2.1 Reagents

Graphite powder (average particle size ∼ 50 μm, purity > 99.5 %) and H₃PO₄ solution (85 wt%) were supplied from Merck Company (Darmstadt, Germany). Zinc oxide (ZnO) nanocarriers (average particle size < 100 nm, purity > 99.5 %), adsorbates of MO (C₁₄H₁₄N₃NaO₃S) as an anionic dye and MB (C₁₆H₁₈ N₃ClS) as a cationic dye, solutions of KMnO₄ (0.02 mol.L^-1 (0.1 N)), H₂O₂ (30 wt%), sodium dodecyl sulfate (SDS) (ACS reagent, ∼ 99 %), Cadmium Chloride (CdCl₂), lead nitrate (Pb(NO₃)₂), and NaOH were obtained from Sigma-Aldrich Company (St. Louis, MO, U.S.). Furthermore, extra pure H₂SO₄ (98 wt%) and HCl (35 wt%) were received from Mojallali company (Mojallali, Iran). All chemicals and reactants were of analytical grade, without any further purification.

2.2 Synthesis of graphene oxide (GO)

As a well-known method, graphene oxide (GO) is dominantly synthesized through the chemical oxidation of natural graphite. In this work, GO was treated by an easy, convenient, and cost-effective method, based on the modified Hummer's method (Oral et al., 2020); (Arabpour et al., 2021). In detail, 70 (mL) of protonated solvent that was prepared through a mixture of H₂SO₄ and H₃PO₄ (9:1 vol ratio) was introduced into a beaker containing 0.45 (g) graphite powder and stirred in an ice bath for 20 (min.). Next, 3.5 (g) KMnO₄ as a strong oxidizing agent was slowly added to the mixture at a constant temperature of 5 °C and let to continue the reaction for 2 h. Then, the resultant suspension was heated to 35 °C and eventually ultrasonicated for 1 h. As the final step of the synthesis method, the mixture was added to 70 (mL) of deionized water to dilute and stop the reaction and 2 (mL) of H₂O₂ to remove any metal ions from the oxidizer. The resulting yellow–brown liquid indicated a considerable extent of oxidation. Ultimately, the remaining solid material which was obtained through filter paper and funnel was treated with 5 % HCl aqueous solution, centrifuged (Hettich, EBA 20), and washed with deionized water repeatedly until the pH of the reaction product was essentially neutral. The synthesized brown-black material was eventually dried in a vacuum oven at 50 °C for 24 h.

2.3 Synthesis of graphene oxide-ZnO (GO-ZnO) nanocomposite

The nanocomposites (GO-ZnO 1%, GO-ZnO 3%, GO-ZnO 5%) were synthesized based on the solution mixing method. To obtain the ZnO dispersion, the corresponding amounts of ZnO nanoparticles were sonicated in 50 (mL) of a homogenous mixture of ethanol/water (1:1 vol ratio) for 2 h. The GO's suspensions were obtained by various extents of the synthesized GO dissolved in 50 (mL) of deionized water containing 1 % SDS and put inside the sonicated bath for about a 2 h period. The SDS surfactant improves the suspension process by maintaining uniform colloidal dispersion and preventing metal particle agglomeration. To achieve the homogenous mixture, next, the GO water suspension was added to the ZnO dispersion in equal amounts and sonicated at ambient temperature (23 ± 1 °C). After 30 (min.) NaOH (1 M) solution was added dropwise till the resulting product was adjusted at the pH = 10. Later, the solution was heated in the water bath for 5 h at an elevated temperature of 85 °C. The precipitate was ultimately collected through centrifugation and washed with deionized water several times, and, at last, it was transferred into an oven at 50 °C for solvent evaporation.

2.4 Structural analysis

The crystalline structure of the synthetic and natural samples was distinguished from the X-ray powder diffraction analysis (XRD) pattern by using the powder diffractometer (EQUINOX-3000, Intel, France) equipped with Cu K_a radiation (λ = 1.541 Å) at 40 (kV) and 30 (mA), with a scanning speed of 2θ = 5/min. between 4 and 90° 2θ angular range. To make micro-morphological observations, the synthesized GO and GO-ZnO samples were subjected to Scanning Electron Microscopy (SEM) using a scanning electron microscope (AIS-2100 Seron Technology, Seron Technology, Korea) operating with up to 20 (kV) acceleration voltage field emission gun at 25 Kx (different) magnifications. Notably, all sample fragments were previously sputter coated through an ultrathin layer of conductive gold.

2.5 Batch adsorption assay

The batch adsorption method was applied to evaluate. The photocatalytic performance of both organometallic species and organic components of typical metathesis reactions. The stock solutions of MB, MO, Cd²⁺, and Pb²⁺ pollutants (1000 ppm) were set up according to the dilution method in the deionized water. A given proportion of the GO-ZnO absorbent was dispersed in a flask of 25 (mL) for each stock solution. The flasks were then transferred to an incubator shaker (150 rpm, SI-100R, tradekorea, South Korea) and thoroughly agitated for 2 h at room temperature (23 ± 1 °C). The pH extent was adjusted by using NaOH (0.1 N) and HNO₃ solutions (0.1 N). Having been filtered to separate the dye solutions from the adsorbent, all solutions were analyzed to determine the contaminant concentration with Uv–Vis spectroscopy. In this work, a UV–Vis. spectrophotometer (Lambda 25, Perkin Elmer, U.S.) was used, and the recorded UV–Vis. spectra have been measured at λ_{MB and MO} = 664 (nm), while Cd²⁺ and Pb²⁺ concentrations were determined through atomic absorption (AA) methodology.

Kinetics and isotherm studies were eventually applied to the obtained sorption data. The measure of sorption capacity q_t (mg.g⁻¹) and the removal efficiency (%R) were determined according to Eqs. (1) and (2), respectively (Dan et al., 2023):

2.6 Adsorption kinetic

The adsorption kinetic trials were conducted by shaking the desired GO-ZnO absorbent (10 mg) with diverse initial concentrations of contaminants for diverse time interims (30–720 min.) as separate experiments. Having been centrifuged to separate the solutions from the solid sorbent, all samples were subjected to determine the dyes and cations concentrations through UV–Vis. spectrophotometer and AA technique, respectively. Solutions pH was also fixed to 2 and 12 for the dye MB and MO and 2 and 10 for the Cd²⁺ and Pb²⁺ removal, respectively, except where the pH effect on the adsorption process was investigated and controlled by supplementing drops of HNO₃ or KOH (1 M) solution. From these measurements, the extent of adsorbed pollutants at the anytime q_t (mg.g⁻¹) was calculated as Eq. (1) for any time (Iriel et al., 2018); (Banivaheb et al., 2021):

2.7 Adsorption isotherms

The isotherm studies were explored to predict the adsorption mechanisms and the distribution behavior of the adsorbate dyes and ions between the solid and fluid. The impact of the dyes and heavy metals' initial concentrations on removal efficiency was understood by GO-ZnO absorbent (10 mg) in contact with diverse initial concentrations of contaminants (C_{i, MB} = 10–125; C_{i, MO} = 10–150; C_{i, Cd}²⁺ =10–100; C_{i, Pb}²⁺ =10–175 mg.L^-1) as separated experiments at constant pH 7. Having been centrifuged to separate the dye solutions from the solid sorbent, all samples were subjected to determine the pollutants concentrations through UV–Vis. and AA spectrophotometers.

2.8 Influence of pH

To evaluate the pH impact on the pollutant's optimum uptake, the weighted quantity of the synthesized GO-ZnO absorbent (10 mg) was rigorously shaken with 25 (mL) of MB, MO, and Cd²⁺ (50 mg.L^-1) and Pb²⁺ (100 mg.L^-1) solutions at various pH values (2–12) for 2 h, as separated tests. Eventually, the solutions and solids were separated, and the filtrate was collected for optimal pH investigation.

2.9 Antibacterial activity

Disk diffusion technique was implemented to investigate the antibacterial function of synthesized nanomaterials. The zone inhibition method was applied to study the antibacterial activity of nanostructures. In this case, two gram-positive bacterial strains of Staphylococcus Aureus (ATCC 25923) and gram-negative ones of Escherichia Coli (ATCC 11229) were cultured in the nutrient agar medium as maintenance for a wide variety of non-fastidious bacteria. The culture media preparation was finalized by suspending the agar powder (23 g) in highly purified water (1 L) and heating (∼45 °C) with frequent agitation for ∼ 2 (min.) to completely dissolve the powder. Later, a 15–20 (mL) volume of the ready media was poured into a 60-mm sterile glass petri dish and left standing for ∼ 30 min. to solidify. Next, the agar-loaded plates were inoculated with 100 (µL) of 108 Colony-forming units (CFU).mL⁻¹ using standard microorganisms' suspensions. The filter paper discs that were thoroughly sterilized were placed on top of inoculated plates and 15 (µL) of the nanomaterial solutions (a quantity of 50 (mg) samples containing 10 % solution in purified water) were pipetted on the disks. Eventually, test samples were firmly sealed to alleviate chances of any contamination and incubated with a shaker (150 rpm) at 37 °C overnight.

3.1 Structural and morphological characterization

The XRD patterns of the pure GO and GO-ZnO nanocomposite are represented in Fig. 1. As observed, no impurity peaks were observed, thereby demonstrating that the resulting composition was a combination of GO and GO-ZnO with high purity and no impurities had been produced. The obtained XRD spectrum also represents the characterization of pristine graphene oxide sheet by diffraction peaks at 2θ of 10.77° related to (0 0 1). This is on account of the presence of the functional groups, including oxygen, on the graphene/graphene oxide layers and the increment of the interlayer distance as well. The obtained XRD pattern of the synthetic nanocomposite expresses the doping of different levels of GO resulting in the wider peak shape and lower intensity of GO-ZnO compared to pristine GO and a decline in crystallinity of the nanocomposite sample. In detail, with regards to previous studies (Malekkiani et al., 2022; Ghoreishi et al., 2013), ZnO characterization peaks represent ranging from 2θ of 30.0° to 70.0°. As observed in Fig. 1, the nanocomposite peaks have gotten weaker and shifted to the right reflecting the coordination reaction between Zn²⁺ and GO, which, in turn, leads to altering the GO-ZnO crystallinity. Therefore, it could be concluded that the crystal structure of ZnO nanoparticles had been successfully transformed into the synthetic nanostructure and positioned on the outer surface of the GO-ZnO. However, a new weak diffraction peak approximately at 2θ of 26° that is related to (0 0 2) was observed, indicating the reduction of the graphene oxide into the graphene, and subsequently the disordered stacking of graphene sheets in the synthesized nanocomposite (Ghoreishi et al., 2013). Indeed, the weakness of the graphene diffraction peak (2θ = 26°) related to the insignificant mass ratio of graphene in comparison with ZnO demonstrates the formation of graphene sheets that have been redecorated by hexagonal ZnO nanoparticles.

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Fig. 1

X-ray diffractograms for the GO and GO-ZnO nanocomposites.

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The surface topography of the samples detected by SEM at various magnifications is depicted in Fig. 2. As illustrated in the inset of Fig. 2(A-B), the morphology of the graphene oxide surface was smooth indicating that it comprised tremendously stacked planes. Owing to cavities that were firmly connected, the edges of the graphene oxide sheets were inclined to fold to create highly crumpled multilayers, resulting in fading of sheet-like structures. However, the SEM images in Fig. 2(C-D) revealed that the introduction of ZnO nanoparticles uniformly dispersing over the GO matrix diminished the congestion, and the surface smoothness disappeared by creating hollow-shaped spaces between the GO layers. As expected, on account of the 3D cross-linked nature of ZnO nanoparticles that tend to be homogeneously coated on the surface of the graphene oxide sheets, the flake-like GO-ZnO morphology was successfully formed over the reaction (Ghoreishi et al., 2013). Moreover, the SEM microphotographs given in Fig. 2 indicated that the nanoparticles were acceptably attached to the GO surface, and the GO matrix considerably prevented the agglomeration of the supplemented nanoparticles, which is due to the uniform distribution and good coupling nature of ZnO. It is noteworthy that the uniform and small agglomeration of the nanoparticles contributes to higher dyes and cations adsorption on the nanocomposite surface.

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Fig. 2

Scanning electron micro-graphs of the GO (A and B) and GO-ZnO nanocomposite (C and D); Transmission electron micrographs with a magnification of 10.00 KX (A and C) and 50.00 KX (B and D).

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3.2 Pollutant adsorption study

The adsorption capability evaluation of the synthetic nanocomposite was carried out through its activities on the removal of the MO and MB pollutants as organic targets and desired heavy metals of the Cd²⁺ and Pb²⁺. So, the effect of concentration and pH traces of the solutions were studied for the removal (%) of the contaminants.

3.2.1

3.2.1 Effect of nanoparticle on adsorption process

Graphene oxide (GO) is one of the most common compounds used as an advanced adsorbent due to its unique properties. These properties such as large surface area, high chemical stability, and mechanical properties can vary and depend on the layer count structure of the compound. One of the main disadvantages of GO is the low adsorption capacity that limits its applications in wastewater treatment. One of the approaches to enhance the adsorption capacity of GO is to incorporate it with various compounds such as polymers and metal oxide nanoparticles. ZnO nanoparticles can act as adsorption sites and improve the adsorption properties of GO. In this study, GO-ZnO nanocomposites with various ZnO loading percentages (1%, 3%, and 5%) were synthesized. The adsorption tests of the synthesized nanocomposites were carried out in batch experiments. The results shown in Fig. 3 indicate that the GO-ZnO nanocomposite that contains 3% ZnO shows the highest adsorption efficiency for all the pollutants. The adsorption capacity of the nanocomposites increased as the amount of ZnO loading increases to 3%. The addition of ZnO over 3% to the GO-ZnO structure results in a decrease in the adsorption capacity. The optimal loading percentage of ZnO to achieve the highest adsorption capacity is nanocomposite containing 3% ZnO. The high pollutant adsorption capacity of the GO-ZnO nanocomposite containing 3% ZnO can be attributed to several phenomena. One of the main reasons is the synergistic effect of the two components. ZnO nanoparticles provide additional adsorption sites while the GO sheets act as an efficient adsorbent due to their large surface area. Also, GO acts as a base that can improve the dispersion and stability of the ZnO nanoparticles in the medium. The nanocomposite that contains 1% ZnO showed the lowest adsorption capacity for all the water pollutants, while the nanocomposite with 5% ZnO showed a lower efficiency compared to the nanocomposite that contains 3% ZnO. The decrease in adsorption efficiency at higher percentages of ZnO can be attributed to the decrease in the surface area of graphene oxide as the percentage of ZnO increased. In addition, an excess of ZnO can also result in the aggregation of ZnO nanoparticles and graphene oxide sheets by forming a new functional group between the GO layers, which might hinder the accessibility of the active sites for adsorption.

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Fig. 3

Effect of different amounts of nanoparticle on the adsorption capacity of the nanocomposite; MB (A), MO (B), Cd²⁺ (C) and Pb²⁺ (D).

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Fig. 3

Effect of different amounts of nanoparticle on the adsorption capacity of the nanocomposite; MB (A), MO (B), Cd²⁺ (C) and Pb²⁺ (D).

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3.2.2

3.2.2 Isotherm adsorption assay

The adsorption dependence behavior of the synthesized nanocomposites to the initial concentration of the dyes and heavy metals in the given range shows up in Fig. 4A & A'. The maximum obtained adsorption capacities (mg.g⁻¹) were 96.15 and 122.01 at the concentrations of 125 and 150 (mg.L^-1) for the MB and MO, and 118.84 and 256.48 at the concentrations of 100 and 175 (mg.L^-1) for the Cd²⁺ and Pb²⁺, respectively. The increase of MB and MO concentration from 10 to 75 (mg.L^-1) led to a sharp increment of the adsorption capacities up to 93.45 to 118.03 (mg.g⁻¹), respectively, while q_e reached a plateau and set to levels of as illustrated in the graph with more increases of the initial concentration dyes. The same trend would happen to the Cd²⁺ and Pb²⁺ with the obtained adsorption capacities up to 106.76 and 253.32 (mg.g⁻¹) at the concentrations of 50 and 125 (mg.L^-1), respectively. The findings also indicate that with the increase in the adsorbate levels, removal efficiency deteriorated from 97.49% to 30.77%, 98.37% to 32.54%, 95.73% to 47.53%, and 97.10% to 58.62% for MB, MO, Cd²⁺ and Pb²⁺, respectively. The diminished adsorption rate with the increase of the operating parameter of the pollutants' concentrations might be credited to a drop in available active areas for the adsorption. At lower concentrations due to the availability of more adsorption/vacant sites, the concentration gradient between the adsorbate in solution and the adsorbate on the adsorbent tends to be higher. Therefore, through the fast diffusion of into the interparticle matrix, the contaminants effectively interact with the nanocomposite sorbent, leading to enhanced removal efficiency (Malekkiani et al., 2022; Ahmada et al., 2016).

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Fig. 4

Influences of the initial solution concentrations (A) and pH (B) on the dyes and cations q_e and removal (%) by the synthetic nanocomposite GO-ZnO; Initial conditions: 25 (mL) of the MB, MO, and Cd²⁺ (50 mg.L^-1) and Pb²⁺ (100 mg.L^-1) adsorbates, the adsorbent 10 (mg).

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3.3 Adsorption kinetics

Time is a key factor for adsorption system designs. The influence of the contact time on the components' adsorption was evaluated to obtain the relevant kinetics parameters under the controlled conditions of pH = 6 and pH = 8 for the dyes and metal ions solutions, respectively, at the initial concentrations up to 50 and 125 (mg.L^-1) for the MB, 75 and 150 (mg.L^-1) for the MO, 50 and 100 (mg.L^-1) for the Cd²⁺, and 75 and 150 (mg.L^-1) for the Pb²⁺ pollutants. The measured reaction kinetic of the dyes and heavy metals adsorption as a function of time were fitted to both pseudo-first-order (PFO) and pseudo-second-order (PSO) kinetic expressions. The kinetics models applied for characterizing the adsorption tendency are expressed as (Bhattacharya and Venkobachar, 1984):

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Fig. 5

Pseudo-first-order and Pseudo-second-order adsorption kinetics models for the MB (A & B), MO (A' & B'), Cd²⁺ (C & D), and Pb²⁺ (C' & D') adsorptions on the synthetic nanocomposite GO-ZnO; Initial conditions: 25 (mL) of the adsorbates, the adsorbent 7.5 and 10 (mg).

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3.4 Equilibrium adsorption isotherms

A deep understanding of adsorption isotherms is crucial for productive adsorption system designs as well as overall the upgrade of adsorption mechanism pathways. Indeed, the connection between adsorbates and adsorbents, in the equilibrium state, can be characterized through adsorption isotherms. To clarify very well-fitting adsorption models, a linear regression analysis has been frequently applied since it has the potential to verify the theoretical assumption consistency of adsorption isotherm models and quantify adsorbates distributions (Ayawei et al., 2017). To understand the maximum adsorbed quantity via the GO-ZnO for the MB and MO dyes and heavy metals of Cd²⁺ and Pb²⁺, equilibrium trials were conducted at different initial concentrations and pH ∼ 6 and ∼ 8 with an adsorbent dose of 10 mg, alongside during the contact time of 45 min. Eventually, the experimental data obtained in the batch adsorption experiments were adjusted to Langmuir, Freundlich, Temkin, and Flory-Huggins isotherms (Temkin, and Flory-Huggins isotherms are described in detail in Appendix A). All the experimental equilibrium data of the pollutant's adsorption were fitted to the applied linearized isotherms (Fig. 6) and the corresponding parameters were reported in Table 2.

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Fig. 6

Linearized fits of the Langmuir, Freundlich, Temkin, and Flory-Huggins (F-H) isotherms (A, B, C, and D, respectively) for the adsorption of the dye pollutants of the MB and MO (at pH ∼ 6) and the heavy metals of the Cd²⁺ and Pb²⁺ (at pH ∼ 8) onto the synthetic GO-ZnO; Initial conditions: 10 mg of the adsorbent, the initial concentration range: 10–175 (mg.L^-1) at 298 K.

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Langmuir adsorption is one of the equilibrium isotherms applied to quantify as well as contrast the adsorptive capacity of varied adsorbents. This isotherm explaining affinity between adsorbents and adsorbates assumes that an adsorption process occurs on homogeneous sites of the solid media and that just monolayer formation takes place without any interactions between the adsorbed molecules (Shaban et al., 2018). Accordingly, Langmuir isotherm clarifies the surface coverage by balancing the respective adsorption and desorption rates (dynamic equilibrium) (Iriel et al., 2018). The q_e (mg.g⁻¹) for Langmuir isotherm was obtained in the linearized form (Eq. (5)) (Dan et al., 2023).

The obtained q_Max., based on the Langmuir isotherm (Fig. 6A and Table 2), was determined as 99, 125, 121.951and 277.778 (mg.g⁻¹) for the MB, MO, Cd²⁺, and Pb²⁺, respectively, that is, the adsorption process using the synthesized adsorbent was very good for the MO dye as it had the highest maximum monolayer adsorption capacity. The K_L extent for the four adsorption systems showed a relatively small level (0.429, 0.382, 0.590, and 0.176 (L.mg⁻¹) for MB, MO, Cd²⁺, and Pb²⁺, respectively), meaning that there was weak interaction between the adsorbates molecules and the absorbent since the active sites adsorbed only one molecule. Meanwhile, the adsorption of the GO-ZnO adsorbent matched the Langmuir isotherm with a coefficient correlation (R² > 0.99) too far closer to 1. This signified that the studied adsorption using the GO-ZnO adsorbent permitted monolayer formation. All the calculated R_L levels were also in the range of 0–1, reflecting the favorable adsorption of the contaminants through the examined nanostructure.

The obtained equilibrium data was also fitted by using the applicable Freundlich isotherm (Eq. (7)) considering a heterogeneous adsorption surface and an exponential distribution of activated sites and their energies. To rephrase it, Freundlich isotherm is contingent on a non-uniform, multilayer, alongside heterogeneous adsorption (Chikate and Kadu, 2014).

R² extents ranging from 0.999 to 1.000 indicate that the empirical adsorption data of the adsorbate on the adsorbent were very well good mathematically fitted in the corresponding model. The Langmuir isotherm described the adsorption behavior of the desired dyes and heavy metals on the synthesized GO-ZnO better than the other studied two-parameter models as the related coefficients of the Langmuir equation were higher for all pollutants (R² > 0.99). Therefore, based on R² according to (Table 2), the Freundlich, Temkin, and Flory-Higgins isotherms were not suitable for the studied dyes and heavy metals adsorption onto the given nanocomposite. The adsorption system with the synthetic GO-ZnO adsorbent for all studied pollutants followed suit with the order of the Langmuir > Temkin > Freundlich > Flory-Higgins. In addition, equilibrium data could not be applied to firmly establish the nature of the present adsorption process. To put it in another way, this model might be characterized by presuming a mono-layer adsorption reaction, that is, the adsorbed layer comprised only one molecule in thickness, accordingly adsorption was able to only occur at a finite sites number. Cautiously, based on the linear curve of the Temkin adsorption (Fig. S1A), the adsorption system with the examined adsorbent was compatible with the Temkin isotherm model. Indeed, the uptake behavior of the selected pollutants was described satisfactorily using the Temkin isotherm model with a reasonable correlation coefficient. At last, it can be concluded that these present dyes and metals adsorption represented, to some extent, by the Langmuir isotherm model followed by Temkin isotherm, meaning that the adsorption by the synthetic GO-ZnO occurred in a multilayer form. According to Ederer et al. (Ederer, 2022), the Temkin isotherm can be applied to describe MB pollutants on GO. The presence of diverse indirect MB interactions with the GO surface that is confirmed by the data of the nonlinear fitting probably comes from the interactions of the MB with GO carbon honeycomb structure and functional groups. Several researches have been also conducted with graphene oxide for the removal of diverse metallic ions, such as Cd, Al, Cu, Ni, Zn, Pb, and Co (Ahmada et al., 2016; Rodríguez et al., 2020; Kong, 2020; Wang, 2018). In all these cases, the Langmuir adsorption model had a very good fit for experimental data.

Table 3 represents a maximum adsorption capacity comparison among various adsorbents and components with their given experimental conditions and mathematical models applied for data fitting towards MB and MO dyes and the metallic ions of Cd²⁺ and Pb²⁺. There are noteworthy differences in q_Max. values as may be expected. However, the lower uptakes of the GO/magnetic cellulose composite, magnetic multi/wall carbon nanotube, GO/polyaniline, CPOM, and fly ash/chitosan do not mean that they are inefficient subjects. The low q_Max. levels of the studied pollutants through the adsorbents reported by other authors (Table 3) should be probably connected with some factors, including synthesis procedures, GO oxidation degree, the hydroxyl groups number of adsorbents' surface, and eventually the degree of structural vacancy defects in the honeycomb structures of the adsorbents such as GO. Conversely, due to any ionized and activated interactions with the dye structure at pH ∼ 7, the GO/SiO₂ nanocomposite tends to improve considerably the MB adsorption capacity up to 555.50 (mg.g¹). Overall, the comparison of the studied pollutants' adsorption on the synthetic nanocomposite and other individual components indicates that the present GO-ZnO would be likely to exhibit acceptable adsorption efficiency towards both given dyes and metal ions.

3.5 Antibacterial assay

Agar testing is a widely used method for evaluating the antibacterial activity of various materials. In this method, a nutrient-rich agar medium is used to grow bacterial colonies, which are then treated with the test material. The agar plates are then incubated under specific conditions to promote bacterial growth, and the degree of bacterial growth inhibition is evaluated by analyzing the size and number of bacterial colonies on the agar plates. The GO-ZnO nanocomposite might be a promising candidate for applying as an antibacterial agent due to its unique combination of properties. The high surface area of the nanocomposite enables it to adsorb bacterial cells, while the photocatalytic activity of the ZnO nanoparticles generates reactive oxygen species (ROS) that damage and kill bacterial cells. The graphene oxide component of the nanocomposite also contributes to its antibacterial activity by disrupting the cellular processes of bacteria. In the case of the agar testing, bacterial colonies of E. coli and Staphylococcus aureus were grown on agar plates, and the GO-ZnO nanocomposite was applied to the surface of the plates. The plates were then exposed to light to activate the photocatalytic activity of the nanocomposite. The results of the agar testing demonstrated (Table 4) that the synthetic GO-ZnO nanocomposite was highly effective against both bacterial pathogens. The nanocomposite significantly reduced the size and number of bacterial colonies on the agar plates, and in some cases, completely inhibited bacterial growth. The effectiveness of the nanocomposite in agar testing is likely due to a combination of factors. The high surface area of the nanocomposite allows for the adsorption of bacterial cells, while the photocatalytic activity of the ZnO nanoparticles generates ROS that damage and kill bacterial cells. Additionally, the graphene oxide component of the nanocomposite may disrupt the cellular processes of bacteria, contributing to its antibacterial activity.

Overall, the agar testing confirms the antibacterial activity of the synthetic GO-ZnO nanocomposite against E. coli and Staphylococcus aureus and suggests its potential for use in various antibacterial applications. The results of the study demonstrate the need for further investigations to determine the optimal concentration and exposure time of the nanocomposite to maximize its antibacterial activity. Additionally, further studies are necessary to fully understand the mechanism of action of the GO-ZnO nanocomposite and its potential side effects before it can be used in practical applications.