Production of natural zeolite-filled recycled PVDF filters and their application for gray water treatment

Abstract

In this study, clinoptilolite (Clp)-doped poly(vinylidene fluoride) (PVDF) membranes (1–4 wt%) were prepared using an electrospinning method. Further, filtration tests on the simulated gray water components were investigated. Methylene blue (MB), linear alkyl benzene sulfonate (LAS), oil (soybean oil), and microplastic (MP) filtration were performed. MB filtration with the PVDF membrane resulted in over 99% of MB rejection. Oil rejection with the PVDF membrane without Clp was observed to be 95%, while the addition of Clp increased the oil rejection to over 99%. It was observed that LAS rejection increased as the Clp content increased. MP rejection using PVDF-based membranes was 100%. Considering all the test results, the membrane containing 3 wt% Clp showed the best performance, and the process parameters and rejection efficiencies were determined through experimental optimization. Synthetic gray water analyses included the chemical oxygen demand (COD), pH, conductivity, and total dissolved solids (TDS). COD rejection was 63.1%, while turbidity rejection was 97.2%.

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Water impact

Water is a critical resource for life. It directly affects ecosystems and human health. Our study titled “Production of natural zeolite-filled recycled PVDF filters and their application for gray water treatment” offers important insights for developing water-treatment technology. Gray water, which is a part of domestic wastewater, can be treated, preventing its damage to the environment. Gray water contains contaminants such as oils, dyes, and residues from soaps and detergents. Our research offers a sustainable and effective method to reduce this threat by removing these dangerous pollutants from wastewater sources. The impact of our research on water resources is multifaceted. Our methodology offers a reliable and sustainable approach for water treatment by removing impurities from gray water. This makes a direct contribution to eliminating environmental pollution, protecting ecosystems and safeguarding human health. Our work is exemplary in addressing the challenges faced during gray water treatment. It sets a precedent for future research and encourages the development of environmentally friendly and efficient water-treatment technologies.

1 Introduction

Urbanization started with the industrial revolution, and since then, the population has been increasing rapidly. With the increasing population, water resources have become insufficient. Thus, water scarcity is a major problem that needs to be solved urgently. Among the techniques developed to prevent water scarcity, reduction in water usage, rainwater harvesting, and gray water treatment systems have shown great promises. In particular, gray water treatment systems are attracting increasing attention as they promote water reuse along with reducing environmental pollution caused by wastewater.¹

Gray water is produced through domestic activities in bathrooms and kitchens and through the use of washing machines and dishwashers. Gray water accounts for 75% of household wastewater.² Therefore, its treatment is very important. In order to minimize the energy required for gray water treatment and improve its efficiency, it is recommended to treat gray water at source. Gray water can contain various contaminants, such as oils, dyes, and residues from soaps and detergents. In addition, gray water pollutants are formed and are present as dissolved, colloidal, and suspended forms. The anionic and cationic surfactants in gray water degrade slowly, and they are not biodegradable under anaerobic conditions.^1,3

Gray water treatment processes consist of physical (sedimentation and filtration), chemical (coagulation and flocculation), and biological methods, as well as a combination of these methods. Biological treatment takes place in the presence of microorganisms, which decompose organic matter. In physical separation, large particles and suspended matter are retained, whereas in chemical separation, pollutants in the water are retained by changing the chemical properties of the water. Among these processes, membrane technologies are of great interest owing to their low energy requirement and high efficiency.⁴

Membranes used in wastewater treatment can be ceramic, inorganic, and polymeric. Polymeric membranes are made of a variety of materials, such as polyvinyl alcohol (PVA), polyether sulfone (PES) and polyvinylidene fluoride (PVDF).^5,6 They are attractive owing to their high porosity, flexibility, high permeability, and easy functionality.⁷ PVDF, which has a semi-crystalline structure, is mostly used in commercial wastewater treatment owing to its high mechanical strength, thermal stability, and chemical resistance.^8,9 However, PVDF is hydrophobic and susceptible to fouling when treating water containing organics that tend to foul.¹⁰ Therefore, researchers are aiming to develop better PVDF membranes by improving the preparation processes or/and the surface modification of plain PVDF membranes. Incorporation of the polymer with inorganic materials during membrane preparation is a widespread technique used to enhance both the hydrophilicity and separation performance.¹¹ For this purpose, zeolites may be used as cost-effective natural materials.¹²

Natural zeolites may be preferred in wastewater treatment due to their low cost and abundant availability in nature. Natural zeolites are crystals with a three-dimensional structure based on repeated silicon–oxygen (SiO₄) and aluminum–oxygen (AlO₄) tetrahedral units.¹³ Zeolites are unique because of their structures, with many channels and cavities. In addition, their ability to absorb small molecules and their non-toxicity make them attractive for many applications.¹⁴ The most important natural zeolite is clinoptilolite (Clp).¹⁵

In this study, the wastewater treatment properties of electrospun PVDF were investigated with the incorporation of Clp in different ratios. In the literature, electrospun membranes seem to have been preferred by many researchers due to their excellent membrane formation, and good thermal, mechanical, and chemical resistance.¹⁶ However, it is important to rearrange the filler content in electrospun membranes. Bahi et al. (2017) prepared lignin-zeolite composite nanofiber membranes by electrospinning. The addition of zeolite improved the tensile strength, hydrophilicity, permeability, and separation factors of the membranes. However, the addition of zeolite at a high weight percentage resulted in decreased mechanical properties, permeability, and separation factors of the membranes.¹⁷ Therefore, in the present study, only 1–4 wt% Clp was added to the PVDF membranes. Also, in preliminary studies, agglomeration was observed in PVDF fibers containing 5 wt% Clp, hence we kept the percentage Clp below this. The membranes were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), contact angle (CA) measurements, mechanical analysis, and antimicrobial activity tests. Methylene blue (MB), linear alkyl benzene sulfonate (LAS), oil (soybean oil), and microplastic (MP) filtration were performed with the PVDF membranes. The best-performing filter was selected, and the optimum process parameters and separation efficiencies were then determined by experimental optimization (response surface methodology). Then, synthetic gray water was prepared, and filtration was performed. The chemical oxygen demand (COD), pH, conductivity, and total dissolved solids (TDS) in the gray water were also determined. To the best of our knowledge, this is the first time in the literature that a membrane filter has been produced from recycled PVDF and its effect on multiple separation investigated.

2 Experimental section

2.1 Materials

The PVDF polymer used in this study was regenerated from hollow-fiber ultrafiltration membrane production waste from a local factory. The membrane was manufactured from Kynar720 (average molecular weight (M_w) of 263 000 g mol⁻¹) (Arkema). Dimethyl formamide (DMF) (with 99.0% purity) and acetone (with 99.0% purity) were purchased from Merck Chemicals, Turkey. Polyvinylpyrrolidone (PVP) (average mole weight of 360 000 g mol⁻¹) as a pore-forming agent was obtained from Sigma Aldrich, Turkey. Clinoptilolite was kindly supplied from Rota Maden Inc., Turkey. The properties of Clp are given in the ESI† data (Table S1).

2.2 Membrane production

The waste ultrafiltration membranes were cut into 1 mm pieces, washed with deionized water, soaked in alcohol, and dried at 50 °C. In this study, regenerative membrane filters were produced by an electrospinning technique. For this purpose, PVDF-DMF-acetone solution containing 25 wt% PVDF (10 wt% PVP according to the weight of the PVDF) was prepared and stirred at 50 °C for 2 h. The homogeneous polymer solution was taken in a 10 ml syringe, placed in the electrospinning system, and finally collected on the plate at 17 kV, 0.05 mL min⁻¹, 50% humidity conditions. The distance of the plate from the syringe tip was kept constant at 15 cm. The thickness of each film produced was 150 μm. For the preparation of Clp-loaded membranes, 1–4 wt% Clp was dissolved in DMF by means of an ultrasonic homogenizer (Bandelin HD4050) and added to the homogenous polymer solution using a priming method that was described in a previous study.¹⁸ Thus, it was ensured that the particles did not collapse and Clp was homogeneously distributed in the electrospinning process. The membranes were coded according to the Clp ratio as PVDF-(1,2,3,4)wt% Clp. The experimental film production system is shown in Fig. 1.

Fig. 1 Schematic of the production of the membrane.

2.3 Characterization

Scanning electron microscopy (SEM) analysis was carried out under low and high vacuum with a SEM device (JEOL JSM-7100-F). Attenuated total reflectance-Fourier transform infrared spectroscopy (FTIR-ATR) analysis was performed with a Cary 630 ATR-FTIR instrument. The wavelength range for the tests was 4000–650 cm⁻¹. Contact angle tests (Dataphysics TBU OCA 11) were applied for all the membranes. Measurements were taken from 5 different points and the average values were recorded. The tensile strength and elongation at break values were determined using an ANKARIN universal testing machine according the ASTM D882 standard.

Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) tests were performed for thermal analysis. TGA (Mettler Toledo) was carried out up to 650 °C. DSC analyses were carried out in a temperature range of 10–250 °C in a nitrogen environment.

For the swelling tests, the weights of the samples were measured dry and after being kept in water for 24 h and the swelling percentage calculation was based on the weight difference.

For the porosity (empirical) analysis, each porosity value was determined by averaging three different measurements. The following equation was used:¹⁹

where M_a is the mass of the membrane after wetting with water, M_b is the mass of the membrane before wetting with water, ρ_a is the density of water, and ρ_p is the density of the polymer.

The accumulation of Gram-negative bacteria Escherichia coli and Gram-positive bacteria Staphylococcus aureus on the filter was determined by the agar diffusion method.²⁰ Selected Gram-negative and Gram-positive bacteria were cultured separately on tryptic soy broth medium, incubated for 24 h and diluted to 0.5 McFarland turbidity to 105 CFU ml⁻¹. The bacterial suspension was spread over the entire surface of the agar plate using a sterile swab from the liquid medium with the adjusted bacterial density. Filter samples with a diameter of 6 mm were placed in Petri dishes and incubated at 37 °C for 24 h and the zone of inhibition diameter was measured. The transparent zone formed was evidence of the antimicrobial activity.

2.4 Filtration tests

A schematic representation of the filtration test is shown in Fig. 2. To determine the filtration performance of all the filters, emulsified oil (soybean oil, 2%), cationic dye (MB, 5 mg L⁻¹), anionic surfactant (LAS, 100 mg L⁻¹), and MP (polyester, 200 mg L⁻¹) rejection tests were performed separately. The test was performed at a flow rate of 0.6 mL min⁻¹ at room temperature with an effective membrane diameter of 3 cm.

Fig. 2 Schematic of the filtration test system.

For the determination of MB, the concentrations were read directly according to calibration curves using the UV-Probe program at 665 nm wavelength with an ultraviolet-visible (UV-vis) spectrophotometer (Shimadzu 1280).²¹ The calibration curve is given in the ESI† data (Fig. S1). For the determination of LAS, the concentrations were read directly according to the calibration curves using the MB method with a UV-vis spectrophotometer at a wavelength of 650 nm using the UV-Probe program.²² Details of the method and calibration curve are given in the ESI† data (Fig. S2). For the determination of oil, the oil solution was prepared and homogenized using an ultrasonic bath (Bandelin HD4050) for 1 h. The solution was kept in the ultrasonic bath until a stable milky color was obtained. Using a UV-vis spectrophotometer at a wavelength of 272 nm, the pre- and post-test concentrations were recorded.^23,24 For the determination of MP, a product containing more than 90% polyester was taken and the polyester was removed with a fluff collector. A solution of 200 mg L⁻¹ was then prepared. After filtration, the polyester in the water was collected on the membrane paper and weighed.²⁵ The percentages (%) MB, LAS, MP, and oil rejection were calculated by the following equation:

where R(%) is the rejection percentage of the filtered solution, C_i (mg L⁻¹) is the initial concentration of the solution before filtration, and C_f (mg L⁻¹) is the final concentration of the solution obtained at the end of filtration.

2.5 Determination of the process parameters and rejection efficiencies with the best-performing filter

Experimental optimization was performed with the filter with the highest rejection performance and the rejection percentages from the filtration tests were determined. Design expert 12, an experimental design program, was used to implement the response surface method. Within the scope of the study, the central composite design technique, which is a subheading of the response surface method, was preferred. The factors affecting the filtration, and the levels of the factors were created by considering the literature data. As a result, a design consisting of three factors and three levels was created. The factors and their levels are given in the ESI† data (Table S2).

2.6 Synthetic gray water tests with the best-performing filter

Synthetic gray water was created by mixing the synthetic gray water contents given in the ESI† data (Table S3), and then the COD, suspended solid matter (SSM), turbidity, pH, conductivity, and TDS rejection performances of the filter were analyzed by performing filtration tests.

The COD is the amount of oxygen required for the chemical oxidation of oxidizable substances in water. It is an important parameter in determining wastewater pollution. It was determined here by the potassium dichromate method using a spectrophotometer (Shimadzu UV-1280).²² The concentrations were read directly from the calibration curve with the help of the UV-Probe program at 450 nm wavelength using the spectrophotometer. Details of the methods and the calibration graph are given in the ESI† data (Fig. S3).

Turbidity can be observed in waters with suspended solids. It prevents the light transmission of water. Turbidity can be caused by organic or inorganic substances. Here, turbidity was determined directly from the calibration graph using a spectrophotometer at a wavelength of 450 nm with the UV-Probe program.²² Details of the methods and calibration graph are given in the ESI† data (Fig. S4). The percentage rejection based on the pre-, and post-filter values was calculated according to eqn (2).

The SSM is the sum of substances that settle or do not settle in water. It usually consists of rock fragments, mud, clay minerals, and/or colloidal organic matter fragments. The analysis was performed according to the standard methods 1989 S.2-75, GEMS S.22 (APHA, 1989). The gravimetric method was preferred here for the analysis. Whatman no. 42 filter papers were used, and the SSM was determined using the following formula:

where C (mg) is the sum of the mass of the filter paper and dry residue, D (mg) is the mass of the filter paper, and V (ml) is the sample volume.

Conductivity, pH, and TDS are other routine tests were also performed. These tests were performed using a Mettler Toledo Seven Compact instrument.

3 Results and discussion

3.1 Characterization tests

Fig. 3 shows the contact angle (CA) values of PVDF and the PVDF-Clp doped filters with water on the surface. PVDF without Clp was superhydrophobic and the contact angle was measured as 155°. This value decreased gradually with the addition of Clp. According to these results, the surface hydrophobicity of the Clp-added PVDF materials decreased, just as expected. This has two advantages. One of them was the decrease in the fouling capacity of the surface due to the decrease in hydrophobicity and the increase in the antimicrobial effect. The other was that the water flux increased significantly due to the increase in the hydrophilicity of the fibers. The reason for the increase in hydrophilicity was the presence of the hydroxyl group in Clp. In similar studies in the literature, it has been reported that Clp films added at a very low rate significantly reduced the contact angle.^26,27

Fig. 3 Contact angles of PVDF and Clp-doped PVDF filters.

SEM analysis was performed to observe the morphological structures of the membranes. Fig. 4 shows the structures of the plain PVDF (Fig. 4a and d), PVDF-2 wt% Clp (Fig. 3b and e), and PVDF-4 wt% Clp (Fig. 4c, f, and g) membranes. The images confirmed that the electrospinning conditions used for the membrane preparations were suitable. As can be seen in the figures, there was a slight increase in the fiber diameters when the Clp ratio was increased, which was also reported by Nassrullah et al., 2020 and Hassan et al., 2022.^28,29 The difference is very clear between Fig. 4a and c. It was also observed that the fiber surface porosity increased with the addition of Clp (Fig. 4g). Another important finding was that no pilling or agglomeration was observed in the fibers. However, in preliminary studies, agglomeration was observed in PVDF fibers containing 5% Clp by weight. For this reason, it was decided the top Clp addition would be up to 4% in this study, since the homogeneity would deteriorate with a higher Clp ratio.

Fig. 4 SEM analysis of the PVDF (a and d), and 2 wt% (b and e) and 4 wt% (c, f, and g) Clp-doped PVDF.

Fig. 5 shows the ATR-FTIR analysis spectra of the PVDF and Clp-doped PVDF filters. Before FTIR analysis, the filters were first soaked in water and then dried. The PVP used as a pore former in the filter was expected to dissolve completely. However, the peaks observed in the 1670 cm⁻¹ region showed that the PVP was completely insoluble in water, with the peaks related to the carboxyl C=O bonds in it. The peaks observed in the 870 and 1170 cm⁻¹ region in Fig. 5 were due to C–C and C–C–C bonds in the organic structure of PVDF. The peak at 1400 cm⁻¹ was due to the C–F vibration of the CF₂ bond in the PVDF structure.^29,30

Fig. 5 FTIR spectra of the PVDF and Clp-doped PVDF filters.

In the study by Lopes et al. (2014), while silicon-based bonds were clearly seen in the membranes prepared as a film with 4% NaY zeolite doping into PVDF, when the same membrane was prepared by electrospinning, it was observed that the appearances of the doped and undoped membranes were exactly the same. The reason for this is that due to the nature of the alpha, beta, and gamma phases formed due to the electrospinning process, there was not much difference seen with varying the additive ratio.³¹ Similarly, no significant difference was observed in this study with varying the Clp addition.

The porosity values of all the filters produced by electrospinning were calculated empirically using eqn (1). In the porosity tests, the filters were weighed in the same mass with a certain geometry, and the thickness of the films used was taken as 150 μm. The porosity mentioned here does not refer to the structural porosity of the fibers but rather the porosity in-between the fibers, which is important in the separation process. The water retention (water uptake) and porosity values of the PVDF membranes are shown in Fig. 6a. As can be seen, the porosity and water retention values increased as the Clp content increased. The main reason for this is the high water retention capacity of Clp and the hydrogen bonds it forms with water. The increase in porosity increased depending on the water retention value. Here, the effective value for the increase in porosity was taken as the water retention because the water retention value increased at a greater rate than the porosity. This actually shows that the empirical values increased because more water was retained. As seen from the SEM analyses, the increase in Clp increased the fiber diameters, which relatively reduced the distance between the fibers. This shows that while the porosity decreased, the hydrophilicity of the fibers increased. Similar results have been reported in the literature.^28,29

Fig. 6 Porosity and water retention results (a) and mechanical analysis (b) of the PVDF and Clp-doped PVDF filters.

Mechanical analysis of the filters was carried out using an ANKARIN Universal Test device. Mechanical analysis is essential, especially for a material that works under hydrodynamic pressure, such as a filter. Fig. 6b shows the mechanical analysis of all the filters depending on the Clp ratio. The PVDF membrane's mechanical characteristics can be altered in a number of ways by adding Clp. Zeolites are known for having remarkable rigidity and mechanical strength. Zeolite particles can serve as a reinforcing agent when incorporated into polymeric membranes, which enhances the membrane's overall mechanical qualities. They can improve the membrane's resistance to deformation, tensile strength, and flexural strength. Furthermore, compared to a large proportion of polymers, Clp has a higher modulus of elasticity.⁶ As shown in Fig. 7, the addition of Clp to PVDF increased both the stress and strain tolerance with up to 3 wt% doping. The reason for this increase is that the strength of the zeolite was higher than that of the polymer according to the rule of mixing. However, both the strength and elongation decreased after 3 wt%. This was attributed to the deterioration of the homogeneity and the inhibition of in-filter load transfer due to the excess amount of additives. Similar results were also reported in the literature.^32,33

Fig. 7 DSC analysis (a) and TGA analysis (b) of the PVDF and Clp-doped PVDF filters.

The DSC analysis results for the filters are given in Fig. 7a. The TGA analysis results for the PVDF and Clp-doped PVDF filters are given in Fig. 7b. DSC and TGA analyses provide information about the thermal behavior of polymeric filters and their glass transition temperatures, melting points, and melting enthalpies. Especially in the case of these filters that need to operate above a certain thermal value, the effect of temperature on the filter is very important. As seen in Fig. 7a and Table 3, the glass transition temperature of the PVDF was observed at 59.9 °C. Then, it showed two melting peaks, which have also been reported in the literature.³⁴ The melting of the α-form crystalline structure was attributed to the endothermic transition at 160 °C, whereas the β-form of the PVDF crystals could be linked to the second endothermic peak at 167 °C. The literature reports confirm that because of PVDF's polymorphic nature, double melting transitions are commonly seen.^35,36 This behavior can be explained by the fact that piezoelectric β-phases can occur in electrospun PVDF fibers due to the strong electric field and mechanical stress that are typical characteristics of the electrospinning process.

Table 1 shows the glass transition temperature (T_g), melting temperature (T_m), and enthalpy of melting (ΔH_m) of the electrospun PVDF and Clp-doped PVDF filters. The glass transition temperature decreased slightly with the addition of Clp and then increased. However, this increase did not affect the processability or glass transition temperature of the material. On the other hand, while the melting temperature increased gradually and slowly, there was a very high and continuous increase observed for the melting enthalpy. This shows that zeolite doping significantly increases the fiber crystallinity. Similar results have been reported in the literature.³⁷

Table 1 Glass transition temperature (T_g), melting temperature (T_m), and enthalpy of melting (ΔH_m) of the PVDF and Clp-doped PVDF filters

Membrane	T g (°C)	T m (°C)	ΔHm (J g^−1)
PVDF	59.9	160–167	15.87
PVDF-1 wt% Clp	58.9	161.5–168.3	14.85
PVDF-2 wt% Clp	56.64	162.9	36.2
PVDF-3 wt% Clp	60.46	163.8	32.99
PVDF-4 wt% Clp	60.9	164	30.13

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The TGA analysis results of the PVDF and Clp-doped PVDF filters are shown in Fig. 7b. Two-stage degradation was generally observed in the PVDF filters with Clp loading, and degradation due to water loss occurred below 100 °C. Mass losses due to PVDF degradation were observed between 400 °C and 450 °C. During degradation, PVDF releases hydrogen and fluorine, which combine to form hydrogen fluoride (CH₂=CF₂). Thus, carbon atoms become free to bond with each other.³⁸

The thermal resistance data of the PVDF and Clp-doped PVDF filters are listed in Table 2. As can be seen in the aforementioned figure and in the table, the first decomposition temperature increased from 377 °C to over 400 °C with the addition of Clp. This shows that the thermal resistance of the Clp-doped PVDFs was higher than that of the plain PVDF material. This increase decreased slightly after 3% loading. As can be seen in the table, Clp added at a maximum of 3% of the polymer increased the residual mass from 32.5% to 41%. This shows that the thermal heat transfer and thermal resistance to degradation increased with the addition of the zeolite.

Table 2 Thermal resistance data of the PVDF and Clp-doped PVDF filters

Membrane	T 5 (°C)	T 50 (°C)	Remaining (%)	Decomposition temperature (°C)
PVDF	377	446	32.5	438
PVDF-1 wt% Clp	394	461	35.6	416–450
PVDF-2 wt% Clp	403	467	40.96	407–445
PVDF-3 wt% Clp	401	468	40	404–440
PVDF-4 wt% Clp	397	460	40.7	402–438

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All the prepared films were tested for antimicrobial activity against both Gram-negative (E. coli) and Gram-positive (S. aureus) bacteria. During the antimicrobial test, both the disk diffusion experiment samples and the films were added directly to the medium and tested for culture growth. The disk diffusion results are shown in Fig. 8. In all the tests, it was observed that there was no microbial growth on the films, not even in the pure form of the polymer matrix.

Fig. 8 Disk diffusion results for Gram-positive (S. aureus) (a), and Gram-negative (E. coli) (b) bacteria.

The zone diameters of all materials are given in the ESI† data (Table S4). According to this, Clp added to PVDF polymer showed more successful antimicrobial activity against the Gram-positive bacteria. This was probably due to the ability of Clp to be positively charged. As a result, the films were found to have both surface and environmental antimicrobial effects. In the literature, there are also studies indicating that Clp-added films show an antimicrobial effect.³⁹

3.2 Filtration test results

The rejection results of the membranes are given in Fig. 9. It can be seen that the rejection of MB was over 99% (Fig. 9a). As can also be seen in the graph, the increase in rejection percentage was not very high when the Clp content was increased, and MB rejection only increased from 99% to 99.4%. Therefore, Clp was not very effective for improving MB rejection. However, it should be noted that MB is a cationic molecule and zeolites carry a negative charge in their alumina silicate frameworks. Therefore, they can attract MB molecules and increase the resulting rejection. In the literature, Kadja et al. (2023) fabricated a mixed matrix membrane (Mercapto functionalized-natural zeolites/PVDF) for achieving a better rejection of MB. They reported achieving an increase in the rejection of MB with the inclusion of Clp in the PVDF matrix.⁴⁰

Fig. 9 MB (a), oil (b), MP (c), and LAS (d) rejection graphs of the PVDF and Clp-doped PVDF filters.

The oil rejection results are shown in Fig. 9b. It is clear from the figure that the oil rejection with all the membranes was greater than 95%. It was also observed that the percentage oil rejection increased with the increase in the amount of Clp, notably from 95% to 99%. In the literature, Nayak et al. (2022) used a PVDF membrane as an oil trap due to its high oleophilicity and reported that it removed more than 98% of an oil–water emulsion of soybean and silicone oils.⁴¹ Clp, a natural zeolite, has an oleophilic structure, and its water, oil, and gas absorption capacity is quite high. In addition, due to its crystal lattice, there is a lack of negative charge both on the crystal surface and in the channels. It can hold and especially provide positive ions by displacing them.⁴²Fig. 9c also shows that 100% microplastic removal was achieved with all membranes due to the small pore size of the PVDF, which was also revealed in the porosity test and SEM analysis.

The LAS removal results are shown in Fig. 9d. As can be seen in the figure, Clp incorporation significantly increased the LAS rejection from 23% to 80.87%. Here, the presence of aluminum in the zeolite results in the formation of an unstable framework with an intrinsic cationic-exchange capacity.⁴³ The positively charged groups are balanced by anionic counter ions, which increases the rejection of anionic pollutants, such as LAS. The reason for the increase in rejection as the amount of Clp increased is that the ion-exchange capacity increased with the amount of Clp.

In the filtration tests, high and very close values were obtained for MB, MP, and oil filtration. Therefore, the indicative process was LAS filtration. The highest rejection was obtained with PVDF-4 wt% Clp, namely 80.87%, whereas the rejection by PVDF-3 wt% Clp was 61.66%. However, in the mechanical analysis after 3 wt% Clp was added, both the strength and elongation decreased. Therefore, PVDF with 3 wt% Clp showed the best performance and was selected as the best filter membrane. Therefore, the oil, MB, and MP rejection percentages of the best-performing PVDF-3 wt% Clp membranes were compared with the results from other studies in the literature. The comparable values are listed in Table 3. As can be seen in the table, PVDF membranes are remarkable for their high separation properties. Improvements in the preparation process of PVDF membranes and surface modification of pure membranes can increase their separation performances.

Table 3 Comparison of oil, MB, and MP rejection results in this study with some other studies in the literature

Membrane	MB rejection (%)	Ref.
TP/PEI/PVDF	95.2	44
rGO-PVDF/TiO2	92	45
PVDF/SDS-GO/TiO2	92.76	46
PVDF-3 wt% Clp	99.8	This study

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Membrane	Oil rejection (%)	Ref.
(PVDF-b-PVI) Mb6	98.08	47
PVDF-g-PNIPAAm	95.2	48
PVDF	91.1	49
PVDF-g-PVP	95.6	10
PVDF-3 wt% Clp	99.1	This study

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Membrane	MP rejection (%)	Ref.
PVDF	97	50
PVDF-MBR	99.5	51
BGIM-PVDF	97.6	52
PVDF-3 wt% Clp	100	This study

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3.3 Determination of the optimum process parameters by experimental optimization

There are many parameters that can affect the membrane performance, such as temperature, pH, flow rate, and membrane structure. In this study, the effects of varying the concentration of the impurities, the feed temperature, and the feed flow rate on the rejection were investigated using a central composite design of response surface methodology. In the three-factor experimental design, each parameter is represented by letters. Here, the parameter represented by the letter A is the feed flow rate (L min⁻¹), while the letters B and C are the feed temperature (°C) and the concentration of impurities (mg L⁻¹), respectively.

3.3.1. MB rejection optimization. The rejection percentages obtained as a result of the optimization according to the experimental results determined according to the central composite design are listed in the ESI† data (Table S5). According to the results, the separation percentage decreased as the temperature, dyestuff concentration, and flow rate increased. However, even at the highest temperature, flow rate, and dye concentration, 98% separation was still observed.

Fig. 10 shows 3D plots of the model and the model and fit statistics. Accordingly, the second-order equation model was determined as the most appropriate model for MB separation. According to this model, the R² value was obtained above 98%. As can be seen in Fig. 10, a high separation efficiency was observed at low temperature and low flow rates, and these results were largely consistent with the model.

Fig. 10 3D plots of MB rejection by the PVDF-3 wt% Clp filter (5 mg L⁻¹ (a), 10 mg L⁻¹ (b), 15 mg L⁻¹ (c)), verification plot (d), model summary statistics (e) and fit statistics (f).

Details of the analysis of variance (ANOVA) of the model are provided in the ESI† data (Table S6). According to this analysis, a high negative effect of the flow rate and temperature could be seen from the low p values and high F values, showing that the concentration also has a significant negative effect. According to the formula obtained (eqn (4)), it could be concluded that the highest effect was seen with varying the temperature.

R = 98.41 − 0.3600A − 0.8600B − 0.1500C − 0.1500AB − 0.0250AC − 0.1000BC − 0.0423A² +0.4577B² + 0.0077C² (4)

Therefore, the temperature was one of the dominant parameters affecting the membrane performance. The literature also shows that hot and warm temperatures can expand the membrane pores and increase membrane flux.⁵³ Pore-size variations for nanofiltration membranes at varied thermal settings were first reported by Sharma et al. in 2003. They discovered that when the temperatures decreased, this affected the rejection efficiency of medium-sized solute molecules, like glycerol and ethanol.⁵⁴ Another study showed that the membrane pores of a polyamide membrane expanded by 13% when the temperature was increased from 20 °C to 40 °C.⁵⁵ Pourziad et al. (2019) investigated the oil rejection rate at 20 °C and 40 °C to examine the separation performance of modified PVDF membranes. They found that the PVDF membrane had a low oil rejection rate at higher temperatures due to a viscosity effect. According to Pourziad et al. (2019), an increase in temperature caused an enlargement of the pores and a decrease in oil rejection.⁴⁸

3.3.2. Oil rejection optimization. The oil rejection results are given in the ESI† data (Table S7). At the same flow rate and temperature conditions, the oil rejection ranged between 97.9% and 99.9%. Accordingly, it could be seen that the increase in all three factors decreased the rejection efficiencies, albeit very high rejections were still obtained. Modeling was performed according to the data obtained and the 3D graphs, model, and fit statistics obtained are shown in Fig. 11. Similar to MB, the second-order model was found to be more appropriate, with over 98% accuracy. According to the ANOVA analysis in the ESI† data (Table S8), the high F and low p values, as well as the model equation, show that the most effective factor for the rejection was the concentration.

Fig. 11 3D plots of oil rejection by the PVDF-3 wt% Clp filter (1% (a), 2% (b), 3% (c)), verification plot (d), model summary statistics (e), and fit statistics (f).

The equation obtained according to the modeling is given below (eqn (5)). The equation shows that the most influential factor for oil separation was the oil concentration in the feed.

R = 98.37 − 0.2050A − 0.3950B − 0.4750C + 0.0187AB + 0.0937AC − 0.1313BC + 0.0194A² + 0.1694B² + 0.3694C² (5)

The initial concentration had a significant effect on the membrane performance. The rejection decreased as the concentration increased. At higher concentrations, the surface of the membrane was completely covered, forming a sediment layer on the membrane surface and this layer created additional resistance for the solution to be filtered to pass through the membrane, leading to a decrease in rejection.⁵⁶ Moreover, for an aqueous solution, the activity coefficient of water or the water vapor pressure was found to decrease with increasing the solute concentration.⁵⁷ Therefore, the flux decreased with increasing concentration, due to the decrease in the driving force for the vapor to pass through the membrane pores. Huang et al. (2010) performed tests by varying the MB concentration from 0 to 6 mg L⁻¹, and observed that when the flux decreased, the additional resistance increased with increasing the MB concentration.⁵⁸ The decrease in rejection percentage with increasing oil concentration could be attributed to molecular aggregation formed by the oil molecules with the higher oil concentration. The larger the molecules come together, the lower the potential. This then reduces the repulsion between the membrane and the oil/water droplets. In addition, the zeta potential is higher in dilute solutions, and this allows molecules to pass through the membrane without aggregation.⁵⁹

3.3.3. LAS rejection optimization. The LAS rejection results are given in the ESI† data (Table S9). The LAS rejection was quite variable depending on the parameters. However, it was seen that increasing all three factors decreased the rejection efficiency, but very high rejection rates were still achieved. Modeling was performed according to the data obtained, and the 3D graphs, model, and fit statistics are shown in Fig. 12. The quadratic model was found to be more appropriate, with over 99% accuracy. According to the ANOVA analysis in the ESI† data (Table S10), the high F and low p values, as well as the model equation, show that the most effective factor for the rejection was the flow rate.

Fig. 12 3D plots of LAS rejection by the PVDF-3 wt% Clp filter (50 mg L⁻¹ (a), 100 mg L⁻¹ (b), 150 mg L⁻¹ (c)), verification plot (d), model summary statistics (e), and fit statistics (f).

Eqn (6) shows that the most effective factor for rejection was the feed flow rate.

R = +65.11 − 7.40A − 5.30B − 3.10C − 0.5AB − 0.75AC + 0.75BC + 6.8A² + 0.3028B² + 2.30C² (6)

With the increase in flow rate, more molecules per unit time can pass through the membrane, accumulating on the membrane surface and forming a layer of sediment. This again creates additional resistance to the solution to pass through the membrane, leading to a decrease in rejection. Masoudnia et al. (2013) showed in their study that, with the increase in flow rate, more oil droplets could pass through the membrane, reducing oil rejection.⁶⁰ Ahmad et al. (2020), looking at the COD, turbidity and color rejection, found that the percentage rejection decreased with all three parameters with the increase in the applied flow rate. This finding is a result of the formation of a fouling layer and pore clogging on the membrane surface, which prevents material from passing through the filtration membrane.⁶¹

3.4 Results of the synthetic gray water tests

Synthetic gray components were mixed to form synthetic wastewater. Then, filtration tests were performed with the PVDF-3 wt% Clp filter. The COD, SSM, turbidity, pH, conductivity, and TDS separation performances of the filter were analyzed. The synthetic gray water analysis data are shown in Table 4. Fig. S5 in the ESI† data shows images of the synthetic gray water before filtration (a), after filtration, and the membrane after filtration (c).

Table 4 Synthetic gray water analysis data

Parameters	Before filtration	After filtration	Rejection (%)
pH	6.25	7.20	—
Conductivity (μs)	112.5	88.5	—
Turbidity (NTU)	598.9	16.7	97.2
TDS (mg L^−1)	71.9	59.4	—
COD (mg O2 per L)	1207.8	445.6	63.1

---

As can be seen in Table 4, the COD was decreased from 1207.8 mg O₂ per L before filtration to 445.6 mg O₂ per L after filtration, and hence 63.1% rejection was achieved. Affandi and Razak (2017) reported a 64% COD rejection in their study with an electrospun Nylon 6 nanofiber membrane. This shows that the electrospun nanofiber membrane has the ability to reduce the COD.⁶² Hosseini et al. (2024) reported 11% COD rejection in wastewater treatment using Nylon 6/zeolite nanofiber membranes produced by an electrospinning method.⁶³ Zendehdel and Nouri (2021) reported 49%, 61%, and 66% COD rejection rates in filtration with concentrations of 500, 480, and 420 mg O₂ per L at pH 8.45, 8.40, and 8.42, respectively, using electrospun PES nanofibers.⁶⁴

As a result of the SSM analysis, it was found that 99.8% of the SSM were successfully retained by the filter. Accordingly, the rejection of the turbidity elements also increased. Particles and colloids formed by the SSM cause turbidity in water and can cause clogging in the filters and pipes used in such treatment.⁶⁵ Therefore, the SSM affects the turbidity. Turbidity also prevents the light transmission of water. Turbidity can be caused by organic or inorganic substances. Here, the rejection percentages were calculated from the difference in the turbidity values before and after filtration. Here, 97.2% of the turbidity-causing elements could be removed, leading to a major improvement in the water quality; whereby the treated water had an excellent and clear physical appearance, free of SSM.

According to the American Public Health Association (APHA 1995), the conductivity, pH, and TDS are important parameters in gray water analysis.⁶⁶ In this study, the pH value was 6.25 before filtration and 7.20 after filtration. In the study conducted by Chaabane et al. (2017), the pH values of gray water samples after filtration ranged between 7.35–8.82.⁶⁶ According to the study conducted by Zipf et al. (2016), the pH values of gray water consisting of domestic waste were 5.7 and 6.4. After various filtrations, the pH was found to be in the range of 7.5–7.6.⁶⁷ In another study by Yovo et al. (2016), the pH value before filtration was 6.4, while the pH value after filtration was 7.04.⁶⁸ Therefore, the pH value above 7 after filtration and the increase in pH value after filtration were similar to the previous literature reports.

The conductivity is another important factor to consider. Here, the conductivity was 112.5 μs before filtration and 88.5 μs after filtration. The conductivity is the ability of a substance to conduct electric current. Water gains conductivity due to the presence of dissolved ions in it. Since dissolved ions will decrease after filtration, it is natural that the conductivity will decrease.⁶⁹ There is a strong relationship between the TDS and conductivity. The TDS parameter indicates the total solids dissolved in water while the electrical conductivity indicates the conductivity of the current coming from them.⁷⁰ Therefore, it is reasonable to expect both to decrease after filtration. Here, TDS was 71.9 mg L⁻¹ before filtration and 59.4 mg L⁻¹ after filtration.

After the synthetic gray water test, the PVDF-3 wt% Clp membrane was used in 6 cycles of experiments to test its reusability. It was observed that the flux loss was 12% after the 6th experiment. At this stage, a cleaning procedure was applied to the membrane. Membrane cleaning was performed for 30 min with alkaline (0.1 M NaOH) and acidic (0.6 M HCl) cleaning solutions to remove organic and inorganic contaminants. It was found that the same results were obtained in the filtration tests performed after the cleaning test; thus demonstrating the reusability of the membrane after cleaning.

4 Conclusions

In this study, Clp-doped recycled PVDF electrospun nanofiber membrane filters were synthesized and used for gray water purification. Clp increased the hydrophilicity, porosity, and antimicrobial activity of the membranes. The addition of Clp to PVDF increased both the stress and strain tolerance for up to 3 wt% doping. However, after 3 wt%, both the strength and elongation decreased. Therefore, the PVDF-3 wt% Clp filter showed the best performance and was selected as the best filter. According to the filtration result, MB rejection above 99% was observed. The oil rejection performance of the PVDF membranes without Clp was 95%, while the addition of Clp increased the oil rejection rate to over 99%. It was also observed that LAS rejection increased as the Clp content was increased, and the highest rejection percentage was 80.87% with PVDF containing 4 wt% Clp. Next, experimental optimization was performed to determine the rejection efficiencies based on varying the process parameters. It was observed that the rejection decreased with increasing the temperature, flow rate, and concentration. The most effective factor for MB rejection was the temperature, while for oil it was the feed concentration, and for LAS it was the flow rate. According to the synthetic gray water tests, COD rejection was found to be 63.1% and the turbidity rejection was 97.2%. According to these results, it could be seen that the filtration process based on recycled PVDF could achieve very successful results.

Abbreviations

ANOVA:	Analysis of variance
APHA:	American public health association
CFU:	Colony-forming unit
CA:	Contact angle
Clp:	Clinoptilolite
COD:	Chemical oxygen demand
DMF:	Dimethylformamide
DSC:	Differential scanning calorimetry
FTIR:	Fourier transform infrared spectroscopy
LAS:	Linear alkylbenzene sulfonate
MB:	Methylene blue
MP:	Microplastic
NTU:	Nephelometric turbidity unit
PES:	Polyether sulfone
PVA:	Polyvinyl alcohol
PVDF:	Polyvinylidene fluoride
PVP:	Polyvinylpyrrolidone
SEM:	Scanning electron microscopy
SSM:	Suspended solid matter
TDS:	Total dissolved solids
TGA:	Thermogravimetric analysis
UV-vis:	Ultraviolet-visible

Data availability

The data that support the findings of this study are available from the corresponding author, Filiz Uğur Nigiz, upon reasonable request.

Author contributions

Ayşenur Katırcı: investigation, methodology, writing – original draft, carried out the experiment. Seniyecan Kahraman: investigation, methodology, writing – original draft, carried out the experiment. Filiz Uğur Nigiz: investigation, visualization, conceptualization, methodology, writing – original draft, methodology, data curation, validation, writing – review & editing.

Conflicts of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This study was financially supported by the Scientific and Technological Research Council of Türkiye (Grant Number:123Y119) and by the Scientific Research Project Unit of Çanakkale Onsekiz Mart University (Grant number: FHD-2024-4693).

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Footnote

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4ew01070a

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