3.1. Characterisation Analysis
The zinc-imprinted polymer (ZnIP) was prepared in three stages. The first stage is the synthesis of a pre–polymerization complex consisting of a polymer (humic acid, HA) and a template molecule (Zn(CH
3COO)
2) under the influence of ultrasound (US). The second stage – a functional monomer (methacrylic acid, MAA), a crosslinking agent (ethylene glycol dimethacrylate, EGDMA) and an initiator (benzoyl peroxide, BP) were added to the pre-polymerization complex. The mixture was subjected to heat treatment at 60°C for 180 minutes. The third stage is the removal of the template molecule from the polymer mesh by acid hydrolysis. An unprinted reference polymer (NIP) was synthesized under similar conditions without the participation of a template molecule.
Table 1 shows the initial components used for the synthesis of ZnIP and NIP.
The results of chemical studies of synthesized ZnIP and NIP are confirmed by data from elemental analysis, IR spectroscopy, X-Ray phase analysis, conductometry and electron microscope. The physico-chemical characteristics of ZnIP and NIP are given in
Table 2.
The results of the elemental analysis (
Table 2) showed a decrease in the oxygen content of ZnIP by 4.12% compared to NIP. This indicates the interaction of Zn
2+ ions with the carboxyl and hydroxyl groups of the polymer, which leads to a decrease in their number in the ZnIP structure. A decrease in the content of oxygen-containing groups in ZnIP also confirms the possibility of binding of these groups to Zn
2+ ions by the mechanism of complexation. The values of the Σ(COOH+OH) content in ZnIP are 4.43 mg-eq/g, and in NIP – 4.95 mg-eq/g. This may indicate that some of the Zn
2+ ions were used to bind to oxygen-containing functional groups of the polymer, which confirms the effectiveness of imprinting. The ZnIP yield is 76.54% and the NIP yield is 77.98%. These values are quite close, which indicates that the imprinting process does not significantly affect the overall yield of the polymer, despite changes in its composition and structure. Thus, the results of the elemental analysis confirm that ZnIP binds Zn
2+ ions to the functional groups of the polymer, which may be important for its applications as a molecular imprint.
IR spectroscopy methods were used to determine the structural characteristics of ZnIP and NIP (
Figure 1).
It was found that the IR spectra obtained by ZnIP and NIP were very similar, since these samples were synthesized using the same methodology and initial reagents. The images of the ZnIP and NIP samples showed peaks in the region of 1010-1139 cm-1, which correspond to the stretching of the C–O bonds of carbohydrates, alcohol and ether groups, indicating the presence of these functional groups in the ZnIP and NIP polymers. Bands with a maximum at 913 cm-1 are associated with the presence of substituted aromatic structures. The changes in the 1385 cm-1 region can be explained by destructive processes that affect the structure of both ZnIP and NIP polymers, leading to a reduction in the length of the aliphatic chain and an increase in the number of annular –CH3 groups. The appearance of a band in the 1600-1650 cm-1 region in both ZnIP and NIP is associated with fluctuations in the C=C double bond of methacrylic acid. The presence of an absorption band in the region of 1700-1720 cm-1 is associated with the stretching of C=O in carboxyl groups. Their presence in the IR spectrum of NIP, but their absence in the spectrum of ZnIP, indicates that a coordination complex is formed in ZnIP, which may make it difficult to detect carboxyl groups. The stretching of peaks in the range of 3200-3560 cm-1, characteristic of hydroxyl groups, may indicate a possible binding of zinc ions in the ZnIP sample by the mechanisms of ion exchange and complexation. Distinct peaks in the 450 and 612 cm-1 regions represent Zn–O bonds.
The surface morphology of ZnIP and NIP was studied using a scanning electron microscope (SEM) (
Figure 2 and
Figure 3).
Micrographs of the ZnIP sample surface show a more porous structure with globular aggregates 125-235 nm thick. These globular aggregates form a porous network, which is characteristic of ZnIP after the removal of Zn2+ ions.
Removal of Zn
2+ ions. From the polymer network, ZnIP creates accessible active sites that can specifically interact with Zn
2+ ions. during the adsorption process. The presence of these accessible sites is clearly demonstrated in raster microscopic images (
Figure 2). As can be seen from the figure, ZnIP samples have a unique structure, which is characterized by spherical cavities. This is due to the fact that imprinting of Zn
2+ ions. In the polymer network, ZnIP creates special "targets" for Zn
2+ ions, which improves their capture rate compared to the fingerprint-free polymer (NIP), which does not have such a specific structural organization.
ZnIP, due to its structure with imprints of Zn2+ ions, has a large number of available active sites, which accelerates the adsorption process and improves interaction with Zn2+ ions. An analysis of the elemental composition and a multilayer EDS map confirm the absence of Zn2+ ions in the resulting product after acid hydrolysis (ZnIP).
A smoother and more uneven surface without visible aggregated inclusions is observed on the scanned surface of the NIP sample (
Figure 3). The results of the analysis of the elemental composition and the multilayer EDS map confirm the characteristics of NIP, demonstrating the absence of specific structural changes characteristic of ZnIP.
3.2. Adsorption Study
Figure 4 shows the time dependences of the degree of sorption of Zn
2+ ions calculated by equation (5).
If we assume that the number of ligands in the ZnIP structure significantly exceeds the initial concentration of Zn2+ ions, then the law of effective masses for the sorption process can switch to a pseudo-order relative to the metal cation.
To determine the pseudo-order, a graphical method was chosen using kinetic equations for reactions of integer order – the first (10), second (11) and third (12):
where: k
i is the rate constant of the i
th order of reaction; t is the reaction time (min).
Based on experimental data, the parameters of three types of linear dependencies were calculated and correlation coefficients were determined (
Table 3).
Higher correlation coefficients were noted when describing experimental data using the kinetic equation of the pseudo-first order reaction. Thus, the first order for ZnIP demonstrates high accuracy, with a correlation coefficient of r=0.9973, for NIP a correlation coefficient of r=0.9970. This confirms that the adsorption reaction for both ZnIP and NIP is best described in the first order. The rate constant for ZnIP (k1=0.0118) is higher than for NIP k1=0.0079, which indicates a higher rate of adsorption of Zn2+ ions for ZnIP. This may indicate that ZnIP has more accessible active sites than NIP.
Thus, the first order is the most accurate model for describing the adsorption kinetics for both ZnIP and NIP. The adsorption rate for ZnIP is significantly higher in all orders of magnitude, which is confirmed by the large values of the rate constants. Second- and third-order models can be used, but they exhibit lower accuracy.
As is known, the quantitative characteristic of sorption is Gibbs specific excess sorption, calculated by equation (1). We experimentally determined the sorption isotherms for Zn
2+ ions at a temperature of 298.0 K. The results are shown in
Figure 5.
According to the obtained equations, the calculated concentrations of the initial molar ion concentrations (C0i) for the pseudo-first-order model are close to experimental ones.
When analyzing sorption properties, not only the percentage of extraction was considered, but also the distribution coefficients and the imprinting factor. The distribution coefficients (D) and the imprinting factor (IF), calculated according to equations (3) and (4), respectively, are presented in
Table 4.
Table 4 shows that the extraction degrees and the values of the distribution coefficients for ZnIP are higher compared to NIP. ZnIP has been found to have a better adsorption capacity than NIP.
The adsorption of Zn2+ ions from aqueous solutions was studied in the pH range 3.0-9.0. The nature of the pH dependence indicates that the Zn2+ ions are extracted by both ZnIP and NIP.
The maximum degree of extraction is observed in the pH range 5.0 at which the imprinting process takes place. Sorption decreases with increasing pH.
The correspondence of the experimental data to the Langmuir and Freundlich equations is proved on the basis of their linear forms by plotting graphs in the appropriate coordinates – if the points fit on a straight line, then this serves as a criterion for the possibility of using these equations to describe sorption isotherms.
Figure 7 shows the experimental data in the coordinates of the linear form of the Freundlich equation.
Based on the determination of linear regression coefficients, the parameters of the Freundlich equations for ZnIP and NIP were calculated (
Table 5).
Expressions (13) and (14) represent the processing of an array of experimental points according to the linear regression equation for Zn
2+ ions of ZnIP and NIP samples, respectively:
Figure 8 shows the experimental data in the coordinates of the linear form of the Langmuir monomolecular adsorption equation.
Based on the determination of linear regression coefficients, the parameters of the equations were calculated – ion sorption constants and their maximum sorption per unit mass of ZnIP and NIP (
Table 6).
Expressions (15) and (16) represent the processing of an array of experimental points according to the linear regression equation for Zn
2+ ions of ZnIP and NIP samples, respectively:
The high correlation coefficients for equations (15) and (16) allow us to assert that the model Langmuir monomolecular adsorption equation adequately describes the isotherms of sorption of Zn2+ ions in the entire range of concentrations studied. The ZnIP sample shows a higher maximum adsorption – 2.1262 mmol/g, compared to NIP – 1.6269 mmol/g and a significantly higher adsorption equilibrium constant of 0.6177 l/mmol for ZnIP and 0.2471 l/mmol for NIP. The correlation coefficients for the ZnIP (r=0.9985) and NIP (r=0.9837) samples indicate that the Langmuir model describes adsorption on the ZnIP sample almost perfectly and well on the NIP.
The Freundlich constant (KFr=1.1832) for ZnIP shows a slightly lower adsorbent capacity compared to NIP (KFr=2.0526). However, the correlation coefficient in the Freundlich equation for the ZnIP sample (r=0.9125) indicates a higher, but not ideal, accuracy of data description by the Freundlich model compared to the Langmuir model compared to NIP (r=0.8670).
The difference between the Langmuir and Freundlich models can be explained as follows. The Langmuir model assumes that adsorption occurs on a homogeneous surface with a fixed number of adsorption centers and the formation of an adsorbate monolayer. The high correlation coefficients r for both ZnIP and NIP indicate that the adsorption on these samples corresponds well to the assumptions of the Langmuir model. This means that the adsorption is most likely limited to a single layer, and the surface of the adsorbent is homogeneous. The Freundlich model describes adsorption on heterogeneous surfaces and takes into account the possibility of multilayer adsorption. However, lower r values for this model compared to the Langmuir model indicate that the assumptions of the Freundlich model correspond less accurately to the actual adsorption process on these samples. This may mean that multilayer adsorption or strong surface heterogeneity are not the dominant factors in this case.
Thus, ZnIP demonstrates better adsorption capacity and is better described by the Langmuir model, which is confirmed by a high r value. This may indicate that adsorption on this sample occurs predominantly in a single layer and on a homogeneous surface. However, Langmuir's model emphasizes that ZnIP is particularly effective at low concentrations of adsorbate, due to its high constant and maximum adsorption. NIP is also well described by the Langmuir model, although its adsorption capacity is somewhat lower. The Freundlich model describes adsorption on this sample with less accuracy, which may be due to the fact that adsorption on this sample is closer to monolayer. The differences in the correlation coefficients between the Langmuir and Freundlich models are due to the fact that the Langmuir model better corresponds to the physical nature of adsorption on these samples, assuming monolayer adsorption on homogeneous surfaces.