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Article

Adsorption of Pesticides, Antibiotics and Microcystin-LR by Graphene and Hexagonal Boron Nitride Nano-Systems: A Semiempirical PM7 and Theoretical HSAB Study

Environmental Molecular and Electromagnetic Physics (EMEP) Laboratory, Department of Soil and Environmental Sciences, National Chung Hsing University, Taichung 40227, Taiwan
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Author to whom correspondence should be addressed.
Crystals 2022, 12(8), 1068; https://doi.org/10.3390/cryst12081068
Submission received: 12 July 2022 / Revised: 24 July 2022 / Accepted: 27 July 2022 / Published: 30 July 2022
(This article belongs to the Section Materials for Energy Applications)

Abstract

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In recent years, graphene (CC) and hexagonal boron nitride (h-BN) have been widely used in water purification and environmental remediation because of their unique physical and chemical properties. Therefore, based on the reaction enthalpy, equilibrium structure, atomic charge, molecular, orbital and electronic spectrum provided by a semiempirical PM7 method, the adsorption of pesticides, antibiotics and microcystin-LR on graphene and hexagonal boron nitride (h-BN) nano-systems was examined. For the adsorption of diazinon, parathion, oxacillin and ciprofloxacin, the results show that as the bond length decreases and the atomic partial charge increases, the adsorption energy increases. The removal efficiency for antibiotics is higher than that for pesticides. Regarding the co-adsorption of pesticides/antibiotics and microcystin-LR on nano-systems, hydrogen bonds play a crucial role in stabilizing the whole structure. In addition, the non-covalent interaction (NCI) diagrams show the adsorption strength of the nano-systems to the pesticides/antibiotics. The energy gap and HSAB global descriptors are calculated based on the energy values of HOMO and LUMO. It is proved that the graphene nano-system has excellent electron-accepting ability, and suitable sensor materials can be designed.

1. Introduction

Graphene is a hexagonal honeycomb lattice composed of carbon atoms with sp2 hybrid orbital. Its most famous feature is the extremely low resistivity, so the electrons move very fast on the surface. The binding energy of CaO in the presence of graphene is 18 kcal/mol larger than that in the absence of graphene, indicating that graphene can act as a support for metal oxides, as it can induce the nucleation of metal oxide nano/microstructures growth, with uniform dispersion that inhibits their agglomeration, and possibly also controlled morphology with high chemical functionality on their surface [1]. High-quality characteristics enable graphene to be used in a wide range of applications, especially in water purification and environmental remediation. Through theoretical calculations based on quantum and molecular mechanics, the results show that graphene has excellent adsorption capacity for Lindane pesticides, which is consistent with the experimental results, and its removal rate is as high as 92.5% [2]. The current trend of graphene research believes that the application of graphene-based materials (e.g., adsorbents, and photocatalysts) to the purification of pesticide-containing wastewater holds great potential [3]. However, the use of unfunctionalized graphene in water purification has some limitations, as its adsorption capacity is limited to the number of oxygen functional groups available, and its sheets tend to aggregate because of interfacial interactions, reducing the effective area of adsorbents [4]. After the improvements, the use of graphene quantum dots as an adsorbent to remove harmful pesticide compounds (e.g., oxamyl) from aqueous solutions has been extensively studied and elucidated [1]. Post-graphene two-dimensional materials (pg-2DMs) are new two-dimensional materials, which have unique physico–chemical properties, including high photocatalytic activity and a large specific surface area; therefore, it also shows broad prospects in the detection or removal of pesticides [5]. Previous literature used heteroatom-doped graphene to create a colorimetric nanozyme sensor array, which could be used for the detection of aromatic pesticides. When different pesticides were adsorbed on graphene, the active sites corresponding to the adsorption positions of nanozymes were masked by different pesticides, and at the same time, the activity of the peroxidase-mimicking of the pesticides was decreased [6]. These improved methods optimized the physico–chemical properties of graphene and strengthened its functions. Even if the performance becomes outstanding, the corresponding pollutants may tend to be specific. According to previous reports, from the adsorption between graphene-based materials and two organophosphorus pesticides, such as dimethoate (DMT) and chlorpyrifos (CPF), it was found that the aliphatic DMT was easily adsorbed on the surface of hydrophilic oxidized graphene, while the aromatic CPF preferred to be adsorbed on the surface of the graphene basal plane with a structural order and preserved π-electron system [7]. The above description reveals the importance of environmental purification efficiency, that is, when the benefits are improved, in order to shorten the residual time of pollutants, it is still necessary to select the most appropriate method to the actual situation.
Recently, the application of hexagonal boron nitride (h-BN) in various fields has become a hot topic, based on its extraordinary characteristics, including high surface area, low density, high thermal stability, mechanical strength, electrical conductivity, corrosion resistance and oxidation resistance. In particular, adsorption, synthesis of novel membranes, and photocatalytic degradation of pollutants have been critically evaluated and developed in water purification or environmental remediation for a period of time [8]. Therefore, through its practicality in environmental science through h-BN materials, the most typical application being the adsorption and removal of pollutants through many experiments, the synthesis of h-BN nanosheets into a large-area adsorbent can be applied to the removal of tetracycline (TC), ofloxacin (OFL) and cephalexin (CFX) in water [9]. Singla et al. prepared h-BN nanomaterials with an excellent adsorption function, and used the adsorption experiments of two antibiotics, ciprofloxacin (CIP) and norfloxacin (NOR), to achieve its characteristics and prove its effectiveness [10]. Of course, in some cases, the antibiotics or other pollutants will determine the degree of effectiveness of the adsorbent: MBCN, BCN and adsorbate produce chemisorption, which is affected by hydrophobic interaction and electrostatic force. Taking antibiotics as an example, due to the micropore-filling effect, when the molecular weight of the antibiotics is larger, it is less likely to enter the micropores, which makes the adsorption capacities decrease [11]. From the results of adsorption kinetics, adsorption thermodynamics, and isothermal adsorption, it is found that the adsorption mechanisms of tetracycline (TC) on p-BN are mainly π–π interaction and electrostatic force [12]. There are reports that the interaction mechanism between boron nitride-based materials and pollutants (inorganic pollutants, such as heavy metal ions or organic pollutants, such as dyes and drug molecules) mainly are the surface complexation, π–π stacking and electrostatic interactions [13]. Then, the application of graphene-like layered hexagonal boron nitride (g-BN) as an adsorbent to remove the fluoroquinolone antibiotic gatifloxacin (GTF) from the aqueous solution was observed and evaluated regarding its adsorption properties that the π–π interaction and electrostatic force are important in the adsorption process [14]. For h-BN, in addition to the dispersion force and electrostatic attraction, it was found to help stabilize atrazine by compensating for repulsive interactions. The results show that the h-BN sheet has a strong affinity for atrazine due to its polar bond and promotes hydrogen bonding with atrazine, which helps by increasing the translational energy barrier of atrazine to different regions’ stable molecules [15]. The new type of hexagonal boron nitride (h-BN) is composed of a large number of BN fibers with a high adsorption capacity and excellent recyclability and can be prepared as an effective adsorbent for antibiotics. The main adsorption mechanisms were π–π electron–donor–acceptor interaction as well as electrostatic force; based on the above, in addition to the π–π interaction and electrostatic force, hydrophobic interaction also has a place [16]. There are many similarities between hexagonal boron nitride and graphene. With proper improvement in terms of the electronic structure, three-dimensional structure, and surface activity, many of its properties are widely expected. The sea urchin-like structure of the porous fibers exhibits strong intermolecular interactions when capturing organic pollutants to the center, that is, the π–π bonding force and the acid–base complexation. In this way, if the BN adsorbent removes pollutants with a sea urchin-like structure, then this material would have broad applicability [17]. Chao et al. proposed a method to promote the removal of antibiotics: the N-defects in the BNNSs framework. The principle may be that it can adjust the morphological and electronic structure of nanomaterials, and enhance the interaction between adsorbents and pollutants [18]. In fact, the conductivity of h-BN is inferior to that of graphene. However, according to the density of state (DOS) spectrum, the band gap of the boron nitride nanocage before and after the adsorption of nalidixic acid decreases from 14.864 (eV) to 7.314 (eV), and its value is significantly reduced, which means that the conductivity of B12N12 will increase significantly at this time. In addition, B12N12 has a large band gap and can be used as an electrochemical sensor to detect nalidixic acid or other organic pollutants [19]. As mentioned above, to make the sensor’s functional application more powerful, Angizi et al. recently transformed 2D h-BN into a choice of ideal material with excellent electrocatalytic activity, high specific surface area, N and B active edges, structural defects, adjustable band gap, and chemical functionalization [20].
Microcystis is a kind of algae commonly found in freshwater, among which M. aeruginosa, causing harmful algal blooms, is more famous; Microcystis produces a kind of intracellular toxin-microcystin, and microcystin-LR is the most common. Its physical and chemical properties are stable, and it has the characteristics of liver toxicity or nephrotoxicity. Quizalofop-Ethyl (QE) is a widely used phenoxy herbicide that contains two enantiomers, of which only the R-enantiomers quizalofop-p-ethyl (QpE) has herbicidal activity. Whether intracellular or extracellular, environmental experiments with M. aeruginosa showed that QpE had a strong stimulating effect on the synthesis of microcystin-LR after 144 h, which promoted the increase in microcystin-LR content. However, exposure to QE kept a stable quantity [21]. The following studies show the same result for antibiotics, which have a particularly significant effect on the growth, photosynthesis, oxidative stress and microcystin release of M. aeruginosa. After 96 hrs, the EC50 values of MOX and GAT were 60.34 and 25.30 μg/L, respectively, indicating that a certain ecological risk in the actual environment would happen [22]. Trying to understand the physiological effects of tetracycline antibiotics on aquatic organisms, Ye et al. investigated the growth characteristics and toxin release of M. aeruginosa. In terms of growth parameters, the toxicity of the following target antibiotics was TC (tetracycline hydrochloride) > CTC (tetracycline hydrochloride) > OTC (salt oxytetracycline); EC10 (0.63, 1.86 and 3.02 mg/L, respectively), and EC20 (1.58, 4.09 and 4.86 mg/L, respectively) [23]. The above represents that antibiotics have varying degrees of influence on inhibiting the production of microcystin-LR, and these research results could be used in practice to reduce the pollution of microcystin-LR in an agricultural ecosystem. The synergy effect is a key to scientific research, which can be used in medicine, media, biology, physics and chemistry, personnel management, etc., and can also promote rapid progress and universal applicability in these fields. The interaction between carbaryl and Microcystis and its impact on animal physiology are very important. Factors include pollutant concentration, environmental temperature or duration, which may cause individual shrinkage, deformation and depression, early or late maturity, stunted growth, and a decrease in the number of offspring. These effects mostly come from synergistic effects, not a single stressor, and thus it is impossible to predict the result from a single stressor [24]. The toxicity of microcystin and each of the antibiotics can be judged in the luminescent bacteria test, represented by the toxic unit (TU) method. The 50% effective concentration of microcystin combined with antibiotics, such as spiramycin and amoxicillin, are 0.56 TU and 0.48 TU by the toxic units, respectively, indicating the synergy between microcystin and each of the antibiotics (EC50 mix < 1 TU) [25]. Proteins in living individuals are rich in multiple functions, such as oxidation, detoxification, or energy metabolism, and so on. They are affected by various single pollutants (e.g., microcystin-LR) or mixed pollutants, which would result in different reaction pathways [26]. From the point of microcystin, because the microcystin release regulatory protein (mcyH) and the four ATP-binding cassette transport proteins are under upregulation, the presence of the antibiotic mixture reduces the radiation effect of UV−C on the microcystin, and even stimulates the release of microcystin in the cyanobacterial cells treated with UV−C. Therefore, the interference effect of antibiotics pollution needs to be considered when using UV−C to treat a contaminated aquatic environment [27].
The enthalpy of edge formation was calculated from the enthalpy of graphene quantum dot (GQD) formation based on the semi-empirical method PM7, using the average van der Waals interaction energy of the graphene layers. By calculating the distance distribution between atoms, we can study structural properties, such as bond lengths, and understand their interaction mechanisms [28]. Furthermore, the semi-empirical method PM7 was shown to provide good performance for calculating the heat of the formation of fused PAHs, and it consistently showed an average error of approximately 0.54 kcal mol per carbon atom in the molecule [29]. Calculate the adsorption energy values between the adatom X and the h-BN monolayer, where X=O, OH, 2OH and H2O. The calculated geometric parameters and adsorption energy values obtained by the semi-empirical method PM7 are in reasonable agreement with the results of the previously reported DFT method [30]. This means that more environmentally friendly semi-empirical calculations can be used for the stability testing of other graphene systems.
In this study, graphene (CC) and hexagonal boron nitride (h-BN) were selected as nano-systems because of their unique physical and chemical properties, which are widely used in adsorption. The organic pollutants are diazinon, parathion, oxacillin and ciprofloxacin, which are very common in aqueous environments, and the microcystin-LR also coexists in the environment. The objective of this study is to investigate the adsorption of nano-systems with organic pollutants and co-adsorbed with microcystin-LR in order to remove these pollutants that are harmful and coexist in the aqueous environment. As we all know, most of the previous studies aimed to remove organic pollutants or microcystin-LR alone. There are few studies on the combination of microcystin-LR and pesticides/antibiotics. Here, the semiempirical PM7 method is used to calculate the reaction enthalpy, equilibrium structure, atomic charge, molecular orbital and electronic spectrum of the nano-systems. In addition, the energy gap and HSAB global descriptors are calculated based on the energy values of HOMO and LUMO, and the frontier molecular orbital (FMO) and electronic excitation spectra can be used to clarify the changes of adding microcystin-LR to the nano-system. This not only shows the difference in electronic properties between CC and h-BN, but also illustrates that the addition of microcystin-LR will stabilize the co-adsorption system. Through this research, we can predict which nano-system has the best removal efficiency of pesticides/antibiotics and can also determine whether microcystin-LR has good co-adsorption capability, aiming to provide a reliable method of water purification and design a high-sensitivity sensor.

2. Materials and Methods

2.1. Molecular Model

Graphene (CC) and hexagonal boron nitride (h-BN) nanosheet models with all the edge atoms terminated by monohydrogen are used for the following calculations. Nanotube Modeler software (JCrystalSoft, 2018) is used to generate the XYZ coordinates of CC and h-BN nanosheets. The 3D structure details of microcystin-LR (mc) are obtained by NMR in the literature. The geometric structure is taken from the RCSB protein database (PDB: 1LCM) [31]. Investigated pesticides and antibiotics include diazinon (dia), parathion (par), oxacillin (oxa) and ciprofloxacin (cip).

2.2. Computational Method

All calculations are performed at the PM7 level using MOPAC 2016 semi-empirical quantum chemistry software [29]. MOPAC 2016 is available from http://openmopac.net (accessed on 15 July 2021). The MOPAC 2016 PM7 results of optimized geometries and Mulliken charges are illustrated by the MoCalc2012 software to study the role of electrostatic interaction and hydrogen bonding in the strength of the binding reaction and show non-covalent intermolecular and intramolecular interactions (NCI) [32,33]. The MoCalc2012 software is also used to draw the energy level diagram. In addition, the Gabedit software is used to read AUX files calculated by MOPAC 2016 to visualize HOMO and LUMO [34]. The ORCA software is used to obtain the singlet and triplet excited state energy of the investigated system through INDO/S-CIS calculations [35,36,37].

2.3. HSAB Global Descriptor

According to HSAB and conceptual density functional theory [38,39,40,41], the escape tendency of the electron density in a molecule and the ability of molecular species to lose electrons can be based on the electronic chemical potential (μ) and chemical hardness (η). μ and η are defined as the first and second derivatives of the energy relative to the number of electrons at a constant external potential. In the ground-state parabola model [42], μ and η can be calculated by the ionization potential (IP) and electron affinity (EA): μ = − (IP + EA)/2, η = (IP − EA)/2.
The highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) represent the ability of the molecule to donate and accept electrons, respectively. In order to easily obtain IP and EA values through single calculation, the HOMO and LUMO energy values are usually used to approximate IP and EA, namely, the ionization potential (IP = −HOMO) and electron affinity (EA = −LUMO). IP and EA approximated by HOMO and LUMO energy values are then used to calculate HSAB reactivity descriptors, such as electronegativity (χ = (I + A)/2), chemical hardness (η = (I − A)/2), chemical potential (μ = −(I + A)/2 = −χ), chemical softness (S = 1/2η) and the electrophilicity index (ω = μ2/2η) [43].

3. Results and Discussion

3.1. Non-Covalent Interaction (NCI)

As depicted in the diagrams of Figures S1 and S2, the regional color where graphene (CC) is bonded with hydrogen atoms from pesticides or antibiotics reveals blue. The phosphorothioate, the benzene ring and the amide groups of dia, the phosphorothioate and the nitro groups of par, the carboxylic acid group of oxa and the carboxyl group of cip that interact with CC also show sporadic blue regions. From the results, it can be realized that pesticides and antibiotics are stabilized on CC through non-covalent interactions (NCI). In addition, it can be seen from the figures that there are more blue regions and fewer yellow regions, indicating that the NCI of antibiotics binding CC is stronger than that of pesticides binding CC. Similarly, the NCI between antibiotics and h-BN is also stronger than that between pesticides and h-BN.
In the previous literature, density functional theory (DFT) calculations were used to study the interaction between the S(O)=P part of organophosphates and specific positions in graphene. The aforementioned positions include point defect-single vacancies, Stone–Wales defects, and epoxy groups [44]. Through adsorption experiments and first-principles DFT methods, it is proved that graphene oxide (GO) can be used as an adsorbent, and the removal efficiency of toxic organophosphorus pesticides in the water phase is very high [45]. The combination of the DFT method, fully atomistic molecular dynamics (MD) simulation, and binding free energy calculations have found that π–π stacking and van der Waals interactions are the main adsorption mechanisms between GO and pesticides [46]. DFT, time-dependent density functional theory (TD-DFT), and MD simulation are used to investigate the interaction between antibacterial fluoroquinolone drug ciprofloxacin (CIP) and organic hydrophilic nanoflakes (graphene oxide and boron nitride oxide) in an aqueous medium. It is found that when CIP is adsorbed, it still retains the optical properties during the π–π electron–donor–acceptor interaction process [47].

3.2. The Reaction Enthalpy, Equilibrium Structure and Atomic Charge

From the calculated reaction enthalpy shown in Table 1, it can be seen that the adsorption affinity of h-BN to pesticides/antibiotics is greater than that of CC. This is because the electronegativity difference between B and N is relatively large, while the B-N bond is a polar bond, and the atomic partial charge tends to be large, resulting in a significant electrostatic interaction. The neutral h-BN sheet with D3h point group symmetry has uniform charge distribution [48]. The charge distribution of CC and h-BN was previously obtained by X3LYP functional and Mulliken charge analysis. The charge of CC is −0.365e to 0.365e, and the charge of h-BN is −0.619e to 0.619e [49]. Dia and par are both organophosphorus pesticides; the phosphorothioate group is their core adsorption structure. The pyrimidine aromatic ring of dia and the nitro group of par also have an obvious ionic characteristics for binding with h-BN to perform chemisorption. There is no difference in the electronegativity of the carbon atoms in CC, the atomic partial charge is very small, and the adsorption mechanism belongs to a weak π–π interaction. Due to π–π interactions, graphene and other carbon-based nanomaterials/nanocomposites can adsorb pollutants with aromatic rings, and pollutants with fewer aromatic rings have weaker interactions [50]. Whether it is h-BN or CC, the adsorption extent of antibiotics is greater than that of pesticides. It can be seen from the equilibrium structures in Figure 1, Figure 2, Figure 3 and Figure 4 that the antibiotics is closer to the nano-systems, which is also the reason for the stronger electrostatic interaction.
For the dia molecule, although the bond lengths of Oa, Ob, and Oc in the phosphorothioate group to CC are shorter (the bond length difference of Oc is the largest), because the positive charge of the B atom is 0.16 higher than that of the C atom, the electrostatic interaction of h-BN is relatively large. The thiophosphates (Oc, Od, Oe) and nitro groups (Na, Oa, Ob) in par are slightly farther from h-BN than from CC. Although the bond length of h-BN is longer, the charge difference of the atom with the largest bond length difference is 0.18, so the Coulomb electrostatic interaction of h-BN is obvious (Figure 1 and Figure 3).
The Na, Hb of amide group and Oa, Oc, Ha of carboxylic acid group in oxa are bound with h-BN. Among them, the bond length of the amide group has a large difference, and because the charge between h-BN and CC is different, the Coulomb electrostatic force of h-BN has a significant effect. The Na and Nb of the pyrazine group in the cip molecule are closer to h-BN than to CC, and Na is the nearest atom to h-BN. In addition, since the positive charge difference between the B atom and the C atom is 0.22, the electrostatic interaction of h-BN-cip is greater than that of CC-cip (Figure 2 and Figure 4). The reaction enthalpy of BN is larger than that of CC, whether it is adsorbing oxa or cip. The adsorption performance of BN beams for antibiotics is better than that of activated carbon and graphene nanosheets. It is speculated that the adsorption mechanism is mainly π–π electron–donor–acceptor interaction, while electrostatic force and hydrophobic interaction play important roles.
Farmanzadeh and Rezainejad used the DFT method to investigate the interaction of the two organophosphorus pesticides, parathion and chlorpyrifos, with armchair and zigzag boron nitride nanotubes in an aqueous and gaseous phase [51]. They also demonstrated that the van der Waals interaction exists between the boron nitride nanotubes and organic pesticides, such as diazinon or hinosan [16]. The calculated results from the Fukui index and atomic partial charges show that organophosphorus pesticides and nanocages are nucleophiles and electrophiles, respectively, that is, the former donates electrons to the latter to form chemical bonds and adsorb; its adsorption site is the thiophosphate group, and the aromatic ring structure of dia and the nitro group of par [52].
Previous studies have shown that the calculated results of infrared (IR), natural bond orbital (NBO), and frontier molecular orbital (FMO) can be used in sensing and removal properties through the ampicillin and boron nitride nanocones adsorption experiment [53]. With DFT calculations, it is known that the π–π interaction and the multilayer stacking form are the main adsorption mechanisms, which prove that the adsorption energy between Bv-BNNS and TC is much higher [54]. According to the DFT calculated results, the interaction and electronic properties of the B12N12-Im, Hn18-Im and Hn16-Im systems at the HSEh1PBE/6-311G(d, p) theoretical level are analyzed and the result shows that the values of the adsorption energy of the system are very large, inferred to be chemisorption, which adsorb pollutants efficiently [55].

3.3. The Co-Adsorption of Microcystin-LR

Microcystin is a monocyclic heptapeptide. The five amino acids, leucine, arginine, methylaspartic acid, alanine and Adda, are adsorbed on the surface of nano-systems, while the methyl dehydroalanine and isoglutamic acid are far away from the nano-system. After co-adsorbing microcystin-LR, the H-bond interaction is formed between the hydrophilic region of pesticides/antibiotics, such as the hydrogen and oxygen atoms of the carboxylic acid group, the oxygen atom of the thiophosphate group, the nitrogen atom of the azetidine group, with the oxygen atoms of arginine and the hydrogen atoms of guanidine in microcystin-LR, resulting in larger reaction enthalpy (Figures S3–S6). However, the interaction with the hydrophobic Adda chain is weak and it is difficult to form hydrogen bonds.
Previous works in the literature have established an on-line solid phase extraction followed by the liquid chromatography mass spectrometry method. This method is rapid, simple and highly sensitive, and is suitable for the determination of pesticides and microcystin-LR in drinking water [56]. Since there is a risk of microcystin, it may be actively implemented by means of biodegradation and photodegradation. However, the reaction relationship between these pollutants or other influencing factors and microcystin is extremely complicated, and any of them has an inconsistent effect on microcystin. Previous works in the literature have shown that high concentrations of glyphosate and chlorothalonil significantly inhibit the degradation of microcystin-LR in the soil, and the half-life is almost doubled; on the contrary, the addition of CO(NH2)2 and dimethoate has no obvious effect; in addition, both the low water content (10%) and high water content (60%) may lead to inhibition of microcystin-LR degradation [57]. Pollutants from household or industrial wastewater, or even agricultural irrigation drainage (e.g., pesticides, herbicides, antibiotics, and preservatives) enter the aquatic environment excessively, and the eutrophic process has been extensively pointed out. In the case of exposure to a kind of antibiotic, amoxicillin, the growth rate is stimulated at the beginning to allow the rapid reproduction of microcystin. As the content increases, the contamination of M. aeruginosa cells and microcystins also increases, that is, if amoxicillin is released and causes harm in the aquatic environment through cyanobacterial bloom [58]. In this work, we are pursuing a simulation that is closer to reality to effectively make that removed and understand the interaction relationship to reduce the damage of pollutants and microcystins to organisms and the environment; therefore, the co-adsorption of pesticides, antibiotics and microcystins are the research objects of this study.
For h-BN, the adsorption of par is far away from the microcystin, and the hydrogen bond is generally considered to be between 2.7 and 3.3 Å, so hydrogen bonds cannot be formed. Although par has no hydrogen bond, the nitro group has strong electrophilicity, so its reaction enthalpy is larger than that of dia. As can be seen from Figures S3–S6, whether it is h-BN or CC, the hydrogen bond of antibiotics is shorter than that of pesticides. In addition, the hydrogen bonds of antibiotics and microcystins-LR on CC are shorter than those of antibiotics and microcystins on h-BN, and there is a greater difference in reaction enthalpy between the antibiotics and microcystin-LR on h-BN and the absence of microcystin-LR.

3.4. The Hard and Soft Acid and Base (HSAB) Global Descriptor

HOMO is the highest molecular orbital occupied by electrons. The higher the energy, the stronger the ability to donate electrons. LUMO is the lowest unoccupied molecular orbital. The more negative the value, the stronger the ability to accept electrons. The HOMO and LUMO energy values are used to calculate the following HSAB reactivity descriptor (Table 2). The energy gap between HOMO and LUMO can be used as a measure of electronic transitions, so it can be used as a measure of the interaction of molecules with other species. Compounds with larger energy gaps have higher chemical hardness. When pesticides and antibiotics are adsorbed on the nano-adsorbent, the energy gap becomes smaller. Among them, the energy gap change of CC is larger than that of h-BN, hence CC is a more suitable candidate for serving as a chemical sensor.
I is the ionization energy (I = −HOMO), which is the minimum energy required to remove an electron. The order is par > oxa > dia > cip. The ionization energy of h-BN is greater than that of CC. When the pollutant is adsorbed on the nano-system, the ionization energy becomes smaller, and the ionization energy of h-BN changes less than CC. When microcystin-LR is co-adsorbed, the ionization energy becomes larger. This is because microcystin-LR has a stable electronic structure and can increase the energy for the ionization.
A is the electron affinity (A = −LUMO). It is the energy released when the system accepts an electron. The order is par > cip > oxa > dia. When adsorbing pesticides or antibiotics, the electron affinity becomes larger, and the change of the electron affinity of h-BN is smaller than that of CC. The electron affinity of antibiotics is greater than that of pesticides. When the microcystin-LR is co-adsorbed, the electron affinity becomes larger.
χ is electronegativity (χ = (I + A)/2), and electrons migrate to the system with higher electronegativity. The order is par > oxa > cip > dia. Among them, dia has the smallest electronegativity, resulting in the lowest reaction enthalpy when adsorbed on the nano-adsorbent. Because there are more atoms with high electronegativity, such as nitrogen and oxygen atoms, microcystin-LR has the greatest electronegativity. When microcystin-LR is co-adsorbed, the electronegativity becomes greater. Pesticides and antibiotics can easily donate electrons to the nano-system with microcystin-LR.
η is the chemical hardness (η = (I − A)/2). The greater the chemical hardness, the greater the resistance to the charge transfer and the lower the possibility of polarization, which represents the greater stability of the entire system. The order is dia > oxa > par > cip. During adsorption, the chemical hardness of h-BN becomes smaller, and the change of the chemical hardness of h-BN is smaller than that of CC. When microcystin-LR is co-adsorbed, CC will be slightly larger, indicating that the co-adsorbed species of pesticides/antibiotics and microcystin-LR tend to be stable.
μ is the chemical potential (μ = −(I + A)/2 = −χ), which is the negative value of electronegativity. The order is opposite to electronegativity. Contrary to χ, the greater the chemical potential, the higher the electron donating tendency of the compound. When the microcystin-LR is co-adsorbed, the chemical potential becomes larger, and pesticides and antibiotics can easily donate electrons to the nano-system.
S is the chemical softness (S = 1/2η). The greater the softness, the easier it is to be polarized, and the higher the reaction enthalpy. The order is the opposite of chemical hardness. The chemical softness of h-BN is obviously less than CC, which means that the latter is more easily polarized and therefore has higher reactivity. When pollutants are adsorbed on the nano-system, the chemical softness becomes larger, and the chemical softness of CC changes more than that of h-BN. When microcystin-LR is co-adsorbed, the chemical softness of CC will change slightly, indicating that the co-adsorbed system tends to be stable. On the contrary, due to less electron redistribution, BN will become larger after co-adsorption.
ω is the electrophilicity index (ω = μ2/2η). The larger the value, the easier it is to accept electrons. par has the largest electrophilicity index because it has an electrophilic nitro group. The electrophilicity index of h-BN is much smaller than that of CC. When pollutants are adsorbed on the nano-system, the electrophilicity index becomes larger, and the electrophilicity change of h-BN is smaller than that of CC. When microcystin-LR is co-adsorbed, the electrophilicity index becomes larger, and the electrophilicity index of CC increases even more. This is because CC has better conductivity and stronger electron acceptance than h-BN. Due to its high electron transfer ability, it is suitable as a sensing material. Previous works in the literature have shown that the manufacture of high-sensitivity sensors that can detect single molecules can increase the concentration of graphene charge carriers through adsorbed gas molecules [59].

3.5. The Frontier Molecular Orbital (FMO)

The orbital lobes in the HOMO diagram of microcystin-LR are concentrated on leucine, alanine and methyldehydroalanine. It can be seen that the main electron donors in microcystin-LR are leucine and alanine. Moreover, the orbital lobes in the LUMO diagram are concentrated on arginine; consequently, the main accepted electron in microcystin-LR is arginine.
The orbital lobes in the HOMO and LUMO diagrams of CC are distributed in the lower and upper parts, respectively. When CC binds to microcystin-LR, the orbital lobes in the HOMO and LUMO diagram cover the entire CC. However, the part close to the arginine and Adda chain is less dense in the HOMO diagram, meaning that its ability to provide electrons is weak. In contrast to the HOMO diagram, the part close to leucine, alanine and methyldehydroalanine in the LUMO diagram is less dense, indicating that its ability to accept electrons is weak.
In the HOMO and LUMO diagrams of h-BN, almost all orbital lobes cover h-BN, but LUMO is denser than HOMO. When h-BN binds to microcystin-LR, the orbital lobes in the HOMO and LUMO diagrams do not cover the entire h-BN. The capability of providing electrons is weak in the upper left corner of HOMO near the arginine and Adda chain. Conversely, the ability to accept electrons is weak in the lower right corner of LUMO near leucine and alanine.
The HOMO–LUMO energy gap is often used to measure the conductivity of a molecule. The smaller the HOMO–LUMO energy gap, the better the conductivity, the greater the softness, and the easier the molecule will react, because the smaller the excitation energy, the higher the polarization rate. Previous studies have found a sign of chemisorption, which does not significantly change the electrostatic potential surface and the plane geometry and energy gap of the sheet. However, this sign is that the frontier molecular orbital distribution on graphene and h-BN flakes after CH4 adsorption is different from that of unadsorbed CH4. In addition, it can be seen that the h-BN flakes not only have a wider electronic energy level, but also the Fermi level and the first LUMO level are lower than those of graphene from the results of the density of states (DOS) [49]. Each carbon atom of graphene has a free pi electron, resulting in a delocalized network of electrons. These free π electrons provide a higher density of electrons above and below the graphene plane, and the interaction with the frontier molecular orbitals of various organic compounds is easier, so the process of electrophilic substitution is easier compared to nucleophilic substitution [60]. From Figure 5, it can be found that the frontal orbital is different between CC/h-BN and CC/h-BN combined with microcystin-LR; besides, the LUMO of CC is greater than that of BN, while the HOMO is smaller than that of h-BN. However, CC has a small energy gap than h-BN. Similarly, the energy gap of CC is smaller than that of h-BN after adding microcystin-LR, and the energy gap size is the same as without microcystin-LR. From the result, CC has better conductivity than h-BN; moreover, it is easier to react with other molecules and easily adsorb other molecules. Therefore, CC is suitable as a sensor material. The working principle of graphene-based sensors is highly dependent on the change in the resistivity (R) of graphene when adsorbing gases/biomolecules on the surface, which is affected by graphene, electron acceptors, and charge transfer when adsorbing molecules, changing the load on graphene affected by the carrier concentration [61].

3.6. The Electronic Excitation Spectrum

The phenomenon of the redshift reduces the energy levels of the unexcited and excited states [62], which is due to the introduction of chromophore or auxochrome into the molecule, or the attractive polarization between the solvent and the absorber. The microcystin-LR has a benzene ring and many nitro groups, which are chromophore and auxochrome, respectively. After adding microcystin-LR, the phenomenon of the redshift occurs, which can be seen from Figure 6. The absorption peak of the π→π* transition is shifted from 560 nm to 798 nm in CC; furthermore, the peak of h-BN is shifted from 200 nm to 238 nm and the wavelength of h-BN changes less than CC because CC has a stronger ability to accept electrons. The red-shift of the C–C stretching vibration band reflects the π–π interaction between graphenes. Likewise, the OH stretching vibrations also have a red shift, which indicates hydrogen bonding after reduction [63]. Previous works in the literature mentioned that, compared with the plasma of silver nanoparticles, the plasma of the graphene–silver hybrid material has a redshift, which is caused by the interaction between the electrons and the graphene sheet [64]. It can be found that the strength not only becomes stronger, but the peaks also move to a place where the wavelength is longer, thus increasing the energy level and reducing the excitation energy of the nano-system electrons.

4. Conclusions

The PM7 method is a stable and useful semiempirical quantum chemistry method, which can be applied to explore the reaction enthalpy, electrostatic interaction, frontier molecular orbital and electronic excitation spectrum for a medium- or large-sized nano-system. Relying on the calculated results, it can be confirmed that h-BN has a higher adsorption affinity than CC. Moreover, by adsorbing antibiotics, the effect is more significant than adsorbing pesticides. When pesticides and antibiotics are adsorbed on the nano-system and co-adsorbed with microcystin-LR, they will form a stable hydrogen bond with the arginine moiety in the structure of microcystin-LR. In this co-adsorbed system, the binding tendency of h-BN is still greater than that of CC. It can be seen from the above results that the combination of h-BN and microcystin-LR has the best removal performance for pesticides and antibiotics and can be used as an efficient environmental remediation agent. In addition, this study calculated global descriptors based on the eigenvalues of HOMO and LUMO. According to the HSAB principle, it is found that CC has a stronger electron-accepting ability than h-BN. From this theoretical result, we suggest that CC can be used as a better sensor material than h-BN. This is the first time we discovered that when microcystin-LR coexists in an aqueous environment, it will increase the sensitivity of pesticides and antibiotics. Nonetheless, in order to achieve real scale practical application, there is still a need to further study these materials and break down the limitations of the research. First is the production of a consistent quality and large quantities of graphene composites with cost-effective synthetic methods. Secondly, the long-term safety and environmental issues of graphene materials must be addressed because the physiological and biochemical processes caused by its impact on living organisms have not been thoroughly studied. Finally, applications in true multi-component wastewaters are still lacking, as most studies have only been conducted on synthetic solution containing one pollutant for research.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/cryst12081068/s1, Figure S1: Non-covalent interaction between pesticides (dia and par)/antibiotics (oxa and cip) and graphene (CC), Figure S2. Non-covalent interaction between pesticides (dia and par)/antibiotics (oxa and cip) and hexagonal boron nitride (h-BN), Figure S3. Co-adsorption structures of pesticides (a) dia and (b) par and microcystin- LR (mc) on graphene (CC), Figure S4. Co-adsorption structures of antibiotics (a) oxa and (b) cip and microcystin- LR (mc) on graphene (CC), Figure S5. Co-adsorption structures of pesticides (a) dia and (b) par and microcystin- LR (mc) on hexagonal boron nitride (h-BN), Figure S6. Co-adsorption structures of antibiotics (a) oxa and (b) cip and microcystin- LR (mc) on hexagonal boron nitride (h-BN).

Author Contributions

Conceptualization, S.-C.C., C.-L.L. and C.M.C.; methodology, S.-C.C., C.-L.L. and C.M.C.; software, S.-C.C. and C.-L.L.; validation, C.M.C.; formal analysis, S.-C.C., C.-L.L. and C.M.C.; investigation, S.-C.C.; resources, C.-M.C.; data curation, S.-C.C.; writing—original draft preparation, S.-C.C.; writing—review and editing, C.M.C.; visualization, S.-C.C., C.-L.L. and C.M.C.; supervision, C.M.C.; project administration, C.M.C.; funding acquisition, C.M.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Science Council of Taiwan, Republic of China and grant number [MOST 111-2321-B-005-004].

Acknowledgments

The authors thank the National Science Council of Taiwan, Republic of China, MOST 111-2321-B-005-004 for providing financial support. Computer time was provided by the National Center for High-Performance Computing.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Equilibrium structures of pesticides (a) dia and (b) par adsorbed on graphene (CC).
Figure 1. Equilibrium structures of pesticides (a) dia and (b) par adsorbed on graphene (CC).
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Figure 2. Equilibrium structures of antibiotics (a) oxa and (b) cip adsorbed on graphene (CC).
Figure 2. Equilibrium structures of antibiotics (a) oxa and (b) cip adsorbed on graphene (CC).
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Figure 3. Equilibrium structures of pesticides (a) dia and (b) par adsorbed on hexagonal boron nitride (h-BN).
Figure 3. Equilibrium structures of pesticides (a) dia and (b) par adsorbed on hexagonal boron nitride (h-BN).
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Figure 4. Equilibrium structures of antibiotics (a) oxa and (b) cip adsorbed on hexagonal boron nitride (h-BN).
Figure 4. Equilibrium structures of antibiotics (a) oxa and (b) cip adsorbed on hexagonal boron nitride (h-BN).
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Figure 5. Energy level diagrams and frontier molecular orbitals (HOMO and LUMO): (a) microcystin-LR (mc), (b) graphene (CC), (c) graphene with microcystin-LR (CC_mc), (d) hexagonal boron nitride (h-BN) and (e) hexagonal boron nitride with microcystin-LR (h-BN_mc).
Figure 5. Energy level diagrams and frontier molecular orbitals (HOMO and LUMO): (a) microcystin-LR (mc), (b) graphene (CC), (c) graphene with microcystin-LR (CC_mc), (d) hexagonal boron nitride (h-BN) and (e) hexagonal boron nitride with microcystin-LR (h-BN_mc).
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Figure 6. Electronic excitation spectra: (a) microcystin-LR (mc), (b) graphene (CC), (c) graphene with microcystin-LR (CC_mc), (d) hexagonal boron nitride (h-BN) and (e) hexagonal boron nitride with microcystin-LR (h-BN_mc).
Figure 6. Electronic excitation spectra: (a) microcystin-LR (mc), (b) graphene (CC), (c) graphene with microcystin-LR (CC_mc), (d) hexagonal boron nitride (h-BN) and (e) hexagonal boron nitride with microcystin-LR (h-BN_mc).
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Table 1. Reaction enthalpy (∆Hf in kcal/mol) of pesticides (dia and par) and antibiotics (oxa and cip) adsorbed by nano-systems (CC and h-BN).
Table 1. Reaction enthalpy (∆Hf in kcal/mol) of pesticides (dia and par) and antibiotics (oxa and cip) adsorbed by nano-systems (CC and h-BN).
Reaction∆Hf
(kcal/mol)
C210 H40 [CC] + C12 H21 N2 O3 S P [dia] → C222 H61 N2 O3 S P [CC_dia]−39.7466
C210 H40 [CC] + C10 H14 N O5 S P [par] → C220 H54 N O5 S P [CC_par]−41.6135
C210 H40 [CC] + C19 H19 N3 O5 S [oxa] → C229 H59 N3 O5 S [CC_oxa]−48.1507
C210 H40 [CC] + C17 H18 N3 O3 F [cip] → C227 H58 N3 O3 F [CC_cip]−54.6826
C210 H40 [CC] + C49 H75 N10 O12 [mc] → C259 H115 N10 O12 [CC_mc]−131.988
B105 N105 H40 [BN] + C12 H21 N2 O3 S P [dia] → C12 H61 N107 O3 B105 S P [BN_dia]−44.5491
B105 N105 H40 [BN] + C10 H14 N O5 S P [par] → C10 H54 N106 O5 B105 S P [BN_par]−44.2583
B105 N105 H40 [BN] + C19 H19 N3 O5 S [oxa] → C19 H59 N108 O5 B105 S [BN_oxa]−59.1402
B105 N105 H40 [BN] + C17 H18 N3 O3 F [cip] → C17 H58 N108 O3 B105 F [BN_cip]−59.1552
B105 N105 H40 [BN] + C49 H75 N10 O12 [mc] → C49 H115 N115 O12 B105 [BN_mc]−142.168
C259 H115 N10 O12 [CC_mc] + C12 H21 N2 O3 S P [dia] → C271 H136 N12 O15 S P [CC_mc_dia]−48.6947
C259 H115 N10 O12 [CC_mc] + C10 H14 N O5 S P [par] → C269 H129 N11 O17 S P [CC_mc_par]−48.7991
C259 H115 N10 O12 [CC_mc] + C19 H19 N3 O5 S [oxa] → C278 H134 N13 O17 S [CC_mc_oxa]−61.9871
C259 H115 N10 O12 [CC_mc] + C17 H18 N3 O3 F [cip] → C276 H133 N13 O15 F [CC_mc_cip]−60.1555
C49 H115 N115 O12 B105 [BN_mc] + C12 H21 N2 O3 S P [dia] → C61 H136 N117 O15 B105 S P [BN_mc_dia]−52.1374
C49 H115 N115 O12 B105 [BN_mc] + C10 H14 N O5 S P [par] → C59 H129 N116 O17 B105 S P [BN_mc_par]−53.7237
C49 H115 N115 O12 B105 [BN_mc] + C19 H19 N3 O5 S [oxa] → C68 H134 N118 O17 B105 S [BN_mc_oxa]−69.7886
C49 H115 N115 O12 B105 [BN_mc] + C17 H18 N3 O3 F [cip] → C66 H133 N118 O15 B105 F [BN_mc_cip]−65.1636
Table 2. The HSAB global descriptors in the present study.
Table 2. The HSAB global descriptors in the present study.
GAP
(eV)
I
(eV)
A
(eV)
χ
(eV)
η
(eV)
μ
(eV)
S
(eV−1)
ω
(eV)
dia8.5718.933 0.362 4.648 4.286 −4.648 0.117 2.520
par8.2179.298 1.081 5.190 4.109 −5.190 0.122 3.277
oxa8.4979.191 0.694 4.943 4.249 −4.943 0.118 2.875
cip7.9838.858 0.875 4.867 3.992 −4.867 0.125 2.967
mc7.60311.084 3.481 7.283 3.802 −7.283 0.132 6.976
CC2.5966.307 3.711 5.009 1.298 −5.009 0.385 9.665
h-BN6.0767.927 1.851 4.889 3.038 −4.889 0.165 3.934
CC_mc2.7407.621 4.881 6.251 1.370 −6.251 0.365 14.261
h-BN_mc5.8069.115 3.309 6.212 2.903 −6.212 0.172 6.646
CC_dia2.5946.316 3.722 5.019 1.297 −5.019 0.386 9.711
CC_par2.6266.343 3.717 5.030 1.313 −5.030 0.381 9.635
CC_oxa2.6546.331 3.677 5.004 1.327 −5.004 0.377 9.435
CC_cip2.6916.334 3.643 4.989 1.346 −4.989 0.372 9.248
h-BN_dia6.0737.950 1.877 4.914 3.037 −4.914 0.165 3.975
h-BN_par6.0097.933 1.924 4.929 3.005 −4.929 0.166 4.042
h-BN_oxa6.0377.945 1.908 4.927 3.019 −4.927 0.166 4.020
h-BN_cip5.9457.871 1.926 4.899 2.973 −4.899 0.168 4.036
CC_mc_dia2.7247.602 4.878 6.240 1.362 −6.240 0.367 14.294
CC_mc_par2.7227.623 4.901 6.262 1.361 −6.262 0.367 14.406
CC_mc_oxa2.7407.583 4.843 6.213 1.370 −6.213 0.365 14.088
CC_mc_cip2.7047.564 4.860 6.212 1.352 −6.212 0.370 14.271
h-BN_mc_dia5.8439.096 3.253 6.175 2.922 −6.175 0.171 6.525
h-BN_mc_par5.8089.118 3.310 6.214 2.904 −6.214 0.172 6.648
h-BN_mc_oxa5.8639.153 3.290 6.222 2.932 −6.222 0.171 6.602
h-BN_mc_cip5.8779.100 3.223 6.162 2.939 −6.162 0.170 6.460
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Chi, S.-C.; Lee, C.-L.; Chang, C.M. Adsorption of Pesticides, Antibiotics and Microcystin-LR by Graphene and Hexagonal Boron Nitride Nano-Systems: A Semiempirical PM7 and Theoretical HSAB Study. Crystals 2022, 12, 1068. https://doi.org/10.3390/cryst12081068

AMA Style

Chi S-C, Lee C-L, Chang CM. Adsorption of Pesticides, Antibiotics and Microcystin-LR by Graphene and Hexagonal Boron Nitride Nano-Systems: A Semiempirical PM7 and Theoretical HSAB Study. Crystals. 2022; 12(8):1068. https://doi.org/10.3390/cryst12081068

Chicago/Turabian Style

Chi, Shu-Chun, Chien-Lin Lee, and Chia Ming Chang. 2022. "Adsorption of Pesticides, Antibiotics and Microcystin-LR by Graphene and Hexagonal Boron Nitride Nano-Systems: A Semiempirical PM7 and Theoretical HSAB Study" Crystals 12, no. 8: 1068. https://doi.org/10.3390/cryst12081068

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