Ecofriendly carbon doping nanomaterials for a breakthrough in detecting and removing toxic gases (NO/NO₂/N₂O)

ABSTRACT

In this paper, the electronic, magnetic, and thermodynamic properties of NO, NO₂, N₂O adsorption by using C-doped boron nitride nanocage have been investigated using density functional theory. Based on nuclear quadrupole resonance (NQR) analysis, carbon-doped on B₅N₁₀ has shown the lowest fluctuation in electric potential and the highest negative atomic charge including 0.1190, 0.1844, and 0.1312 coulomb in NO→C–B₄N₁₀, NO₂→C–B₄N₁₀, and N₂O→C–B₄N₁₀, respectively. The C-doped complexes can be an appropriate option with the highest tendency for electron acceptance in the adsorption process. The reported results of nuclear magnetic resonance (NMR) spectroscopy have exhibited that atom doping of C on the B₄N₁₀ surface increases NO, NO₂, N₂O adsorption. The observed increase in the chemical shift anisotropy spans for N atoms, O(2) for NO/N₂O adsorption and O(2)/O(18) for NO₂ adsorption on the C–B₄N₁₀. Finally, Gibbs free energy alteration has shown that for a given number of nitrogen donor sites in NO, NO₂, N₂O, the stabilities of complexes owing to doping atom of C can be considered as: NO₂→C–B₄N₁₀ > N₂O→C–B₄N₁₀ > NO→C–B₄N₁₀. The procedure used in this research can be applied to the characterization of gaseous pollutants in any adsorption process.

KEYWORDS:

• C–B₄N₁₀
• gas detection
• eco-friendly technique
• computational modelling

1. Introduction

To address the most considerable environmental challenges, a probe for high-performance gas sensing materials is essential. Gas adsorption induces changes in the material’s work function, suggesting the potential application of these materials as catalysts. The development in micro and nano technologies enabled fabrication of structures whose function depends on adsorption-desorption processes. That dependence can be favourable like in affinity-based chemical and biochemicals sensors including graphene-based gas sensors, or undesirable like in microresonators whose adsorption-induced mass fluctuations provoke frequency instabilities. Although the process itself is not new, corresponding models are still under development. A requirement for models is that they need to be fast, reliable and flexible, suitable for stand-alone use or incorporation in multiscale models of complex systems [1–6].

Furthermore, modelling of adsorption capacities and parameters for equations of adsorption kinetics and dynamics, the employment of artificial neural networks is used to explore the effect of surface structure on the adsorption process. In a combination of molecular simulation and machine learning was used to examine the role of various pore topological structures on the CO₂ capture capabilities of metal organic frameworks [7]. Boron nitride nanomaterials have been used owing to their unparalleled specifications of eco-friendly attributes for pollutant adsorption and semiconducting property [8–11]. Boron nitride nanomaterials usually exhibit semi-leading behaviour, which is considered a proper alternative to carbon nanotubes. The properties of boron and nitrogen atoms which are the first neighbours of carbon in the periodic table, make boron nitride an interesting subject of numerous studies [12–14]. In recent years, different investigations on the adsorption of chemical contaminants and applying various boron nitride nanostructures as adsorbents for water purification have been studied [15–17].

Various physical shapes of boron nitride (BN)-based nano adsorbents such as nanoparticles, fullerenes, nanotubes, nanofibers, nanoribbons, nanosheets, nanomeshes, nanoflowers, and hollow spheres have been broadly considered possible adsorbents owing to their exceptional characteristics such as large surface area, structural variability, great chemical/mechanical strength, abundant structural defects, high reactive sites, and functional groups [18,19].

Adsorption involving charged adsorbates causes a change in the double layer and the potential at the outer Helmholtz plane, influencing the adsorption rates of both anodic and cathodic reactions. The first three modes are intimately with adsorption and the double layer involves interaction of the adsorbates and the intermediate products. These compounds have been formed during the partial electrochemical reactions and interaction of the adsorbed intermediates with organic molecules which can either inhibit or enhance electrode reaction rate.

Among all porous materials with potential applications for gas adsorption, boron nitride (BN), with its outstanding thermal and chemical stability, might be of great interest. Particularly, this research work aims to assess the influences of doping atom of C on the B₄N₁₀ for increasing gas detection through measurement of some parameters containing charge transfer, electric potential, electromagnetic and thermodynamic properties, functional group and examine the removal of selected toxic gas molecules including NO, NO₂ and N₂O during adsorption process.

2. Theoretical insights, applied material and method

2.1. Adsorption of gas molecules on C–B₄N₁₀

The aim of this study is to remove toxic gas molecules including NO, NO₂, N₂O from air through an eco-friendly approach by using C-doped B₄N₁₀ (Figure 1). B₅N₁₀ nanosensor was modelled in the presence of doping atoms of carbon which can increase the gas sensing potential of the nanosurface. In our research, sample characterization was performed by CAM – B3LYP – D3/EPR–3, LANL2DZ level of theory.

Figure 1. Application of C–B₄N₁₀ towards adsorption of gas molecules of NO, NO₂, N₂O and formation of complexes: NO→C–B₄N₁₀, NO₂→C–B₄N₁₀, and N₂O→C–B₄N₁₀, complexes using CAM–B3LYP–D3/6–311+G (d,p), LANL2DZ calculation.

Figure 1 has shown the process adsorption of gas molecules of NO, NO₂, N₂O on the C – B₄N₁₀ surface which towards formation of complexes containing NO→C – B₄N₁₀, NO₂→C – B₄N₁₀ and N₂O→C – B₄N₁₀ by molecular modelling computations. The charge distribution of mentioned complexes is calculated due to the Bader charge analysis [20].

The trapping of NO, NO₂ and N₂O molecules by C – B₄N₁₀ was successfully incorporated due to binding formation consisting of N→C (Figure 1). Regardless of which gas molecule, the boron nitride nanocage expanded to accommodate the gas molecules by enhancing the selective sensitivity through different doping atoms of C (Figure 1).

2.2. Application of density functional theory (DFT) approach

Hohenberg-Kohn (HK) functions have rigidly made the electronic density permissible as fundamental variable to electronic and structure computations. In other words, development of the applied DFT methodology only became notable after W. Kohn and L. J. Sham released their reputable series of equations which are introduced as Kohn-Sham (KS) equations [21–26].

Considering the electronic density within the KS image directs us to a remarkable reduction of quantum computing. Thus, the KS methodology lightens the route for pursuing systems that cannot be discussed by conventional ab-initio methodologies. Kohn and Sham introduces the solution which brings up the mono-electronic orbitals to account the kinetic energy in a simple and relatively exact, by finding a residual modification that might be computed apart. So, one starts with a reference model of M with non-interacting electrons related to the external potential $v_s$ and with Hamiltonian [25,26]:

(1) ${\widehat{H}}_{\mathit{s}}=-{\displaystyle \sum _i^M\frac{1}{2}}{\overline{V}}_{\mathit{i}}^2+{\displaystyle \sum _i^M{v}_s}\left({\overrightarrow{r}}_{\mathit{i}}\right)={\displaystyle \sum _i^M{\widehat{h}}_{\mathit{s}}};{\widehat{h}}_{\mathit{s}}=-\frac{1}{2}{\overline{V}}_{\mathit{i}}^2+v_s\left({\overrightarrow{r}}_{\mathit{i}}\right)$(1)

By representing the single particle orbitals ${\psi }_i$ all electronic densities physically acceptable for the system of ‘non-interacting’ electrons are written in the Equation 2(2) $\mathit{\rho }\left(\vec{r}\right)={\sum }_i^M{\left|{\psi }_i\left(\vec{r}\right)\right|}^2$(2) [25,26]:

(2) $\mathit{\rho }\left(\vec{r}\right)={\sum }_i^M{\left|{\psi }_i\left(\vec{r}\right)\right|}^2$(2)

Finally, the total energy could be measured by the KS method due to the Equation 3(3) $\mathit{E}\left[\mathit{\rho }\right]={\displaystyle \sum _i^M{n}_i}{\psi }_i-\frac{1}{2}{\overline{V}}^2+v_{\mathit{ext}}\left(\overrightarrow{r}\right)+\frac{1}{2}\int \mathit{\rho }\overrightarrow{r}\overrightarrow{r}-\overrightarrow{r}\text{d}{\overrightarrow{r}}^{}{\psi }_i+E_{\mathit{xc}}\left[\mathit{\rho }\right]+\frac{1}{2}{\displaystyle \sum _{\beta }^N{\displaystyle \sum _{\mathit{\alpha }\ne \mathit{\beta }}^N\frac{Z_{\alpha }{Z}_{\beta }}{\left|{\overrightarrow{R}}_{\mathit{\alpha }}-{\overrightarrow{R}}_{\mathit{\beta }}\right|}}}$(3) [25,26]:

(3) $\mathit{E}\left[\mathit{\rho }\right]={\displaystyle \sum _i^M{n}_i}{\psi }_i-\frac{1}{2}{\overline{V}}^2+v_{\mathit{ext}}\left(\overrightarrow{r}\right)+\frac{1}{2}\int \mathit{\rho }\overrightarrow{r}\overrightarrow{r}-\overrightarrow{r}\text{d}{\overrightarrow{r}}^{}{\psi }_i+E_{\mathit{xc}}\left[\mathit{\rho }\right]+\frac{1}{2}{\displaystyle \sum _{\beta }^N{\displaystyle \sum _{\mathit{\alpha }\ne \mathit{\beta }}^N\frac{Z_{\alpha }{Z}_{\beta }}{\left|{\overrightarrow{R}}_{\mathit{\alpha }}-{\overrightarrow{R}}_{\mathit{\beta }}\right|}}}$(3)

Therefore, the precise exchange energy functional is described by the Kohn – Sham orbitals in lieu of the density which is cited as the indirect density functional. This research has employed the penetration of the hybrid functional of three-parameter basis set of B3LYP (Becke, Lee, Yang, Parr) within the conception of DFT upon theoretical computations [27,28]. The popular B3LYP (Becke, three-parameter, Lee – Yang – Parr) and exchange-correlation functional become based on Equation 4(4) $E_{\mathrm{X}\mathrm{C}}^{\mathrm{B}3\mathrm{L}\mathrm{Y}\mathrm{P}}=\left(1-\mathit{\alpha }\right)E_{\mathrm{x}}^{\mathrm{L}\mathrm{S}\mathrm{D}\mathrm{A}}+\mathit{\alpha }{E}_{\mathrm{x}}^{\mathrm{H}\mathrm{F}}+\mathit{b\Delta }{E}_{\mathrm{x}}^{\mathrm{B}}+\left(1-\mathit{c}\right)E_{\mathrm{c}}^{\mathrm{L}\mathrm{S}\mathrm{D}\mathrm{A}}+\mathit{c}{E}_{\mathrm{c}}^{\mathrm{L}\mathrm{Y}\mathrm{P}}$(4) [29–31]:

(4) $E_{\mathrm{X}\mathrm{C}}^{\mathrm{B}3\mathrm{L}\mathrm{Y}\mathrm{P}}=\left(1-\mathit{\alpha }\right)E_{\mathrm{x}}^{\mathrm{L}\mathrm{S}\mathrm{D}\mathrm{A}}+\mathit{\alpha }{E}_{\mathrm{x}}^{\mathrm{H}\mathrm{F}}+\mathit{b\Delta }{E}_{\mathrm{x}}^{\mathrm{B}}+\left(1-\mathit{c}\right)E_{\mathrm{c}}^{\mathrm{L}\mathrm{S}\mathrm{D}\mathrm{A}}+\mathit{c}{E}_{\mathrm{c}}^{\mathrm{L}\mathrm{Y}\mathrm{P}}$(4)

$\mathit{\alpha }=0.20,\mathit{b}=0.72,\mathit{c}=0.81$ show a generalized gradient approximation: the Becke exchange functional [32] and the correlation functional of Lee, Yang and Parr [33] for B3LYP and $E_{\mathrm{c}}^{\mathrm{L}\mathrm{S}\mathrm{D}\mathrm{A}}$ is the VWN local spin density approximation to the correlation functional [34].

In this article, the rigid PES using DFT calculations has been computed applying Gaussian 16 revision C.01 software [35]. The input Z-matrix for adsorption of NO, NO₂ and N₂O molecules in air by the C – B₄N₁₀ has been designed with GaussView 6.1 [36] using 6–311+G (d,p), EPR–3, LANL2DZ basis set. In this study, the interaction between gas molecules and C – B₄N₁₀ was modelled and analysed. As revealed by DFT-based analysis, the potency of C – B₄N₁₀ for grabbing gas molecules was determined mainly by the electronegativity of the functional groups, as well as the interaction between the C – B₄N₁₀ and the gas molecules.

3. Results and discussion

Gas molecules that are dominant polluants in air are NO, NO₂ and N₂O. The data has evaluated the efficiency of boron nitride nanocage doped with carbon for gas detection. In fact, it can be remarked the chemisorptive nature of the bond among the gas molecules with boron and nitrogen elements through the equilibrium distribution of doping atom of C, B₅N₁₀, and a monolayer attribute.

3.1. PDOS & electronic evaluating

The electronic structures of gas adsorption (G) using C-doped B₅N₁₀ as the selective sensor for detecting and grabbing gas molecules in the air have been illustrated using CAM – B3LYP – D3/6–311+G (d,p), LANL2DZ level of theory.

Figure 2(a–f) shows the projected density of state (PDOS) of G→C – B₄N₁₀ through gas molecules adsorption. The appearance of the energy states (p-orbital) of C, N, O within the gap of C – B₄N₁₀ induces the reactivity of the system. It is clear from the figure that after trapping with gas molecules, there is a significant contribution of p-orbital in the unoccupied level. Therefore, the curve of partial PDOS has described that the p states of N atoms in gas molecules and C atom in C – B₄N₁₀ are overcoming due to the conduction band Figure 2(a–f). A distinguished adsorption trait might be seen in G→C – B₄N₁₀ because of the potent interaction between the p states of nitrogen atom in gas molecules with p states of C in C – B₄N₁₀ complexes.

Figure 2. PDOS of gas molecules of NO, NO₂, N₂O adsorbed on C–B₄N₁₀ including a) NO→C–B₄N₁₀, b) NO₂→C–B₄N₁₀, and c) N₂O→C–B₄N₁₀ complexes by CAM–B3LYP–D3/6–311+G (d,p), LANL2DZ.

NO→C – B₄N₁₀ has indicated one sharp peak for C in Figure 2(a) around −7.5 eV. Furthermore, NO₂→C – B₄N₁₀ Figure 2(b) has exhibited a strong peak around −9 eV through the graphs for C atom. Furthermore, the C graph with a sharp peak around −9 eV in N₂O→C – B₄N₁₀ Figure 2(e) has been shown. Based on the PDOS of adsorbed gas molecules of NO, NO₂ and N₂O and the surface coverage, both in equilibrium, we can estimate the surface density of adsorption sites.

3.2. Insight to nuclear quadrupole resonance (NQR)

As the EFG at the citation of the nucleus in NO, NO₂, N₂O is allocated by the valence electrons twisted in the attachment with close nuclei of C – B₄N₁₀ through trapping of gas molecules, the NQR frequency at which transitions occur is particular for G→C – B₄N₁₀ complexes (G= NO, NO₂, N₂O) (Table 1). The NQR method is related to the multipole expansion in Cartesian coordinates as the equation (5)(5) $\mathit{V}\left(\mathit{r}\right)=\mathit{V}\left(0\right)+\left[\left(\left.\left.\frac{\mathrm{\partial V}}{\mathrm{\partial }{x}_i}\right)\right|0.x_i\right)\right]+\frac{1}{2}\left[\left(\left.\left.\frac{{\mathrm{\partial }}^2\mathit{V}}{\mathrm{\partial }{x}_i{x}_j}\right)\right|0.x_i{x}_j\right)\right]+\dots$(5) [37,38]:

(5) $\mathit{V}\left(\mathit{r}\right)=\mathit{V}\left(0\right)+\left[\left(\left.\left.\frac{\mathrm{\partial V}}{\mathrm{\partial }{x}_i}\right)\right|0.x_i\right)\right]+\frac{1}{2}\left[\left(\left.\left.\frac{{\mathrm{\partial }}^2\mathit{V}}{\mathrm{\partial }{x}_i{x}_j}\right)\right|0.x_i{x}_j\right)\right]+\dots$(5)

Table 1. The electric potential (E_p/a.u.) and bader charge (Q/e) through NQR calculation for NO→C – B₄N₁₀, NO₂→C – B₄N₁₀, and N₂O→C – B₄N₁₀ complexes using CAM – B3LYP – D3/EPR–3, LANL2DZ calculation.

NO→C–B4N10			NO2→C–B4N10			N2O→C–B4N10
Atom	Q	Ep	Atom	Q	Ep	Atom	Q	Ep
N1	0.1466	−18.1839	N1	0.16124	−18.1173	N1	0.02433	−18.2323
O2	−0.0949	−22.2001	O2	−0.1127	−22.2184	N2	0.0758	−18.1955
B3	0.0321	−11.2869	B3	0.03517	−11.28	B3	0.0273	−11.2777
N4	−0.014	−18.2911	N4	−0.0082	−18.2851	N4	−0.0131	−18.2725
N5	−0.0458	−18.268	N5	−0.0420	−18.2631	N5	−0.0475	−18.2591
B6	0.0310	−11.2865	B6	0.0365	−11.2801	B6	0.0317	−11.278
B7	0.0323	−11.2871	B7	0.0351	−11.28	B7	0.0330	−11.279
B8	0.0316	−11.287	B8	0.0364	−11.2801	B8	0.0330	−11.2794
N9	−0.0256	−18.2799	N9	−0.0233	−18.2733	N9	−0.0037	−18.282
N10	−0.0447	−18.2682	N10	−0.0420	−18.2631	N10	−0.0528	−18.2625
N11	−0.0369	−18.2631	N11	−0.0295	−18.2567	N11	−0.0200	−18.2508
N12	−0.0337	−18.2633	N12	−0.0287	−18.2568	N12	−0.022	−18.254
N13	−0.0326	−18.2642	N13	−0.0295	−18.2567	N13	−0.0283	−18.2551
N14	−0.0328	−18.2626	N14	−0.0287	−18.2568	N14	−0.0190	−18.2536
C15	0.1190	−14.5472	C15	0.1844	−14.5136	C15	0.1312	−14.5096
N16	−0.0259	−18.2804	N16	−0.0232	−18.2733	N16	−0.0042	−18.283
N17	−0.0091	−18.2903	N17	−0.0082	−18.2851	N17	−0.0121	−18.272

After that, a simplification on the equation (5), there are only the second derivatives related to the identical variable for the potential energy [37,38]:

(6) $\mathit{U}=-\frac{1}{2}\underset{\mathcal{D}}{\int }{d}^3\mathit{r}{\rho }_r\left[\left(\left.\left.\frac{{\mathrm{\partial }}^2\mathit{V}}{\mathrm{\partial }{x}_i^2}\right)\right|0.x_i^2\right)\right]=-\frac{1}{2}\underset{\mathcal{D}}{\int }{d}^3\mathit{r}{\rho }_r\left[\left(\left.\left.\frac{\mathrm{\partial }{E}_i}{\mathrm{\partial }{x}_i}\right)\right|0.x_i^2\right)\right]=-\frac{1}{2}\left.\left(\left.\frac{\mathrm{\partial }{E}_i}{\mathrm{\partial }{x}_i}\right)\right.\right|0.\underset{\mathcal{D}}{\int }{d}^3\mathit{r}\left[\mathit{\rho }\left(\mathit{r}\right).x_i^2\right]$(6)

There are two parameters which must be gotten from NQR experiments: the quadrupole coupling constant, $\mathit{\chi }$, and asymmetry parameter of the EFG tensor $\mathit{\eta }$ [37,38]:

(7) $\text{Chi}=e^2\mathit{Q}{q}_{\mathit{zz}}/\mathit{h}$(7)

(8) $\mathit{\eta }=\mathit{\hspace{0.17em}}{q}_{\mathit{xx}}-q_{\mathit{yy}}/q_{\mathit{zz}}$(8)

where $q_{\mathit{ii}}$ are ingredients of the EFG tensor at the quadrupole nucleus determined in the EFG principal axes system, $\mathit{Q}$ is the nuclear quadrupole moment, $\mathit{e}$ is the proton charge and $\mathit{h}$ is the Planck’s constant [39,40].

In this research work, the electric potential as the quantity of work energy through carrying over the electric charge from one position to another position in the essence of electric field has been evaluated for NO→C – B₄N₁₀, NO₂→C – B₄N₁₀, and N₂O→C – B₄N₁₀ complexes (Table 1).

In Table 1, the Bader charge and electronic potential properties of C – B, N in C – B₄N₁₀ and N, O of gas molecules trapped on doped-boron nitride nanocages have been investigated. The amounts indicate that with increasing the negative charge of different atoms, the electric potential resulted from NQR calculations increase. Moreover, the doping atom of C (15) on the B₄N₁₀ has shown the most potential for accepting the electron from electron donor of N (1) in NO, NO₂, N₂O adsorbed on the B₅N₁₀ (Table 1).

Furthermore, in Figure 3(a – c), it has been sketched the electric potential of nuclear quadrupole resonance for some atoms of C/B, N in C – B₄N₁₀ and N, O of gas molecules trapped on doped-boron nitride nanocages which has been calculated by CAM – B3LYP – D3/EPR–3, LANL2DZ.

Figure 3. Electric potential (E_p/a.u.) versus bader charge (Q/e) through NQR calculation for a) NO→C–B₄N₁₀, b) NO₂→C–B₄N₁₀, and c) N₂O→C–B₄N₁₀ complexes by CAM–B3LYP–D3/EPR–3, LANL2DZ.

In Figure 3(a), it was observed the behaviour of NO adsorption on the C – B₄N₁₀ with high sensitivity based on relation coefficient of R² = 0.9468. Adsorption of NO₂ on the C – B₄N₁₀ in Figure 3(b) has illustrated the same sensing as NO. In addition, Figure 3(c) has resulted that N₂O→C – B₄N₁₀ has a good detecting for N₂O removal from air through relation coefficient of R² = 0.9424.

It’s vivid that the curve of C – B₄N₁₀ is waved by these gas molecules. The fluctuated peaks for electric potential have been shown around NO NO₂≈N₂O trapping on the C – B₄N₁₀ which demonstrate the electron accepting specifications of nitrogen and oxygen versus carbon doped on the B₅N₁₀ Figure 3(a–c). Besides, it can be considered that silicon as a semiconductor element in the functionalized B₅N₁₀ might have more impressive sensitivity for accepting the electrons from NO Figure 3(a), NO₂ Figure 3(b)and N₂O Figure 3(c) in the process of adsorption mechanism. However, carbon-doped on B₅N₁₀ has shown the lowest fluctuation between Bader charge versus electric potential extract from NQR parameters and the highest negative atomic charge including 0.1190 coulomb in NO→C – B₄N₁₀, 0.1844 coulomb in NO₂→C – B₄N₁₀, and 0.1312 coulomb in N₂O→C – B₄N₁₀ which can be an appropriate option with the highest tendency for electron accepting in the adsorption current (Table 1). In fact, the uptake of gas molecules has been known to be associated with C – B₄N₁₀, indicating that the adsorbed gas molecules in the C-doped nanocage can be internalized through a different pathway from pristine nanocage.

3.3. Analysis of NMR spectrums

Based on resulted amounts, nuclear magnetic resonance (NMR) spectrums of C – B₄N₁₀ as the potent sensor for adsorbing toxic gas molecules containing NO, NO₂, N₂O molecules can unravel the efficiency of C – B₄N₁₀ for detecting and removing of these hazardous gases in air as an ecofriendly approach.

From the DFT calculations, it has been attained the chemical shielding (CS) tensors in the principal axes system to estimate the isotropic chemical-shielding (CSI) and anisotropic chemical-shielding (CSA) [41]:

(9) ${\sigma }_{\mathit{iso}}=\left({\sigma }_{11}+{\sigma }_{22}+{\sigma }_{33}\right)/3$(9)

(10) ${\sigma }_{\mathit{aniso}}={\sigma }_{33}-\left({\sigma }_{22}+{\sigma }_{11}\right)/2$(10)

The NMR data of isotropic (σ_iso) and anisotropic shielding tensors (σ_aniso) of gas molecules trapped in the C – B₄N₁₀ towards formation of NO→C – B₄N₁₀, NO₂→C – B₄N₁₀, and N₂O→C – B₄N₁₀ complexes have been computed by Gaussian 16 revision C.01 program package [35] and been shown in Table 2.

Table 2. Data of NMR shielding tensors for selected atoms of NO→C – B₄N₁₀, NO₂→C – B₄N₁₀, and N₂O→C – B₄N₁₀ complexes using CAM – B3LYP – D3/6–311+G (d,p), LANL2DZ calculation.

NO→C–B4N10			NO2→C–B4N10			N2O→C–B4N10
Atom	σiso	σaniso	Atom	σiso	σaniso	Atom	σiso	σaniso
N1	767.22	574.98	N1	355.92	240.70	N1	41.33	1687.67
O2	1697.96	1904.72	O2	1494.82	344.94	N2	864.66	932.50
B3	83.21	75.50	B3	82.62	80.50	B3	69.95	136.15
N4	698.49	846.36	N4	675.11	728.24	N4	1952.94	3217.63
N5	419.17	284.09	N5	419.86	100.44	N5	4341.51	5912.65
B6	84.90	76.89	B6	83.98	77.82	B6	70.45	117.46
B7	83.80	78.10	B7	82.60	80.57	B7	97.47	105.05
B8	84.84	75.04	B8	83.99	77.83	B8	86.46	108.18
N9	421.55	778.5	N9	337.76	725.45	N9	747.56	7237.79
N10	417.63	182.60	N10	419.80	100.64	N10	2423.12	3261.16
N11	574.52	402.81	N11	565.20	477.6	N11	381.13	2220.66
N12	538.46	433.46	N12	585.31	503.19	N12	423.86	1511.34
N13	581.63	365.00	N13	565.92	478.21	N13	98.49	2976.83
N14	556.56	519.43	N14	585.41	503.81	N14	71.03	2659.88
C15	8.39	43.65	C15	49.99	87.76	C15	6.56	79.12
N16	390.13	810.91	N16	337.34	725.90	N16	1026.01	6313.65
N17	685.03	860.42	N17	674.45	727.66	N17	2268.01	3633.97

In Table 2, NMR data has reported the notable amounts for NO, NO₂, N₂O which were adsorbed on the C – B₄N₁₀ as the selective sensor for detecting gas molecules in air. The observed increase in the chemical shift anisotropy spans for N atoms, O(2) for NO/N₂O adsorption and O(2)/O(18) for NO₂ adsorption on the C – B₄N₁₀. The observed weak signal intensity near the parallel edge of the nanocage pattern may be due to boron binding induced non-spherical distribution of these complexes.

It is remarkable that doping of C on B₅N₁₀ might promote the stability of nanocage that results in enhanced magnetic alignment of complexes. Interestingly, the reported results show that C element can be optimized to achieve optimal alignment of nanocage in the presence of an applied magnetic field.

In fact, the adsorption of NO, NO₂, N₂O can introduce spin polarization on the C – B₄N₁₀ which indicates that these surfaces might be applied as magnetic scavenging surface as a gas detector. Isotropic and anisotropic shielding fluctuate with the occupancy in the electron accepting gas molecules trapped in the atom-doped on the boron nitride nanocage.

Figure 4 exhibited the same tendency of shielding for boron and nitrogen; however, a considerable deviation exists from doping atom of C (15) through interaction with N (1) of NO, NO₂, N₂O during adsorbing on the B₅N₁₀.

Figure 4. The NMR spectrums for a) NO→C–B₄N₁₀, b) NO₂→C–B₄N₁₀, and c) and N₂O→C–B₄N₁₀ complexes using CAM–B3LYP–D3/6–311+G (d,p), LANL2DZ.

In Figure 4(a–c), gas molecules of NO, NO₂, N₂O in the complexes of NO→C – B₄N₁₀ Figure 4(a), NO₂→C – B₄N₁₀ Figure 4(b), and N₂O→C – B₄N₁₀ Figure 4(c) denote the fluctuation in the chemical shielding during ion trapping. Figure 4(a–c) shows the gap chemical shielding between carbon doping of C – B₄N₁₀ nanocage and gas molecules.

In the NMR spectroscopy, it has been observed the remarkable peaks around interaction of NO, NO₂, N₂O molecules through adsorbing on the C – B₄N₁₀ during toxic gas detection and removal from air; however, there are some fluctuations in the chemical shielding behaviours of isotropic and anisotropy attributes. Therefore, the authors believe that the extracted results would be useful in the design of C – B₄N₁₀ based doped nanomaterials for increasing the adsorption of gas molecules in addition to the structural studies using solid-state and solution NMR techniques.

3.4. IR spectroscopy and thermodynamic factors

The IR calculations have been accomplished for adsorption of NO, NO₂, N₂O molecules by C – B₄N₁₀ during toxic gas sensing in air. Therefore, it has simulated the several clusters containing NO→C – B₄N₁₀ Figure 5(a), NO₂→C – B₄N₁₀ Figure 5(b), and N₂O→C – B₄N₁₀ Figure 5(c) complexes using CAM – B3LYP – D3/6–311+G (d,p), LANL2DZ.

Figure 5. The frequency (cm⁻¹) changes through the IR spectrums for a) NO→C–B₄N₁₀, b) NO₂→C–B₄N₁₀, and c) and N₂O→C–B₄N₁₀ complexes using CAM–B3LYP–D3/6–311+G (d,p), LANL2DZ.

The graph of Figure 5(a) has been observed in the frequency range between 200–800 cm⁻¹ for NO→C – B₄N₁₀ with several sharp peaks around 327.09, 337.61, 359.54, 595.74 and 664.20 cm⁻¹.

The graph of Figure 5(b) has been observed in the frequency range between 200–1100 cm⁻¹ for NO₂→C – B₄N₁₀ with several sharp peaks around 414.80, 475.93, 492.51, 521.43, 618.93, 664.49, and 666.55 cm⁻¹. Besides, Figure 5(c) has exhibited the frequency between 100–1200 for N₂O →C – B₄N₁₀ with sharp peaks around 345.39, 374.87, 469.76, 528.65, 592.59, 597.92, 624.44, 659.94, 669.69, 702.84, and 706.06 cm⁻¹.

The IR spectra of NO, NO₂, N₂O adsorption with C – B₄N₁₀ have demonstrated that the structure of the dominant complex correlates with the electron potency of doped C on the B₅N₁₀. As it has been seen the doped nanocage of C – B₄N₁₀ has the most fluctuations and the highest tendency for adsorption of NO, NO₂ and N₂O Figure 5(a–c). Therefore, it can be found that IR spectroscopy of (G)-adsorbed C – B₄N₁₀ is now well-placed to address specific questions on the individual effect of charge carriers (gas molecule-nanosensor), as well as doping atoms on the overall structure Figure 5(a–c). The analytical IR spectroscopy has described herein the selection of experimental parameters, and data processing. Atmospheric NOx is primarily a consequence of the combustion of fossil fuels at high temperatures. However, NOx is also readily produced by other means, including the burning of biomass material, soil emissions, and lightning strikes. The procedure used in this research can be applied to the characterization of gaseous pollutants in any adsorption process. Table 3 through the thermodynamic specifications concluded that C – B₄N₁₀ due to adsorption of NO, NO₂ and N₂O might be more efficient nanosensors for detecting and removing the gas molecules from polluted air.

Table 3. The thermodynamic characters of NO→C – B₄N₁₀, NO₂→C – B₄N₁₀, and N₂O→C – B₄N₁₀ complexes using CAM – B3LYP – D3/6–311+G (d,p), LANL2DZ calculation.

Compound	Dipole moment (Debye)	∆E^o×10^−3 (kcal/mol)	∆H^o×10^−3 (kcal/mol)	∆G^o×10^−3 (kcal/mol)	S^o (cal/K.mol)
NO→C–B4N10	0.2465	−510.557	−510.556	−510.588	103.732
NO2→C–B4N10	1.4314	−557.713	−557.712	−557.745	108.608
N2O→C–B4N10	1.9683	−544.868	−544.867	−544.902	116.794

Thermodynamic parameters of gas molecules adsorption with C – B₄N₁₀ have been determined using DFT theoretical technique. It has been shown that for a given number of nitrogen donor sites in NO, NO₂, N₂O, the stabilities of complexes owing to doping atom of C be considered as: NO₂→C – B₄N₁₀> N₂O→C – B₄N₁₀ > NO→C – B₄N₁₀ (Table 3).

The thermodynamic data in Table 3 could detect the maximum efficiency of C atom doping of B₅N₁₀ for gas molecules adsorption through $\mathrm{\Delta }{\mathrm{G}}_{\mathrm{a}\mathrm{d}\mathrm{s}}^{\mathrm{o}}$ which depends on the covalent bond between NO, NO₂, N₂O molecules and C – B₄N₁₀ as a potent sensor for air pollution removal. The adsorption process of NO, NO₂, N₂O molecules on the C – B₄N₁₀ is affirmed by the $\mathrm{\Delta }{\mathrm{G}}_{\mathrm{a}\mathrm{d}\mathrm{s}}^{\mathrm{o}}$ quantities: $\mathit{\hspace{0.17em}}\mathrm{\Delta }{\mathrm{G}}_{\mathrm{a}\mathrm{d}\mathrm{s}}^{\mathrm{o}}=\mathit{\hspace{0.17em}}\mathrm{\Delta }{\mathrm{G}}_{\mathrm{G}\to \mathrm{C}-\mathrm{B}4\mathrm{N}10}^{\mathrm{o}}-\left(\mathrm{\Delta }{\mathrm{G}}_{\mathrm{G}}^{\mathrm{o}}+\mathit{\hspace{0.17em}}\mathrm{\Delta }{\mathrm{G}}_{\mathrm{C}-\mathrm{B}4\mathrm{N}10}^{\mathrm{o}}\right);$ G = NO, NO₂, N₂O. Table 3 has shown that the key role of doped atom of C during interaction between the adsorbates of NO, NO₂, N₂O molecules as the electron donors and the adsorbent of C – B₄N₁₀ as electron acceptor. The interaction of carbon and gas molecules with solid surfaces is discussed within the framework of physisorption and chemisorption. Hereby also the description of chemisorption processes in terms of multidimensional potential hypersurfaces obtained from density functional theory (DFT) is briefly presented. BN-based material can be a noteworthy alternative to other porous materials for the removal of exhaust gas pollutants. However, many steps are needed to synthesize porous BN materials with a good composition, structure and porosity. Besides, it is suspected that defects within the BN structure or carbon-doping would be needed to ameliorate gas sorption. In this research, a porous carbon-doped BN is simulated in order to increase its gas adsorption efficiency.

4. Conclusion

Atmospheric NOx is primarily a consequence of the combustion of fossil fuels at high temperatures. However, NOx is also readily produced by other means, including the burning of biomass material, soil emissions, and lightning strikes. The procedure used in this research can be applied to the characterization of gaseous pollutants in any adsorption process. This research has investigated doping of C element on the boron nitride nanosensor (C – B₄N₁₀) for enhancing toxic gas sensing of these nanomaterials for air pollution removal. Therefore, NO, NO₂, N₂O molecules separation involving the C – B₄N₁₀ has been experimented based on electrostatic interactions between the gas molecules and C – B₄N₁₀. The electromagnetic and thermodynamic properties of C – B₄N₁₀ complex were computed using density functional theory. The results have illustrated that chosen gas molecules adsorbed on the C – B₄N₁₀ are rather stable with the most stable adsorption site being in the centre of C – B₄N₁₀ system. The doping atom of C (15) on the B₄N₁₀ has shown the most potential for accepting the electron from electron donor of N (1) in NO, NO₂, N₂O adsorbed on the B₅N₁₀. Moreover, Gibbs free energy alteration has shown that for a given number of nitrogen donor sites in NO, NO₂, N₂O, the stabilities of complexes owing to doping atom of C be considered as: NO₂→C – B₄N₁₀> N₂O→C – B₄N₁₀ > NO→C – B₄N₁₀. Indeed, it has been proven that carbon-doping alters the surface chemistry of boron nitrides and creates structural defects, which increases the number of active sites such as basic N groups suitable for NO, NO₂, N₂O adsorption. The above analysis shows that we can use the adsorbed phase as a small thermodynamic system. This allows the close relationship between the subdivision potential and the dependence of intensive properties on the internal structure of nanomaterials to be considered for gas adsorption.

Acknowledgements

In successfully completing this paper and its research, the authors are grateful to Kastamonu University.

Disclosure statement

No potential conflict of interest was reported by the author(s).