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Article

A Selective, Efficient, Facile, and Reusable Natural Clay/Metal Organic Framework as a Promising Adsorbent for the Removal of Drug Residue and Heavy Metal Ions

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Environmental Science and Industrial Development Department, Faculty of Postgraduate Studies for Advanced Sciences, Beni-Suef University, Beni-Suef 62521, Egypt
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Materials Science and Nanotechnology Department, Faculty of Postgraduate Studies for Advanced Science (PSAS), Beni-Suef University, Beni-Suef 62511, Egypt
3
Zoology Department, Faculty of Science, Beni-Suef University, Beni-Suef 62511, Egypt
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Department of Biology, College of Science, Imam Mohammad bin Saud Islamic University, Riyadh 11623, Saudi Arabia
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Department of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia
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Department of Chemistry, Faculty of Science, Beni-Suef University, Beni-Suef 62511, Egypt
*
Author to whom correspondence should be addressed.
Colloids Interfaces 2024, 8(5), 50; https://doi.org/10.3390/colloids8050050
Submission received: 10 July 2024 / Revised: 16 August 2024 / Accepted: 27 August 2024 / Published: 5 September 2024

Abstract

:
It is imperative to eliminate heavy metals and pharmaceutical residual pollutants from wastewater to reduce their detrimental effects on the environment. In this work, natural zeolite and a 2-amino terephthalic acid-based multi-metallic organic framework were used to create a new composite that can be utilized as an adsorbent for cadmium and safinamide. The adsorption study was examined in a variety of settings (pH, adsorbent dosage, pollutant concentration, and time). Moreover, Zeta potential, BET, SEM, FTIR, XRD, and SEM measurements were used to characterize the adsorbents. The adsorption process was confirmed using FTIR, XRD, and SEM analysis. Various nonlinear adsorption isotherm models were applied to adsorption results. The results showed a significantly better adsorption ability for safinamide and cadmium using zeolite/MOF compared to zeolite. Adsorption kinetics were represented by five models: pseudo first-order, pseudo second-order, intraparticle diffusion, mixed first- and second-order, and the Avrami model. Regarding both adsorbent substances, safinamide adsorption was best represented by the intraparticle diffusion model. In contrast, the pseudo second-order and intraparticle diffusion models for zeolite and zeolite/MOF, respectively, better fit the experimental results in the case of cadmium adsorption. The thermodynamic parameters ΔH°, ΔS°, and ΔG° were investigated through temperature tests carried out at 25, 35, 45, and 55 °C. Exothermic and spontaneous adsorption processes were demonstrated by the computed values. The study of adsorbent regeneration involved the use of several chemical solvents. The DMSO solvent was shown to have the highest adsorbent regeneration method efficiency at 63%. Safinamide elimination was lessened by organic interfering species like cefixime and humic acid compared to inorganic species like chloride, sulphate, and nitrate, most likely as a result of intense competition for the few available active sites. Using zeolite/MOF nanocomposite, the percentage of safinamide removed from spiked real water samples (tap water, Nile River water, and groundwater samples) was 48.80%, 64.30%, and 44.44%, respectively. Based on cytotoxicity results, the highest percentages of cell viability for zeolite and zeolite/MOF at 24 h were 83% and 81%, respectively, in comparison to untreated controls. According to these results, zeolite and zeolite/MOF composites can be used as effective adsorbents for these pollutants in wastewater.

1. Introduction

Numerous environmental problems, particularly water pollution, have emerged with population growth and industrialization [1]. The primary water pollutants affecting the ecosystem are organic compounds and heavy metals [2,3]. Pharmaceuticals are organic micropollutants with high toxicity and low biodegradability, which may adversely affect aquatic life. Such organic compounds can cause hyperactivity, delayed hatching, and increased body size in zebrafish embryos [4,5]. Many studies have shown that annual wastewater releases roughly 300 tonnes of various micropollutants, including pesticides and industrial chemicals, into the environment [6,7]. Heavy metal pollutants, such as cadmium, cobalt, copper, chromium, nickel, and lead, are released into surface water bodies through industrial effluents, posing a threat to living organisms [8]. These toxic substances can lead to various health issues, including cancer, organ shrinkage, immune and neurological dysfunction, and even fatal illnesses [9,10]. Therefore, using simple, cost-effective techniques, pharmaceuticals and heavy metals should be removed efficiently from water streams [11]. Different methods, such as adsorption, biodegradation, ozonation [8], photocatalysis, membrane filtering, coagulation, and flocculation, have been employed to treat pharmaceutical wastewater and heavy metals [12,13,14,15,16]. Each method has advantages and disadvantages, such as generating hazardous by-products in the catalysis method and the costly nature of operation and maintenance [17]. Adsorption is a promising technique for removing various pollutants from wastewater since it is an effective and low-cost method. In addition, adsorption is a versatile technique since adsorbents’ properties may be changed by modifying their surfaces’ hydrophobicity, reactivity, surface energy, surface loading, roughness, and surface area [9]. Many effective adsorbents are applied for pharmaceuticals and heavy metals such as activated carbon, metal-organic frameworks, and biomass. For the majority of the last few decades, activated carbon has been utilized as an adsorbent to recover industrial and municipal wastewater. However, the high price of activated carbon has motivated researchers to look for appropriate, less expensive adsorbents, particularly in developing nations [18]. These adsorbents’ principal drawback is their lacklustre selectivity. Furthermore, the random pore that may impede the target metal ion’s efficient transport contributes to the comparatively low adsorption kinetic. Additionally, because of their weak coordination chemistry with the metal ion, treatment is needed for the metal ion, such as acidification and impregnation to a particular group that increases the adsorption capacity and selectivity [11]. Because of this, current research has concentrated on creating affordable substitutes utilizing a variety of natural resources and industrial wastes [19].
Natural substances include silica and zeolite [20,21,22,23,24]. Natural zeolites are hydrated aluminosilicate materials with varying pore sizes and are suitable for ion exchange, adsorption, and dehydration [25]. Due to their wide availability and diverse properties, natural zeolites have been extensively studied and exploited [26,27]. MOFs’ huge specific surface area, high porosity, variety of functionalities, and good thermal stability have piqued the curiosity of researchers studying adsorption applications. Pollutant diffusion on the skeleton and the accessibility of adsorption sites are facilitated by a large specific surface area and high porosity. Simultaneously, MOF metal composites could be created by carefully choosing organic connectors and connecting them to metal nodes, which would improve the adsorption capacity and recovery in addition to adjusting the size and shape of pores. Due to these unusual characteristics, the last few years have seen a surge in research interest in the field of MOF-based materials, and this class of materials has also been investigated as a potential novel platform for the adsorption and removal of contaminants in water media [19]. Zeolite (as a cheap alternative) and MOF (as an advanced, efficient adsorbent) were combined in a nanocomposite that was investigated as an adsorbent to remove cadmium as a representative example of a heavy metal (Table 1) and safinamide as an example of a pharmaceutical. In this work, a multi-metallic MOF was prepared and supported on natural zeolite to form a composite. They were characterized, and their removal efficiency for both safinamide and cadmium was investigated.

2. Materials and Methods

2.1. Chemicals

Natural Egyptian zeolite ore was collected from the northwestern region of Beni-Suef Governorate (N 29°25′12″, E 31°9′36″). Copper nitrate (Cu(NO3)2·3H2O), cobalt nitrate (Co(NO3)2·6H2O), and nickel nitrate (Ni(NO3)2·6H2O) were acquired from Loba Chemie, Piochem, and Alpha Chemika, respectively. 2-amino terephthalic acid and N,N dimethyl formamide were purchased from Sigma Aldrich and Carlo Erba. A 1000 ppm standard cadmium solution was obtained from Scharlab.

2.2. Synthesis of Co/Ni/Cu-NH2BDC MOF Metal-Organic Frameworks

Co/Ni/Cu-NH2BDC MOF was prepared using a simple solvothermal technique where 2-amino terephthalic acid (3 mmol) was dissolved in 120 mL of N,N-dimethyl formamide then the metal salts Co(NO3)2. 6H2O (2 mmol), Cu(NO3)2.4H2O (0.5 mmol), and Ni(NO3)2.6H2O (0.5 mmol) were added. This precursor was added to a Teflon-lined stainless steel vessel that was kept at 160 °C for 12 h. Then, the product was cooled, separated, washed, dried, and stored for further use.

2.3. Synthesis of Zeolite/MOF Composite

In total, 2 g of the natural zeolite were suspended in 20 mL ethanol for 24 h under continuous stirring. A suspension of 0.25 g of the MOF in 50 mL ethanol was then added dropwise on zeolite and was left under stirring for 24 h. The formed nanocomposite was separated, washed several times with distilled water, and dried at 60 °C for 12 h.

2.4. Characterization

Both adsorbents were characterized using a PANalytical (Empyrean, Malvern Panalytical Ltd., Malvern, UK) X-ray diffractometer with Cu-Kα radiation from two-theta of 5° to 80° to determine the crystallinity of the sample. In addition, the functional groups before and after adsorption were determined using Fourier transform infrared (FTIR) spectroscopy (Bruker-Vertex 70, Bruker, Ettlingen, Germany) from a 400 to 4000 cm−1 wavenumber. The morphology of the ore was investigated using a field emission scanning electron microscope (Gemini Zeiss-Sigma 500 VP, Jena, Germany). Textural properties of the prepared material were investigated at 77 K by the N2 adsorption–desorption isotherms using a Micromeritics ASAP 2010 device. The zeta potential investigation was conducted using a Zetasizer Nano instrument (Zeta-Meter Plus 3.0 equipment, Malvern Panalytical Ltd., Malvern, UK). Samples of both materials were suspended in 1 mL of water, ultrasonicated for 30 min, and measured in disposable folded capillary cells provided by the manufacturer.

2.5. Adsorption Experiments

Typically, 0.1 g of the adsorbents (zeolite, zeolite/MOF) was added to 20 mL of adsorbate solution, changing the adsorbate concentrations from 20 to 1000 mg/L for safinamide and from 3 to 20 mg/L for Cd2+. The mixture was stirred for 2 h at 25 °C. By adding either 0.10 mol/L HCl or 0.10 mol/L NaOH solution, the initial pH of the solution was changed to values between 3 and 9, and the kinetic study was performed using 20 mg/L for each pollutant investigated. After centrifuging and separating the sample, an atomic absorption spectrophotometer and a UV-visible spectrophotometer were used to measure Cd2+ and safinamide concentrations, respectively. Calibration curves for safinamide detection are provided in the Supporting Information (Figure S1). The following formulas [45,46] were used to calculate the adsorption percentage and the adsorption capacity qe (mg/g):
a d s o r p t i o n   p e r c e n t a g e = C o C e C o × 100
q e = ( C o C e ) × V m
Co and Ce are the initial adsorbate concentration and the equilibrium concentration, respectively (mg/L), m is the mass of the adsorbent, and V is the volume of the solution (L) [47].
For adsorption isotherm experiments, the Langmuir and Freundlich isotherm models were investigated to fit the experimental results for both Cd2+ and safinamide. The details of these models are illustrated in Table S1. Finally, safinamide and Cd2+ ion adsorption kinetics were investigated and then fitted to various kinetic models (Table S2).
The examined experiments were repeated more than 5 times.

2.6. Effect of Temperature

In ideal circumstances, the impact of temperature on the adsorption process was examined. Each flask holding 20 ppm of Cd2+ at 25, 35, 45, and 55 °C received 0.1 g of zeolite/MOF at pH 9. For 120 min, the flasks were shaken at various temperatures. After filtering the zeolite/MOF out of the cd solution, an atomic absorption spectrophotometer was used to measure the cd concentration.

2.7. Regeneration Experiments

For adsorbent recovery investigations, desorbents such as acetone, ethanol, methanol, isopropanol, dimethylsulfoxide, dimethylformamide, and acetonitrile were utilized. Following the adsorption process, ten milligrams of adsorbent were combined with twenty milliliters of desorbent reagent. The samples were then agitated at 25 °C and 120 rpm for 24 h. The regeneration efficiency was determined using ultraviolet-visible spectrophotometry to quantify safinamide. Five regeneration cycles were implemented in adsorbent reuse experiments.

2.8. Real Sample Investigation

Zeolite/MOF was used at the optimum adsorption conditions to treat three real water samples (tap water, Nile River water, and groundwater) by spiking the collected samples with 20 ppm of safinamide.

2.9. Cytotoxicity Study

The potential cytotoxicity of the materials was evaluated in Vero cells using the MTT assay. Vero cells derived from the kidney of an African green monkey (ATCC CCL-81) were cultured in DMEM at a density of 5 × 104 cells/mL. The cells were seeded in 96-well plates and incubated for 24 h at 37 °C and 5% CO2. After 24 h and 48 h, the medium was removed, and the cells were treated with varying concentrations of zeolite and zeolite/MOF samples (6.25, 12.5, 25, 50, 100, and 200 μg/mL) diluted in PBS. Each concentration was performed in triplicate. Some wells contained only solvent as a negative control. After 4 h and 48 h incubation at 37 °C and 5% CO2, 10 μL of MTT reagent were added. Once orange formazan developed, absorbance was measured at 595 nm using an ELISA reader. The percentage of viable cells was calculated using Equation (3).
Cell viability (%) = absorbance of treatment − absorbance of Control media/absorbance of control of cells − absorbance of Control media × 100%.

3. Results and Discussion

3.1. Characterization of Adsorbents

The crystal structure of the pure zeolite, pure Cu/Ni/Co ABDC (MOF), and zeolite/MOF samples were determined using the XRD test. As seen in Figure 1, the zeolite sample displayed clear, high-intensity XRD patterns that indicate the sample is crystalline. Based on the JCPDS Card No 00-025-1349, zeolite material showed the Clinoptilolite type indexed to 020, 200, 001, −220, 113, −131, 400, −222, −422, 151, and −621 at the 2θ = 9.9°, 11.3°, 13.1°, 15.2°, 17.3°, 19.13°, 22.1°, 26.3°, 28.2°, 30.1°, and 32.06°, respectively [30,31]. The XRD patterns for the MOF sample were 2θ = 9.2, 11.2, 14.3, 16.7, 17.8, 21.01, 24.3, 26.2, 43.4, and 44.7, which corresponded to (110), (220), (020), (333), (211), (202), (222), (040), (200), and (111), according to existing literature [48,49,50]. The presence of copper nanoparticles was confirmed by 2θ = 16.7 and 43.4 indices to the 020 and 200 planes, respectively [47,49]. 2θ = 44.7 (111) also confirmed the presence of nickel nanoparticles. Finally, cobalt was validated using the JCPDS Card No 00-018-0424 [50]. The XRD patterns revealed the zeolite patterns with more intensity for the zeolite/MOF. There was a definite overlap in the 110 and 220 planes for MOF and 020 and 200 planes for zeolite, which may explain why there are no MOF peaks in the zeolite/MOF spectrum.
The crystallite size of the zeolite and zeolite/MOF was computed depending on the Debye–Scherrer equation (Equation (4)) [49,51].
D = Kλ/(βCosθ)
where K is a constant equal to 0.9, λ is the X-ray wavelength (Cu Kα = 0.15405 nm), β is the full width at half maximum, and θ is the Bragg’s angle. Zeolite and zeolite/MOF were calculated to have crystallite sizes of 3.07 nm and 17.4 nm, respectively. The higher crystallite size of zeolite/MOF compared to pure zeolite indicates the deposition of MOF particles into zeolite layers.
As shown in Figure 2, FT-IR spectra were used to evaluate and study the chemical structure of the generated materials. FTIR for zeolite, MOF, and zeolite/MOF samples are shown in Figure 2a. The water vapor molecules adsorbed on the surface and within pores of the zeolite matrix can be detected due to the stretching vibration of hydroxyl (-OH) groups evident from the broad peak at 3600–3300 cm−1 [52] and at 1700–1595 cm−1 [53]. The unique functional groups in zeolites, such as Si–O stretching vibrations, indicate their tetrahedral silicon–oxygen structure and are found in the 1100–1000 cm−1 range [54]. The band at 1058 cm−1 originates from the Si–O–Si bond [55]. Within the zeolite lattice, the stretching vibrations of the Al–O bonds are found at 800–750 cm−1, Si–O–Si bends are seen at 650–600 cm−1, and a band between 450 and 500 cm−1 is attributed to Si–O–Al [54,56,57].
As for the MOF sample, OH-related bands similar to those of the zeolite sample could be observed due to the presence of adsorbed water molecules. In addition, the broad band at approximately 3400 cm−1 originate from the asymmetric stretching mode of the N–H bond [58]. The peaks at 1550 cm−1 and 1392 cm−1 can be assigned to the asymmetrical and symmetrical stretching modes of the carboxylate groups [58]. The band at 1230 cm−1 may be assigned to C–N stretching vibrations [59]. Bands at 1052 cm−1 and 774 cm−1 can be attributed to the stretching vibration of the benzene ring, while the band around 673 cm−1 can be attributed to the COO bond [60]. Finally, the band at approximately 557 cm−1 can be attributed to metal–oxygen–hydrogen bending vibration (Ni–OH, Co–OH, and Cu–OH) [48]. The band at 897 cm−1 can be assigned to the carboxylic group [61]. For zeolite/MOF, the peaks originating from the zeolite phase were dominant in the spectra owing to the low loading of the MOF phase in the composite. A stronger indication of a chemical link between the MOF and zeolite could come from the increased strength of the OH and hydrogen interaction bands at 3600–3300 cm−1 and 1700–1595 cm−1.
Figure 2b shows the FTIR spectra of spent adsorbent after adsorption. As shown, safinamide has numerous FTIR bands originating from functional groups in its structure. After adsorption, such bands were not clearly observed, probably due to their low loading and higher transmittance from bands originating from the adsorbent itself. After cadmium adsorption, no obvious change was also noticed for the FTIR of the spent adsorbent, probably because of the ion exchange nature of zeolite for cadmium ions. Interaction between cadmium and OH groups in the zeolite structure may be pronounced in the increased intensity of low wavenumber peaks below 1000 cm−1, which usually originate from metal–oxygen interaction.
The SEM morphology of zeolite (Figure 3a) showed a plate-like structure with a thickness of between 50 and 60 nm. The petal-like form indicates a high surface area suitable for the adsorption process. The MOF (Figure 3b) showed thick particles, ranging in size from 400 to 600 nm, with uneven, prismatic-edged forms. The nanocomposite zeolite/MOF (Figure 3c) showed the petal-like structures of the zeolite particles with a homogenous prismatic shape, indicating the formation of MOF within zeolite structures. To acquire elemental variations of surface features, qualitative EDX analysis and SEM study were combined for zeolite and zeolite/MOF, as depicted in Figure 3d and Figure 3e, respectively.
The SEM image of the resulting composite, which can be seen in Figure 3f,g, has verified that the adsorbate has successfully adhered to the composite material by occupying the well-defined spaces and pores that have emerged in the SEM image of the prepared adsorbent, which displays a compact homogenous structure. Additionally, as seen in image (f), the skeleton has collapsed, the material surface is no longer tightly bound, and a significant number of amorphous particles, the majority of which may be adsorbed Cd2+ metal ions, have attached themselves to the material surface following the adsorption reaction.
The surface of the zeolite, Figure 3d, comprises O, Al, and Si with atomic ratios of 75.77%, 5.32%, and 18.9%, respectively. Figure 3e shows the elemental surface study of zeolite/MOF, which contains the main metals of MOF and zeolite. O, Al, Si, Co, Ni, and Cu elements have atomic ratios of 78.73%, 4.48%, 16.3%, 0.21%, 0.07%, and 0.01%, respectively. The absence of other foreign elements reflects the purity of the synthesized zeolite/MOF sample.
The textural characteristics of the zeolite and zeolite/MOF material, such as specific surface area, pore volume, and pore size, were distributed using the N2 adsorption–desorption technique in Figure 3g,h. The two materials estimated an isotherm type of IV and a hysteresis loop type of H3 [62]. H3 type is related to a broad range of non-uniformly sized slit-shaped pores that appear in solids [63]. The specific surface area, pore volume, and average pore size of zeolite/MOF are all greater than those of pure zeolite, as shown in Table 2. These results significantly promote the formation of a Zeolite/MOF composite. Figure 3i displays the pore size distribution estimated from the nitrogen desorption branch of the isotherm. Notably, the Zeolite/MOF sample demonstrated the narrowest pore size.
Zeta potential experiments demonstrate the stability of the synthesized zeolite/MOF material. They assess how strongly electrically charged particles in a solution will either attract or repel one another. Zeolite/MOF material zeta potential measurements, which were −27.9 mV, demonstrate the produced nanoparticles’ great degree of stability. Figure 4a shows the zeta potential, and Figure 4b shows the size distribution of zeolite/MOF material. Figure 4c,d demonstrate the zeta potentials of zeolite and MOF samples, respectively. The Zeolite/MOF size was 730.4 nm. The zeta potentials for zeolite and MOF samples were calculated to be −18.6 mV and −12.6 mV, as shown in Figure 4.

3.2. Adsorption Study

3.2.1. Effect of pH

The elimination of contaminants from water is significantly affected by pH. Its effect on the removal process is caused by the charge it provides to the pollutants and adsorbents. Safinamide has a pKa of 7.4 [64]. At pH < 7.4, safinamide is primarily cationic, while at pH > 7.4, the anionic form is the major species. Also, the point of zero charge of zeolite and zeolite/MOF calculated by the pH drift method is 6.9 and 7.01, respectively. When the pH of safinamide solution > pHpzc of two adsorbents, the surface charges will be positive, while at pH < pH pzc, the charge will be negative. The effect of pH on the adsorption of safinamide and Cd2+ (Figure 2b and Figure 5A) shows a maximum adsorption percentage of 48.8% for safinamide at pH 5 for both adsorbents. Then, the adsorption percentage decreases at pH > 5, demonstrating that the alkaline environment fails to improve the adsorption of safinamide on two adsorbents. Consequently, this decline in safinamide adsorption above pH 5 may be attributed to the decreased electrostatic attraction between safinamide molecules and zeolite, as well as zeolite and MOF, which possess negatively charged surfaces and the competition between OH groups and the negatively charged safinamide molecule. As presented in Figure 5, showing the effect of pH on the adsorption percentage of (A) safinamide and (B) Cd2+ onto zeolite and zeolite/MOF.B, the adsorption of Cd2+ ions onto zeolite and zeolite/MOF is high with increasing pH. The maximum adsorption percentage of Cd ions (48.9%) by zeolite was observed at a pH of 7. In contrast, the percentage of Cd adsorbed onto zeolite/MOF increased from 27.8% to 80% with increasing pH from 3 to 9. The relatively low Cd adsorption at low pH may be related to the structural alteration of zeolite in acidic environments and the competition for active binding sites on the adsorbent between H+ and Cd2+ ions [65,66]. When the pH is high (7–9), the concentration of hydrogen ions decreases, thereby increasing the availability of active binding sites for cadmium ions.

3.2.2. Effect of Adsorbent Dose

The dosage of the adsorbent is a critical variable that significantly influences the adsorption procedure. Figure 6A shows the adsorption of safinamide onto zeolite and zeolite/MOF. The drug adsorption percentage rose with the increase in the amount of zeolite until the maximum value reached 0.15 g. Beyond this value, the adsorption percentage stabilized. Meanwhile, for zeolite/MOF, the amount of the absorbed drug rose with the increasing amount of zeolite/MOF until the maximum was reached at 0.1 g/L. Figure 6B depicts the effect of zeolite and zeolite/MOF dosage on the removal of Cd2+. The removal efficiency of Cd2+ reached 97.19% for a 0.1 g adsorbent dose of zeolite. On the other hand, over the range of investigated dosages, the zeolite/MOF adsorbent showed a maximum adsorption percentage of 99.9%.

3.2.3. Adsorption Isotherm

An adsorption isotherm is used to establish a relation between adsorption equilibrium and the initial concentration of adsorbate [67]. Several adsorption isotherms can be used to evaluate the adsorbate distribution between the liquid and solid phases once the adsorbent uptake has reached equilibrium. The amount of adsorbate per unit mass of the adsorbent as a function of concentration at constant pH and temperature is represented by fitting the data to the adsorption isotherm model. It can be used to describe how materials are adsorbed onto the surface of the adsorbent and determine the maximum adsorption capacity of drug residue or Cd2+ metal ions. The Langmuir and Freundlich models were investigated in this work to explain adsorption isotherms.
The Langmuir model for the two-parameter models postulates that adsorption occurs at particular, similar adsorption sites localized on the catalyst surface, coating it with a monolayer of the adsorbate. The Freundlich isotherm model describes the multilayer adsorption of adsorbed molecules onto a heterogeneous adsorbent surface. To compare which isotherm equations match the data the most exactly, the highest determination coefficient, R2, is employed. The R2 values and all other characteristics for each isotherm are compared in Tables S3 and S4 for safinamide and Cd metal ion adsorption, respectively. According to the calculated coefficients (R2) in Table 3, the adsorption data suited Langmuir isotherm models (Figure 7a) most effectively for the adsorption of safinamide onto zeolite and zeolite/MOF (Figure 7b). This can reflect that the adsorption of safinamide on both adsorbents was monolayer adsorption. For cadmium adsorption, the best model to fit the experimental data on the zeolite support was the Freundlich isotherm model (Figure 7c), which reflects a heterogeneous adsorption nature with multilayer adsorption. On the other hand, when the nanocomposite was used, the Langmuir model (Figure 7d) showed the highest R2 value (Table 3), Table 4 which reflects monolayer adsorption for Cd metal ions. The statistical error validity statistics for the isotherm models are shown in Table 5, Table 6, Table 7 and Table 8. It has been noted that the values of various statistical techniques increase with model quality and decrease with the degree of agreement between the experimental quantity adsorbed (qe, exp) and the calculated quantity adsorbed (qe, cal). The coefficient of regression (R2) was mentioned to help the comparison of the best model. R2 values that are higher and tighter are qe, exp, and qe, cal values.
The dimensionless constant, RL (separation factor), can be calculated from the following equation [67]:
R L = 1 1 + K L C o  
RL values designate the adsorption as unfavorable when RL > 1, linear when RL = 1, favorable when 0 < RL < 1, and irreversible when RL = 0. In this study, RL for safinamide and Cd2+ adsorption on zeolite was calculated to be 0.25 and 0.7, respectively. As for zeolite/MOF, the values of RL were 0.96 and 0.959 for safinamide and Cd2+, respectively. These values indicate favorable adsorption of both adsorbates on both adsorbents. For Cd2+ adsorption on zeolite, the value of 1/n from the Freundlich model was less than one, which indicates a favorable physisorption condition [68]. The Toth, Langmuir–freundlich, and Sips three-parameter models were also applied. In general, these models are useful for illustrating heterogeneous adsorption frameworks with both low and extremely good adsorbate quality limits [69]. The Langmuir–Freundlich isotherm model provides a signal concerning heterogeneous surfaces and the adsorption energy circulation on them [69]. A combination of the Langmuir and Freundlich isotherm models is the Sips isotherm model. This model minimizes the Freundlich model at low adsorbate concentrations but predicts the Langmuir model at high adsorbate concentrations [70]. By comparing other multicomponent adsorption isotherms, the Khan isotherm model has been utilized to describe the experimental data for the adsorption of various contaminants from aqueous solutions with the lowest average percentage error [71]. The Freundlich and Langmuir isotherms’ components are combined to form the Redlich–Peterson isotherm model [72]. Due to the Fritz–Schunder three-parameter isotherm’s huge number of coefficients, it was designed to accommodate a wide range of experimental results [73]. The highest determination coefficient, R2, is used to compare which isotherm equations most closely match the data. The R2 values and all other characteristics for each isotherm are compared in Table 3 for safinamide or Cd2+ adsorption [74,75].

3.2.4. Adsorption Kinetics Investigation

The ability to estimate the adsorption rate is important for the development of any adsorption system because it enables the selection of the optimal adsorption time. The following kinetic models were tested: pseudo first-order, pseudo second-order, intraparticle diffusion, mixed 1- and 2-order, and the Avrami model. The parameters for each model were determined and summarized in Table 9 and Table 10 for safinamide and Cd adsorption, respectively. According to R2 in Table 9, data were best fitted with intraparticle diffusion for the adsorption of safinamide onto zeolite (Figure 8a). The same model showed the highest R2 value when zeolite/MOF was used (Figure 8b). The intraparticle diffusion model is one of the internal diffusion models that reflects that the adsorbate diffusion within the adsorbent is the slowest step [76]. This model shows that the intra-particle diffusion step is the rate-determining step [77]. The adequacy of this model can reflect the difficulty of safinamide diffusion due to its large size within the zeolite pores either before or after the addition of the MOF phase.
According to R2 in Table 10, data were best fitted with a pseudo second-order model for the adsorption of Cd onto zeolite (Figure 8c), while adsorption information suited the intraparticle diffusion model for the adsorption of Cd onto zeolite/MOF (Figure 8d). The adequate fitting of the kinetic data to the pseudo second-order model can indicate that the zeolite support has abundant active sites that can adsorb Cd2+ easily and quickly, probably leading to a diffusion-limited adsorption process [76,78]. In other words, this model suggests that Cd2+ adsorption occurs at a very fast rate compared to the rate of diffusion of these ions from the bulk of solution to the active sites present on the zeolite surface within its pores. After MOF addition to the zeolite, it can be assumed that the MOF phase decreased the pore size of the zeolite support and increased the resistance of Cd2+ diffusion within the pores rather than from the bulk of the solution, leading to an internal diffusion limited adsorption process.

3.3. Desorption Study

Desorption and regeneration steps are required to investigate the applicability of a given adsorbent. If an adsorbent cannot be desorbed or regenerated effectively, the application value of the adsorbent is reduced and may create secondary environmental pollution. Therefore, the nanocomposite was regenerated using different solvents (methanol, ethanol, acetonitrile, isopropanol, acetone, dimethylformamide, and dimethylsulfoxide). As shown in Figure 9a, the desorption efficiency reached above 35.04% after 24 h using methanol, 29.51 using ethanol, and 2.17 using isopropanol. In addition, acetonitrile did not result in appreciable safinamide desorption, while acetone and dimethylformamide showed desorption efficiencies of 21.6% and 61.8%. The eluent showing the highest desorption efficiency was dimethylsulfoxide, which reached 63.74%, probably due to the high solubility of safinamide in dimethylsulfoxide, which reached 30 mg/mL [79]. Reuse of the adsorbent was conducted in DMSO, as shown in Figure 9b, where almost no observable loss in removal efficiency was observed for three consecutive cycles, indicating the promising reusability of this adsorbent.

3.4. Adsorbent Stability and Selectivity

Adsorbent stability was assessed by soaking zeolite/MOF adsorbent in water for 24 h and collecting its XRD diffraction pattern. Figure 9c shows that no significant changes were observed for both samples, indicating the reasonable stability of this adsorbent in water effluents.
Adsorption selectivity for the safinamide drug was studied by adding 25 mg/L of different interfering species (Cl, NO3, SO42−, humic acid, and cefixime drug) under adsorption optimum conditions. Each of them was added separately to form a binary solution. The removal percentage for each initial concentration of the added interfering species is shown in Figure 10a. The removal percentage for interfering ions of concentrations of 100 ppm is summarized in Figure 10b. As shown in Figure 10b, the removal efficiency of safinamide was lower in nearly all binary solutions than in solutions without interfering species [80,81]. Moreover, organic compounds reduced the removal of safinamide more than inorganic compounds, where the addition of cefixime reduced the removal percentage to 34%. These results can be attributed to competition between organic compounds for the adsorption groups, and the large size of the organic structure may fill the adsorbent pores.

3.5. Thermodynamic Investigation

The thermodynamic parameters for the interaction between safinamide were analyzed at different temperatures, as shown in Table 11 and Figure 11. The results indicate that the reaction is energetically favorable and spontaneous under standard conditions, with negative ΔG° values across all temperatures. The negative ΔH° suggests heat release, characteristic of an exothermic process, while the negative ΔS° indicates a decrease in disorder during the reaction. The decrease in ΔG° with increasing temperature implies reduced spontaneity at higher temperatures. Further analysis using the van’t Hoff equation can provide insights into the temperature dependence and equilibrium constant (K) of the reaction [82]. Overall, the thermodynamic data reveal that the safinamide reaction is exothermic, spontaneous at room temperature, and less spontaneous at elevated temperatures.

3.6. Real Water Sample Analysis

The removal percentage of safinamide using collected real water sources (tap water, Nile River water, and groundwater samples) by spiking 20 ppm, pH 5, and 0.10 g zeolite/MOF nanocomposite was 48.80%, 64.30%, and 44.44% for tab water, Nile River water, and groundwater, respectively.

3.7. Adsorbent Cost Analysis

Table 1 compares the maximum adsorption capacity of the prepared zeolite/MOF with similar zeolite- and MOF-based adsorbents in the literature. The current zeolite/MOF is among the highest for Cd2+ removal. Higher adsorption capacities are predominantly observed in adsorbents composed of MOFs as compared to zeolites. As MOF adsorbents typically cost around USD 7/g, this may result in a probable rise in price. In contrast, zeolites generally cost approximately USD 1.5–3.5/kg, i.e., more than 1000-fold less than MOF adsorbents [83]. Other adsorbents reported in Table 1 and in recent reviews [27,30,35] showed smaller maximum adsorption capacities than the prepared zeolite/MOF.

3.8. Adsorption Mechanism

A simple mechanism for safinamide adsorption on zeolite is illustrated in Figure 12a. The molecules of this drug diffuse from the bulk of the solution to the pores of the zeolite. Due to the large size of this molecule, its diffusion is slow. When this drug is adsorbed on the active sites within the pores, the adsorption step is much faster than diffusion, leading to an internal diffusion-limited process, as discussed in the kinetics section. The drug can be adsorbed on specific active sites on the zeolite structure, which probably provides electrostatic interaction between partially negative atoms in the drug structure and partially positive sites within the zeolite framework. This leads to adsorption of a heterogeneous nature when equilibrium is reached, as discussed in the adsorption isotherm section. When MOF is added to the zeolite, the pores can get narrower, and the diffusion-limited step still controls the overall adsorption of this drug (Figure 12b). However, the MOF phase offers more active sites for this drug, probably due to hydrogen bonding and electrostatic interactions. This leads to monolayer homogenous adsorption at equilibrium, as discussed in the adsorption isotherm section.
In the case of Cd2+ ions, the diffusion of such small ions is much faster, and the process is not limited to internal diffusion (Figure 12c). However, diffusion from the bulk of the solution to within the pores of zeolite can be the rate-limiting step, as reflected by the pseudo second-order kinetic model. This can be attributed to the complex nature of the pore network of zeolites, which leads to an external diffusion limitation adsorption process. When Cd2+ ions reach the zeolite surface, ion exchange can occur at specific sites in the zeolite framework, leading to heterogeneous adsorption in nature. When MOF is added to the zeolite phase (Figure 12d), the MOF particles can narrow the pores and lead to an internal diffusion limitation. When the MOF phase is present, part of the active sites for Cd2+ adsorption may be lost due to the presence of the MOF phase itself adsorbed on the surface of zeolite. This can have a negative effect on the adsorption capacity of the zeolite support. However, the MOF phase can provide interaction sites with Cd2+ ions, thus increasing the adsorption capacity of the overall nanocomposite. In this work, the maximum adsorption capacity for the zeolite and the zeolite/MOF were calculated to be 550.69 mg/g. This can indicate that any decrease in adsorption sites due to the presence of MOF was compensated for by its interaction with Cd2+. This interaction is homogenous with monolayer adsorption, as reflected by the Langmuir isotherm model. Also, the skeleton collapsed, the material surface was no longer tightly bound, and a significant number of amorphous particles, the majority of which may be adsorbed Cd2+ metal ions, attached themselves to the material surface following the adsorption reaction.

3.9. Cytotoxicity of the Investigated Adsorbent

Figure 13 shows the cytotoxic activity of the tested compounds, zeolite and zeolite/MOF, at varying concentrations as determined by MTT assays. Cytotoxicity was examined after 24 h and 48 h using a 200 μg/mL concentration. The maximum percentages of cell viability compared to untreated controls at 24 h were 83% and 81% for zeolite and zeolite/MOF, respectively. After 48 h of treatment, the cell viability compared to untreated controls was 81% and 79% for zeolite and zeolite/MOF, respectively. These cytotoxicity assays were performed in triplicate ((n = 3) ± SD). The results demonstrate that the cytotoxic activity of zeolite and zeolite/MOF at 48 h was enhanced compared to 24 h. As evidenced by the results, the cytotoxicity activity of zeolite is very close to that of zeolite/MOF and slightly lower than it.

4. Conclusions

In this work, zeolite and its novel composite with a 2-amino terephthalic acid-based multi-metallic metal-organic framework were synthesized, involving an improvement in surface area where its value was 24.63 and 41.86 m2/g for zeolite and zeolite/MOF, respectively. Their adsorption efficiency was best at pH 5 (48.8%) for safinamide, while for cadmium, pH 7 and 9 (48.9%) were the best for zeolite and zeolite/MOF, respectively. The maximum adsorption capacity of the zeolite/MOF composite reached 500.69 mg/g for safinamide and 550.69 mg/g for cadmium. The values of the thermodynamic parameters, i.e., Δ G°, ΔH°, and Δ S°, were established by thermodynamic studies of the removal of cadmium metal ions by zeolite/MOF. These values are very promising compared to other materials reported in the open literature. Therefore, it can be concluded that further modifications and investigations can pave the road towards an efficient adsorbent for numerous organic and inorganic applications.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/colloids8050050/s1, Figure S1: Calibration curve for Safinamide detection using UV-VIS spectrophotometer; Table S1: Isotherm models investigated in this study; Table S2: Adsorption kinetics equations investigated for non-linear regression of kinetic data.

Author Contributions

Conceptualization, R.M., A.A.F. and H.M.M.; methodology, R.M., R.A. and Z.E.E.; software, R.A., H.A.Y. and Z.E.E.; validation, R.A., H.A.Y. and Z.E.E.; formal analysis, R.M., A.A.A., H.A.R. and S.I.O.; investigation, R.M., R.A. and Z.E.E.; resources, R.M., A.A.F. and H.M.M.; data curation, R.A. and Z.E.E. and H.A.Y.; writing—original draft preparation, R.A. and Z.E.E. and H.A.Y.; writing—review and editing, R.M., A.A.F. and H.M.M.; visualization, R.M., R.A. and Z.E.E.; supervision, R.M., A.A.F. and H.M.M.; project administration, R.M., A.A.A., H.A.R. and S.I.O.; funding acquisition, A.A.A., H.A.R. and S.I.O. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R5), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Acknowledgments

This study/publication was made possible by the generous support of the American people through the United States Agency for International Development (USAID). The contents are the responsibility of [Rania Shaban Taha Abdelazeem] and do not necessarily reflect the views of USAID or the United States Government. In addition, this study/publication (Project ID: TAILORED ENZYMATIC AND NANO-BASED TREATMENT OF WASTEWATER TO DETOXIFY HEAVY METALS AND DEGRADE ANTIBIOTICS) was made possible by the generous support of the American people through the United States Agency for International Development (USAID). The contents are the responsibility of [Hamdaa Mahmoud] and do not necessarily reflect the views of USAID or the United States Government.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. XRD patterns of pure Cu/Ni/Co ABDC (MOF) and Zeolite/MOF samples.
Figure 1. XRD patterns of pure Cu/Ni/Co ABDC (MOF) and Zeolite/MOF samples.
Colloids 08 00050 g001
Figure 2. FTIR analysis of (a) zeolite, MOF, and zeolite/MOF. (b) Zeolite/MOF after safinamide adsorption (zeolite/MOF/Safinamide), and zeolite/MOF after cadmium adsorption (zeolite/MOF/Cd) samples.
Figure 2. FTIR analysis of (a) zeolite, MOF, and zeolite/MOF. (b) Zeolite/MOF after safinamide adsorption (zeolite/MOF/Safinamide), and zeolite/MOF after cadmium adsorption (zeolite/MOF/Cd) samples.
Colloids 08 00050 g002
Figure 3. SEM micrographs of (a) zeolite, (b) pure MOF, and (c) Zeolite/MOF samples. (d,e) EDX analysis of zeolite and zeolite/MOF samples, respectively, (f) for the Zeolite/MOF sample after Cd 2+ adsorption, N2 adsorption–desorption isotherms of (g) Zeolite, (h) Zeolite/MOF samples and (i) pore size distribution of Zeolite/MOF.
Figure 3. SEM micrographs of (a) zeolite, (b) pure MOF, and (c) Zeolite/MOF samples. (d,e) EDX analysis of zeolite and zeolite/MOF samples, respectively, (f) for the Zeolite/MOF sample after Cd 2+ adsorption, N2 adsorption–desorption isotherms of (g) Zeolite, (h) Zeolite/MOF samples and (i) pore size distribution of Zeolite/MOF.
Colloids 08 00050 g003aColloids 08 00050 g003b
Figure 4. (a) zeta potential and (b) Size distribution of zeolite/MOF material. (c,d) are the zeta potentials of zeolite and MOF samples, respectively.
Figure 4. (a) zeta potential and (b) Size distribution of zeolite/MOF material. (c,d) are the zeta potentials of zeolite and MOF samples, respectively.
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Figure 5. Effect of pH on the adsorption percentage of (A) safinamide and (B) Cd2+ onto zeolite and zeolite/MOF.
Figure 5. Effect of pH on the adsorption percentage of (A) safinamide and (B) Cd2+ onto zeolite and zeolite/MOF.
Colloids 08 00050 g005
Figure 6. Effect of adsorbent dose on the adsorption of (A) safinamide and (B) Cd (II) onto zeolite and zeolite/MOF.
Figure 6. Effect of adsorbent dose on the adsorption of (A) safinamide and (B) Cd (II) onto zeolite and zeolite/MOF.
Colloids 08 00050 g006
Figure 7. Best fit isotherm model for safinamide adsorption onto (a) zeolite and (b) zeolite/MOF; best-fit isotherm model for Cd2+ adsorption onto (c) zeolite and (d) zeolite/MOF.
Figure 7. Best fit isotherm model for safinamide adsorption onto (a) zeolite and (b) zeolite/MOF; best-fit isotherm model for Cd2+ adsorption onto (c) zeolite and (d) zeolite/MOF.
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Figure 8. Kinetic model fitting for safinamide adsorption onto (a) zeolite and (b) zeolite/MOF; kinetic model fitting for Cd2+ adsorption onto (c) zeolite and (d) zeolite/MOF.
Figure 8. Kinetic model fitting for safinamide adsorption onto (a) zeolite and (b) zeolite/MOF; kinetic model fitting for Cd2+ adsorption onto (c) zeolite and (d) zeolite/MOF.
Colloids 08 00050 g008
Figure 9. (a) Desorption of safinamide using different eluents, (b) reuse of Co/Ni/Cu-NH2BDC MOF/zeolite nanocomposite, and (c) XRD diffractograms of zeolite/MOF adsorbent before and after recycling.
Figure 9. (a) Desorption of safinamide using different eluents, (b) reuse of Co/Ni/Cu-NH2BDC MOF/zeolite nanocomposite, and (c) XRD diffractograms of zeolite/MOF adsorbent before and after recycling.
Colloids 08 00050 g009aColloids 08 00050 g009b
Figure 10. Removal percentage of zeolite/MOF for safinamide in the presence of different competing adsorbates (a) with different initial concentrations and (b) at 100 mg/L initial concentration.
Figure 10. Removal percentage of zeolite/MOF for safinamide in the presence of different competing adsorbates (a) with different initial concentrations and (b) at 100 mg/L initial concentration.
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Figure 11. The study of variations in Kd with temperature enables us to estimate the thermodynamic parameters.
Figure 11. The study of variations in Kd with temperature enables us to estimate the thermodynamic parameters.
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Figure 12. Possible adsorption mechanism of safinamide onto (a) zeolite and (b) zeolite/MOF and Possible adsorption mechanism of Cd onto (c) zeolite and (d) zeolite/MOF.
Figure 12. Possible adsorption mechanism of safinamide onto (a) zeolite and (b) zeolite/MOF and Possible adsorption mechanism of Cd onto (c) zeolite and (d) zeolite/MOF.
Colloids 08 00050 g012aColloids 08 00050 g012b
Figure 13. Cell viability (%) of zeolite and zeolite/MOF at different concentrations after (a) 24 h and (b) 48 h (n = 3) ± SD.
Figure 13. Cell viability (%) of zeolite and zeolite/MOF at different concentrations after (a) 24 h and (b) 48 h (n = 3) ± SD.
Colloids 08 00050 g013
Table 1. Studies reporting the adsorption of Cd2+ on zeolite- and MOF-based adsorbents compared to the current study.
Table 1. Studies reporting the adsorption of Cd2+ on zeolite- and MOF-based adsorbents compared to the current study.
AdsorbentpHEquilibrium Time (min)Adsorbent DoseRemoval Percent (%)qmax (mg/g)Reference
TMU-5 metal organic framework7-15 mg/L-1929[28]
MoS4-Cu-BTC-30--833.3[29]
CaFu-MOF7350--781.2[29]
Fe3O4@UiO-66–NH26300--714.3[30]
MIL-53(Fe)-1-50--714.28[31]
Amino-decorated magnetic metal-organic framework7200.05 g-693[31]
silica-coated metal organic framework6-15 mg/L-634[28]
Co/Ni/Cu-NH2BDC MOF/natural Zeolite ore925 550.69This work
PAN/chitosan/UiO-66-NH2 nanofibers-90--415.6[29]
UiO-66@mSi-SO3H7 100 mg/L-410[28]
Fe3O4@ZIF-86300--370[30]
Corn Silk/Corn Silk/Zeolite-Y570.009 g-315.27[32]
zeolitic imidazolate framework-8724020 mg80312.5[33]
Bimetallic Ag–Fe MOF7120--265[34]
zeolitic imidazolate framework-871520 mg40263.16[33]
Cu-MOF-600.5 g98.62219.05[35]
magnetic zeolite5240--204.2[36]
UiO-66 MOF modified with Melamine5501 g/L84146.6[37]
TMU-16-NH2 MOF6300.05 g98.91126.6[38]
zeolite NaX51202 g/L>90%100.11[39]
Zeolite from oil shale ash----95.6[40]
SO3H Functionalized Cu3(BTC)2 MOF6101 mg/mL9988.7[41]
natural clinoptilolite zeolite decorated by Fe3O4 nanoparticles6601 g/L68.919.9[42]
Na- and Fe-modified zeolitic tuffs6420--18[43]
Iranian natural zeolite314401 g>90%4[44]
Table 2. Specific surface, pore volume, and average pore size of zeolite and zeolite/MOF samples.
Table 2. Specific surface, pore volume, and average pore size of zeolite and zeolite/MOF samples.
NanomaterialSurface Area (m2/g)Pore Volume (cm3 g−1)Pore Size (nm)
zeolite24.630.09114.7
zeolite/MOF41.860.17316.5
Table 3. Adsorption isotherm fitting parameters for safinamide adsorption onto zeolite and zeolite/MOF.
Table 3. Adsorption isotherm fitting parameters for safinamide adsorption onto zeolite and zeolite/MOF.
Isotherm ModelsParameterValue
ZeoliteZeolite/MOF
LangmuirQmax (mg/g)88.91500.69
KL (L/mg)0.0030.00042
R20.9980.999
Freundlich1/n0.790.79
KF0.520.52
R20.9940.992
Redlich–PetersonKR0.750.3
aR0.0070.0017
R20.8870.985
TemkinAT (L/mg)2.6123301.612330
bT390.6960600.6960
R20.7150.858
Sipsqm (mg/g)64.0323.76
Ks0.0060.01
1/n1.011.24
R20.9780.928
Langmuir–FreundlichqMLF (mg/g)62.1919.32
KLF (L/mg)0.00630.027
MLF1.136
R20.9990.956
TothKe0.50.55
KL0.000010.007
N2.31.2
R20.9990.899
KahnQm (mg/g)34.3231.11
bK0.0060.006
aK0.320.18
R20.9860.985
Fritz–SchlunderqmFSS (mg/g)19.1755.19
K10.670.04
K23.290.79
m10.470.58
m20.000060
R20.9360.952
Table 4. Adsorption isotherm fitting parameters for Cd (II) adsorption onto zeolite and zeolite/MOF.
Table 4. Adsorption isotherm fitting parameters for Cd (II) adsorption onto zeolite and zeolite/MOF.
Isotherm ModelsParameterValue
ZeoliteZeolite/MOF
LangmuirQmax (mg/g)500.69550.69
KL (L/mg)0.00210.0021
R20.9700.962
Freundlich1/n0.671.49
KF1.430.71
R20.9870.923
TemkinAT (L/mg)1.151.05
bT4.314.15
R20.9810.646
Redlich–PetersonKR0.911.18
aR0.000010.0000001
R20.8220.847
Langmuir–FreundlichqMLF (mg/g)5.5234.47
KLF (L/mg)0.390.089
MLF 1.091.61
R20.9990.922
Sipsqm (mg/g)5.5242.5
Ks0.370.02
1/n1.091.6
R20.9990.923
TothKe2.228.5
KL0.170.00012
N1.37.3
R20.9990.852
KahnQm (mg/g)180.179.1
bK0.0060.014
aK0.290
R20.9860.875
Fritz–SchlunderqmFSS (mg/g)13.99.84
K10.110.077
K20.0680.068
m10.671.49
m200.930
R20.9870.923
Table 5. Summary of the determined error functions for the non-linear adsorption isotherm models for safinamide adsorption onto zeolite.
Table 5. Summary of the determined error functions for the non-linear adsorption isotherm models for safinamide adsorption onto zeolite.
FunctionLangFranLan-FruTothSipsBaudu
SSE/ERRSQ10.7985811.142415.765542.2801822428.948120.6874
X20.7299082.3944971.411190.11622572.102615.226423
R20.9961880.9955540.9937090.9991950.0307060.9574
Adjusted R20.9898550.9875780.9780490.997426−0.748350.83323
MAE0.8103961.0198740.8706450.38020712.640432.652084
MAPE/ARE15.8014952.8314511.6765.25855848.5649530.09969
RMSE1.0953731.180171.4038140.50334217.424653.661927
RMSE_21.2420361.3627421.7756990.61646622.040644.912991
NRMSE 0.078720.1073680.1277150.0361731.5852450.263167
HYBRID20.316270.4419418.68167.88783677.7039354.17944
HYBRID_210.4272539.9082828.223811.9370821442.052104.5285
HYBRID_30.7299082.3944971.411190.11622572.102615.226423
MPSD25.1081795.3788721.695838.62227170.9715649.45509
MPSD_20.4412945.4582770.2353550.0446062.5184811.222903
SAE/EABS7.2935668.158996.9651583.421867101.123523.86876
RMS22.1433382.6005217.152067.04005556.1079536.86164
NSD0.2214330.8260050.1715210.0704010.5610790.368616
ARE_24.90326968.228472.9419330.49562431.4810213.58781
ARE_37.38110929.20376.064172.34668519.8371612.28721
Table 6. Summary of the determined error functions for the non-linear adsorption isotherm models for safinamide adsorption onto zeolite/MOF.
Table 6. Summary of the determined error functions for the non-linear adsorption isotherm models for safinamide adsorption onto zeolite/MOF.
FunctionLangFranLan-FruSipsKhanBauduToth
SSE/ERRSQ0.0731155.5449450.0236270.0285910.009390.0021550.003454
X20.0080051.6407730.0210210.0240260.4700370.0027220.000346
R20.999910.9931750.9999710.9999650.9876790.9999970.999996
Adjusted R20.999730.9795940.9998840.9998590.951020.9999840.999983
MAE0.0738330.6775430.0490580.0526340.7929770.0143020.015911
MAPE/ARE2.48536492.3073111.5409712.323774.1188344.1643610.838876
RMSE0.1022010.890020.0580970.0639081.1957890.0175450.022214
RMSE_20.1209261.0530850.0768560.0845421.5818810.0268010.029387
NRMSE0.0192670.1677840.0109520.0120480.2254270.0033080.004188
HYBRID3.47951129.230220.196721.56667.2079599.7168421.468033
HYBRID_20.16010432.815470.5255210.60065111.750920.0907310.00864
HYBRID_30.0080051.6407730.0210210.0240260.4700370.0027220.000346
MPSD3.606687158.674822.7780324.335867.5711639.5130391.482882
MPSD_20.00650412.588850.2075350.2368940.0229290.0271490.00088
SAE/EABS0.5168314.7428020.3434040.3684415.5508360.1001140.111375
RMS3.048207134.104717.2185718.396185.7232616.2277461.120953
NSD0.0304821.3410470.1721860.1839620.0572330.0622770.01121
ARE_20.092916179.84072.9647913.3841940.3275570.3878480.012565
ARE_31.15211450.686816.5080076.9531022.1631892.3538670.42368
Table 7. Summary of the determined error functions for the non-linear adsorption isotherm models for the adsorption of Cd2+ onto zeolite.
Table 7. Summary of the determined error functions for the non-linear adsorption isotherm models for the adsorption of Cd2+ onto zeolite.
FunctionLangFranLan-fruSipsKhanBauduToth
SSE/ERRSQ0.6310320.0667190.0053730.0053730.0236020.0077030.004007
X20.4019960.0532060.0028270.0028260.0216680.0045080.002607
R20.9444720.9941290.9995270.9995270.9979230.9993220.999647
Adjusted R20.7840550.9765850.9962190.9962190.9834030.9945790.99718
MAE0.3458940.104860.0267540.0267360.056760.032040.023335
MAPE/ARE25.072768.7658161.5608581.558935.4917932.27931.605197
RMSE0.3552560.1155160.0327810.0327810.0687040.039250.028308
RMSE_20.4586330.149130.0518310.0518310.1086310.062060.044759
NRMSE 0.5121450.166530.0472580.0472580.0990460.0565840.04081
HYBRID41.7879314.609693.9021463.89732613.729485.6982514.012993
HYBRID_213.399871.7735320.1413740.1413241.0834190.2254140.130363
HYBRID_30.4019960.0532060.0028270.0028260.0216680.0045080.002607
MPSD35.2101415.383482.905132.90367411.7424.6054243.155022
MPSD_20.3719260.0709950.0016880.0016860.0275750.0042420.001991
SAE/EABS1.729470.5243010.1337720.1336780.2837990.1602010.116673
RMS27.2736611.9161.8373661.8364457.4262922.9127261.995411
NSD0.2727370.119160.0183740.0183640.0742630.0291270.019954
ARE_27.4385251.4199090.0337590.0337250.5514980.084840.039817
ARE_312.197155.3289950.8216950.8212833.3211391.3026110.892375
Table 8. Summary of the determined error functions for the non-linear adsorption isotherm models for the adsorption of Cd2+ onto zeolite/MOF.
Table 8. Summary of the determined error functions for the non-linear adsorption isotherm models for the adsorption of Cd2+ onto zeolite/MOF.
FunctionLangFranLan-FruSipsBaudu
SSE/ERRSQ0.7482480.45510.4582080.4576220.455174
X20.689220.5062780.5221220.5191050.506484
R20.9374090.9619310.9616710.961720.961925
Adjusted R20.7574720.8506230.6992450.6996220.701197
MAE0.3696430.2664390.2633530.264110.266297
MAPE/ARE33.0539527.5841727.5768927.5968427.57782
RMSE0.3868460.3016950.3027240.302530.30172
RMSE_20.4994160.3894870.4786480.4783420.477061
NRMSE0.5637510.4396610.4411590.4408770.439696
HYBRID55.0899245.9736268.9422268.9920968.94454
HYBRID_222.9740116.8759226.1060825.9552725.32418
HYBRID_30.689220.5062780.5221220.5191050.506484
MPSD52.0110350.4549463.2096762.9360861.81552
MPSD_20.8115440.763710.7990920.792190.764232
SAE/EABS1.8482131.3321951.3167631.3205491.331485
RMS40.2875739.0822339.977339.8042739.09557
NSD0.4028760.3908220.3997730.3980430.390956
ARE_216.2308915.2742115.9818515.843815.28464
ARE_318.0171517.4781117.8783917.8010117.48407
Table 9. The parameters of kinetic models for the adsorption of safinamide onto zeolite and zeolite/MOF.
Table 9. The parameters of kinetic models for the adsorption of safinamide onto zeolite and zeolite/MOF.
ModelParametersValues
ZeoliteZeolite/MOF
Pseudo first-orderK1 (min−1)0.028.06589 × 108
qe (mg/g)0.290.82
Adjusted R20.760.74
Reduced chi-square 0.0020.02
R20.780.77
Pseudo second-orderK2 (g/(mg min))0.14.48995 × 1044
qe (mg/g)0.320.82
Adjusted R20.820.75
Reduced chi-square 0.0010.022
R20.840.77
Intraparticle
diffusion
Kip0.060.013
Cip0.0170.0011
R20.9830.994
Reduced chi-square 0.0010.01
Adjusted R20.9810.993
Mixed first- and
second-order
K (g/(mg min))0.00480.25
qe (mg/g)0.390.89
f20.0980.03
R20.9670.950
Reduced chi-square0.0030.099
Adjusted R2 0.9580.942
Avrami modelKav (min−1)0.0120.23
nav1.430.23
qe (mg/g)0.290.88
R20.7690.949
Reduced chi-square 0.0050.03
Adjusted R20.7430.941
Table 10. The parameters of kinetic models for the adsorption of Cd onto zeolite and zeolite/MOF.
Table 10. The parameters of kinetic models for the adsorption of Cd onto zeolite and zeolite/MOF.
ModelParametersValues
ZeoliteZeolite/MOF
Pseudo first-orderK1 (min−1)0.28 ± 0.052.23 ± 0.07
qe (mg/g)3.841.04 × 1011
Adjusted R20.970.95
Reduced chi-square0.060.034
R20.970.96
Pseudo second-orderK2 (g/(mg min))0.140.304 ± 0.04
qe (mg/g)4.042.4 ± 0.03
Adjusted R20.9930.99
Reduced chi-square0.0120.0024
R20.9940.99
Intraparticle
diffusion
Kip3.130.013
Cip0.080.001
R20.9920.994
Reduced chi-square0.0090.01
Adjusted R20.9900.993
Mixed first- and
second-order
K (g/(mg min))0.00480.33
qe (mg/g)0.392.31
f20.0980.0064
R20.9670.982
Reduced chi-square0.00010.00006
Adjusted R20.9600.979
Avrami modelKav (min−1)0.0120.29
nav1.431.16
qe (mg/g)0.292.31
R20.7690.975
Reduced chi-square0.00050.0003
Adjusted R20.7220.971
Table 11. Thermodynamic parameters for the Cd2+ adsorption process.
Table 11. Thermodynamic parameters for the Cd2+ adsorption process.
DrugT (K)%RΔG°
(KJ/mol)
ΔH°
(KJ/mol)
ΔS°
(J/mol K)
Safinamide29899−13.1021−118.973−365.7329
30880−5.32485
31856−2.47018
32854−2.32746
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Abdelazeem, R.; Younes, H.A.; Eldin, Z.E.; Allam, A.A.; Rudayni, H.A.; Othman, S.I.; Farghali, A.A.; Mahmoud, H.M.; Mahmoud, R. A Selective, Efficient, Facile, and Reusable Natural Clay/Metal Organic Framework as a Promising Adsorbent for the Removal of Drug Residue and Heavy Metal Ions. Colloids Interfaces 2024, 8, 50. https://doi.org/10.3390/colloids8050050

AMA Style

Abdelazeem R, Younes HA, Eldin ZE, Allam AA, Rudayni HA, Othman SI, Farghali AA, Mahmoud HM, Mahmoud R. A Selective, Efficient, Facile, and Reusable Natural Clay/Metal Organic Framework as a Promising Adsorbent for the Removal of Drug Residue and Heavy Metal Ions. Colloids and Interfaces. 2024; 8(5):50. https://doi.org/10.3390/colloids8050050

Chicago/Turabian Style

Abdelazeem, Rania, Heba A. Younes, Zienab E. Eldin, Ahmed A. Allam, Hassan Ahmed Rudayni, Sarah I. Othman, Ahmed A. Farghali, Hamada M. Mahmoud, and Rehab Mahmoud. 2024. "A Selective, Efficient, Facile, and Reusable Natural Clay/Metal Organic Framework as a Promising Adsorbent for the Removal of Drug Residue and Heavy Metal Ions" Colloids and Interfaces 8, no. 5: 50. https://doi.org/10.3390/colloids8050050

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