Sensitivity of SnO2 nanoparticles/reduced graphene oxide hybrid to NO2 gas: A DFT study

doi:10.21203/rs.3.rs-1377649/v1

The sensitivity of SnO₂ nanoparticles/reduced graphene oxide hybrid to NO₂ gas is discussed in the present work using density functional theory (DFT). The SnO₂ nanoparticles shapes are taken as pyramids, as proved by experiments. The reduced graphene oxide (rGO) edges have oxygen or oxygen-containing functional groups. However, the upper and lower surfaces of rGO are clean, as expected from the oxide reduction procedure. Results show that SnO₂ particles are connected at the edges of rGO, making a p-n heterojunction with a reduced agglomeration of SnO2 particles and high gas sensitivity. The DFT results are in good agreement with the experimental characterization of both SnO₂ and rGO using energy gap and XPS values. Gibbs free energy, enthalpy, and entropy of the various considered reactions are calculated. Results show that the sensitivity of the rGO/SnO₂hybrid to NO₂ gas is the result of the interplay of the dissociation and oxidation reactions of NO₂ gas.

NO2

Reduced graphene oxide

SnO2

Gas sensor

Graphene is a material with high potential applications [1–3]. These applications include solar cells [1], LEDs [2], and many other applications [3]. The same is true for graphene oxide [4]. One contemporary application of graphene or graphene oxide is in gas sensing [5, 6]. Graphene is proved to be better than MWCNT in gas sensing [7]. The large surface area of graphene is one of the important features that give graphene superiority in gas sensing operations. This superiority is also kept even after the mixture of graphene with other materials since the mixed materials are dispersed on graphene surfaces or edges that prevent agglomeration [8,9]. Graphene oxide can be activated using materials that remove oxygen-containing functional groups on the surfaces of graphene oxide. Hydrazine is one of these materials that are used as an oxygen scavenger from graphene oxide surface [8]. The resultant material is called reduced graphene oxide (rGO). rGO is an n-type semiconductor [10].

Tin oxide is one of the most used materials in gas sensing [11, 12]. It is a p-type semiconductor [13]. It has been used practically to detect various gases. The high number of oxygen vacancies in SnO₂ can enhance gas sensing operation by accepting or donating oxygen to the censored gas.

Nitrogen dioxide (NO₂) is an important polluting gas that is produced in large quantities due to vehicle engines and from smoking and kerosene heaters. As a result, monitoring NO₂ is of vital importance. The use of graphene or graphene oxide has been suggested several times to build sensors for NO₂ gas [9,14,15]. Adding other sensing materials to graphene or its oxide is a common practice. SnO₂ is one of these materials that improve graphene sensitivity to NO₂ gas [7,16–18]. In addition to SnO₂ other catalysts such as SnS₂, Ag, or Pd can also improve the sensitivity of graphene or its oxide [16–18].

The use of density functional theory (DFT) has proved to give valuable information about gas sensing mechanisms, including the various properties of materials used in the sensing operation [19,20]. This includes related electronic structure properties such as the energy gap, vibrational properties of Raman and IR spectroscopy, X-ray photoelectron spectroscopy (XPS), and thermodynamic properties such as Gibbs free energy, enthalpy, and entropy.

In the present work, DFT is used to analyze the gas sensing properties of SnO₂/rGO hybrid to NO₂ gas. The properties of the different materials used in this work are discussed. The results are compared with experimental findings of the various materials used in the sensing operation. Thermodynamic properties such as Gibbs free energy, enthalpy, and entropy of the various reactions are evaluated to estimate the reaction rates of NO₂ with the sensing materials.

DFT at the B3LYP/6-311G** is used in the present work to simulate the structure and different properties of the sensing materials of the SnO₂/rGO hybrid and their interaction with NO₂ gas. Previous works on SnO₂ surveyed different methods and bases to perform electronic structure calculations such as GGA, LDA, B3LYP, and PBE0 [21]. B3LYP was found to give a bandgap that is more consistent with experimental results. Previous use of B3LYP in gas sensor calculations gave satisfactory results in comparison with experiments [22, 23]. The basis 6-311G** reflects the size of molecules and the total number of atoms in the present work. A small number of atoms can give us the freedom to use a more intricate basis, while a large number of atoms can restrict the use of a detailed and complicated basis. SDD basis is used for heavy Sn atoms that cannot be represented by 6-311G** basis. Dispersion corrections are important for the present calculations because of long-range forces between the interacting molecules. GD3BJ dispersion correction version is added [24]. Gaussian 09 molecular facilities program is used to perform present calculations [25].

Previous works on SnO₂ relied on the pyramid structure of its surface [20,23,26]. Pyramids on the SnO₂ surface are also confirmed experimentally [22]. Figure 1a shows the pyramid SnO₂ cluster used in the present calculations. The stoichiometry of this cluster (Sn₁₀O₁₆) is carefully chosen so that adding more oxygen to this cluster (such as Sn₁₀O₁₇) will make the Gibbs free energy of reaction positive, and the cluster will return to the optimum stoichiometry Sn₁₀O₁₆ in a specific reaction rate. This is in agreement with experimental results that SnO₂ has a lot of vacancies [23]. The Sn-O bond length is in the range of 1.9 to 2.1 Å, which is in agreement with the literature [27].

Graphene has a well-known hexagonal honeycomb structure. Coronene (C₂₄H₁₂) is used frequently to represent graphene [28–30]. However, we use oxygen instead of hydrogen (C₂₄O₆) to simulate the real existence of oxygen in the air and not the rare hydrogen. A variation of C-C bond length in the range (1.32 to 1.5 Å) according to bond distance from edges is in agreement with the experiment [31]. A lower range for C = O and C-O (1.22 to 1.45 Å) is also in agreement with the experiment [31]. C₂₄O₆ (as in Fig. 1b) is called reduced graphene oxide since no oxygen-containing functional groups exist on the surface of this cluster. Practically, the edges of the graphene cluster of atoms are terminated by oxygen, hydroxyl, or oxygen-containing functional groups. The upper and lower surfaces of graphene can also be terminated by oxygen or oxygen-containing groups. However, the functional groups on graphene surfaces can be removed easily, which is not the case for functional groups at the edges. The removal of an OH group by hydrazine (N₂H₄) from the surface and edges of reduced graphene oxide in Fig. 1b can be given by the following reactions (in all the following reactions we use the standard conditions of 25 ̊C and 1 atm unless mentioned otherwise):

C₂₄O₆(OH)+¼N₂H₄→C₂₄O₆+¼N₂ + H₂O (Surface ∆G = 1.681 eV), (1)

C₂₄O₆(OH)+¼N₂H₄→C₂₄O₆+¼N₂ + H₂O (Edge ∆G = 4.632 eV) (2)

∆G is the Gibbs free energy of the reaction. We can see from the upper two equations that removing the OH functional group from the edge of graphene requires three times the energy required to remove the OH group from the surface. The same is not true for removing oxygen from the surface and edge. Oxygen can be completely removed using hydrazine [8]. The UV radiation can break the OH bond to graphene at the surface only. The energy of a 532 nm (2.331 eV) can break this bond [14] so are the 365 nm (3.397 eV) radiation as in reference [9].

NO₂ gas at low temperatures decomposes to NO and O₂ [32, 33] in an endothermic reaction as in the reaction:

NO₂→NO+½O₂ (∆G = 0.416 eV) (3)

The decomposition of NO₂ near the surfaces of catalysts affects the ability to sensor NO₂ since it decreases the concentration of the gas near the sensor surface. The rate of decomposition is given by [34]:

$$\frac{\text{d}\left[\text{N}{\text{O}}_{2}\right]}{\text{d}\text{t}}=-{\text{C}}_{1}\left[\text{N}{\text{O}}_{2}\right]\text{k}\left(\text{T}\right).$$

4

In the above equation, [NO₂] is the concentration of NO₂ gas. C₁ is an empirical coefficient that can be found experimentally. k(T) is the temperature-dependent part:

$$\text{k}\left(\text{T}\right)=\text{T}{ \text{e}\text{x}\text{p}}^{\left(\frac{-{\Delta }{\text{G}}_{\text{a}}}{{\text{k}}_{\text{B}}\text{T}}\right)}$$

5

T is the temperature, ∆G_a is the Gibbs free energy of activation, and k_B is the Boltzmann constant. The same method of Eq. (4) can be used to calculate the reaction between NO₂ gas and the SnO2/reduced graphene oxide hybrid:

$$\frac{\text{d}\left[\text{N}{\text{O}}_{2}\right]}{\text{d}\text{t}}=-{\text{C}}_{2}\left[\text{N}{\text{O}}_{2}\right][{\text{S}\text{n}}_{10}{\text{O}}_{16}/{\text{C}}_{24}{\text{O}}_{6}]\text{k}\left(\text{T}\right).$$

6

Solving Eq. (4) and Eq. (6) for the concentration of NO₂ (assuming [NO₂] is not appreciably affected by the two reactions):

[N${\text{O}}_{2}$]$=$[N${\text{O}}_{2}{]}_{0}{\text{e}\text{x}\text{p}}^{-{\text{C}}_{1}\text{k}\left(\text{T}\right)\text{t}}$ (7)

[N${\text{O}}_{2}$]$=$[N${\text{O}}_{2}{]}_{0}{\text{e}\text{x}\text{p}}^{-{\text{C}}_{2}[{\text{S}\text{n}}_{10}{\text{O}}_{16}/{\text{C}}_{24}{\text{O}}_{6}]\text{k}\left(\text{T}\right)\text{t}}$ (8)

Figure 2 shows the HOMO (highest occupied molecular orbital) and LUMO (lowest unoccupied molecular orbital) of both SnO₂ (represented by the Sn₁₀O₁₆ cluster) and the rGO (represented by the C₂₄O₆ cluster) and their energy gaps. The experimental energy gap of SnO₂ is 3.6 to 3.92 eV [27, 35] which is around our calculated 3.875 eV value. The experimental energy gap of rGO is in the range between 1.00 to 1.69 eV [16]. The present calculated gap of rGO represented by C₂₄O₆ is 1.336 eV which is nearly the average of the experimental range. The p-n heterojunction formed between rGO and SnO₂ [36] is of the straddling gap since the HOMO and LUMO energy levels of rGO are within that of SnO_2, as shown in Fig. 2. If the two materials (SnO₂ and rGO) do not interact at all, the final gap should be that of rGO. However, this is not the case. The high affinity of carbon atoms drags oxygen atoms from SnO₂ because of the lower affinity of Sn atoms, as in Fig. 3b. In addition, a bond is formed between carbon and tin atoms. Due to these interactions, the final material is called the rGO/SnO₂ hybrid, which is some kind of a composite at the molecular or nanoscale [37]. The final calculated gap of the rGO/SnO₂ hybrid is 1.534 eV, with the HOMO and LUMO energy levels moved to be higher than that of rGO as in Fig. 2.

Besides the energy gap, calculations of the electronic structure of Sn₁₀O₁₆ and C₂₄O₆ clusters and hybrid reveal other quantities such as XPS that match the experimental values of SnO₂ and rGO as in Table 1. As an example, O1s energy level in rGO alone is in the range − 520.716 to -524.302 eV, which is in good agreement with experimental XPS spectra of reference [38]. The O1s energy level in Sn₁₀O₁₆ is in the range − 520.139 to -521.808 eV, which is only 2% different than experimental 531.1 eV value. The O1s theoretical energy level in the rGO/SnO₂ hybrid is in the range − 519.511 to -524.308 eV, which incorporates both Sn₁₀O₁₆ and C₂₄O₆ within its range. Although carbon atoms exist only in the C₂₄O₆ cluster, the C1s level in the hybrid is wider than that of the C₂₄O₆ cluster alone, as in Table 1.

Table 1

Some present calculated properties of rGO and SnO₂ clusters and their rGO/SnO₂ hybrid in comparison with experimental references.
Quantity	Theoretical	Experimental	Experimental references
rGO energy gap eV	1.336	1.00 to 1.69	[16]
SnO₂ energy gap eV	3.875	3.6 to 3.92	[27, 35, 39]
rGO/SnO₂ energy gap eV	1.534	-	-
XPS rGO O1s eV	-520.716 to -524.302	-531.19 to -533.8	[38]
XPS SnO₂ O1s eV	-520.139 to -521.808	531.1	[40]
XPS rGO/SnO₂ O1s eV	-519.511 to -524.308	-	-
XPS rGO C1s eV	-278.790 to -280.899	-284.83 to -291.2	[38]
XPS rGO/SnO₂ C1s eV	-278.321 to -282.307	-	-

Figure 3a shows our initial theoretical arrangement of attaching the SnO₂ cluster (Sn₁₀O₁₆) to the rGO cluster (C₂₄O₆). In this attachment, the base of the SnO₂ pyramid is put on the rGO surface. However, after performing self-consistent field calculations of the present density functional theory, the SnO₂ cluster is repelled so that the attachment is made between one of the carbon atoms at the edge of rGO and one Sn atom at the edge of SnO₂ as in Fig. 3b. This arrangement is consistent with the above-mentioned high and powerful reactivity of rGO edges with respect to the rGO surface. This is also consistent with experimental findings in FESEM and SEM images in which SnO₂ nanoparticles are stacked on rGO sides and edges [8,9].

NO₂ sensitivity is only triggered by its interaction with either rGO or SnO₂ in the rGO/SnO₂ hybrid. This interaction changes the energy gap value that ultimately changes the resistivity of rGO/SnO₂. The oxidation of the SnO₂ cluster in the rGO/SnO₂ hybrid can be described by the equation:

C₂₄O₆/Sn₁₀O₁₆ + NO₂ → C₂₄O₆/Sn₁₀O₁₇ + NO (∆G = 1.255 eV) (9)

The reaction in the upper equation is endergonic, and we can use Eqs. (4) and (5) to determine the reaction rate. To determine the reaction rate, the Gibbs free energy of activation ∆G_a should be determined as in the following reaction:

C₂₄O₆/Sn₁₀O₁₆ + NO₂ → [C₂₄O₆/Sn₁₀O₁₆ ---NO₂]^‡ (∆G_a= -0.0595 eV) (10)

In the above reaction, [C₂₄O₆/Sn₁₀O₁₆ ---NO₂]^‡ is the transition state. The value of the activation energy (∆G_a= -0.0595 eV) is negative, which means that the formation of the transition state is an exergonic reaction. The steps of this reaction are shown in Fig. (4).

Gibbs free energy, enthalpy, and entropy of a reaction are connected via the relation:

$$\varDelta \text{G}=\varDelta \text{H}-\text{T}\varDelta \text{S}$$

11

∆H is the change in enthalpy or the enthalpy of reaction. ∆S is the change in entropy, while the term T∆S is the entropy energy of the reaction. As we have seen before in Eq. (5) that Gibbs free energy of activation determines the rate of reaction. The enthalpy of reaction is the heat produced or absorbed in the reaction. The entropy of reaction is usually related to the difference between the number of reacting molecules and the number of product molecules. In Table 2, we listed the different reactions encountered in this work, including their Gibbs free energy, enthalpy, and entropy. We can see from Table 2 that most of the reactions have a higher number of product molecules than the number of interacting molecules and, consequently, positive entropy energy. The two exceptions are reactions number 6 and 7 in Table 2. Reaction number 6 has an equal number of reactants and products and very small entropy energy. Reaction number 7 has the number of products less than the reactants and hence negative entropy energy. The sign of the entropy energy affects the value of Gibbs free energy and the final rate of reaction.

Table 2

Gibbs free energies of reactions and activation and their components (enthalpy and entropy) at standard temperature and pressure (temperature 298.15 Kelvin and pressure 1 atm). (S) represents surface reactions and (E) represents edge reactions.
n	Reaction	ΔG (eV)	ΔH (eV)	TΔS (eV)
1	C₂₄O₆(OH)+¼N₂H₄→C₂₄O₆+¼N₂ + H₂O (S)	1.681	2.075	0.393
2	C₂₄O₆(OH)+¼N₂H₄→C₂₄O₆+¼N₂ + H₂O (E)	4.632	5.063	0.431
3	C₂₄O₇+½N₂H₄→C₂₄O₆+½N₂ + H₂O (S)	-0.199	0.159	0.358
4	C₂₄O₆+½N₂H₄→C₂₄O₅+½N₂ + H₂O (E)	-1.542	-1.095	0.446
5	NO₂→NO+½O₂	0.416	0.626	0.209
6	C₂₄O₆/Sn₁₀O₁₆ + NO₂ → C₂₄O₆/Sn₁₀O₁₇ + NO	1.255	1.244	-0.011
7	C₂₄O₆/Sn₁₀O₁₆ + NO₂ → [C₂₄O₆/Sn₁₀O₁₆ ---NO₂]^‡	-0.0595	-0.447	-0.387
8	C₂₄O₆/Sn₁₀O₁₇ → C₂₄O₆/Sn₁₀O₁₆ +½O₂ (S)	-0.838	-0.618	0.220
9	C₂₄O₆/Sn₁₀O₁₇ → C₂₄O₅/Sn₁₀O₁₇ +½O₂ (E)	1.224	1.474	0.250

Finally, Fig. (5) summarizes the reactions that take place when NO₂ gas reacts with C₂₄O₆/Sn₁₀O₁₆ cluster hybrid. The first reaction is the dissociation of NO₂ gas to NO and O₂ gases (the upper arrow in Fig. (5)). This reaction can take place even before NO₂ reaches the surface of the C₂₄O₆/Sn₁₀O₁₆ cluster, in which the hybrid can be considered as a catalyst for the dissociation reaction. Due to this reaction, the concentration of NO₂ decreases as it approaches the C₂₄O₆/Sn₁₀O₁₆ surface (the arrow on the left side of Fig. (5)). The remaining NO₂ concentration reacts with both rGO and SnO₂ parts of the rGO/SnO₂ hybrid. At room temperature, the interaction with both rGO and SnO₂ does not change the concentration of NO₂ appreciably. The interaction of NO₂ with rGO takes place only one time, after which the oxygen atom attached to rGO will not be able to escape due to the high Gibbs energy of separation as in reaction number 9 in Table 2. This causes the resistance of the SnO₂/rGO sensor to increase even after stopping NO₂ gas from flowing. This does not happen for the oxygen connected to the SnO₂ cluster due to negative Gibbs energy of separation of oxygen from SnO₂ as in reaction number 8 in Table 2. The ability of NO₂ gas to oxidize the rGO/SnO₂ hybrid can make it easily distinguished from other gases that mainly reduce oxygen from the sensor, such as NH₃, CO, acetone, ethanol, methanol gases [8,37].

The sensitivity of the rGO/SnO₂ hybrid increases as we increase the temperature until the temperature reaches between room temperature to 150 ̊C after which it drops depending on the method of manufacturing and concentration of NO₂ [8,41,42]. However, examining Eqs. (5) and (8), we can see that the reaction rate should increase with temperature. The reason for the drop of sensitivity in high temperatures is that the concentration of NO₂ decreases rapidly in high temperatures due to dissociation before reaching rGO/SnO₂ hybrid surface, as we discussed in Fig. 5.

The interaction of NO₂ gas with rGO/SnO₂ hybrid is analyzed using the DFT method and compared with available experimental findings. The calculated energy gaps and XPS levels are in good agreement with the experiment. DFT calculations show that SnO₂ and rGO are connected by their edges due to the high reactivity of rGO edges with respect to their surface. The energy gap of the rGO/SnO₂ hybrid is in between that of SnO₂ and rGO due to the reaction between them. The present results also show that the sensitivity of the rGO/SnO₂ hybrid to NO₂ is mostly due to SnO₂ interaction with NO₂ gas. The effect of rGO is to distribute SnO₂ nanoparticles evenly on rGO edges and to reduce agglomeration of SnO₂. The sensitivity of the rGO/SnO₂ hybrid to NO₂ increases with temperature until the NO₂ dissociation in the air reduces the concentration of NO₂ reaching the surface of rGO/SnO₂ appreciably and decreases the sensitivity.

Author contribution: Conceptualization: Abdulsattar; formal analysis:

Abdulridha; investigation: Hussein; methodology: Abdulsattar, and Abdulridha;

project administration: Abdulsattar; supervision: Abdulsattar; writing—

original draft: Abdulsattar

Ethics approval: Not applicable.

Consent to participate: Not applicable.

Consent for publication: All co-authors have seen and approved the manuscript.

Conflict of interest: The authors declare no competing interests.

[1] C. Redondo-Obispo, P. Serafini, E. Climent-Pascual, T.S. Ripolles, I. Mora-Seró, A. De Andrés, C. Coya, Effect of Pristine Graphene on Methylammonium Lead Iodide Films and Implications on Solar Cell Performance, ACS Appl. Energy Mater. 4 (2021) 13943–13951. https://doi.org/10.1021/acsaem.1c02738.

[2] H. Qiu, X. Zhao, H. Li, Y. Li, J. Li, J. Yang, Highly flexible and thermal conductive films of graphene/poly(naphthylamine) and applications in thermal management of LED devices, J. Appl. Polym. Sci. 138 (2021). https://doi.org/10.1002/app.51383.

[3] F. Nemati, M. Rezaie, H. Tabesh, K. Eid, G. Xu, M.R. Ganjali, M. Hosseini, C. Karaman, N. Erk, P.-L. Show, N. Zare, H. Karimi-Maleh, Cerium functionalized graphene nano-structures and their applications; A review, Environ. Res. 208 (2022). https://doi.org/10.1016/j.envres.2022.112685.

[4] H.-J. Qu, L.-J. Huang, Z.-Y. Han, Y.-X. Wang, Z.-J. Zhang, Y. Wang, Q.-R. Chang, N. Wei, M.J. Kipper, J.-G. Tang, A review of graphene-oxide/metal–organic framework composites materials: characteristics, preparation and applications, J. Porous Mater. 28 (2021) 1837–1865. https://doi.org/10.1007/s10934-021-01125-w.

[5] J.H. Choi, J.S. Seo, H.E. Jeong, K. Song, S.-H. Baeck, S.E. Shim, Y. Qian, Effects of Field-Effect and Schottky Heterostructure on p-Type Graphene-Based Gas Sensor Modified by n-Type In2O3 and Phenylenediamine, Appl. Surf. Sci. 578 (2022). https://doi.org/10.1016/j.apsusc.2021.152025.

[6] S. He, Y. Liu, W. Feng, B. Li, X. Yang, X. Huang, Carbon monoxide gas sensor based on an α-Fe 2 O 3 /reduced graphene oxide quantum dots composite film integrated Michelson interferometer , Meas. Sci. Technol. 33 (2022). https://doi.org/10.1088/1361-6501/ac39d3.

[7] V. Srivastava, K. Jain, At room temperature graphene/SnO<inf>2</inf> is better than MWCNT/SnO<inf>2</inf> as NO<inf>2</inf> gas sensor, Mater. Lett. 169 (2016) 28–32. https://doi.org/10.1016/j.matlet.2015.12.115.

[8] Z. Wang, Z. Jia, Q. Li, X. Zhang, W. Sun, J. Sun, B. Liu, B. Ha, The enhanced NO<inf>2</inf> sensing properties of SnO<inf>2</inf> nanoparticles/reduced graphene oxide composite, J. Colloid Interface Sci. 537 (2019) 228–237. https://doi.org/10.1016/j.jcis.2018.11.009.

[9] Z. Zhang, Z. Gao, R. Fang, H. Li, W. He, C. Du, UV-assisted room temperature NO<inf>2</inf> sensor using monolayer graphene decorated with SnO<inf>2</inf> nanoparticles, Ceram. Int. 46 (2020) 2255–2260. https://doi.org/10.1016/j.ceramint.2019.09.211.

[10] V.S. Kindalkar, P. Kumar, C.H. Shraddha, K. Ananya, S.M. Dharmaprakash, Evaluation of optoelectronic properties of Nd: YAG Laser deposited rGO thin film for n-type transparent electrode applications, in: S. V.K., P. C.L., Y. S.M. (Eds.), 64th DAE Solid State Phys. Symp. 2019, DAE-SSPS 2019, American Institute of Physics Inc., Department of Physics, Mangalore University, Mangalagangothri, 574199, India, 2020. https://doi.org/10.1063/5.0016705.

[11] X. Kang, N. Deng, Z. Yan, Y. Pan, W. Sun, Y. Zhang, Resistive-type VOCs and pollution gases sensor based on SnO2: A review, Mater. Sci. Semicond. Process. 138 (2022). https://doi.org/10.1016/j.mssp.2021.106246.

[12] S. Das, V. Jayaraman, SnO2: A comprehensive review on structures and gas sensors, Prog. Mater. Sci. 66 (2014) 112–255. https://doi.org/10.1016/j.pmatsci.2014.06.003.

[13] A. Marikuts, M. Rumyantseva, A. Gaskov, Effect of n-type Doping of SnO2 and ZnO on Surface Sites and Gas Sensing Behaviour, in: B. G., Z. Z., B. I. (Eds.), 30th Eurosensors Conf. Eurosensors 2016, Elsevier Ltd, Chemistry Department, Moscow State University, Vorobyevy gory 1-3, Moscow, 119991, Russian Federation, 2016: pp. 1082–1085. https://doi.org/10.1016/j.proeng.2016.11.345.

[14] X. Yan, Y. Wu, R. Li, C. Shi, R. Moro, Y. Ma, L. Ma, High-Performance UV-Assisted NO<inf>2</inf> Sensor Based on Chemical Vapor Deposition Graphene at Room Temperature, ACS Omega. 4 (2019) 14179–14187. https://doi.org/10.1021/acsomega.9b00935.

[15] H. Chen, L. Ding, K. Zhang, Z. Chen, Y. Lei, Z. Zhou, R. Hou, Preparation of chemically reduced graphene using hydrazine hydrate as the reduction agent and its NO<inf>2</inf> sensitivity at room temperature, Int. J. Electrochem. Sci. 15 (2020) 10231–10242. https://doi.org/10.20964/2020.10.72.

[16] Z. Wang, Y. Zhang, S. Liu, T. Zhang, Preparation of Ag nanoparticles-SnO<inf>2</inf> nanoparticles-reduced graphene oxide hybrids and their application for detection of NO<inf>2</inf> at room temperature, Sensors Actuators, B Chem. 222 (2016) 893–903. https://doi.org/10.1016/j.snb.2015.09.027.

[17] Z. Wang, T. Zhang, C. Zhao, T. Han, T. Fei, S. Liu, G. Lu, Anchoring ultrafine Pd nanoparticles and SnO<inf>2</inf> nanoparticles on reduced graphene oxide for high-performance room temperature NO<inf>2</inf> sensing, J. Colloid Interface Sci. 514 (2018) 599–608. https://doi.org/10.1016/j.jcis.2017.12.075.

[18] S. Zheng, Y. Li, J. Hao, H. Fang, Y. Yuan, H.-S. Tsai, Q. Sun, P. Wan, X. Zhang, Y. Wang, Hierarchical assembly of graphene-bridged SnO<inf>2</inf>-rGO/SnS<inf>2</inf> heterostructure with interfacial charge transfer highway for high-performance NO<inf>2</inf> detection, Appl. Surf. Sci. 568 (2021). https://doi.org/10.1016/j.apsusc.2021.150926.

[19] M.A. Abdulsattar, R.H. Jabbar, H.H. Abed, H.M. Abduljalil, The sensitivity of pristine and Pt doped ZnO nanoclusters to NH3 gas: A transition state theory study, Optik (Stuttg). 242 (2021). https://doi.org/10.1016/j.ijleo.2021.167158.

[20] M.A. Abdulsattar, H.H. Abed, R.H. Jabbar, N.M. Almaroof, Effect of formaldehyde properties on SnO<inf>2</inf> clusters gas sensitivity: A DFT study, J. Mol. Graph. Model. 102 (2021). https://doi.org/10.1016/j.jmgm.2020.107791.

[21] T. Shao, F. Zhang, W. Zhang, Density functional theory study on the electronic structure and optical properties of SnO2, Xiyou Jinshu Cailiao Yu Gongcheng/Rare Met. Mater. Eng. 44 (2015) 2409–2414. https://doi.org/10.1016/s1875-5372(16)30031-5.

[22] M.A. Abdulsattar, D.A. Nassrullah, Z.T. Abdulhamied, Light alkanes physisorption and chemisorption on SnO2 pyramid clusters surface as a function of temperature: A DFT study, J. Adv. Pharm. Educ. Res. 9 (2019) 118–124. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090878116&partnerID=40&md5=7ac074ac114e6cf887d954a079d50573.

[23] M.A. Abdulsattar, Transition state theory application to H2 gas sensitivity of pristine and Pd doped SnO2 clusters, Karbala Int. J. Mod. Sci. 6 (2020) 13. https://doi.org/10.33640/2405-609X.1615.

[24] E.-L. Zins, Microhydration of a Carbonyl Group: How does the Molecular Electrostatic Potential (MESP) Impact the Formation of (H2O)n:(R2C═O)Complexes?, J. Phys. Chem. A. 124 (2020) 1720–1734. https://doi.org/10.1021/acs.jpca.9b09992.

[25] M.J. Frisch, G.W. Trucks, H.B. Schlegel, G.E. Scuseria, M.A. Robb, J.R. Cheeseman, G. Scalmani, V. Barone, B. Mennucci, G.A. Petersson, H. Nakatsuji, M. Caricato, X. Li, H.P. Hratchian, A.F. Izmaylov, J. Bloino, G. Zheng, J.L. Sonnenberg, M. Hada, M. Ehara, K. Toyota, R. Fukuda, J. Hasegawa, M. Ishida, T. Nakajima, Y. Honda, O. Kitao, H. Nakai, T. Vreven, J.A.J. Montgomery, J.E. Peralta, F. Ogliaro, M. Bearpark, J.J. Heyd, E. Brothers, K.N. Kudin, V.N. Staroverov, R. Kobayashi, J. Normand, K. Raghavachari, A. Rendell, J.C. Burant, S.S. Iyengar, J. Tomasi, M. Cossi, N. Rega, J.M. Millam, M. Klene, J.E. Knox, J.B. Cross, V. Bakken, C. Adamo, J. Jaramillo, R. Gomperts, R.E. Stratmann, O. Yazyev, A.J. Austin, R. Cammi, C. Pomelli, J.W. Ochterski, R.L. Martin, K. Morokuma, V.G. Zakrzewski, G.A. Voth, P. Salvador, J.J. Dannenberg, S. Dapprich, A.D. Daniels, Ö. Farkas, J.B. Foresman, J. V. Ortiz, J. Cioslowski, D.J. Fox, Gaussian 09, Revision A.02, (2009).

[26] M.A. Abdulsattar, R.H. Jabbar, H.M. Fadhel, S.A. Alkharkhe, SnO2 nanocluster interaction with noble and environmental gases: a DFT study, Struct. Chem. 33 (2022) 71–79. https://doi.org/10.1007/s11224-021-01823-w.

[27] O. V Filonenko, A.G. Grebenyuk, V. V Lobanov, Quantum chemical modeling of the structure and properties of SnO2 nanoclusters , Him. Fiz. Ta Tehnol. Poverhni. 12 (2021) 283–290. https://doi.org/10.15407/HFTP12.04.283.

[28] S. Prodhan, S. Mazumdar, S. Ramasesha, Correlated electronic properties of a graphene nanoflake: Coronene, Molecules. 24 (2019). https://doi.org/10.3390/molecules24040730.

[29] M.F. Budyka, Semiempirical study on the absorption spectra of the coronene-like molecular models of graphene quantum dots, Spectrochim. Acta - Part A Mol. Biomol. Spectrosc. 207 (2019) 1–5. https://doi.org/10.1016/j.saa.2018.09.007.

[30] B. Saha, P.K. Bhattacharyya, Density Functional Study on the Adsorption of 5-Membered N-Heterocycles on B/N/BN-Doped Graphene: Coronene as a Model System, ACS Omega. 3 (2018) 16753–16768. https://doi.org/10.1021/acsomega.8b02340.

[31] R.D. Johnson, NIST Computation Chemistry Comparison and Benchmark Database, NIST Standard Reference Database Number 101 Release 14, (2006). https://doi.org/10.18434/T47C7Z.

[32] T. Jirsak, J. Dvorak, J.A. Rodriguez, Adsorption of NO2 on Rh(111) and Pd/Rh(111): photoemission studies, Surf. Sci. 436 (1999) L683–L690. https://doi.org/10.1016/S0039-6028(99)00656-1.

[33] P.G. Ashmore, M.G. Burnett, Concurrent molecular and free radical mechanisms in the thermal decomposition of nitrogen dioxide, Trans. Faraday Soc. 58 (1962) 253–261. https://doi.org/10.1039/tf9625800253.

[34] Joseph W. Ochterski, Thermochemistry in Gaussian, (2000).

[35] S.M. Yakout, Engineering of visible light photocatalytic activity in SnO2 nanoparticles: Cu2+-integrated Li+, Y3+ or Zr4+ dopants, Opt. Mater. (Amst). 116 (2021). https://doi.org/10.1016/j.optmat.2021.111077.

[36] X. Wang, A. Marikutsa, M. Rumyantseva, A. Gaskov, A. Knotko, X. Li, P-n Transition-Enhanced Sensing Properties of rGO-SnO2 Heterojunction to NO2 at Room Temperature, IEEE Sens. J. 20 (2020) 4562–4570. https://doi.org/10.1109/JSEN.2020.2966233.

[37] Z. Wang, T. Zhang, T. Han, T. Fei, S. Liu, G. Lu, Oxygen vacancy engineering for enhanced sensing performances: A case of SnO2 nanoparticles-reduced graphene oxide hybrids for ultrasensitive ppb-level room-temperature NO2 sensing, Sensors Actuators, B Chem. 266 (2018) 812–822. https://doi.org/10.1016/j.snb.2018.03.169.

[38] R. Al-Gaashani, A. Najjar, Y. Zakaria, S. Mansour, M.A. Atieh, XPS and structural studies of high quality graphene oxide and reduced graphene oxide prepared by different chemical oxidation methods, Ceram. Int. 45 (2019) 14439–14448. https://doi.org/10.1016/j.ceramint.2019.04.165.

[39] A.A. Yousif, R.M. Hathal, H.R. Abed, The Effectiveness of Decorating Antimony on the Structural, Optical, and Electrical Characteristics of SnO2 Nanowires, J. Electron. Mater. 50 (2021) 5442–5452. https://doi.org/10.1007/s11664-021-09070-9.

[40] S. Malvankar, S. Doke, R. Gahlaut, E. Martinez-Teran, A.A. El-Gendy, U. Deshpande, S. Mahamuni, Co-Doped SnO2 Nanocrystals: XPS, Raman, and Magnetic Studies, J. Electron. Mater. 49 (2020) 1872–1880. https://doi.org/10.1007/s11664-019-07865-5.

[41] H. Zhang, J. Feng, T. Fei, S. Liu, T. Zhang, SnO2 nanoparticles-reduced graphene oxide nanocomposites for NO2 sensing at low operating temperature, Sensors Actuators, B Chem. 190 (2014) 472–478. https://doi.org/10.1016/j.snb.2013.08.067.

[42] N. Tammanoon, A. Wisitsoraat, C. Sriprachuabwong, D. Phokharatkul, A. Tuantranont, S. Phanichphant, C. Liewhiran, Ultrasensitive NO2 Sensor Based on Ohmic Metal-Semiconductor Interfaces of Electrolytically Exfoliated Graphene/Flame-Spray-Made SnO2 Nanoparticles Composite Operating at Low Temperatures, ACS Appl. Mater. Interfaces. 7 (2015) 24338–24352. https://doi.org/10.1021/acsami.5b09067.

Sensitivity of SnO₂nanoparticles/reduced graphene oxide hybrid to NO₂ gas: A DFT study

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Abstract

Figures

Introduction

Theory

Results And Discussion

Conclusions

Declarations

References

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