there is a better dispersion [ 42 , 43 ]. content_tagsTable 6 exhibits the measured zeta potential of GNP C300 (−50.80 mV) is the most stable compared to other three GNPs. GNP M5 has the least absolute value with −20.87 mV, which considered its tendancy to aggregate since it is lower than −30 mV [ 44 ]. Both GNP C750 and C300 possessed an average diameter of less than 2 µm, while M5 and M15 with 4.21 µm and 6.79 µm, respectively. Table 6. Zeta potential and average diameter of different types of graphene nanoplatelets using dynamic light scattering. GNP average diameter (nm) zeta potential (mV) C750 933.67 −44.63 C300 1010.00 −50.80 M15 6794.67 −33.90 M5 4205.33 −20.87
Preliminary adsorption study
Figure 5 presents the preliminary adsorption study of four different types of GNPs C750, C300, M15 and M5 towards SMX. Based on the characterization, C750 possessed the advantage of a higher surface area of the four materials tested. concepts↗concepts↗concept_edgescontent_tagsHowever, it is found that C300 has the highest removal efficiency compared to other types of GNPs despite the fact C750 has a higher surface area. Furthermore, C300 has the highest stability based on the zeta potential. sensesThis finding was contrary to expectations that a higher surface area will have better adsorption efficiency [ 45 ], though the result of removal efficiency is similar to what has been reported by Al-Khateeb [ 35 ]. Thus, other factors must be taken into consideration to achieve a higher percentage of adsorption. mechanisms↗This might be owing to clumping or aggregation of C750 because of its high surface area which causes lower yet good adsorption of SMX. limitationsAfter centrifugation and filtration, some GNPs may have not filtered thoroughly owing to the small size of C750 able to go through 0.22 µm CA syringe filter. Because the objective of this preliminary study was to choose the best adsorbent, C300 was chosen. On top of that, C300 has a lower manufacturing cost compared to C750 which reduces the total cost for the overall process [ 46 , 47 ]. Thus, C300 was further used for the batch adsorption study with different parameters: solution pH, GNP amount, initial concentration of SMX and contact time. Figure 5. Preliminary test of different type of graphene nanoplatelets (GNPs).
Evaluation of adsorption behaviours of graphene nanoplatelets C300 towards sulfamethoxazole and acetaminophen
Effect of solution pH
To assess the adsorption behaviours of GNP C300, a batch adsorption study was performed to remove SMX and ACM by using GNP C300 as adsorbent. Solution pH is an important factor in the adsorption of pharmaceuticals. The effect of solution pH on the adsorption of pharmaceuticals was studied from pH 2 to 10 in a 10 ml solution volume of 20 mg l −1 concentration using 20 mg GNP C300 for 20 min. As displayed in figure 6 , the adsorption ability of GNP C300 towards both SMX and ACM was affected by the pH value of the solution. As the initial pH of the solution increased from 2 to 4, the adsorption capacity of SMX onto GNP C300 gradually increased ( figure 6 a ). On the other hand, the adsorption capacity and removal efficiency for ACM increased gradually from acid to neutral then decreased as it further increased ( figure 6 b ). content_tagsMaximum adsorption was detected at pH 4 (99.27%) for SMX and ACM at pH 8 (98.38%). The lowest removal for SMX was detected at pH 10 with 85.65% and for ACM at 76.8% at pH 2. concepts↗concept_edgescontent_tags↗The increasing solution pH was unfavourable for the removal of SMX molecules and resulted in a low adsorption capacity at higher pH. Because SMX is known as an acidic organic compound with dissociation constant (pKa) of 1.6 and 5.7, the removal of the targeted compound was better under acidic conditions (pH < pKa) than at basic pH (pH > pKa). In other words, when solution pH is less than their pKa values, they are present in aqueous solution as a protonated form and these observations are in agreement with the results in the previous works [ 33 , 48 ]. Figure 6. The effect of solution pH on ( a ) sulfamethoxazole and ( b ) acetaminophen using adsorption by GNP C300.
Effect of graphene nanoplatelets amounts
Different amounts of GNP C300 were used for adsorption towards a 10 ml of 20 mg l −1 adjusted to pH 4 in 20 min for SMX and pH 8 for ACM based on previous optimum conditions. From the results presented in figure 7 , concepts↗with the increase in GNP C300 amount from 5 mg to 60 mg, the removal efficiency increased; however, the adsorption capacity for both pharmaceuticals decreased. At low adsorbent dosage, adsorption sites were fully available, resulting in higher adsorption capacity. At a higher GNP C300 amount, the active sites of the adsorbent which prepared to bind with the pharmaceutical molecules were not fully used in comparison to lower adsorbent dosages. The increase in the amount of GNP C300 may cause aggregation of adsorbent and possibility of collisions between solid particles [ 49 , 50 ], and consequently, the available adsorption sites may decrease as well owing to the adsorption capacity of GNP C300 for SMX and ACM. Figure 7. The effect of GNP amount on ( a ) sulfamethoxazole and ( b ) acetaminophen using adsorption by GNP C300.
Effect of initial concentration
It is crucial to study the effect of initial concentration upon revealing any adsorption process. Thus, a set of experiments was carried out at different initial concentrations of 10 to 100 mg l −1 using previously optimized parameters. Figure 8 shows that the adsorption capacity of pharmaceutical increased as the initial SMX and ACM concentration increased from 10 to 100 mg l −1 with an almost linear trend. concepts↗concept_edgescontent_tags↗The higher the initial concentration, the more adsorbate molecules available for adsorption, resulting in a higher adsorption capacity at higher pharmaceutical concentrations. However, as the initial concentration increased more than 40 mg l −1 , the removal efficiency slightly decreased. Nevertheless, the range of removal efficiency is still more than 98%. Figure 8. The effect of initial concentration on ( a ) sulfamethoxazole and ( b ) acetaminophen using adsorption by GNP C300.
Effect of contact time
The contact time between both pharmaceuticals and C300 was studied with several sets of batch adsorption experiments using the previously optimized condition at different times of 2 to 60 min, and the results are presented in figure 9 . As shown in the figure, SMX and ACM adsorption by GNP C300 occurred very fast initially and then the rate slowed down as the contact time increased. Both adsorption capacity and removal efficiency have the same trend. During the initial period, the adsorption capacity of the pharmaceuticals rapidly increased with time as many active sites were available on the surface of GNP C300 for binding of pharmaceutical molecules [ 51 ]. These available active sites were gradually occupied as time increased thus resulting in reducing adsorption rate [ 50 ]. Figure 9. The effect of contact time on ( a ) sulfamethoxazole and ( b ) acetaminophen using adsorption by GNP C300.
Adsorption isotherm and kinetic
Langmuir and Freundlich isotherm models were applied to investigate the adsorption equilibrium between the pharmaceuticals and GNP C300. As shown in table 7 , the adsorption data fitted well with both Langmuir and Freundlich isotherms and this finding was similarly reported in [ 52 ]. The R 2 value obtained from the Langmuir isotherm model were 0.9952 for SMX and 0.9946 for ACM, revealing that the Langmuir isotherm model slightly fit better and is more suitable for describing the adsorption process of the pharmaceuticals onto GNP C300. content_tagsThis illustrated that adsorption of SMX and ACM on GNP C300 was monolayer adsorption occurring on a homogenous surface without interaction between the adsorbate. Table 7. Comparison of adsorption isotherm and kinetic for sulfamethoxazole and acetaminophen. isotherm Langmuir Freundlich n K L 2 R 2 n K F R 2 SMX 210.084 0.374 0.9952 1.193 52.034 0.9848 ACM 56.211 0.721 0.9946 1.435 21.230 0.9842 kinetic pseudo-first order pseudo-second order K 1 Q e R 2 K 2 Q e R 2 SMX 0.108 0.129 0.6743 7.059 6.653 0.9999 ACM 0.115 0.435 0.8218 1.815 6.667 0.9999
Adsorption kinetic with a sample concentration of 20 mg l −1 was further studied, and the kinetic parameters as well as the correlation coefficient, R 2 were acquired by linear regression. concepts↗concepts↗concept_edgesAccording to the data presented in the table, the pseudo-second-order model fitted better than the pseudo-first-order kinetic models. Based on the pseudo-second-order model, the correlation coefficients ( R 2 ) value was 0.9999 for both SMX and ACM which was greater than pseudo-first order. Thus, the pseudo-second-order model was more suitable for describing the process of SMX and ACM adsorption on GNP C300 in agreement with chemisorption being the rate-controlling step [ 53 – 55 ]. The intraparticle diffusion model by Weber and Morris derived from Fick's second law of diffusion was applied to explain further on the diffusion mechanism which includes three steps. The first two steps are transport steps, and the last step is a reaction step [ 1 ]: concepts↗content_tags↗(i) film diffusion (external diffusion), which is the transport of adsorbate from the bulk phase to the external surface of the adsorbent; concepts↗content_tags↗(ii) pore diffusion, which is the transport of adsorbate from the external surface into the pores; and (iii) surface reaction, which the adsorbate will attach to the internal surface of the adsorbent. The data show multilinearity (electronic supplementary material, table S1) limitationswhich indicates that the intraparticle diffusion controls the adsorption process within the early stage, but was not the rate-determining step for the whole adsorption process similarly found in previous research [ 35 ].
The maximum adsorption capacities for both ACM and SMX from this paper were compared with other adsorption capacities reported in the literature. Table 8 summarizes the previous research using graphene and activated carbon as adsorbent using the adsorption method. Table 8. Previous research on sulfamethoxazole and acetaminophen. adsorbents pollutant adsorption capacity (mg g −1 ) references graphene nanoplatelet C300 SMX 210.08 this work powder activated carbon SMX 86 [ 56 ] mesoporous silica-magnetic graphene oxide nanocomposite SMX 15.46 [ 34 ] multi-walled carbon nanotubes SMX 29 [ 57 ] graphene nanoplatelet C300 ACM 56.21 this work graphene nanoplatelets C750 ACM 18.07 [ 35 ] graphene ACM 18.28 [ 58 ] activated carbon from Quercus Brantii (oak) ACM 45.45 [ 59 ]
After adsorption analysis
Table 9 compares the BET results before and after the adsorption of SMX and ACM. After the adsorption process, one can see the surface area of adsorbent decreased to that before the adsorption process, C300 (390.30 m 2 g −1 ) while after the adsorption process, C300-SMX (325.62 m 2 g −1 ) and C300-ACM (291.70 m 2 g −1 ). content_tagsThis shows adsorption had occurred as the SMX molecules adhered to the surface of GNP C300 thus resulting in a notably lower surface area, micropore area and external surface area. Table 9. Comparison before and after adsorption of SMX and ACM towards GNP C300 using BET analysis. BET surface area (m 2 g −1 ) micropore area (m 2 g −1 ) total pore volume (cm 3 g −1 ) external surface area (m 2 g −1 ) C300 390.30 83.65 0.41 306.65 C300-SMX 325.62 38.33 0.37 287.29 C300-ACM 291.70 11.86 0.36 279.84
Field emission scanning electron microscopy (FESEM)/energy dispersive X-ray (EDX) was used to observe the adsorbent surface and elemental analysis ( figure 10 ). After the adsorption process, other elements were present on the surface of GNP C300 of other elements besides carbon. The elements of oxygen and nitrogen were detected on the surface of GNP C300 after adsorption of SMX and ACM. There was also the presence of sulfur found on the C300-SMX sample. Figure 10. FESEM images of GNP C300 after adsorption of ( a ) SMX and ( b ) ACM. EDX analysis of GNP C300 after adsorption of ( c ) SMX and (d) ACM.
To get a better view of the adsorption mechanisms, molecular docking was applied, and the data are detailed in table 10 . Binding energy measures the affinity of the GNP-SMX complex and the sum of energies of each molecule separately. The lower the energy value, the more stable it is. content_tagsThe binding energies for both molecules were negative values; −7.54 kcal mol −1 and −5.29 kcal mol −1 for SMX and ACM, respectively, which means the SMX and ACM were bound spontaneously to the surface of GNP C300 without consuming energy. The ΔGbind obtained for GNP-SMX is higher 2.25 kcal mol −1 than GNP-ACM which is in good agreement with experimental. content_tagsIn the experimental results, GNP shows high maximum adsorption capacity towards SMX (210.08 mg g −1 ) compared to ACM (56.21 mg g −1 ). mechanisms↗This different adsorption capacity of GNP towards pollutants can be explained by the strength of the binding energy obtained from the docking results. Both pollutants preferred to bind at the surface layer of GNPs. Van der Waals, hydrogen bonds and desolvation energy described energy loss with the interaction between pharmaceuticals and GNP and solvent upon binding which revealed the chemisorption occurred exothermically (electronic supplementary material, figure S2). Table 10. Molecular docking of GNP-SMX and GNP-ACM. (VDW, Van der Waals.) binding energy, Δ Gbind (kcal mol −1 ) VDW + H-bond + desolvation energy (kcal mol −1 ) electrostatic energy (kcal mol −1 ) GNP-SMX −7.54 −8.74 0.00 GNP-ACM −5.29 −5.89 0.00
The adsorption mechanism of GNP towards the targeted pollutants can take place in the form of electrostatic interactions (cation or anion attraction), π–π interaction, hydrophobic interaction and hydrogen bonding [ 60 , 61 ]. Both SMX and ACM molecules contain an aromatic group or benzene ring (electronic supplementary material, figure S3). mechanisms↗The adsorption mechanism is mainly owing to interaction of the electron-rich GNP surface and the protonated aniline ring of pharmaceutical molecules. mechanisms↗When the pH is near or equal to the pKa of pharmaceutical, the pharmaceutical molecules exist in neutral form thus it favours hydrogen bonding and π–π interaction with GNPs. When the solution pH drifted to more acid or basic conditions, electrostatic interactions will occur between the GNP and pharmaceutical molecules.
Regeneration
As depicted in figure 11 , the removal efficiency for both SMX and ACM using GNP C300 through four regeneration cycles by different eluents: 0.005 M NaOH, 0.005 M HCl and 5% ethanol-deionized water is shown. By using chemical regeneration, interaction forces formed between the adsorbed pharmaceutical pollutants and the eluent molecules causing the SMX and ACM molecules to leave the adsorption sites of the adsorbent and dissolve in the eluent [ 62 ]. Among the used eluents for the adsorption of SMX, 0.005 M HCl and 5% ethanol-deionized water were able to regenerate GNP C300 where high removal efficiencies could be achieved even after the fourth cycle with 98.79%–95.18% and 98.33%–95.95%, respectively. When washed with 0.005 M NaOH, graphene efficiency was reduced from 99.28% to 78.8% in the second cycle, having the lowest percentage after the fourth cycle (32.84%). GNP C300 was able to remove 95.58%–71.45% of ACM when washed with 5% ethanol-deionized water which is the highest followed by 0.005 M NaOH and 0.005 M HCl, with removal efficiencies of 96.01%–64.35% and 97.23%–26.08%, respectively. The surface of GNP was held by weak intermolecular interactions viz. Van der Waals forces and dipole–dipole interaction [ 38 ]. limitationsAfter several cycles, the removal efficiency of GNP is reduced because of the loss of GNP during the washing process as it was not fully separated by centrifugation. content_tagsConclusively, regeneration of the GNP C300 by 5% ethanol-deionized water was considered the suitable eluent for both pollutants, SMX and ACM with high removal efficiencies after several adsorption–desorption cycles. Figure 11. Removal efficiency of GNP C300 ( a ) SMX ( b ) ACM versus regeneration cycle using different eluents.
Real water application
Based on figure 12 , it can be concluded that GNP C300 managed to remove most of the pharmaceutical pollutants from the spiked real water samples. content_tagsMore than 98% of SMX were removed from all three real water samples: Langat river water, Kuyoh river water and tap water, while for ACM the removal efficiency was somewhat lower than SMX yet more than 90%. As shown in the figure, GNP C300 able to remove, respectively, 93.83%, 95.76% and 96.45% of ACM, as for SMX 98.10%, 98.79% and 99.88% from Langat river water, Kuyoh river water and tap water. The results proved that GNP C300 is also suitable for the real water application. Figure 12. Removal efficiency of GNP C300 on real water samples; Langat river water, Kuyoh river water and tap water.
Conclusion
In conclusion, all four types of GNPs were able to remove SMX and ACM from water. GNP C300 shows the highest adsorption capacity compared to GNP C750, M15 and M5. The unexplored potential of GNP C300 and the rest has revealed the other types GNP that work better compared to C750, which is a bit costly and faces an agglomeration problem. The removal of pharmaceuticals with different pKa values was strongly affected by pH. phenomenoncontent_tagsIt is proved that the adsorption of SMX and ACM using GNP C300 was owing to chemisorption as the data were best fitted with pseudo-second order. The adsorption data fitted well with both Langmuir and Freundlich isotherms. Owing to slightly higher R 2 , the Langmuir model was more suitable for describing the adsorption process of GNP C300 towards both pharmaceuticals. In addition, GNP C300 can remove up to 99% of SMX and ACM. On top of that, a negative value of binding energy from docking showed that the adsorption was spontaneous and exothermic. In addition, 5% ethanol-deionized water was found to be the best eluent for the regeneration of GNP C300 as adsorbent for the removal of SMX and ACM. Real water application results showed that GNP C300 managed to remove most of the pharmaceutical pollutants from the environmental samples. contributionclaim_typeGNP C300 exhibits great potential as an excellent adsorbent with high adsorption ability for the removal of SMX and ACM, and thus may also be used towards other pharmaceutical pollutants.
Supplementary Material
Relations on this page carry a quotation for the claim. Where a relation was separately evidenced — and so tested against the vocabulary for its type — the row says so; 7 of 7 relations here carry that mark. The rest are the tagger’s reading of the sentence quoted beside them.
This record holds no relations between claims or controls. A layer is empty when the tagger recorded nothing in it — which is not the same as the paper having nothing to record.
| facet | tag | field | conf. | whose words |
|---|---|---|---|---|
| object_of_study | adsorptive removal of sulfamethoxazole and acetaminophen from water by graphene nanoplatelets | object_of_study | the paper's words | |
| research_question | how efficiently GNPs remove SMX and ACM from water by adsorption | research_question | the paper's words | |
| contribution | GNP C300 identified and optimised as an adsorbent reaching 99% removal, with regeneration and real-water tests | contribution | the paper's words | |
| claim_type | method | claim_type | the paper's words | |
| phenomenon | chemisorption of pharmaceutical pollutants onto graphene nanoplatelets | phenomenon | the paper's words | |
| method | experiment also in: experiment | method | the paper's words | |
| mechanisms | Adsorption mainly comes from the electron-rich GNP surface interacting with the protonated aniline ring. also in: electron-rich surface interaction | mechanisms[0] | 0.75 | the tagger's words |
| mechanisms | Near the pKa the drugs are neutral, favouring hydrogen bonding and π–π interaction with GNPs. also in: neutral form near pKa | mechanisms[1] | 0.75 | the tagger's words |
| mechanisms | C750's high surface area may make it clump, lowering its adsorption of SMX. status: This might be owing to also in: aggregation of C750 | mechanisms[2] | 0.6 | the tagger's words |
| mechanisms | The different capacities for SMX and ACM can be explained by the docking binding energies. also in: binding energy | mechanisms[3] | 0.65 | the tagger's words |
| limitations | Some small C750 particles may have passed the 0.22 µm filter. | limitations[0] | 0.7 | the tagger's words |
| limitations | Removal efficiency drops over regeneration cycles because GNP is lost in washing. | limitations[1] | 0.8 | the tagger's words |
| limitations | Intraparticle diffusion controls only the early stage, not the whole process. | limitations[2] | 0.7 | the tagger's words |
| concepts | graphene nanoplatelets also in: graphene nanoplatelets | concepts[0] | 0.75 | the paper's words |
| concepts | GNPs also in: GNPs | concepts[1] | 0.95 | the paper's words |
| concepts | sulfamethoxazole also in: sulfamethoxazole | concepts[2] | 0.75 | the paper's words |
| concepts | SMX also in: SMX | concepts[3] | 0.95 | the paper's words |
| concepts | adsorption also in: adsorption | concepts[4] | 0.8 | the paper's words |
| concepts | adsorption capacity also in: adsorption capacity | concepts[5] | 0.85 | the paper's words |
| concepts | removal efficiency also in: removal efficiency | concepts[6] | 0.7 | the paper's words |
| concepts | solution pH also in: solution pH | concepts[7] | 0.7 | the paper's words |
| concepts | initial concentration also in: initial concentration | concepts[8] | 0.7 | the paper's words |
| concepts | C300 also in: C300 | concepts[9] | 0.75 | the paper's words |
| concepts | C750 also in: C750 | concepts[10] | 0.75 | the paper's words |
| concepts | pseudo-second-order model also in: pseudo-second-order model | concepts[11] | 0.75 | the paper's words |
| concepts | pseudo-first-order also in: pseudo-first-order | concepts[12] | 0.7 | the paper's words |
| concepts | film diffusion also in: film diffusion | concepts[13] | 0.9 | the paper's words |
| concepts | pore diffusion also in: pore diffusion | concepts[14] | 0.9 | the paper's words |
| concepts | D band also in: D band | concepts[15] | 0.85 | the paper's words |
| concepts | G band also in: G band | concepts[16] | 0.85 | the paper's words |
| concepts | sharp peak also in: sharp peak | concepts[17] | 0.65 | the paper's words |
| concepts | zeta potential also in: zeta potential | concepts[18] | 0.85 | the paper's words |
| senses | surface area - expected to raise adsorption efficiency, an expectation this paper's C300 result contradicts | senses[0] | 0.75 | the tagger's words |
| concept_edges | GNPs —same-as→ graphene nanoplatelets the relation itself is separately evidenced · strength of the relation: 0.95 · the relation stated: (GNPs) also in: GNPs · graphene nanoplatelets | concept_edges[0] | 0.95 | the tagger's words |
| concept_edges | SMX —same-as→ sulfamethoxazole the relation itself is separately evidenced · strength of the relation: 0.95 · the relation stated: (SMX) also in: SMX · sulfamethoxazole | concept_edges[1] | 0.95 | the tagger's words |
| concept_edges | C300 —contrasted-with→ C750 the relation itself is separately evidenced · strength of the relation: 0.85 · the relation stated: compared ... despite | concept_edges[2] | 0.85 | the tagger's words |
| concept_edges | pseudo-second-order model —contrasted-with→ pseudo-first-order the relation itself is separately evidenced · strength of the relation: 0.85 · the relation stated: fitted better than also in: pseudo-second-order model · pseudo-first-order | concept_edges[3] | 0.85 | the tagger's words |
| concept_edges | G band —is-a→ sharp peak the relation itself is separately evidenced · strength of the relation: 0.8 · the relation stated: which is a also in: G band · sharp peak | concept_edges[4] | 0.8 | the tagger's words |
| concept_edges | solution pH —causes→ adsorption capacity the relation itself is separately evidenced · strength of the relation: 0.8 · the relation stated: resulted in also in: solution pH · adsorption capacity | concept_edges[5] | 0.8 | the tagger's words |
| concept_edges | initial concentration —causes→ adsorption capacity direction on the measure: increases · the relation itself is separately evidenced · strength of the relation: 0.8 · the relation stated: resulting in a higher also in: initial concentration · adsorption capacity | concept_edges[6] | 0.8 | the tagger's words |
| content_tags | C300 removed the most SMX although C750 has the larger surface area. | content_tags.findings[0] | 0.9 | the tagger's words |
| content_tags | Langmuir fitted slightly better, indicating monolayer adsorption on a homogeneous surface. | content_tags.findings[1] | 0.8 | the tagger's words |
| content_tags | Pseudo-second-order kinetics fitted better, taken as chemisorption. | content_tags.findings[2] | 0.8 | the tagger's words |
| content_tags | Docking gave negative binding energies, meaning spontaneous binding. | content_tags.findings[3] | 0.8 | the tagger's words |
| content_tags | Adsorption lowered the BET surface area of C300. | content_tags.findings[4] | 0.8 | the tagger's words |
| content_tags | 5% ethanol-deionized water was the suitable eluent for regeneration. | content_tags.findings[5] | 0.8 | the tagger's words |
| content_tags | C300 removed over 98% of SMX and over 90% of ACM from real water samples. | content_tags.findings[6] | 0.85 | the tagger's words |
| content_tags | Raman ratios show the GNPs are multilayer. | content_tags.findings[7] | 0.8 | the tagger's words |
| content_tags | the transport of adsorbate from the bulk phase to the external surface of the adsorbent also in: film diffusion | content_tags.definitions[0] | 0.9 | the tagger's words |
| content_tags | the transport of adsorbate from the external surface into the pores also in: pore diffusion | content_tags.definitions[1] | 0.9 | the tagger's words |
| content_tags | known as the disorder band also in: D band | content_tags.definitions[2] | 0.85 | the tagger's words |
| content_tags | maximum adsorption capacity for SMX and ACM | content_tags.quantities[0] | 0.9 | the tagger's words |
| content_tags | optimum pH for SMX and ACM | content_tags.quantities[1] | 0.9 | the tagger's words |
| content_tags | BET surface area of C750 and C300 | content_tags.quantities[2] | 0.9 | the tagger's words |
| content_tags | zeta potential of GNP C300 | content_tags.quantities[3] | 0.9 | the tagger's words |
| content_tags | pH of the pharmaceutical solution, 2 to 10 also in: solution pH | content_tags.variables[0] | 0.8 | the tagger's words |
| content_tags | starting pharmaceutical concentration, 10 to 100 mg l −1 also in: initial concentration | content_tags.variables[1] | 0.8 | the tagger's words |
Tags that could not be placed in the text:
What was deliberately not tagged, and why, is recorded per paper by the tagger. Where a paper has no such record, this page says so rather than implying that nothing was declined.