Synergistic adsorptive and photocatalytic removal of diazinon using CdS-modified guar gum/chitosan nanofibers

2.2.1. Synthesis of cadmium sulfide (C)

The method reported by Tangsiri and Favero was utilized, with slight modifications, to prepare CdS nanoparticles [20,21]. A 100 mL aliquot of 42.5 mmol/L Cd(NO₃)₂·4H₂O solution was gradually added dropwise to 100 mL of 50 mmol/L (NH₄)₂S aqueous solution while vigorously stirring at 1500 rpm. Following complete addition, stirring was continued for a further 3 h, resulting in the production of solid precipitate with dark yellow color. The formed solid was collected by centrifugation at 3000 rpm, cleaned several times with distilled water, and dried at 80°C for 6 h.

2.2.2. Fabrication of chitosan nanofiber (CS)

CS nanofibers were fabricated via electrospinning, following the methods reported by Bahtiyar and Alzahrani with slight modifications [22,23]. Two different solutions were generated: CS (2% w/v) and PVA (5% w/v) in 2% acetic acid, each of them being magnetically stirred until complete dissolution was attained. After combining the two previously produced solutions in a 60:40 ratio (PVA: chitosan), they were homogenized using magnetic stirring at 1200 rpm. The resulting solution was added to a 5 mL syringe fitted with an 18-G stainless steel needle. Electrospinning was performed using an electrospinning system (NANON-01A, MECC, Japan) at 30°C under ambient air humidity conditions. Maintaining a constant temperature throughout the electrospinning process is critical to produce homogenous nanofibers with a uniform shape. This is achieved by placing the electrospinning unit inside a temperature-controlled chamber. The gap between the needle tip and the specimen plate remained at 15 cm, with a feed rate of 0.4 mL/h at a voltage of 25 kV. To improve the production rate, several polymer solution jets were used concurrently via the multi-jet system incorporated into the electrospinning setup. The electrospun nanofibers were subsequently dried at 50°C under vacuum conditions.

2.2.3. Preparation of guar gum/chitosan nanofiber (GCS)

GCS nanofibers were fabricated following the same procedure as CS nanofibers, with the addition of guar gum solution (1% w/v) to the CS solution before mixing with the PVA solution.

2.2.4. Preparation of CGCS

Cadmium CGCS were prepared by sonicating a 1% (w/v) cadmium sulfide solution in deionized water for 120 min, followed by mixing 10 mL of this solution with the previously prepared GCS solution. The previously described electrospinning procedure was then carried out to produce the CdS-decorated GCS nanofibers (Scheme S1).

The ratios applied between all the materials used, including PVA, CS, guar gum, and CdS during the electrospinning procedures, were determined through numerous trials to obtain a suitable homogeneous nanofiber without any observable bead defects.

2.6.1. Photocatalytic kinetics of diazinon degradation

DZ degradation kinetic studies on C and CGCS were evaluated by the Langmuir-Hinshelwood (L-H) model (Eq.13). The equation was simplified into a PFO kinetic model with an apparent rate constant, kₐₚₚ (min⁻¹). The half-life time (t₁/₂) for DZ photodegradation was obtained using Eq. (14).

2.6.2. Thermodynamics of DZ photocatalytic degradation

The Arrhenius (Eq. 15) and Eyring-Polanyi (Eq. 16) models were used to analyze thermodynamic parameters associated with DZ photocatalytic oxidation, such as activation entropy change (∆*S°, kJ/mol·K), activation enthalpy change (∆*H°, kJ/mol), and activation energy (E_a, kJ/mol). Furthermore, the activation Gibbs free energy shift (∆*G°, kJ/mol) was computed using Eq. (17).

Herein, A (s⁻¹), k_b (1.381×10⁻²³ J/K), and h (6.626×10⁻³⁴ J·s) represent the Arrhenius constant, Boltzmann constant, and Planck constant, respectively.

3.1.1. Thermogravimetric curve analysis

The thermogravimetric analysis (TGA) curves for CS, GCS, C, and CGCS from 20^oC to 800°C have been revealed in Figure S1(a). The mass losses observed at approximately 175°C can be attributed to the physically sorbed exterior and internal molecules of water, as well as gases such as carbon dioxide or hydrogen absorbed from the surroundings. For CS, GCS, C, and CGCS, the corresponding mass losses are 9.7%, 7.5%, 1.4%, and 9.7%, respectively. Due to their hydrophilic nature, materials containing biopolymers exhibited the highest capacity for water sorption. Furthermore, the addition of guar gum to chitosan reduces vapor losses, likely due to potential contacts between the functional groups of the two biopolymers. Cadmium sulfide nanoparticles (C) exhibited a lower ability to sorb surrounding water molecules due to their poor surface chemical functional groups. Cadmium sulfide exhibits strong thermal stability, experiencing only another 1.9% mass loss when heated up to 800°C, which is likely due to sulfur sublimation at elevated temperatures [24]. The mass loss observed in all nanofibers containing biopolymers between approximately 200-350°C (6.1%, 6.6%, and 4.8% for CS, GCS, and CGC, respectively) is attributed to the decomposition of guar gum and chitosan chains, as well as the dehydration of sugar rings. Increasing the temperature from 350°C to 570°C results in a mass loss of 65.3%, 57.2%, and 51.5% for CS, GCS, and CGCS, respectively. These earlier mass losses are associated with the complete decomposition of sugar chains and polymer degradation. The two temperature increases suggest that the incorporation of CdS into the biofibers to form CGCS enhances its thermal stability. The total mass loss at 800°C for CS, GCS, C, and CGCS was 83.1%, 79.4%, 3.3%, and 67.1%, respectively, suggesting that: the combination of guar gum with chitosan improves its thermal stability, while the further incorporation of CdS into the nanofiber increases its thermal stability.

3.1.2. Textural characterization via nitrogen adsorption-desorption studies

Figure S1(b) displays the nitrogen adsorption-desorption isotherms of the developed solid adsorbents, while their corresponding textural properties have been summarized in Table 1. Based on the IUPAC grouping, all solid materials displayed type IV adsorption isotherms with an H2-type hysteresis loop (except CS), recommending the presence of both micropores and mesopores. CS nanofiber, having a low surface area or highly accessible pores, may not display hysteresis, as adsorption and desorption happen at almost identical rates. The measured specific surface area values of CGCS > GCS > C > CS are 99.2, 89.5, 76.1, and 68.6 m²/g, correspondingly, while the total pore volume was determined to be 0.0908, 0.0829, 0.0825, and 0.0636 cm³/g, correspondingly. The inclusion of CdS into the nanofiber may be responsible for the distortion of the textural structure and the creation of new pores, which contribute to the increase in surface area, with CGCS having 1.1 times the surface area of GCS. The computed pore size ranged from 2.36 to 4.40 nm (radius, 1.18 to 2.2 nm), confirming the presence of mesoporosity.

3.1.3. Investigation of surface chemical functional groups (ATR-FTIR and pH_PZC)

Attenuated total reflectance Fourier transform infrared (ATR-FTIR) curves for CS, GCS, C, and CGCS have been demonstrated in Figure S1(c). For CS, a broad absorption band between 3400 and 3290 cm⁻¹ is observed, which links to overlapping O–H and N–H stretching vibrations, typical of hydroxyl and primary amine groups in the polysaccharide structure. The amide I transmittance peak, appearing around 1641 cm⁻¹, is ascribed to the C=O stretching of residual N-acetyl groups, while the amide II band near 1550 cm⁻¹ results from N–H bending vibrations. A noticeable peak at nearly 1028 cm⁻¹ reflects the C–O stretching vibration, confirming the integrity of the polysaccharide backbone. Another band, observed close to 1660 cm⁻¹, is associated with the C=O stretching in the acetamide group (NHCOCH₃). Additionally, the bands found in the range of 803–631 cm⁻¹ correspond to out-of-plane C–H bending and skeletal vibrations, which further confirm the presence of the pyranose ring structure in the chitosan matrix. The FTIR spectrum of C exhibited characteristic bands at 576, 1000, 1125, 1375, 1627, and 3423 cm⁻¹. The band at 576 cm⁻¹ is assigned to Cd–S bond stretching vibrations, while the bands at 1000 and 1125 cm⁻¹ relate to C–O stretching modes. The absorption at 1375 cm⁻¹ is associated with asymmetric O–H bending, and the bands at 1627 and 3423 cm⁻¹ are assigned to O–H stretching vibrations, likely arising from contacts between molecules of water and the CdS surface.

In the FTIR spectrum of GCS, a broad transmittance peak observed at 3419 cm⁻¹ is attributed to the stretching vibrations of –OH groups, while the band at 2923 cm⁻¹ is assigned to C–H stretching modes. The band at 1623 cm⁻¹ corresponds to the symmetric stretching of C=O groups, and the signal at 814 cm⁻¹ is associated with vibrations of the mannogalactose backbone characteristic of guar gum [25,26]. Notably, due to interactions between guar gum and CS, the characteristic bands of CS originally observed at 1408 and 1028 cm⁻¹ were shifted to 1412 and 1022 cm⁻¹, respectively, indicating successful incorporation of both components into the GCS matrix. For CGCS, the ATR-FTIR spectrum displays all the characteristic peaks corresponding to C, CS, and guar gum, with slight shifts observed in the respective absorption bands.

The final pH of solid materials is known to be largely determined by the type of surface functional groups present and their ability to attract positively or negatively charged ions from the surrounding medium. The measured pH at the point of zero charge (pH_PZC) for CS, GCS, C, and CGCS were calculated to be 6.9, 6.4, 6.3, and 7.1, respectively, indicating that the materials are around a neutral medium (Figure S1d). The surface of nearly all materials is positively charged at pH< 7 and negatively charged at pH> 7.

3.1.4. XRD analysis for all the prepared solid materials

The XRD analysis is displayed in Figure S1(e). The XRD pattern of CS characteristically shows two representative semicrystalline peaks at around 12.6° and 21.4° (2θ), related to its crystalline regions, while in the GCS these peaks are significantly decreased or broadened, giving mainly a diffuse halo near 22.3° due to the drop in crystallinity after blending and electrospinning. Pure CdS (C) displays the well-defined reflections of hexagonal wurtzite CdS (JCPDS 41-1049), with clear peaks noticed near 26.6°, 43.9°, and 52.1°, although peak broadening is often obvious at the nanoscale. For the CGCS composite nanofiber, the diffraction pattern is a superposition of the broad amorphous band of the polymer matrix around 21.7° and the sharp diffraction peaks of CdS were slightly shifted and appeared at 40.4°, and 50.1°, confirming the successful integration of CdS nanocrystals within the polymer nanofiber framework. The polymer halo is typically mild, but the strength of CdS reflections varies depending on loading and dispersion, with minor peak widening showing nanoscale crystallite size and interaction with the biopolymer substrate.

The crystallite size, lattice constant, and microstrain of the CdS phase (C) were calculated from XRD data using the Scherrer equation and conventional lattice geometry relations. The calculations used the strongest diffraction peak at 2θ = 26.6°, which corresponded to the (002) plane of hexagonal CdS. According to Bragg’s law, the interplanar spacing was 3.35 Å, resulting in a c lattice parameter of roughly 6.70 Å. This value is comparable with previously reported wurtzite CdS values. To demonstrate the impact of peak widening, the average crystallite size decreased from ∼40.8 nm (β=0.2°) to ∼16.3 nm (β=0.5°) and ∼8.2 nm (β=1.0°). These findings indicate that the CdS domains in the composite are nanocrystalline, with strain effects increasing as the coherent domain size decreases.

3.1.5. Energy band gap investigation

The UV-vis DRS spectra shown in Figure S2 reveal that the synthesized semiconductors exhibit broad reflectance across the 200-800 nm range, suggesting their ability to absorb both ultraviolet and visible light. The estimated band gap energies for C and CGCS were approximately 2.32 eV and 2.28 eV, respectively. This slight reduction in band gap upon combining C and GCS to form CGCS nanofibers implies improved electrical conductivity and more efficient charge transfer, contributing to enhanced photocatalytic performance. The observed changes in optical absorption could be attributed to alterations in the structural and morphological features of the photocatalysts. Additionally, variations in bandgap energy may result from differences in electron–hole pair generation and separation efficiency, which are crucial to the photocatalytic process. Notably, the narrower bandgap of CGCS nanofibers allows for effective excitation under visible light, leading to the generation of electron-hole pairs on the catalyst surface. This facilitates light absorption, promotes redox reactions, and significantly improves photocatalytic activity [27].

3.1.6. Morphological characterization via SEM

SEM images of CdS (C) (a), CS nanofibers (b), GCS (c), and CGCS (d, e) at 10 and 30 kX magnifications, respectively, have been shown in Figure S3. The CdS nanoparticles appear as aggregated spheres with an irregular morphology, indicating limited stability and a high degree of particle agglomeration. The CS nanofibers exhibit a fibrous and entangled structure, forming a relatively smooth and continuous network. The surface becomes rougher and more textured with the addition of guar gum, as seen in Figure (S3c). This suggests that the two biopolymers were successfully incorporated and interacted with one another, as evidenced by the increased fiber thickness and surface imperfections. The CGCS composite’s images (d) and (e) display that the CdS nanoparticles are uniformly dispersed throughout the GCS nanofiber matrix. The surface seems granular and heterogeneous at 10 kX magnification (d), but at 30 kX magnification (e), it is evident that CdS nanoparticles are finely distributed throughout the nanofiber network. Strong connections between CdS and the biopolymer matrix are indicated by this homogeneous integration, which might improve the material’s functional qualities by exposing more active sites and increasing surface area. The presence of CdS nanoparticles, which can introduce internal stress and disrupt the polymer network structure, likely leads to uneven shrinkage during the drying stage and is probably the main cause of the cracking observed in the CGCS nanofiber. It’s important to note that the CGCS nanofibers were imaged using SEM after being deposited on aluminum foil. This explains the black background and the spherical features seen in the images, which are actually due to the foil’s surface. On the other hand, the CS and GCS samples were imaged without an aluminum foil, so these background features do not appear.

3.2.1. Nanofiber solid dosage

The ratio of adsorbent mass to the volume of pollutant solution (m/v, g/L) is a key parameter in evaluating adsorption capacity. In this investigation, the influence of nanofiber adsorbent dosage was assessed across a range of 1-5 g/L, using 50 mL of DZ solution at an original concentration of 300 mg/L, pH 7, and 25°C, with a shaking period of 6 h. As illustrated in Figure 1(a), at lower adsorbent dosages, the removal efficiency was limited due to the higher ratio of DZ molecules relative to available active sites. However, increasing the dosage from 1 to 3 g/L resulted in a substantial enhancement in removal efficiency, with removal percentages rising from 46.2%, 52.3%, and 71.6% to 56.2%, 61.2%, and 94.3%, in the case of CS, GCS, and CGCS, respectively. This development is attributed to the improved availability of active sites per DZ molecule. Beyond 3 g/L, further rises in adsorbent dosage did not significantly affect removal performance, likely due to particle aggregation at higher dosages, which can lead to reduced surface area and active site accessibility. Additionally, increasing the adsorbent dosage reduces the concentration gradient between the solution and the adsorbent surface, which weakens the mass transfer driving force and leads to a decline in the adsorption rate. Moreover, adsorption equilibrium is rapidly established at very low residual DZ concentrations, limiting further adsorption before the full capacity of the adsorbent sites can be utilized. These findings indicate that an adsorbent dosage of 3 g/L is optimal for the following investigations.

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Figure 1.

(a) The impact of solid dosage and (b) pH on the adsorption of DZ onto CS, GCS, and CGCS (C_i=300 mg/L, T=25 ^oC, t=6 h, solid dosage=1-5 g/L, pH=2-10).

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3.2.2. The influence of pH on the adsorption efficiency

The initial pH of the pollutant solution notably impacts both the surface charge characteristics of the solid and the ionization situation of DZ molecules. Given that DZ has a pKₐ value of approximately 2.8, it exists predominantly in a protonated form at pH values below 2.8 (positively charged), while it converts to the deprotonated form at higher pH levels (negatively charged). The point of zero charge (pH_PZC) of the synthesized nanofiber adsorbent is around 6.8, indicating that the surface is positively charged at pH values lower than 6.8 and becomes negatively charged above this point. It is important to note that at the point of zero charge (pH_PZC) of a solid material, the surface carries a net zero electrical charge. As the pH deviates from the pH_PZC, the surface charge begins to change gradually in a stepwise manner, not abrupt. Specifically, at pH values above the pH_PZC, the surface becomes increasingly negatively charged, while at pH values below the pH_PZC, the surface acquires a gradually positive charge. This means that both positive and negative surface charges intensify in a gradual and stepwise fashion on either side of the pH_PZC [28]. As revealed in Figure 1(b), DZ adsorption is relatively low under acidic conditions. At pH 2, the removal efficiencies were 20.6%, 34.4%, and 61.2% for CS, GCS, and CGCS, respectively. This reduced removal performance at low pH can be attributed to electrostatic repulsion between the positively charged DZ molecules and the positively charged nanofiber surfaces. Raising the pH of the solution to 7 resulted in a notable enhancement in removal efficiency, increasing by 2.7, 1.8, and 1.6-fold for CS, GCS, and CGCS, respectively. This improvement is likely due to favorable electrostatic relations between the negatively charged DZ and the neutral or slightly positively charged adsorbent surface near the pH_PZC. However, further increasing the pH=10 led to a decline in removal efficiency, dropping by 4.1%, 2.2%, and 0.9% for CS, GCS, and CGCS, respectively. This decrease is apparently due to electrostatic repulsion between the negatively charged DZ and the produced negatively charged adsorbent surface [29]. Based on these results, pH 7 was identified as the ideal situation for DZ adsorption onto the fabricated nanofiber adsorbents.

3.2.3. Kinetic parameters and the impact of time on DZ adsorption

The influence of shaking time on DZ adsorption onto CS, GCS, and CGCS nanofibers was examined over a period of up to 6 h, as illustrated in Figure S4. To describe the adsorption kinetics, three nonlinear kinetic models were applied: PFO (Eq. 3), PSO (Eq. 5), and the Avrami model (Eq. 6). The corresponding kinetic parameters obtained from these models have been inserted in Table 2. As shown in Figure S4, the experimental data points plotted as capacity of adsorption (q_t, mg/g) versus shaking time (t, h), estimated using Eq. (4), demonstrate a rapid initial adsorption rate. This is ascribed to the abundance of available active sites on the solid relative to the DZ molecules at the beginning of the process. After approximately 4 h, the adsorption rate declined, indicating the approach to equilibrium. Therefore, 4 h was determined as the equilibrium time and was used in subsequent adsorption experiments.

Applying the nonlinear kinetic models as PFO (Figure S4a), PSO (Figure S4b), and Avrami (Figure S4c), and assessing the associated data in Table 2, it was discovered that the PFO equation more accurately explains the adsorption of DZ onto all investigated nanofiber adsorbents than the PSO model. The PFO model’s higher correlation coefficient (R²=0.9926) and lower reduced chi-square value (χ²=0.7215) support this finding in contrast to the PSO model’s values (R²=0.9761; χ² = 1.8178), which were calculated as average values across the samples. Furthermore, the predicted maximum adsorption capacities from the PFO kinetic model (q_cal, mg/g) are extremely close to those obtained from the Langmuir nonlinear model (q_m, mg/g) when compared to the significant variance calculated from PSO (5.4% and 20.6%, respectively). The rate constants k₁ (h⁻¹) for the adsorption of DZ onto CS, GCS, and CGCS nanofibers were determined to be 0.5478, 0.6897, and 0.7084 h^-1, respectively. These values indicate that CGCS exhibits the highest adsorption rate among the three, which can be assigned to its enhanced surface area, improved porosity, and a greater number of accessible active sites. Thus, the PFO model is the most relevant kinetic model, indicating that the adsorption process is essentially physical in nature.

The plotting of the Avrami nonlinear kinetic model to describe DZ adsorption onto CS, GCS, and CGCS nanofibers is supported by the high correlation coefficients (R²=0.9872-0.9980) and low reduced chi-square values (χ²=0.1265-0.9704). The adsorption capacities estimated by the Avrami model (q_AV, mg/g) closely match those obtained from the Langmuir isotherm, with differences of 8.8%, 5.9%, and 5.0% for CS, GCS, and CGCS, respectively, further validating the model’s suitability. The Avrami exponent values (n_AV​) for all nanofibers fall near unity (0.9945–1.0489), indicating a single-step adsorption process on a relatively homogeneous surface, consistent with a first-order-like mechanism. Moreover, the calculated Avrami rate constants (K_AV​, h⁻¹) show the order CGCS (0.7394) > GCS (0.6876) > CS (0.5664), confirming that CGCS exhibits the highest adsorption rate among the studied materials [30]. Overall, the findings acquired from the Avrami equation are in close harmony with those from the PFO model.

3.2.4. The influence of DZ starting concentration

The impact of the initial pollutant concentration was evaluated under optimal adsorption conditions, including shaking time (4 h), pH (7), solid dosage (3 g/L), and constant temperature (25°C), to enable the application of various nonlinear isotherm models. Accordingly, the nonlinear Langmuir (Figure 2a, Eq. 7), Freundlich (Figure 2b, Eq. 9), and Sips (Figure 2c, Eq. 10) models were employed using initial DZ concentrations ranging from 30 to 300 mg/L. The outcomes derived from all the applied nonlinear equations have been summarized in Table 2.

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Figure 2.

(a) Langmuir, (b) Freundlich, and (c) Sips nonlinear isotherm plots for DZ adsorption onto CS, GCS, and CGCS (T=25 ^oC, t=4 h, solid dosage=3 g/L, pH=7, C_i=30-300 mg/L).

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The adsorption isotherms of DZ onto all tested nanofiber-based solid adsorbents were well described by the three applied nonlinear models, Langmuir, Freundlich, and Sips, as shown in Figures 2(a-c) and Table 2. The experimental data in Figure 2 demonstrate that the capacity of adsorption increased significantly at lower equilibrium concentrations, attributed to the strong interaction between DZ molecules and the abundant existing active sites on the adsorbent surfaces. Among the models, the Langmuir model provided the best fit to the experimental data, as evidenced by its higher correlation coefficients (R²=0.9712-0.9933) and lower reduced chi-square values (χ²=0.3120-1.8960), compared to those of the Freundlich model (R²=0.8859-0.9698; χ² = 1.4098-6.0154). The maximum adsorption capacities estimated from the Langmuir model were 60.87, 62.09, and 99.49 mg/g for CS, GCS, and CGCS, respectively, indicating that CGCS exhibits 1.64 and 1.60 times higher adsorption capacity than CS and GCS. This enhancement is likely due to the presence of diverse surface functional groups and a developed surface area. Moreover, the Langmuir constants (b, L/mg) followed the order CGCS (0.6307) > GCS (0.3168) > CS (0.177), signifying a stronger affinity and faster adsorption of DZ onto CGCS. The dimensionless separation factor (R_L) for all adsorbents fell within the range of 0 to 1, confirming the satisfactory nature of DZ adsorption on the studied nanofiber materials.

The Freundlich constant n, also referred to as the heterogeneity factor, provides insights into the nature of the adsorption process. When n = 1, the adsorption is linear values of n < 1 suggest a chemical adsorption mechanism, while n > 1 indicates a favorable physical adsorption process. Additionally, the value of 1/n offers further interpretation: 1/n < 1 corresponds to a typical Langmuir isotherm, whereas 1/n > 1 implies cooperative adsorption. In this study, n values ranged from approximately 2.6 to 3.8, and 1/n values were between 0.2674 and 0.3862, confirming that the adsorption process is predominantly physical and aligns with a favorable Langmuir-type isotherm [30]. The Freundlich constant K_F (L^1/n. mg^1-1/n/g) values for CGCS (42.5186), GCS (20.1045), and CS (14.2563) indicate that CGCS possesses a significantly higher adsorption capacity for DZ compared to the other nanofiber-based adsorbents.

The Sips model incorporates features of both the Freundlich and Langmuir isotherms. At lower adsorbate concentrations, the behavior aligns with the Freundlich model, whereas at higher concentrations, it tends toward the Langmuir model, indicating the formation of a monolayer adsorption. The higher correlation coefficient values (R², 0.9859-0.9978), along with the lower reduced chi-square values (χ², 0.1036-1.0834), confirm the good fit of the Sips nonlinear model. The calculated maximum adsorption capacities from the Sips model (q_s​, mg/g) for all the investigated samples are 53.28, 69.75, and 126.94 mg/g for CS, GCS, and CGCS, respectively, which deviate from the values obtained using the Langmuir model by an average of 17.5%. This difference arises primarily because the Sips model accounts for surface heterogeneity and variable adsorption energies, enabling it to more accurately represent real-world adsorption systems compared to the idealized assumptions of the Langmuir model. For CS, the n_s value being less than one indicates the existence of adsorption sites with different energy levels. In contrast, n_s​ values greater than one for GCS and CGCS imply the occurrence of cooperative adsorption and possibly multilayer formation in certain cases [31].

3.2.5. Adsorption studies using a spiked real wastewater sample

Prior to any treatment procedures, an actual wastewater sample was taken from the organic laboratory of the Department of Chemistry, College of Science, University of Tabuk, Saudi Arabia, to illustrate the produced adsorbents’ practical application. The obtained sample, which already included a variety of organic pollutants, was spiked with DZ to generate a high contamination level of 300 mg/L. This spiked wastewater was then used to evaluate the adsorption capacity of CS, GCS, C, and CGCS in the presence of competing organic species. The adsorption experiments were carried out under controlled circumstances by adding 0.15 g of adsorbent to 50 mL of DZ solution at pH 7, keeping it at 25°C, and agitating it at 120 rpm for 4 h. The maximum adsorption capacity (q_m, mg/g) was then calculated for each adsorbent.

The capacity of adsorption from distilled water is significantly higher than that of actual wastewater. In distilled water, the maximal adsorption capacities of DZ onto CS, GCS, and CGCS were 60.87, 62.09, and 99.49 mg/g, respectively, demonstrating the adsorbents’ excellent effectiveness in a clean medium devoid of competing species. In contrast, when wastewater was utilized as a solvent, the capacities dropped to 43.81, 47.42, and 89.17 mg/g. This reduction is mostly caused by the presence of diverse organic and inorganic compounds in wastewater, which compete with DZ for adsorption sites or partly block them, reducing absorption effectiveness. Nonetheless, CGCS retained the best adsorption capacity in both media, proving its superior efficacy and stability under real-world settings and validating its viability for practical wastewater treatment applications.

3.2.6. Desorption and nanofiber reusability

DZ is a moderate polar organophosphorus pesticide with notable hydrophobic characteristics, giving it a strong affinity for organic solvents. As shown in Figure S5(a), the desorption efficiency (De%) of various solvents as acetone, methanol, ethanol, and isopropanol, were evaluated. Among these, acetone demonstrated the highest desorption efficiency, followed by isopropanol, while methanol exhibited the lowest desorption efficiency. The higher performance of acetone can be linked to its nature as a polar aprotic solvent, which effectively dissolves organic molecules like diazinon through dipole interactions without the interference of hydrogen bonding. Isopropanol, due to its bulkier alkyl group, forms a less extensive hydrogen-bonding network, enhancing its ability to solubilize hydrophobic compounds. In contrast, methanol’s small molecular size and high polarity promote a dense hydrogen-bonding network, which reduces its efficiency in solubilizing and desorbing hydrophobic molecules like DZ. Therefore, acetone was chosen as the regenerating agent for the solid adsorbent nanofiber.

The reusability of the synthesized solid adsorbent nanofiber was evaluated over six consecutive adsorption/desorption cycles (Figure S5b). The results showed a slight decrease in removal efficiency, with reductions of 2.4%, 2.1%, and 1.8% for CS, GCS, and CGCS, respectively. These minor losses confirm the sustainability and robust reusability of the materials. The gradual decline in adsorption efficiency is likely attributed to the partial loss or blockage of active adsorption sites during the regeneration and cleaning steps involved in each cycle.

3.3.1. Photolysis and photocatalytic degradation of DZ

The investigations were controlled both in the absence (photolysis) and presence of C and CGCS as catalysts (photocatalysis), using a catalyst dosage of 1.5 g/L and 200 mL of DZ solution with an initial concentration of 30 mg/L at pH 7 and 25°C. The process included a 30-min dark adsorption period followed by 120 min of light irradiation, as illustrated in Figure S6(a). During the initial dark phase, the adsorption removal efficiencies were 2% and 5% for C and CGCS, respectively, indicating minimal DZ removal via adsorption alone. Following the irradiation phase, DZ degradation efficiencies were recorded as 22% for photolysis (without any catalyst), 76% with C, and 90% with CGCS. These results showed that the photocatalytic performance of C and CGCS significantly exceeded that of photolysis, achieving approximately 3.4 and 4.1-fold greater degradation, respectively, after 120 min of irradiation. This demonstrates the ability of both C and CGCS to absorb light and actively participate in the photocatalytic degradation of DZ. Furthermore, CGCS exhibited superior photocatalytic activity compared to C, achieving nearly 1.2 times higher degradation efficiency. This enhanced performance may be attributed to its larger surface area (99.2 vs. 76.1 m²/g) and slightly lower energy band gap (2.28 vs. 2.32 eV), both of which contribute to improved photocatalytic behavior.

3.3.2. Influence of photocatalyst dose

The photocatalyst dosage, defined as the ratio of catalyst mass to the volume of pollutant solution, plays an essential role in photocatalytic performance. In this experiment, the impact of catalyst dosage on the degradation efficiency of DZ was evaluated after 120 min of photocatalysis using both C and CGCS as photocatalysts. The experiments were carried out under fixed conditions: 200 mL of 30 mg/L DZ solution at pH 7 and 25°C, with varying catalyst dosages of 0.5- 2.5 g/L. As shown in Figure S6(b), at the lowest dosage (0.5 g/L), the degradation efficiencies were relatively low, 64% for C and 77% for CGCS, likely due to the limited number of active sites relative to the number of DZ molecules. Increasing the catalyst dosage up to 1.5 g/L resulted in a substantial enhancement in degradation, reaching 76% and 90% for C and CGCS, respectively. This development is ascribed to the increased availability of catalytic active sites, which improved light absorption and facilitated the excitation of electrons from the valence to the conduction band. Consequently, more electron-hole pairs and reactive species such as hydroxyl and radicals of superoxide were generated, accelerating the oxidation process. However, further increasing the dosage beyond 1.5 g/L led to a slight decline in degradation efficiency by approximately 1.9% for C and 6.0% for CGCS. This reduction is attributed to many factors, such as particle agglomeration, increased turbidity, and the shielding and light scattering effects, which hinder light penetration and reduce the effective surface area exposed to illumination. As a result, 1.5 g/L was identified as the best photocatalyst dose for subsequent photocatalytic experiments.

3.3.3. The influence of initial diazinon concentrations

Initial concentration of pollutants is critical to the photocatalytic process, impacting parameters such as adsorption behavior, light penetration, the production of reactive species, and overall degrading efficacy. Proper optimization of this parameter is critical for increasing the effectiveness and economic viability of pollution removal in environmental treatment systems.

The photocatalytic degradation percentage of DZ was measured after 120 min of treatment at pH 7 and 25°C, using a fixed photocatalyst dosage of 1.5 g/L and varying the initial concentrations of DZ (10, 15, 25, 30, and 50 mg/L) as shown in Figure S6(c). It is observed that an increase in the initial concentration of DZ led to a noticeable decline in degradation efficiency. Specifically, increasing the concentration from 10 to 30 mg/L resulted in a reduction of 8.1% and 8.4% in the degradation of DZ in the presence of C and CGCS, respectively. A further increase to 50 mg/L caused a more significant drop in degradation efficiency of 30.1% for C and 27.6% for CGCS compared to the performance at 10 mg/L.

This drop in efficiency at higher initial concentrations can be linked to several factors: (i) intensified competition among DZ molecules for the limited reactive sites on the photocatalyst surface, (ii) saturation of the catalyst’s surface with excess pollutant molecules, (iii) the photocatalyst’s limited capacity to generate electron-hole pairs and reactive species due to its fixed quantity, and (iv) decreased light penetration into the solution, which limits the generation of reactive oxygen species and ultimately reduces photocatalytic activity [32].

3.3.4. Photocatalytic degradation of DZ at different application temperatures

The impact of temperature on the photocatalytic degradation of DZ was assessed by carrying out experiments at 25, 30, 35, and 40°C, using 200 mL of a 30 mg/L DZ solution at pH 7, with a catalyst concentration of 1.5 g/L and an irradiation time of 120 min. As illustrated in Figures S6d and S6e, the efficiency of degradation increased with temperature for both C and CGCS. For C, the degradation percentage rose from 76% at 25°C to 86% at 40°C after 120 min of irradiation. In the case of CGCS, a more pronounced enhancement was observed, with degradation reaching 100% at 40°C after only 97 min, compared to 81% at 25°C. This temperature-dependent improvement in photocatalytic activity is attributed to faster reaction kinetics, enhanced diffusion of DZ molecules to the catalyst surface, and more efficient desorption of degradation products [33]. However, this enhancement is generally effective only within an optimal temperature range; exceeding this range may result in a plateau or even a reduction in degradation efficiency due to potential catalyst deactivation or increased electron-hole recombination. Notably, CGCS consistently demonstrated superior catalytic performance compared to C under all tested temperatures.

3.3.5. Kinetics and thermodynamic parameters for diazinon photodegradation

Kinetic and thermodynamic parameters assist in optimizing the conditions for DZ degradation, guiding the selection of an appropriate photocatalyst, and offering valuable insights into the photodegradation mechanism. This understanding is crucial for the efficient design and potential scale-up of environmental remediation strategies.

The photocatalytic degradation kinetics of DZ using C and CGCS were analyzed by applying the linear form of the pseudo-first order Langmuir-Hinshelwood (L-H) model (Eq. 13) to the experimental data. The model fits for both C and CGCS at several temperatures (25-40°C) have been illustrated in Figures 3(a, b), respectively, with the parallel results summarized in Table 3. As shown in Table 3, the high correlation coefficients (0.9729 to 0.9988) confirm that the Langmuir-Hinshelwood model accurately describes the degradation kinetics across the tested temperatures. The apparent rate constant (kₐₚₚ, min⁻¹) is higher for CGCS than for C, indicating the superior photocatalytic performance of CGCS, which can be assigned to its larger surface area and narrower energy band gap. For both photocatalysts, raising the temperature from 25 to 40°C led to approximately 1.4 and 1.8-fold increases in kₐₚₚ for C and CGCS, respectively. This suggests that elevated temperatures enhance the photocatalytic degradation rate due to increased DZ breakdown via hydroxyl radicals and improved molecular diffusion, indicating the endothermic nature of the degradation process. Moreover, the half-life time (t₁_/₂, min) was consistently shorter for CGCS than C, reflecting its higher activity. Additionally, as the temperature rose from 25 to 40°C, the half-life time decreased from 57.27 to 42.00 min for C and from 38.50 to 22.07 min for CGCS. This decrease in half-life with rising temperature is mainly due to the enhanced reaction kinetics and greater efficiency of the photocatalytic process driven by thermal activation [34].

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Figure 3.

Langmuir-Hinshelwood kinetic plot in the presence of (a) C and (b) CGCS. (c) Arrhenius plot, (d) Eyring-Polanyi, and (e) Photocatalyst reusability for DZ degradation.

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Thermodynamic parameters, including the activation entropy change (Δ*S°, kJ/mol·K), activation enthalpy change (Δ*H°, kJ/mol), and activation energy (E_a, kJ/mol), were determined using the Arrhenius equation (Eq. 15, Figure 3c), Eyring-Polanyi model (Eq. 16, Figure 3d), and the Gibbs-Helmholtz equation (Eq. 17). The corresponding values for DZ degradation in the presence of C and CGCS have been presented in Table 3. The effectiveness of the linear fittings for both the Arrhenius and Eyring-Polanyi models is supported by high correlation coefficients (R², 0.9226-0.9785). The activation energy required when using CGCS as a photocatalyst is approximately 6.27 kJ/mol lower than that for C, indicating the larger photocatalytic activity of CGCS. This conclusion is further supported by the higher frequency factor (A, s^-1) value observed for CGCS (8749.8 s⁻¹) compared to C (2325.4 s⁻¹), reflecting a higher rate of effective collisions. According to Eqs. (16) and (17), the positive activation enthalpy values (12.99 and 28.72 kJ/mol for C and CGCS, respectively) confirm that the degradation process is endothermic. Furthermore, the negative entropy change suggests a reduction in molecular randomness at the catalyst surface, and the increasing Gibbs free energy values indicate that the process is non-spontaneous under the studied conditions.

3.3.6. Reusability of photocatalysts

The reusability of the photocatalysts (C and CGCS) was evaluated over seven repeated cycles of DZ degradation. After 120 min of irradiation, the degradation efficiency (Deg%) was calculated, showing a slight decline from 76% to 68% for C and from 90% to 82% for CGCS between the first and seventh cycles (Figure 3e). The observed reduction in photocatalytic performance may be attributed to the partial loss of active sites and potential accumulation of catalyst particles, which can lead to a decline in effective surface area. Despite the decline in activity over repeated cycles, both photocatalysts can still be regarded as efficient and reusable materials for photocatalytic applications.

Recyclability investigations and morphological examinations confirmed the stability of CGCS. After seven rounds of photocatalytic destruction of DZ, CGCS retained a high level of photocatalytic activity with just a minor decrease in efficiency, showing its great reusability. Furthermore, SEM examination of the used CGCS (Figure S3f) indicated that the surface morphology was largely unaltered when compared to the fresh material, indicating that no substantial structural degradation or aggregation occurred with repeated usage. This morphological stability, together with prolonged photocatalytic efficacy, illustrates the strength of CGCS and its promise as a long-lasting and dependable material for practical wastewater treatment applications.

3.3.7. Mechanism of DZ photodegradation onto CGCS nanofiber

The photocatalytic degradation of DZ over CGCS nanofibers is initiated by a visible-light-driven process launched by the CdS semiconductor. When irradiated, CdS absorbs photons and forms electron-hole pairs (e⁻/h⁺). The photogenerated electrons migrate to the conduction band and react with dissolved oxygen to form superoxide radicals (^•O₂⁻), while the holes in the valence band oxidize water or hydroxyl groups to produce hydroxyl radicals (^•OH). These extremely reactive oxygen species, together with direct hole oxidation, attack diazinon molecules adsorbed on the nanofiber surface, causing the breaking of P-O-C and C-N bonds and a gradual transition into smaller intermediates. Finally, these intermediates are mineralized into CO₂, H₂O, and inorganic phosphate/sulfate. The GCS nanofiber matrix not only increases DZ adsorption by raising its local concentration around CdS sites, but it also improves catalyst dispersion and stability, speeding up the overall degrading process.