Physica E 116 (2020) 113735
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Physica E: Low-dimensional Systems and Nanostructures journal homepage: http://www.elsevier.com/locate/physe
Interaction of nitrotyrosine with aluminum nitride nanostructures: A density functional approach Zahra Rostami a, *, Maryam Maskanati b, Salah Khanahmadzadeh c, Mohammad Dodangi d, Milad Nouraliei e a
Department of Chemistry, Payame Noor University (PNU), P.O. Box, 19395-3697, Tehran, Iran Department of Chemistry, North Tehran Branch, Islamic Azad University, Tehran, Iran Department of Chemistry, Mahabad Branch, Islamic Azad University, PO Box,443, Mahabad, Iran d Department of Chemistry, Central Tehran Branch, Islamic Azad University, Tehran, Iran e Young Researchers and Elite Club, Central Tehran Branch, Islamic Azad University, Tehran, Iran b c
A R T I C L E I N F O
A B S T R A C T
Keywords: AlN nanostructures Nitrotyrosine Biosensor Density functional theory
We investigated the adsorption of nitrotyrosine on the AlN nanostructures including zero-dimensional nano cluster, one-dimensional nanotube, and two-dimensional nanosheet using density functional theory calculations. Density functional theory calculations were performed for calculation of adsorption energy, energy band gap, changes in the energy band gap, charge transfers, and nature of interactions; upon adsorption of nitrotyrosine on the AlN nanostructures. In order to go further and gain insight into the binding features of considered AlN nanostructures with nitrotyrosine, the Atoms in Molecules analysis was performed. Our results determine the electrostatic features of the nitrotyrosine/AlN nanosheet bonding. Also, when the nitrotyrosine is adsorbed on the AlN nanostructures, their electrical conductivity is increased, revealing that the AlN nanomaterials can yield an electronic signal at the presence of this modified amino acid and can be utilized as chemical sensors. The order of sensitivity is as follows: AlN nanosheet > AlN nanotube > AlN nanocluster. Our results show that among the AlN nanostructures, the AlN nanosheet may be a promising candidate for detection of nitrotyrosine.
1. Introduction Recently, III-V nanomaterials including nanoclusters, nanowires, nanotubes, nanocones, and nanosheets have attracted wide interests [1–5] due to their intersting properties. Among various nanomaterials, aluminum nitride (AlN) nanostructures show more technological ap plications due to their superior electrical and structural properties [6,7]. Recently, there have been several studies on the synthesis and novel properties of AlN nanomaterials [8–10]. Previously, the AlN nanotubes (AlNNTs) with diameter ranging from 30 to 80 nm has been synthesized [11]. Also, the synthesis of AlNNTs with high efficient approaches has been reported in the recent studies [12–14]. Zhang et al. [15] also revealed that the AlN nanotubes (AlNNTs) are energetically stable with sp2 hybridization for both aluminum and nitrogen atoms [16]. The fullerene-like (AlN)n (n ¼ 2–41) nanoclusters (AlNNCs) were also stud ied and it was revealed that the (AlN)12 is the most stable nanocluster in this class [17]. Two-dimensional (2D) nanosheet materials have attracted huge interests due to their performances in technological
applications [18–20]. Accordingly, many attempts have been recently dedicated to synthesis of AlN nanosheets (AlNNSs) [21–27]. Nitrotyrosine is a modified amino acid with superior properties than tyrosine or any other of the genetically encoded amino acids. The rule of nitrotyrosine in various diseases such as Parkinson’s and Alzheimer’s has been recently revealed [28,29]. Therefore, sensing of nitrotyrosine during biological procedures is an important step in diagnosis of pro gressive disease. Recently, the feasibility of utilizing nanostructures as bio-detectors for nitrotyrosine detection has been investigated theoret ically [30,31]. The studies reveal that the electronic properties of these nanostructures are very sensitive to the presence of nitrotyrosine. Accordingly, recent researches exhibit that the carbon-base nano structures are suitable biosensors for detection of nitrotyrosine. In continuation of recent studies, here we investigate the potential application of three types of AlN nanomaterials including nanocluster, nanotube, and nanosheet in detection of nitrotyrosine amino acid using density functional theory (DFT) calculations. The main objective of the present study is to explore theoretically nitrotyrosine/AlN systems to
* Corresponding author. E-mail address:
[email protected] (Z. Rostami). https://doi.org/10.1016/j.physe.2019.113735 Received 20 July 2019; Received in revised form 7 September 2019; Accepted 21 September 2019 Available online 26 September 2019 1386-9477/© 2019 Elsevier B.V. All rights reserved.
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Fig. 1. The optimized structures of pristine AlNNC, AlNNT, AlNNS nanomaterials, and nitrotyrosine.
search the possibility of controlled detection of nitrotyrosine. The values of adsorption energy, molecular electrostatic potentials, electronic properties, density of states, and ultraviolet–visible (UV–Vis) spectra of the systems were calculated and analyzed. Moreover, properties extracted from the quantum theory of atoms in molecules (QTAIM) were utilized to determine the nature of interactions.
atomic energy and the amount of atoms type i (i ¼ Al and N), and j is the total number of atoms present in the AlN systems. Moreover, the highest occupied molecular orbital-lowest unoccupied molecular orbital energy gap (HOMO-LUMO energy gap (Eg)) has been calculated for investi gating the effect of nitrotyrosine adsorption on the electronic properties of the considered AlN nanomaterials. Also, natural bond orbital (NBO) charge analysis [36] has been performed for calculating charge transfer between AlN and nitrotyrosine molecule. In order to gain further in sights into the nature of interactions in the considered complexes, QTAIM analysis was also performed using AIMALL package [37], and the corresponding wave functions were generated at the PBE/6-31 þ G (d) level of theory.
2. Computational details DFT calculations have been performed to obtain a better under standing for geometry relaxation and energetic analyses of nitrotyrosine on the AlN nanomaterials. The generalized-gradient approximation (GGA) of Perdew, Burke, and Ernzerh (PBE) [32] of exchange-correlation functional along with the dispersion correction introduced by Grimme (PBE þ D3) is performed for geometry optimi zation and electronic properties calculation [33]. Our calculations were performed using Gaussian 09 software [34] by employing 6–31 þ G(d) basis set. To verify that the optimized geometries correspond to the local minima, the vibrational frequency calculation was performed. The adsorption energy (Eads) of a nitrotyrosine was measured as the energy difference between the optimized nitrotyrosine/AlN complexes and the assembly of the isolated AlN and nitrotyrosine. The negative Eads values verify the favorable adsorption configuration and, hence, the smallest Eads value corresponds to the most stable adsorption geometry. Furthermore, cohesive energy (Ecoh) was calculated; it is a well-accepted parameter to evaluate the feasibility for the experimental synthesis of the predicted AlN nanomaterials [35]. Ecoh of the AlNNC, AlNNT, and AlNNS materials was calculated using the following formula: �. � X j (1) ECoh ¼ Etot ni Ei
3. Results and discussion 3.1. Structural and electronic properties of pristine AlNNC, AlNNT, and AlNNS The optimized structures of the AlN nanostructures and nitrotyrosine are represented in Fig. 1. As shown in this figure, the Al12N12 nano cluster has been made of 8 hexagons and 6 tetragons with Th symmetry. The angles in tetragons and hexagons vary from 86� to 92� and from 114� to 124� , respectively. Structurally, two different Al–N bonds are recognized in the AlNNC; one is shared by two hexagons (1.81 Å) and another between a hexagon and a tetragon (1.88 Å). AlNNT is a (5,0) zigzag tube with the length and dimeter of 16.76 Å and 5.39 Å, respec tively (Fig. 1). Two kinds of the Al–N bonds can be recognized along the tube which one is parallel with the tube axis with length of 1.83 Å and another is diagonal with length of 1.84 Å. Fig. 1 also shows that AlNNS is formed from 27 Al, 27 N, and 18 H atoms. The equilibrium Al–N bond length of AlNNS is in the range of 1.81–1.83 Å. Due to the absence of PBC in molecular calculations, it was necessary to saturate the dangling
i
where Etot, Ei, and ni being the total energy of the AlN nanomaterials, the 2
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Fig. 2. DOS spectrums for the pristine AlNNC (a), AlNNT (b), and AlNNS (C). The arrows indicate the Eg values of the AlN nanomaterials.
Fig. 3. ESP analysis and the HOMO and LUMO of the pristine AlN nanomaterials.
Al and N bonds in the AlNNT and AlNNS with H atoms. Moreover, we calculated the cohesive energies based on the defini tion in Eq. (1). The calculated Ecoh show the feasibility for the experi mental synthesis of the predicted AlN nanomaterials. The calculated cohesive energies for the AlNNC, AlNNT, and AlNNS nanomaterials are respectively, 5.71 eV, 6.13 eV, and 10.80 eV. We note that the calculated cohesive energies for AlNNC and AlNNT are significantly lower than the AlN bulk (Ecoh ¼ ~ 11 eV) [38] and AlNNS. In fact, the Ecoh for AlN nanocluster and nanotube were lower than that for the AlN bulk and AlN sheet, and this implies the difficulty in producing AlN nanoclusters and nanotubes. Our calculations also present that the Eg values of 3.55 eV, 4.10 eV, and 4.73 eV, for the AlNNC, AlNNT, and AlNNS, respectively. The density of state (DOS) spectrum of the three types of AlN nanomaterials are represented in Fig. 2. The results suggest that the AlN nanomaterials are typical semiconductors with a wide Eg values. For the AlNNC, valence and conduction levels shift to higher and
lower energies, respectively, leading to significant reduction of the nanocluster’s Eg. All in all, the relative order of Eg of the considered AlN nano structures is as follows: AlNNS > AlNNT > AlNNC. It has been recently revealed that the Eg can be related to the kinetic stability of the nano materials and larger Eg shows higher kinetic stability [39]. It is worth pointing out that the obtained results are in agreement with the stability trends reported by previous studies [40]. The electrostatic potential (ESP) maps over AlN systems are shown in Fig. 3. In the ESP maps, the red (negative areas) and blue (positive areas) colors depict the relative accumulation and depletion of charge density, respectively. The ESP maps show (Fig. 3) that the Al atoms of considered systems are the most favorable places for the attraction of nucleophilic agents. The top-views of frontier molecular orbital (FMO) analysis of the pristine AlN nanomaterials are also shown in Fig. 3. This figure clearly shows that the LUMOs of the studied systems are predominantly 3
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Fig. 4. The contour plot of electron density for the ALNNC (a), ALNNT (b), and AlNNS (C).
Fig. 5. The most stable configurations of the adsorbed nitrotyrosine on the surface of AlNNC (a), AlNNT (b), and AlNNS (c).
distributed on the Al atoms. Consequently, in line with the ESP analysis, the favorable areas of Al atoms in the AlN nanomaterials for the attraction of nucleophilic species has also been demonstrated by the FMO analyses. Also, we have performed the NBO calculation on the AlNNC, AlNNT, and AlNNS. The NBO atomic charges on the Al atoms of the AlNNC, AlNNT, and AlNNS nanomaterials are þ1.10 e, þ1.22 e, and þ1.31 e, respectively. This shows that a notable charge transfers from Al atoms towards the N atoms in the AlN systems. The contour plot of electron density for the AlNNC, AlNNT, and AlNNS nanostructures are also represented in Fig. 4. The contour plot of electron density analysis is a useful analysis to estimate the reactive places on the molecular sur faces based on the distribution of charge density [41]. As shown in this figure, the charge density in the AlN nanostructures are located on the N atoms. Accordingly, the favorable sites of Al atoms in the AlN nanomaterials for the attraction of nucleophilic species has also been demonstrated by the contour plot of electron density analysis.
the various initial orientations are given in the Supplementary Material (Fig. S1). The most stable structures, the shortest distances between AlN systems and nitrotyrosine, and the Eads values are represented in Fig. 5. As exhibited in this figure, nitrotyrosine in optimized geometries shows the highest propensity to interaction with the Al and N atoms of the AlN nanostructures, which is in agreement with ESP and FMO an alyses (Fig. 3). The interaction distances for the nitrotyrosine/AlNNC, nitrotyrosine/AlNNT, and nitrotyrosine/AlNNS complexes are shown in Fig. 5, which for the nitrotyrosine/AlNNS are approximately small and determine that adsorption can be chemical. On the other side, our results show a relatively large value for the interaction distance in the nitro tyrosine/AlNNC and nitrotyrosine/AlNNT complex and reveal that the adsorption can be physisorption. The results show that the AlN nano materials interact with nitrotyrosine with adsorption energies of 4.23, 5.96, and 8.71 eV, respectively. The high adsorption energies of the nitrotyrosine adsorbed on the AlN nanosheet lead to chemisorption of molecule on the surface of considered system. It can be interpreted by the shorter interaction distance between the N, O, and H atoms of nitrotyrosine and the Al and N atoms of the AlNNS in the corresponding complex. This evidence suggests that the AlNNS can be better for adsorption of nitrotyrosine. It is worth pointing out that the obtained result is consistent with the reactivity trends projected by the ESP, FMO, and NBO analyses. In fact, the maximum Eads value for the nitrotyrosine/ AlN complexes is related to the system with the maximum positive charge on the Al atoms which had been predicted as the most favorable site for the nucleophilic agents. In order to explore the solvent effect, the adsorption of nitrotyrosine on the AlN nanostructures in the aqueous
3.2. Nitrotyrosine adsorption on the AlN nanomaterials 3.2.1. Energetic analysis In order to decide the most stable adsorption configurations on the surface of studied AlN nanomaterials, diverse initial configurations were tested [42] which is ascribed to locating the oxygen and nitrogen atoms of nitrotyrosine molecule above the different places with respect to the nanomaterials including the center of tetragonal, and hexagonal rings and top of Al and N atoms of the AlNNC, AlNNT, and AlNNS. The optimized geometries of the nitrotyrosine/AlN complexes obtained from 4
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nitrotyrosine/AlN complexes are calculated at PBE/6–31 þ g(d) level of theory. Table 1 lists the most important transitions (highest oscillator strengths (f)) for the considered systems. As results show, the maximum absorption wavelength (λ) exist in the spectrum of pristine AlNNC, AlNNT, and AlNNS are placed at 544 nm, 661 nm, and 502 nm with f values of 0.0530, 0.0670, and 0.0512, respectively (Table 1). The peaks observed at λ are dominantly due to the HOMO→LUMO transitions. After the adsorption of nitrotyrosine on the surface of AlN nanostructures, absorption bands of pristine AlN get shifted to the higher wavelength area. Therefore, our results show that the electronic spectra of nitrotyrosine/AlN complexes exhibit a red shift toward higher wavelengths (lower energies). The maximum red shift (64 nm) is related to the nitrotyrosine/AlNNS complex compared to the original parent nanosheet. 3.2.3. AIM analysis AIM is a powerful technique to estimate intermolecular interactions that it identifies bond critical point (BCP) between interactive systems through the topological parameters. The BCPs were placed and extrac ted the charge density (ρc) and the Laplacian of charge density (r2 ρc ) at each of them to allow the decision on the nature of interactions. The energetic properties of BCPs are often considered as the electron energy density at BCP (HC). It should be noted that the HC is sum of two pa rameters: the kinetic electron energy density (KC) and the potential electron energy density (VC). Also, the negative value of the r2 ρc at BCP reveals the concentration of the electron charge among the nuclei of the interacting atoms and it shows covalent bonds-shared interactions. The application of AIM to our complexes can be useful to analysis the nitrotyrosine/AlN interaction topology of our systems. Molecular graphs of the optimized nitrotyrosine/AlN complexes are represented in Fig. 8. From the results in Table 2, for the nitrotyrosine/AlN complexes, the calculated values of ρc in BCPs are in the range 0.0100–0.0637 a.u., whereas the values of r2 ρc are between 0.0410 and 0.6162 a.u. The results show that the calculated electron density properties of the nitrotyrosine/AlN complexes determine that Al⋯N, Al⋯O, and N⋯H bonds possess large charge density, and positive r2 ρc value. These properties rationalize electrostatic features of the Al⋯O bonding. It is obvious that in the case of positive r2 ρc and negative HC, the interaction
Fig. 6. Comparative analysis of the Eads values for the nitrotyrosine/AlN complexes computed in gas phase (white) and solution (black).
phase were also investigated. The effect of the solvent (water with ε ¼ 78.4) was calculated using polarized continuum model (PCM) more specifically; the integral-equation formalism [43]. Fig. 6 shows a comparative analysis of the Eads values of the nitrotyrosine/AlN com plexes computed in gas phase and solution. The results show (Fig. 6) that all the energies in gas phase (white) and aqueous phase (black) are negative and, so, the complexes are sta ble. The higher value of adsorption energies (more negative) in the solvent phase reveals that the AlN nanostructures can increase their solubility and modify their interaction with the. To verify the effects of the nitrotyrosine on the electronic properties of the AlN nanostructures, the corresponding partial density of state (PDOS) spectrums have been presented in Fig. 7. As results show, in the AlNNC and after nitrotyrosine adsorption, the HOMO and LUMO levels of nanocluster change slightly and conse quently its Eg value are almost unchanged (Eg ¼ 3.50 eV). On the other hand, in the nitrotyrosine/AlNNT and nitrotyrosine/AlNNS complexes, valence and conduction levels shift to higher and lower energies, respectively. Consequently, the Eg values of the AlNNT and AlNNS decrease as compared to their pristine counterparts. The calculated Eg of the nitrotyrosine/AlNNT and nitrotyrosine/AlNNS are, respectively, 3.93 and 3.77 eV. Consistent with the large adsorption energy, very large change in the Eg after adsorption (%ΔEg) indicates that the nitrotyrosine adsorption induces deep effect on the electronic structures of AlNNS (ΔEg ¼ 20%). The ΔEg for the nitrotyrosine/AlNNC and nitrotyrosine/AlNNT are, respectively, 1.4% and 4.1%. However, considerable change of about 20% in the Eg value for the nitrotyrosine/ AlNNS demonstrates the high sensitivity of the electronic properties of AlNNS toward the nitrotyrosine adsorption.
Table 1 Calculated maximum absorption wavelength (λ), oscillator strengths (f), and dominant transition contribution for the pristine AlN nanomaterials as well as nitrotyrosine/AlN complexes.
3.2.2. UV–vis spectra The UV–vis spectra of the pristine AlN nanomaterials as well as
Molecule
λ (nm)
f
Major contribution
AlNNC Nitrotyrosine/AlNNC AlNNT Nitrotyrosine/AlNNT AlNNS Nitrotyrosine/AlNNS
544 560 661 695 502 566
0.0530 0.0426 0.0670 0.0526 0.0512 0.0701
HOMO→LUMO HOMO→LUMO HOMO→LUMO HOMO→LUMO HOMO→LUMO HOMO→LUMO
(78%) (60%) (71%) (57%) (75%) (66%)
Fig. 7. PDOS spectrums for the nitrotyrosine/AlNNC (a), nitrotyrosine/AlNNT (b), and nitrotyrosine/AlNNS (c) complexes. The arrows indicate the change of the state’s location after nitrotyrosine adsorption. 5
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Fig. 8. Molecular graph of the nitrotyrosine/AlNNC (a), nitrotyrosine/AlNNT (b), and nitrotyrosine/AlNNS (c) complexes. Large circles correspond to attractors and small red circles are bond critical points. The lines are bond paths. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) Table 2 Topological parameters at BCP of interaction contacts in considered nitrotyrosine/AlN complexes (au). Complexes
Bond
ρc
r 2 ρc
Kc
nitrotyrosine/AlNNC
Al⋯N Al⋯O N⋯O N⋯H N⋯H Al⋯O Al⋯O Al⋯O N⋯H N⋯H Al⋯O Al⋯O Al⋯O Al⋯O Al⋯O N⋯H N⋯H
0.0488 0.0530 0.0100 0.0120 0.0343 0.0471 0.0452 0.0260 0.0119 0.0118 0.0492 0.0519 0.0396 0.0548 0.0355 0.0637 0.0102
0.3710 0.4650 0.0447 0.0458 0.1094 0.4107 0.3803 0.0724 0.0451 0.0410 0.4430 0.4880 0.3089 0.5167 0.2455 0.6162 0.0335
0.0818 0.1044 0.0095 0.0095 0.0086 0.0902 0.0835 0.1383 0.0094 0.0307 0.0972 0.1069 0.0674 0.114 0.0539 0.0201 0.0067
nitrotyrosine/AlNNT
nitrotyrosine/AlNNS
is partly covalent in nature, but in case of positive HC the nature of interaction is electrostatic. Therefore, the studied complexes have r2 ρc > 0 and HC < 0 which indicate that, all Al⋯O bonds in the nitrotyrosine/ AlNNS are a polar covalent bond. Moreover, for interacting areas in the nitrotyrosine/AlNNC and nitrotyrosine/AlNNT, both r2 ρc and HC are positive and HC/|VC| ratios are greater than 1 suggesting weakly bonded interactions with non-covalent nature. On the other hand, the negative sign of HC and HC/|VC|<1 for the Al⋯O interactions are indicator of a stronger interaction with partially covalent character. The large negative values of Eads for nitrotyrosine/ AlNNS complex (Fig. 4) are consistent with the strong interaction as predicted by the AIM topological parameters. The large ρ values (Table 2) for the nitrotyrosine/AlNNS complex show that there is a strong interaction between the Al⋯O in the nitrotyrosine/AlNNS com plex. It is worth pointing out that the obtained AIM results for the nitrotyrosine/AlNNS complex are consistent with the interaction trends projected by Eads, ESP, and FMO analyses.
VC 0.0709 0.0925 0.0078 0.0077 0.0089 0.0778 0.072 0.1226 0.0096 0.034 0.0937 0.0984 0.0675 0.0999 0.0565 0.0221 0.005
between two adjacent is defined by � rffiffiffiffiffiffiffiffiffiffiffiffiffiffi � π λ exp k ¼ t2 4kB T ℏ2 kB Tλ
Hc
KC/|Vc|
0.0109 0.0118 0.0016 0.0018 0.0033 0.0124 0.0115 0.0157 0.0018 0.0016 0.0134 0.0150 0.0098 0.0151 0.0074 0.0020 0.0016
1.1537 1.1286 1.2179 1.2338 0.9663 1.1594 1.1597 1.1281 0.9792 0.9029 1.0374 1.0864 0.9985 1.1411 0.9540 0.9095 1.3400
(2)
Here, t is the inter-molecular transfer integral, λ is the reorganization energy, ℏ is the Planck constant, kB is the Boltzmann constant and T is the temperature (298 K, in the present study). The reorganization energy (λ) for the self-exchange hole and electron transfer processes can be computed using the Nelsen’s four-point method [47]. � � λ� ¼ E � E� Eo � (3) o � þ ½E� where λþ and λ are the hole and electron reorganization energy, respectively. E� o is the energy of the cation or anion computed with the optimized structure of the neutral molecule, E� � is the energy of the cation or anion calculated with the optimized cation or anion structure, E� is the energy of the neutral molecule calculated at the cationic or anionic state, and Eo is the energy of the neutral molecule at ground state. The absolute value of the transfer integral (t) for electron [hole] transfer is also calculated
3.2.4. Carrier mobility Our results suggest that AlNNS is the best candidate for detection of nitrotyrosine. Accordingly, we study the hole and electron mobilities for the dimer of AlNNS. Carrier mobility is one of the most important pa rameters that should be considered in conductivity of material [44,45]. Using the Marcus theory [46], the rate constant for the charge hopping
t¼
ELþ1½H�
EL½H
where ELþ1½H� and EL½H 6
(4)
1�
2 1�
are the energies of the LUMOþ1 and LUMO
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Fig. 9. Top and side views of the optimized structures for the stacked pattern and the HOMO and LUMO distributions of the AlNNS dimer. Table 3 Charge transport parameters of the AlNNS. AlNNS
1
tþ (eV)
λþ (eV)
kþ (s
)
0.001
0.261
1.20 � 109
μþ (cm2/Vs)
t (eV)
λ (eV)
k (s 1)
μ (cm2/Vs)
0.001
0.012
0.114
2.73 � 1012
2.038
[HOMO and HOMO-1] in the closed-shell configuration of the neutral state, respectively. Using the Einstein equation, the hole and electron mobility (μþ and μ ) can be obtained from following equation [48].
μ¼
e D kB T
electron (λ ̶ ¼ 0.114 eV) and high transfer integral of electron (t ̶ ¼ 0.012 eV), represents the high electron transfer rates and electron mobility. Furthermore, because t ̶ in AlNNS is larger than tþ, then, higher k ̶ and μ ̶ are induced; hence, the electron transport is more efficient than the hole. On the basis of these achievements, we conjecture that the adsorbing nitrotyrosine on the AlNNS can significantly affect the elec tron transport of the AlNNS.
(5)
kB is the Boltzmann constant, T is the temperature, e is the electronic charge, and D is the diffusion coefficient which can be obtained from the Einstein-Smoluchowski relation [49]. D¼
R2 k 2
4. Conclusion We investigated the electronic sensitivity of AlN nanotube, AlN nanosheet, and AlN nanocluster toward nitrotyrosine using DFT calcu lations. The AlN energy gap values are calculated to be ~4 eV. Furthermore, upon the interaction of nitrotyrosine, the electronic properties of AlN nanostructures changes, which are observed from the DOS plot. Among tested AlN nanostructures, the most pronounced effect of nitrotyrosine adsorption has been observed on the electronic structure of AlN nanosheet (%ΔEg ¼ 20). The changes in the electronic charac teristics confirm the strong interaction of nitrotyrosine with AlNNS. In addition, the solvent effect of nitrotyrosine is also studied. Also, the nature of intermolecular interactions is investigated by QTAIM analysis. It is worth pointing out that the QTAIM result is consistent with the reactivity trends projected by the Eads, ESP, FMO, and NBO analyses. In fact, the strongest electrostatic features of the nitrotyrosine/AlN bonding is related to the system with the maximum positive charge on the Al atom, highest Eads value which had been predicted as the most favorable site for the nucleophilic agents. From the overall results, the findings suggested that AlN nanosheet is a promising candidate for detection of nitrotyrosine.
(6)
where R is the effective length of the charge transfer approximated by the molecular center-to-center distance of a dimer. As shown in Fig. 9, the optimized structure of AlNNS dimer form face-to-face π-stacking arrangements. Moreover, the distance between the two layer is small in AlNNS (2.10 Å), indicating the strong Al⋅⋅⋅N interaction. To obtain further insight into the electronic structures of considered dimer, the HOMO and LUMO energy levels are depicted in Fig. 9. For the AlNNS dimer, the LUMO shape indicates a diffused electron distribution. The delocalization of the LUMO throughout the whole conjugated system suppresses the carrier recombination, which facili tates the electron movement. Moreover, this strong interlayer orbital overlap in LUMO offers that AlNNS should be a good candidate for ntype semiconductors because the LUMO is believed to be important in electron transport [45]. Table 3 lists the computed charge transport properties of the AlNNS. Calculated properties for hole and electron are shown by “þ” and “ ̶ “signs. As Table 3 shows, the AlNNS with low reorganization energy for 7
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Acknowledgement
[21] M. Ishihara, T. Manabe, T. Kumagai, T. Nakamura, S. Fujiwara, Y. Ebata, S.i. Shikata, H. Nakahata, A. Hachigo, Y. Koga, Synthesis and surface acoustic wave property of aluminum nitride thin films fabricated on silicon and diamond substrates using the sputtering method, Jpn. J. Appl. Phys. 40 (2001) 5065. [22] R. Yakimova, A. Kakanakova-Georgieva, G.R. Yazdi, G.K. Gueorguiev, M. Syv€ aj€ arvi, Sublimation growth of AlN crystals: growth mode and structure evolution, J. Cryst. Growth 281 (2005) 81–86. [23] A. Kakanakova-Georgieva, G.K. Gueorguiev, R. Yakimova, E. Janz�en, Effect of impurity incorporation on crystallization in AlN sublimation epitaxy, J. Appl. Phys. 96 (2004) 5293–5297. [24] A. Omidvar, Edge-functionalized graphene nanoflakes as selective gas sensors, Sens. Actuators B Chem. 202 (2014) 622–630. [25] A. Omidvr, Electronic structure tuning and band gap opening of nitrogen and boron doped holey graphene flake: the role of single/dual doping, Mater. Chem. Phys. 202 (2017) 258–265. [26] A. Omidvar, Reversible hydrogen adsorption on Co/N4 cluster embedded in graphene: the role of charge manipulation, Chem. Phys. 493 (2017) 85–90. [27] A. Omidvar, Charge-controlled switchable CO adsorption on FeN4 cluster embedded in graphene, Surf. Sci. 668 (2018) 117–124. [28] N. Abello, H.A.M. Kerstjens, D.S. Postma, R. Bischoff, Protein tyrosine nitration: selectivity, physicochemical and biological consequences, denitration, and proteomics methods for the identification of tyrosine-nitrated proteins, J. Proteome Res. 8 (2009) 3222–3238. [29] J.M. Souza, G. Peluffo, R. Radi, Protein tyrosine nitration-functional alteration or just a biomarker, Free Radic. Biol. Med. 45 (2008) 357–366. [30] N. Ding, X. Lu, C.-M. Lawrence, Wu, Nitrated tyrosine adsorption on metaldoped graphene: a DFT study, Comput. Mater. Sci. 51 (2012) 141–145. [31] R. Majidi, A.R. Karami, Nitrotyrosine adsorption on carbon nanotubes: a density functional theory study, Indian J. Phys. 88 (2014) 483–487. [32] J. P Perdew, K. Burke, M. Ernzerhof, Generalized gradient approximation made simple, Phys. Rev. Lett. 77 (1996) 3865–3868. [33] S. Grimme, Semiempirical GGA-type density functional constructed with a longrange dispersion correction, J. Comput. Chem. 27 (2006) 1787. [34] M.J. Frisch, G.W. Trucks, H.B. Schlegel, G.E. Scuseria, M.A. Robb, J.R. Cheeseman, et al., Gaussian 09, Revision D.01, Gaussian, Inc., Wallingford, CT, 2009. [35] T. Li, C. He, W. Zhang, A novel porous C4N4 monolayer as a potential anchoring material for lithium-sulfur battery design, J. Mater. Chem. A 7 (2019) 4134–4144. [36] A.E. Reed, L.A. Curtiss, F.A. Weinhold, Intermolecular interactions from a natural bond orbital, donor-acceptor viewpoint, Chem. Rev. 88 (1998) 899–926. [37] K.F. Biegler, J. Schnbohm, D. Bayles, A Program to Analyze and Visualize Atoms in Molecules, 2001. [38] C. Stampfl, C.G. Van de Walle, Density-functional calculations for III-V nitrides using the local-density approximation and the generalized gradient approximation, Phys Rev. B 59 (1999) 5521–5535. [39] J.-i. Aihara, Reduced HOMO-LUMO gap as an index of kinetic stability for polycyclic aromatic hydrocarbons, J. Phys. Chem. A 103 (1999) 7487–7495. [40] A. Hosseinian, E. Vessally, A. Bekhradnia, K. Nejati, G. Rahimpour, Benzoylethanamine drug interaction with the AlN nanosheet, nanotube and nanocage: density functional theory studies, Thin Solid Films 640 (2017) 93–98. [41] C. He, J.H. Zhang, W.X. Zhang, T.T. Li, Type-II InSe/g-C3N4 heterostructure as a high-efficiency oxygen evolution reaction catalyst for photoelectrochemical water splitting, J. Phys. Chem. Lett. 10 (2019) 3122–3128. [42] T.T. Li, C. He, W.X. Zhang, Electric field improved the sensitivity of CO on substitutionally doped antimonene, Appl. Surf. Sci. 427 (2018) 388–395. [43] J. Tomasi, B. Mennucci, R. Cammi, Quantum mechanical continuum solvation models, Chem. Rev. 105 (2005) 2999–3094. [44] M.M. Dong, C. He, W.X. Zhang, A tunable and sizable bandgap of a g-C3N4/ graphene/g-C3N4 sandwich heterostructure: a van der Waals density functional study, J. Mater. Chem. C 5 (2017) 3830–3837. [45] A. Mohajeri, A. Omidvar, H. Setoodeh, Fine structural tuning of thieno[3,2-b] pyrrole donor for designing banana-shaped semiconductors relevant to organic field effect transistors, J. Chem. Inf. Model. 59 (2019) 51930–51945. [46] R.A. Marcus, On the theory of oxidation-reduction reactions involving electron transfer, J. Chem. Phys. 24 (1956) 966–978. [47] S.F. Nelsen, M.J.R. Yunta, Estimation of Marcus λ for p-phenylenediamines from the optical spectrum of a dimeric derivative, J. Phys. Org. Chem. 7 (1994) 55–62. [48] Y. Geng, H. Li, S. Wu, Y. Duan, Z. Su, Y. Liao, The influence of thienyl-S, sdioxidation on the photoluminescence and charge transport properties of dithienothiophenes: a theoretical study, Theor. Chem. Acc. 129 (2011) 247–255. [49] P.W. Atkins, Physical Chemistry, fifth ed., Oxford University Press, Oxford, U.K., 1994.
The authors are grateful to Payame Noor University-Iran for computational resources and financial supports. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.physe.2019.113735. References [1] M. Machado, R. Mota, P. Piquini, Electronic properties of BN nanocones under electric fields, Microelectron. J. 34 (2003) 545–547. [2] A. Omidvar, Catalytic activation of O2 molecule by transition metal atoms deposited on the outer surface of BN nanocluster, J. Mol. Graph. Model. 77 (2017) 218–224. [3] J. Beheshtian, M. Kamfiroozi, Z. Bagheri, A. Ahmadi, B12N12 nano-cage as potential sensor for NO2 detection, Chin. J. Chem. Phys. 25 (2012) 60–64. [4] A. Omidvar, Design of a novel series of donor-acceptor frameworks via superalkalisuperhalogen assemblage to improve the nonlinear optical responses, Inorg. Chem. 57 (2018) 9335–9347. [5] A. Omidvar, Catalytic role of transition metals supported on niobium oxide in O2 activation, Appl. Surf. Sci. 434 (2018) 1239–1247. [6] V.N. Tondare, C. Balasubramanian, S.V. Shende, D.S. Joag, V.P. Godbole, S. V. Bhoraskara, Field emission from open ended aluminum nitride nanotubes, Appl. Phys. Lett. 80 (2002) 4813–4815. [7] Q. Wu, Z. Hu, X. Wang, Y. Lu, K. Huo, S. Deng, N. Xu, B. Shen, R. Zhang, Y. Chen, Extended vapor–liquid–solid growth and field emission properties of aluminium nitride nanowires, J. Mater. Chem. 13 (2003) 2024–2027. [8] C. Liu, Z. Hu, Q. Wu, X. Wang, Y. Chen, H. Sang, J. Zhu, S. Deng, N. Xu, Vaporsolid growth and characterization of aluminum nitride nanocones, J. Am. Chem. Soc. 127 (2005) 1318–1322. [9] C. Liu, Z. Hu, Q. Wu, X. Wang, Y. Chen, W. Lin, H. Sang, S. Deng, N. Xu, Synthesis and field emission properties of aluminum nitride nanocones, Appl. Surf. Sci. 251 (2005) 220–224. [10] W. Qian, Y. Zhang, Q. Wu, C. He, Y. Zhao, X. Wang, Z. Hu, Construction of AlNbased core- shell nanocone arrays for enhancing field emission, J. Phys. Chem. C 115 (2011) 11461–11465. [11] V. Tondare, C. Balasubramanian, S. Shende, D. Joag, V. Godbole, S. Bhoraskar, M. Bhadhade, Field emission from open ended aluminum nitride nanotubes, Appl. Phys. Lett. 80 (2002) 4813. [12] C. Balasubramanian, S. Bellucci, P. Castrucci, M. Crescenzi, S. Bhoraskar, Scanning tunneling microscopy observation of coiled aluminum nitride nanotubes, Chem. Phys. Lett. 383 (2004) 188–191. [13] B. Yin, Y. Bando, Y. Zhu, M. Li, C. Tang, D. Golberg, An ultraviolet organic thinfilm solid-state laser for biomarker applications, Adv. Mater. 17 (2005) 31–34. [14] G. Stan, C.V. Ciobanu, T.P. Thayer, G.T. Wang, J.R. Creighton, K.P. Purushotham, L.A. Bendersky, R.F. Cook, Elastic moduli of faceted aluminum nitride nanotubes measured by contact resonance atomic force microscopy, Nanotechnology 20 (2009) 35706. [15] D. Zhang, R. Zhang, Chem. Theoretical prediction on aluminum nitride nanotubes, Phys. Lett. 371 (2003) 426–432. [16] W.H. Goh, G. Patriarche, P.L. Bonanno, S. Gautier, T. Moudakir, M. Abid, G. Orsal, A.A. Sirenko, Z.H. Cai, A. Martinez, A. Ramdane, L. Le Gratiet, D. Troadec, A. Soltani, A. Ougazzaden, Structural and optical properties of nanodots, nanowires, and multi-quantum wells of III-nitride grown by MOVPE nano-selective area growth, J. Cryst. Growth 315 (2011) 160–163. [17] J. Beheshtian, A.A. Peyghan, Z. Bagheri, Selective function of Al12N12 nano-cage towards NO and CO molecules, Comput. Mater. Sci. 62 (2012) 71–74. [18] A. Omidvar, Electronic structure tuning and band gap opening of nitrogen and boron doped holey graphene flake: the role of single/dual doping, Mater. Chem. Phys. 202 (2017) 258–265. [19] A. Omidvar, Dissociation of O2 molecule on Fe/Nx clusters embedded in C60 fullerene, carbon nanotube and graphene, Synth. Met. 234 (2017) 38–46. [20] A. Omidvar, Borophene: a novel boron sheet with a hexagonal vacancy offering high sensitivity for hydrogen cyanide detection, Computational and Theoretical Chemistry 1115 (2017) 179–184.
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