Computer-Aided design for the preparation of magnetic molecularly imprinted polymers for recognition of ethyl carbamate

doi:10.21203/rs.3.rs-2998534/v1

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Computer-Aided design for the preparation of magnetic molecularly imprinted polymers for recognition of ethyl carbamate

https://doi.org/10.21203/rs.3.rs-2998534/v1

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In this study, computer-aided design of molecularly imprinted systems was carried out using the quantum chemistry software Gaussian. Based on density functional theory (DFT), the interaction energies of the template-monomer complexes were calculated under the B3LYP, 6-31G+(d,p) basis set, and the reaction sites and Imprinting ratio were predicted based on the electrostatic potential map and NBO charge transfer. The urethane magnetic molecularly imprinted polymers (EC-MMIPs) were successfully prepared using surface molecular imprinting technique with Fe3O4 as the magnetic carrier. The polymers were characterized by scanning electron microscopy, Fourier transform infrared, X-ray diffraction, vibrating sample magnetometry and thermogravimetric analysis. The results of isothermal adsorption and dynamic adsorption experiments showed that the EC-MMIPs had good adsorption performance, reaching the maximum adsorption amount (18.53 µg/mg) within 40 min. In competitive adsorption experiments, the speckle coefficient was 2.3. In addition, EC-MMIPs showed good adsorption efficiency even after five uses.

magnetic molecularly imprinted polymers

ethyl carbamate

computer simulation

density functional theory

Ethyl carbamate, also known as urethane, is usually a white crystal or powder. In the last century, ethyl carbamate has been used as a synthetic raw material for drugs ¹ and has been clinically used as an anesthetic, as well as in the treatment of tumors leukemia, and multiple myeloma. ^2–5 However, as early as 1943, it was confirmed that ethyl carbamate could induce lung tumors in mice, which proved its potential carcinogenicity ⁶. Since then, numerous experiments have successively revealed the harm of ethyl carbamate. It has been reported that exposure to multiple doses of ethyl carbamate in rodents can inhibit their humoral immunity ⁷ and induce a variety of tumors in the animals' livers, lungs, thymus, mammary glands, and skin. Therefore, ethyl carbamate is considered a "multipotent" carcinogen ⁸, and studies have shown that ethyl carbamate can directly cause human liver cancer ⁹. In 1974, the International Agency for Research on Cancer (IARC) officially listed EC as a Class 2B carcinogen (possible carcinogen for humans), and it was further upgraded to a Class 2A carcinogen in 2007 ¹⁰. In 1976, it was proven that ethyl carbamate was a chemical produced in the fermentation process of various alcoholic beverages and foods¹¹. Due to the widespread existence and harmfulness of ethyl carbamate, its relative molecular weight is small, its molecular structure characteristics are not obvious, and its enrichment and removal are relatively difficult. Therefore, effective methods are needed to enrich or reduce ethyl carbamate in food.

Molecular imprinting technology (MIT) is a promising high-efficiency separation technology, that is widely used in the environment, food, health, as well as other fields of toxic and harmful pollutant treatment, pesticide removal, and so on. A molecularly imprinted polymer (MIPs) with a specific cavity structure developed based on the "antigen-antibody" and "key and lock" hypotheses can have specific recognition for a predetermined template molecule ¹². Template molecules and appropriate functional monomers were pre-polymerized in a pore-forming agent, and crosslinkers and initiators were added. Under external factors such as light, electricity, heat, and ultraviolet light, template molecules, functional monomers, and crosslinking agents were copolymerize ¹³. After polymerization, template molecules were removed, leaving binding sites with complementary shapes, sizes, and functions with target analytes ¹⁴. The prepared polymers can enrich template molecules in complex substrates, and are widely used in many fields such as solid-phase extraction, solid-phase microextraction, chromatography, and sensors ¹⁵.

However, traditional molecularly imprinted polymer template molecules are difficult to remove cleanly, have a low adsorption capacity, and have low mass transfer rate ^{16, 17}, and MIPs used for solid-phase extraction need to be centrifugation, which has disadvantages such as incomplete separation and difficult recovery. However, magnetic surface molecularly imprinted polymers (MMIPs) prepared by using Fe₃O₄ as a magnetic core overcome the disadvantages of traditional MIPs and can be separated quickly and easily under the action of a magnetic field only ¹⁸. Nowadays, MMIPs have been widely used to extract natural products from complex matrices, such as bovine hemoglobin, antibiotics, etc ^19–21.

In addition, the design of MIPs with excellent adsorption performance mostly relies on experiments, including the selection of templates, the screening of functional monomers, and the ratio between templates and monomers, but the wide variety of functional monomers available makes the design and development of MIPs relatively time consuming and wasteful of experimental reagents ^{22, 23}. With the development of computer simulation technology, computational chemistry-assisted research is a rational and rapid method to find the optimal conditions for the preparation of MIPs, and computer simulations play an important role in determining the best functional monomers, optimizing the synthesis conditions, and elucidating the molecular imprinting recognition mechanism ²⁴.

In this study, computer simulation technology was used to design imprinted polymers based on density functional theory (DFT) to screen the optimal functional monomer and imprinted ratio, and the template-monomer complex model was constructed through computer simulation. Then used ethyl carbamate (EC) as a template molecule and Fe₃O₄ as the magnetic carrier, magnetic molecularly imprinted polymers (EC-MMIPs) of ethyl carbamate (EC) were prepared by a surface molecular imprinting technique, and the adsorption properties were studied and analyzed.

2.1 Materials

All commercial reagents were analytical grade. Deionized water was used in this study. FeCl₃·6H₂O, FeCl₂·4H₂O, tetraethyl orthosilicate (TEOS, 98%), methanol (MeOH, 99.5%), methacrylic acid (MAA, 99%), azoisobutyronitrile (AIBN,99%), 3-(Trimethoxysilyl) propyl methacrylate (MPS, 97%), ethyl carbamate (EC, 98%), methyl carbamate (MC) butyl carbamate (BC), ethylene dimethacrylate (EGDMA, 98%) and ethyl acetate were purchased from Aladdin Industrial Co. (Shanghai, China). NH₃H₂O (25%) was obtained from Tianjin Fengchuan Chemical Reagent Technology Co. Ltd. Toluene was obtained from Sichuan Xilong Science Co.,Ltd. Rice wine were purchased from the local supermarket.

2.2 Characterization

Scanning electron microscopy (SEM, gemin-300, Zeiss, Germany) was used to measure the morphologies of nanoparticles. Fourier transform infrared spectra (FT-IR) were performed on the Tensor-27 spectrometer (Bruker, USA). X-ray diffraction (XRD) patterns were characterized by Ultima Ⅳ (Rigaku, Japan). The magnetic properties were measured using a vibrating sample magnetometer (VSM, MPMS-3, Quantum Design, USA). Thermal Gravity Analysis (TGA) was performed from room temperature to 800 ℃ with a heating rate of 20 ℃ /min under a nitrogen atmosphere by the Q5000IR (TA, USA).

2.3 Selection of functional monomer

In this study, Gaussian 09 and GaussView were used for computer simulation. The basis set was 6–31 + G(d,p) and the density functional theory (DFT) and B3YLP functional were used for calculation. Firstly, the structure optimization and energy calculation of template molecules and four common functional monomers (acrylamide (AM), methacrylic acid (MAA), 4-vinyl pyridines (4-VP), and hydroxyethyl methacrylate (HEMA)) were carried out by this method, their structures are shown in Fig. 1. Then the binding energy (ΔE) of the template molecules and each monomer was calculated. The equilibrium method was adopted to eliminate the base-set superposition error (BSSE) proposed by Boys et al ²⁵, and the minimum binding energy ΔE was the best. The binding energy of the template-monomer complex ΔE is calculated as follows:

$$\varDelta \text{E}= {\text{E}}_{\text{c}\text{o}\text{m}\text{p}\text{l}\text{e}\text{x}}-{\text{E}}_{\text{t}\text{e}\text{m}\text{p}\text{l}\text{a}\text{t}\text{e}}-\text{n}{\text{E}}_{\text{m}\text{o}\text{n}\text{o}\text{m}\text{e}\text{r}}+{\text{E}}_{\text{B}\text{S}\text{S}\text{E}}$$

where ΔE is the total energy of the template–monomer complex, and E_template and E_monomer are the single point energies of the template and the corresponding monomer, respectively, n is the ratio of monomer to ethyl carbamate.

2.4 Action reaction site analysis

The polymerization process of non-covalent molecular imprinting relies primarily the interaction of hydrogen bonds, ionic bonds (electrostatic interaction), π-π interaction, and hydrophobic effect to a form template-functional monomer complex. The imprinting sites can be predicted by natural layout analysis and electrostatic potential diagrams of molecules. The natural bond orbital theory (NBO) can analyze the number of atoms in molecules, the structure of molecules, and the intramolecular and intermolecular hyperconjugated interactions. The NPA charge transfer between template molecules and function-al monomers can be judged by the calculation and analysis of natural bond orbit theory (i.e., NPA charge), and the site of action and force can be predicted ²⁴. Electrostatic potential (ESP) is mapped to the isosurface with an electron density of 0.001 to obtain the color filling diagram of the electrostatic potential on the molecular surface²⁶, which can directly reflect the active sites of molecules and provide a reference for the identification of host and guest molecules.

2.5 Scale analysis of template – monomer

Different imprinting ratios have a great influence on the specific recognition performance of the complex, and the appropriate molar ratio of the template molecule to functional monomer can make the imprinting polymer have better recognition performance. Possible hydrogen bonds were formed according to the hydrogen reaction sites, and the complex configurations formed by EC and MAA at different imprinting ratios were constructed and optimized. The binding energy was calculated, and the minimum was the best.

2.6 Synthesis of adsorbent materials

Synthesis of magnetic Fe₃O₄ particles. Magnetic Fe₃O₄ particles were synthesized by coprecipitation ²⁷. Briefly, in a three-neck beaker 3.01 g of FeCl₃·6H₂O and 1.10 g of FeCl₂·4H₂O were dissolved in 100 mL of deionized water. The mixture was heated to 60 ℃ and 10 mL of 25% ammonia were added with vigorous agitation. After 30 min at 60 ℃, the temperature was raised to 80 ℃ and remained for 30 min, this work was completed under a nitrogen atmosphere. The products were collected by an external magnetic field and washed five times. Finally the products were freeze-dried for 12 hours.

Synthesis of Fe₃O₄@SiO₂ particles. Fe₃O₄ nanoparticles (500 mg) were dispersed into 100 mL of ethanol/water (4:1, v/v) under ultrasonication for 15 min. Then, 10 mL of 25% ammonia and 5 mL of TEOS were added sequentially. The solution was stirred for 12 hours at 40 ℃. The Fe₃O₄@SiO₂ microspheres were obtained by magnetic separation, washed three times with water, and freeze-dried overnight.

Synthesis of Fe₃O₄@SiO₂-CH = CH₂. For vinyl modification, Fe₃O₄@SiO₂ (400 mg) was dispersed into 80 mL of toluene under ultrasonication for 15 min. Then added 4 mL of MPS. Next, the mixture was stirred for 24 hours at 60 ℃. The products were magnetically separated and rinsed several times with ethanol and water. Finally, the products were freeze-dried for 12 hours.

Synthesis of EC-MMIPs and EC-NMIPs ²⁸. Ethyl carbamate (1 mmol) and MAA (4 mmol) were dissolved in a three necked flask with 60 mL of toluene and stored in the refrigerator for 12 hours. Afterward, Fe₃O₄@SiO₂-CH = CH₂ (150 mg) was added to the mixture and ultrasound for 15 min, followed by EGDMA (20 mmol) and AIBN (60 mg). The final mixture was degassed with nitrogen for 3 min to remove oxygen and incubated at 65 ℃ for 24 h. After the reaction, the products were washed with methanol five times and separate by magnet. Finally, the template was eluted with methanol/glacial acid (9:1, v/v) until ethyl carbamate could not detected by GC-FID. Then EC-MMIPs were freeze-dried for 12 hours. The Fig. 2 shows the schematic diagram of the EC-MMIPs preparation.

Ethyl carbamate magnetic nonimprinted polymers (EC-NMIPs) were prepared under the same conditions without adding ethyl carbamate.

2.7 Adsorption experiments

The adsorption isotherm study was performed as follows: 5 mg of MMIPs or NMIPs were added in 5 mL EC solutions of different concentrations (20–100 µg/mL). After shaking for 90 min at room temperature, then adsorbed materials were quickly separated with a strong magnet, the supernatant was filtered through a 0.22 µm filter membrane and the concentration of EC in the supernatant was determined by GC-FID Eq. (1) to calculate the adsorption capacity (µg/mg) of the polymers ²⁹.

$${Q}_{e}=\frac{\left({C}_{0}-{C}_{e}\right)\times V}{m}$$

Where Q_e (µg/mg) was represented the mass of EC adsorbed by per gam of magnetic adsorbent, C₀ (µg/mL) represented initial concentration of EC, C_e (µg/mL) represented the EC concentration of supernatant under adsorption, V (m/L) represented the volume of EC solution used, and m (mg) represented the mass of the polymers.

In the adsorption kinetics experiments, MMIPs/NMIPs (10 mg) was mixed with 5 mL EC (80 µg/mL), then placed in a constant temperature shaker and shaken for 3, 5, 10, 15, 20, 25, 30, 40, 60 and 90 min at room temperature. Finally, the polymers were separated by magnetic field. The residua concentration of EC in the supernatant was determine by GC-FID and the adsorption capacity (µg/mg) of polymers was calculated using the following Eq. (2).

$${Q}_{t}= \frac{\left({C}_{0}-{C}_{t}\right)\times V}{m}$$

where C₀ (µg/mL) was the initial concentration of EC solution, C_t meant the concentration of EC at different contact times, V mL) was the volume of solution used, and m (mg) was the weight of the adsorbent.

The competitive selective adsorption experiment was used to test the specificity of the adsorbent to EC. Methyl carbamate (MC) and butyl carbamate (BC) were selected as the structural analogues. In brief, 10 mg of MMIPs and NMIPs were added to 5 mL of analogue solutions (80 µg/mL) at room temperature and shaken for 2 hours. The remaining steps were the same as isotherm adsorption experiments.

In order to estimate the reusability of EC-MMIPs, five cycles of the adsorption-desorption process were performed for EC by using the same polymers. Briefly, 10 mg polymers were added to 5 mL EC solution (80 µg/mL) and oscillated for 60 min at room temperature. The EC-MMIPs were separated by magnet and supernatant was determined. Then, the polymer was eluted with methanol/acetic (v/v, 9/1) ultrasonic for 60 min, and the polymer was dried to complete the remaining cyclic adsorption.

3.1 Theoretical selection of functional monomer

According to the binding energy formula, the ratio between the template and each monomer was 1:1. As shown in Fig. 3, the order of the binding energies of the complexes was ΔE (EC-MAA) <ΔE (EC-MA) < ΔE (EC-4VP) <ΔE (EC-HEMA), indicating that the EC-MAA complex was more stable than other complexes. Therefore, MAA was chosen as the functional monomer.

3.2 Determination of action sites between template molecules and functional monomers

Charge transfer of bonded atoms during hydrogen bonding leads to electron recombination ³⁰. The electrostatic potential distributions of the template molecule (EC) and functional monomer (MAA) after conformation optimization are shown in Fig. 4. All electronegative atoms (O or N) can be used as hydrogen bond donors, and polar hydrogen atoms of functional monomers can be used as hydrogen bond receptors to form hydrogen bonds ²². The template-monomer complex was constructed with predicted action sites based on the ESP map.

As shown in Fig. 4A, the proton acceptors of the template molecule (EC) were N1 (-0.592), O6 (-0.549) and O5 (-0.385), and the proton donors were H2 (0.308) and H3 (0.318). In Fig. 4B, the proton acceptors of MAA were O10 (-0.482) and O11 (-0.472), and the donor was H12 (0.375).

3.3 Determination of imprinting ratio

During the simulation calculation, the models with EC and MAA imprinting ratios of 1:1, 1:2, 1:3 and 1:4 were studied, and the results are shown in Fig. 5A. The binging energy of the complex gradually decreased as the imprinting ratio increased, and when the optimal ratio was exceeded, the monomer may form unwanted hydrogen bonds through non-characteristic sites, reducing the polymer’s selectivity ²⁴. The binding energy of the complex was minimized when the imprinting ratio was 1:4, and the structure of the complex is shown in Fig. 5B.

3.4 Characterization

The micromorphology of EC-MMIPs and EC-NMIPs was characterized by SEM as can be seen in Fig. 6. As shown in the figure, the microspheres of A and B appear to agglomerate after being wrapped by a layer of imprinted polymer, because the process of polymerization and cross-linker reduces the dispersion of particles. Remarkably, the surface of EC-MMIPs was rougher than that of EC-NMIPs. This was due to imprinting voids after removal of template molecules in EC-MMIPs. The blotting cavity formed on the surface of the blotting layer increases the adsorption area and the number of binding sites, thus improving the adsorption capacity of EC-MMIPs³¹.

The spectra of FI-IR were shown in Fig. 7A. In all samples, the peak at 580 cm^− 1 belonged to the Fe-O stretching vibration of Fe₃O₄ nanoparticles. The curve of Fe₃O₄@SiO₂, the new characteristic peaks at 803 cm^− 1, 480 cm^− 1 and 1090 cm^− 1 were attributed to the stretching vibration of S-i-O and Si-O-Si, respectively. The peaks at about 1565 cm^− 1 and 1460 cm^− 1 in Fe₃O₄@SiO₂-CH = CH₂ were assigned to the C = C-H group in the modified after MPS. Finally, the peaks at 2950 cm^− 1, 1150 cm^− 1 and 1730 cm^− 1 in the spectra of EC-MMIPs were due to stretching vibrations of C-H, C-O and C = O in EGDMA, respectively, while the peak at 1730 cm^− 1 was also the characteristic peak of C = O in MAA. The absorption peaks indicated that all reactions were successfully synthesized during the preparation of EC-MMIPs.

The crystal structures of all materials were determined by X-ray diffraction patterns, and spectra were presented in Fig. 7B. Six characteristic peaks: (220), (311), (400), (422), (511) and (440) were observed for all the samples ³², which indicates that the surface modification did not alter the crystalline structure of Fe₃O₄ nanoparticle.

Figure 8A indicated magnetic properties of Fe₃O₄, Fe₃O₄@SiO₂-CH = CH₂ and EC-MMIPs, the saturation magnetization were 67.6 emu/g, 47.4 emu/g and 37.6 emu/g, respectively. Compared with Fe₃O₄, the saturation magnetization of Fe₃O₄@SiO₂-CH = CH₂ and EC-MMIPs gradually decreases, which is due to the surface modification and functionalization of Fe₃O₄, which form a polymer coating and imprinted layer of a certain thickness on the surface of Fe₃O₄. However, it doesn’t affect the separation of EC-MMIPs by the magnetic field in short time.

The thermal stability of prepared nanoparticles was shown in Fig. 8B. As the result, both samples lost approximately 2.8% of their mass at 260 ℃, which was mainly due to desorption of the organic solvent and the evaporation of water in the polymer structure ³³. When the temperature was continuously increased to 800 ℃, the mass loss of Fe₃O₄@SiO₂-CH = CH₂ was about 8.82%, which was caused by the thermal loss of silanol group and MPS on the surface. Compared with Fe₃O₄@SiO₂-CH = CH₂, the mass loss of EC-MMIPs was 26.2%, which was mainly due to the thermal decomposition of the imprinted layer³⁴, indicated that the good thermal stability of EC-MMIPs within 260 ℃.

3.5 Adsorption performance study

The isothermal adsorption curves of EC-MMIPs and EC-NMIPs are shown in Fig. 9A. With the increase in concentrations, the binding amount gradually increased and reached a dynamic equilibrium. When the EC concentration exceed 80 µg/mL, the adsorption capacity of EC-MMIPs and EC-NMIPs tends to be saturated. The adsorption capacity of EC-MMIPs was significantly higher than that of EC-NMIPs, about 2.2 times that of EC-NMIPs. It can be attributed to the fact that the surface of EC-MMIPs has more imprinted cavities than the EC-NMIPs surface.

The adsorption isotherm describes how molecules are adsorbed to the surface of an adsorbent. Therefore, Langmuir and Freundlich models (Eqs. (3) and (4), respectively) were used to fit the adsorption isotherm data.

Langmuir model: $\frac{{C}_{e}}{{Q}_{e}}=\frac{{C}_{e}}{{Q}_{m}}+\frac{1}{{bQ}_{m}}$ (3)

Freundlich model: $\text{log}{Q}_{e}=\text{log}k+\frac{1}{n}\text{log}{C}_{e}$ (4)

In the equation, Q_m (µg/mg) is the theoretical maximum adsorption capacity, C_e (µg/mL) is the equilibrium concentration of EC, and Q_e (µg/mg) represent the adsorption capacity at adsorption equilibrium, b is the equilibrium constant (mL/µg) of the Langmuir model, k is the Freundlich model equilibrium constant and n is a constant. The relevant parameters and R² of the two models were calculated, the results are shown in Table 1. The Langmuir model (R²_{EC − MMIPs} = 0.9929, R²_{EC − NMIPs} = 0.9967) was better fitted than that Freundlich model (R²_{EC − MMIPs} = 0.95637, R²_{EC − NMIPs} = 0.9848), Fig. 9B showed the Langmuir regression curve, which indicated that EC-MMIPs was monolayer adsorbed with homogeneous structure ³⁵.

Table 1

Adsorption isotherm constants of Langmuir model and the Freundlich model.
	Langmuir			Freundlich
	Q_m	b	R²	k	n	R²
EC-MMIPs	27.73	0.041	0.9929	2.3302	1.9612	0.9563
EC-NMIPs	11.31	0.040	0.9967	1.5813	2.5521	0.9846

Table 2

Adsorption rate constants of pseudo-first-order rate kinetic model and pseudo-second-order kinetic model.
	Pseudo-first-order			Pseudo-second-order
	Q_e	k₁	R²	Q_e	k₂	R²
EC-MMIPs	15.13	0.1414	0.9752	19.76	0.0026	0.9984
EC-NMIPs	11.73	0.2002	0.9402	9.26	0.0117	0.9987

The adsorption dynamic curves of EC-MMIPs and EC-NMIPs on EC are shown in Fig. 9C. The adsorption capacity increased with the increase over time, reaching saturated in 30 ~ 40 min. The maximum adsorption capacities of EC-MMIPs (Q_e=18.53 µg/mg) and EC-NMIPs (Q_e=8.77 µg/mg) were reached at 40 and 30 min, respectively. At the beginning of the adsorptive process, there were a large number of unoccupied imprinted cavities on the surface of EC-MMIPs, and the carboxyl groups on MAA form hydrogen bonds with EC, so that EC is quickly adsorbed to the surface of EC-MMIPs, until all the cavities are occupied and the adsorption equilibrium was reached. The results showed that the adsorption performance of EC-MMIPs was better than that of EC-NMIPs, which was related to the specific matching between the imprinted cavity on the surface of EC-MMIPs and EC.

In order to study the adsorption mechanism, the Pseudo-first-order adsorption kinetic model and the Pseudo-second-order adsorption kinetic model were used to fit the experimental data. Equations (5) and (6).

Pseudo-first-order : $\text{ln}\left({Q}_{e}-{Q}_{t}\right)=ln{Q}_{e}-{k}_{1}t$ (5)

Pseudo-second-order : $\frac{t}{{Q}_{t}}=\frac{1}{{k}_{2}{Q}_{e}}+\frac{t}{{Q}_{e}}$ (6)

where Q_e and Q_t meant the amounts of EC on the sorbent at equilibrium and t was the adsorption time (min), respectively. k₁ was the Pseudo-first-order rate constant and k₂ belongs to the Pseudo-second-order rate constant. The relevant parameters and R² of the two models were calculated, and the results are shown in Table 2. The Pseud-o-second-order kinetics model (R²_{EC − MMIPs} = 0.99846 R²_{EC − NMIPs} = 0.9987 was better fitted than that the Pseudo-first-order kinetics (R²_{EC − MMIPs} = 0.97521, R²_{EC − NMIPs} = 0.94023). Figure 9D shows the Pseudo-second-order kinetics regression curve, this indicated that the whole adsorption process is mainly chemisorption. Which meant that in the EC-MMIPs cavity, ethyl carbamate could form hydrogen bonds with methacrylic acid to achieve chemical adsorption.

In order to evaluate the selectivity of EC-MMIPs for the adsorption of ethyl carbamate, methyl carbamate and butyl carbamate were chosen as competitive substrates. Meanwhile, the selectivity of EC-MMIPs and EC-NMIPs to ethyl carbamate was further evaluated by imprinting factor (α) and selectivity factor (β) determination²⁸, which were calculated according to Eqs. (7) and (8), respectively.

$$\alpha ={Q}_{MMIP}/{Q}_{NMIP}$$

$$\beta ={\alpha }_{EC}/{\alpha }_{other}$$

Among them, Q_MMIP and Q_NMIP (µg/mg) were adsorption capacities of EC-MMIPs and EC-NMIPs, respectively. α_EC and α_other were the imprinting factors for template and analogs.

The results are shown in the table. α value reflects the difference of EC-MMIPs and EC-NMIPs on EC adsorption, β value reflects the selective adsorption capacity of adsorbent on EC in complex mechanism. The results showed that EC-MMIPs still had good adsorption effect on ethyl carbamate in the presence of competitive substrates, and its adsorption capacity was significantly greater than that of structural analogues.

Table 3

The selectivity parameters of EC-MMIPs and EC-NMIPs
analyte	Q_EC−MMIPs	Q_EC−MMIPs	α	β
EC	17.55	7.62	2.30	\
MC	7.64	7.2	1.06	2.16
BC	3.6	3.3	1.09	2.11

The experimental results were based on the initial adsorption capacity of EC-MMIPs on EC (100%). The adsorption rates of four cycles of elution and adsorption experiments were shown in Fig. 10, and the adsorption rates were 98.4%, 97.5%, 98.1% and 92.6% successively. The results showed that the adsorption rate of EC-MMIPs decreased after five cycles of adsorption, and there was adsorption rate of 92.6% at the fifth adsorption. This was because the spatial structure of EC-MMIPs was relatively stable, the binding site was relatively firm, and the structure of the imprinted cavity could remain stable under acid or high temperature.

In this study, the theoretically optimal functional monomer (MAA) was screened by calculating and analyzing four common functional monomers based on density flooding theory (DFT) using computer simulation techniques. By analyzing the hydrogen bonding sites between template molecules and functional monomers, the polymer model was constructed by different imprinting ratios, and the optimal imprinting ratio was calculated and analyzed as 1:4. EC-MMIPs were synthesized on the vinyl-functionalized Fe₃O₄@SiO₂ surface by combining with surface molecular imprinting techniques. The polymers were characterized by SEM, FT-IR, XRD, VSM and TGA, and the results showed that the preparation was successful. The adsorption experiment results show that the polymer has good adsorption properties and has good application potential.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

ACKNOWLEDGMENTS

The authors would like to thank all the panelists for their experimental support. This work was supported by the National Natural Science Foundation of China (31660437).

AUTHOR CONTRIBUTIONS

All authors have read and approved the final manuscript. Hongyuan Li designed and performed research, and wrote the paper. Hongwei Cui and Yue Wu contributed essential reagents and tools. Xujia Hu supervised and provided financial support.

DATE AVAILABILITY

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

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Computer-Aided design for the preparation of magnetic molecularly imprinted polymers for recognition of ethyl carbamate

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Abstract

Figures

1 Introduction

2 Methods

2.1 Materials

2.2 Characterization

2.3 Selection of functional monomer

2.4 Action reaction site analysis

2.5 Scale analysis of template – monomer

2.6 Synthesis of adsorbent materials

2.7 Adsorption experiments

3 Result and discussion

3.1 Theoretical selection of functional monomer

3.2 Determination of action sites between template molecules and functional monomers

3.3 Determination of imprinting ratio

3.4 Characterization

3.5 Adsorption performance study

4 Conclusion

Declarations

References

Additional Declarations

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