Open access peer-reviewed chapter

Application of TiO2 Nanotubes Gas Sensors in Online Monitoring of SF6 Insulated Equipment

By Ju Tang, Xiaoxing Zhang, Song Xiao and Fuping Zeng

Submitted: February 7th 2017Reviewed: March 6th 2017Published: June 7th 2017

DOI: 10.5772/intechopen.68328

Downloaded: 557

Abstract

Titanium dioxide nanotube arrays (TNTAs) are a typical three-dimensional nanomaterial. TNTA has rich chemical and physical properties and low manufacturing costs. Thus, TNTA has broad application prospects. In recent years, research has shown that because of its large specific surface area and nanosize effect, the TNTAs have an enormous potential for development compared with other nanostructure forms in fields such as light catalysis, sensor, and solar batteries. TNTAs have become the hotspot of international nanometer material research. The tiny gas sensor made from TNTA has several advantages, such as fast response, high sensitivity, and small size. Several scholars in this field have achieved significant progress. As a sensitive material, TNTA is used to test O2, NO2, H2, ethanol, and other gases. In this chapter, three SF6 decomposed gases, namely SO2, SOF2 and SO2F2, are chosen as probe gases because they are the main by-products in the decomposition of SF6 under PD. Then, the adsorption behaviors of these gases on different anatase (101) surfaces including intrinsic, Pt-doped and Au-doped, are studied using the first principles density functional theory (DFT) calculations. The simulation results can be used as supplement for gas-sensing experiments of TNTA gas sensors. This work is expected to add insights into the fundamental understanding of interactions between gases and TNTA surfaces for better sensor design.

Keywords

  • SF6 decomposed gas
  • anatase TiO2 surface
  • metal doping
  • adsorption
  • sensing mechanism
  • density functional theory

1. Introduction of titanium nanotubes

TiO2 nanotubes are typically one-dimensional material, which has a wealth of physical and chemical properties and low production cost, and therefore, it bears a broad application prospects [1, 2]. In particular, recent studies show that, due to large specific surface area and nanosize effect, compared with other forms of nanostructures, TiO2 nanotubes show great potential for development in photocatalysis, sensors, solar cells and other areas [1, 3, 10]. It has become the research focus of nanomaterials internationally [1, 49]. The particular photocatalytic properties of TiO2 under UV irradiation can degrade pollutants and reduce desorption time, thus extending the lifetime of sensors that based on TiO2, which provides more opportunity for the development of high-quality new sensors.

1.1. Properties of titanium nanotubes

TiO2 is one common type of N semiconductor oxide, of which the outer electron distribution is 3d24s2. The molecular structure of TiO2 belongs to flash zinc crystal lattice. Its structural center, Ti atom, is surrounded by six oxygen atoms, forming an octahedral structure which coordination number is 6. TiO2 outer layer of 3d electronics is not active and 4 valence electrons of it form a covalent bond with O atom. From the above, we can know that the chemical properties of TiO2 are very stable. It cannot dissolve in most acid, such as hydrochloric acid, nitric acid and dilute sulfuric acid, except concentrated sulfuric acid and hydrofluoric acid. The band gap of TiO2 is approximately 3.2 eV. Its electrical conductivity is extremely low at room temperature. Even at high temperature, it only has a small conductivity. So its resistance is very big. We can almost see TiO2 as an insulator. TiO2′s conductance is achieved by activating the exciting electrons on the additional energy level to the conduction band. The additional level can be introduced from defects and impurities in TiO2. So the types and quantities of these defects and impurities determine the TiO2 conductivity type. Therefore, some methods may be employed to form a certain type of defect and impurity level or defect levels in the band gap to change the conductive properties of TiO2.

There are three TiO2 polymorphs in nature: rutile, anatase and brookite. Anatase and rutile structures are most widely used. Although rutile and anatase TiO2 crystalline belong to the same tetragonal, but they have two different lattices. And thus, the X-ray images are different.

Anatase TiO2 XRD diffraction angle 2θ is located in 25.5°, and rutile TiO2 XRD diffraction angle 2θ is located in 27.5°. Rutile TiO2 crystal forms a titanium atom in the lattice center, surrounded by six oxygen atoms which are located in octahedral edges and corners, and a cell composed of two moleculars is the most stable crystal structure. Anatase TiO2 crystal form is composed of four TiO2 molecules in a crystal cell, which is stable at low temperature. When the temperature reaches 610°C, it gradually transforms into rutile, and its transformation accelerated rapidly at 730°C, and it can transform into rutile completely at 915°C. Plate titanium ore TiO2 crystal form, belonging to orthorhombic system, is a cell composed of six TiO2 moleculars, which is an unstable crystal form that transforms into rutile type when the temperature is higher than 650°C. Figure 1 is the schematic diagram for the three kinds of morphology of crystalline structure of TiO2.

Figure 1.

Morphology of crystalline structure of TiO2 (a) rutile (b) anatase (c) brookite.

Plate titanium ore crystal form belongs to the metastable phase, and thus its structure is unstable, which is therefore rarely used in industrial production. Anatase and rutile belong to the same crystal system, but the atomic arrangement of rutile is compact, so its relative density as well as refractive index is larger, and it has very good properties of scattered light, as well as the shielding effect to UV light, while anatase, with good photocatalytic activity, has a wide application prospect in the aspects of environmental protection and electrochemical sensor.

1.2. Preparation method of titanium nanotubes

Currently, there are three types of the method for preparing TiO2 nanotubes, namely chemical template method, electrochemical method and hydrothermal method.

1.2.1. Chemical template method

The chemical template method involves assembling nanostructured primitive units into the porous template that forms nanotube structure. In the process of preparation of TiO2 nanotube template, first, a porous alumina is prepared by anodizing, which is used as a template later, and then impregnates titanium-containing compound into the template by sol-gel method. After turning titanium-containing compound that entered into the porous alumina template into the metal oxide that possesses a template with a similar pore diameter and morphology of nanotube structure by a high temperature annealing process, porous alumina template is then dissolved with concentrated alkali. Since the metal oxide is not dissolved in concentrated alkali, metal oxide nanotubes such as TiO2 nanotubes can be obtained, which have similar pore morphology to porous alumina template after washing by water. Martin et al. [1113] successfully prepared nanotubes of TiO2, Co3O4, MnO2, WO3 and ZnO and other metal oxides using this method.

1.2.2. Electrochemical method (anodic oxidation method)

Anodic oxidation method uses metal as an anode. Under the influence of applied electric field and electrolyte solution, electrochemical oxidation of the metal appears. Thereby a metal oxide film is produced on the surface of a metal. The formed metal oxide film will gradually dissolve because of the chemical reaction caused by the response plasma in electrolyte solution. The regional of chemical dissolution of metal oxide film is in nanoscale level. Therefore, when the speed of producing metal oxide by electric film dissolution is larger than the rate of chemical dissolution, the oxide film is ever thickening and accompanied by numerous nanopore deepening constantly caused by chemical dissolution. When the speed of producing metal oxide by electric film dissolution is equal to the rate of chemical dissolution, the thickness of the oxide film and the depth of the nanopores do not change. At this time, a certain thickness oxide film with a metal oxide nanotube structure is ready. With the controlling of the different experimental conditions in certain electrolyte, we can prepare TNTA with different diameters and lengths by anodizing. In 2001, Grimes [14] first reported that the TNTA with ordered arrangement can be obtained at room temperature after directly anodizing for pure titanium sheet in an HF aqueous solution. Grimes [10] studied the growth of the nanotubes changes under different conditions of the anodizing electrolyte. The length of the nanotubes can be increased when the electrolyte exhibits weak acid. In the case of organic phase electrolyte, the tube walls are smoother and the tube length can also reach about a hundred micrometers.

1.2.3. Hydrothermal method

Since the hydrothermal preparation method is simple and cheap, it is widely used in industrial production processes. TiO2 nanotubes prepared by this way are typically entwined and disorderly: first preparing TiO2 nanoparticles, and then mixing the nanoparticles with strong alkaline solution. Under conditions of high temperature and pressure, monolayer nanosheets curl of TiO2 in the alkali solution appears. Its formation mechanism is similar to that of multi-walled carbon nanotubes; it is a combination process from one-dimensional to two-dimensional and three-dimensional. After forming the TiO2 nanotubes, the product is neutralized by weak acid to neutralize the strong alkaline solution, and centrifuging it to get powdery TiO2 nanotubes. Using this method, Kasu’s team processed the TiO2 nanoparticles powder and NaOH solution at 110°C, then washed the reactants with water and hydrochloric acid and finally get TiO2 nanotubes [15].

2. Intrinsic and surface-modified TiO2 nanotubes gas sensors

2.1. Intrinsic TiO2 nanotubes gas sensors

2.1.1. Investigation of gas-sensing simulation of intrinsic TiO2 nanotubes

Three SF6 decomposed gases, namely SO2, SOF2, and SO2F2, are chosen as probe gases because they are the main by-products in the decomposition of SF6 under PD. The adsorption behaviors of these gases on an anatase (101) surface are studied using the first principles density functional theory (DFT) calculations.

2.1.1.1. Adsorption models and calculation methods

The optimal lattice size of bulk anatase given in MS is 3.776 × 3.776 × 9.486 Å3, which is very small compared with the size of a single TiO2 nanotube. Thus, the gas molecules adsorbed in a small area of the TNTAs surface are simulated, and the nanotube-array structure is not taken into account. The prepared TNTAs are calcined at a high temperature in an oxygen-rich environment, and oxygen atoms should occupy the oxygen vacancies on the TNTAs surface [16]. The phenomenon is consistent with the findings that many thermodynamically stable (101) facets dominate the surface of most anatase nanocrystals [17]. Therefore, the gas-array interaction can be properly simulated on the anatase (101) surface.

Periodic boundary model is adopted in this work, and the 2 × 2 supercell of the anatase (101) surface is created in MS, as shown in Figure 2. The size of the supercell is 10.88 × 7.55 × 17.84 Å3. In order to avoid the interaction between adjacent cells which is induced by the periodic boundary condition, the vacuum layer above surface is about 12 Å. The atoms on the bottom layer are fixed, and the structure of the supercell is optimized.

Figure 2.

2 × 2 supercell of the anatase (101) surface.

The generalized gradient approximation (GGA) exchange-correlation function parameterized by Perdew, Burke, and Ernzerhof [18] is employed for the electron-electron exchange and correlation interactions. Moreover, the double numerical basis set plus polarization functions (DNP) [19, 20] are used. All optimized structures are obtained with a precision of 1 × 10−5 Ha for energy, 2 × 10−3 Ha/Å for force, and 5 × 10−3 Å for displacement, the convergence threshold for the electronic self-consistent field is set to 1 × 10−6 Ha. A Fermi smearing of 5 × 10−4 Ha is used. To speed up the convergence and reduce calculation time, the DIIS (direct inversion in an iterative subspace) is used at the same time. The Brillouin zone is sampled at 2 × 3 × 1 k-mesh [21]. All spin-unrestricted DFT calculations are performed using the Dmol3 package [19, 20].

The band gap is 2.16 eV, which is closer to other simulation results [22, 23] but smaller than the experimental gap (3.24 eV [24]). The reason for this is the well-known deficiency of the GGA arithmetic [25] in which DFT maps the problem of N interacting electrons onto a system of N non-interacting fictitious particles. Therefore, the calculation scheme is effective, and the results and conclusions are reasonably reliable.

The active atoms of the anatase (101) surface are Ti5c and O2c, as shown in Figure 2. Figure 3 shows band structure of the optimized supercell. To find the most stable adsorption structures, the three gas molecules should approach the active atoms on the surface in different orientations and behaviors. Figure 4 shows the most stable adsorption structures of the three gas molecules.

Figure 3.

Band structure of the optimized supercell.

Figure 4.

Optimized geometric structures of (a) SO2, (b) SOF2, and (c) SO2F2 adsorbed on the anatase (101) surface. Ti and O atoms are in gray and red, respectively. Binding distances are in Å.

2.1.1.2. Adsorption parameters and analysis

The gas-surface interaction can be described using the adsorption energy Ead defined as Ead = Esurf/gas - Egas - Esurf, where Egas is the energy of one isolated gas molecule in its optimized structure, Esurf is the total energy of the TiO2 structure, and Esurf/gas is the total energy of the adsorption structure [1]. Ead < 0 means that the adsorption process is exothermic and spontaneous.

The change in charge distribution should be known. Therefore, the charge transfer q is calculated using the Mulliken population analysis and is defined as the charge variation of isolated gas molecules when it is adsorbed [1]. A positive q value means that the charge is transferred from the molecule to the anatase surface. The binding distance d is defined as the nearest distance between the molecule and the surface. The calculated adsorption parameters are shown in Table 1.

SystemStructureEad/eVq/ed
SO2a−0.3430.0942.424
SOF2b−0.2750.0432.493
SO2F2c−0.1860.0083.230

Table 1.

Calculated adsorption energy, charge transfer, and binding distance.

The adsorption energies are negative, indicating that the adsorptions are exothermic and spontaneous. The values of energy released in the adsorptions are SO2 > SOF2 > SO2F2, and all are small (<0.6 eV). This finding indicates that the molecules of the three gases are physisorbed, not chemisorbed, on the anatase (101) surface. Thus, gas molecules cannot effectively be adsorbed on TNTAs at room temperature because of the small adsorption energy, indicating that the experimental responses of the three gases may also be very small at room temperature. When the temperature is high, the Ti5c-O2c bonds will be stretched with the increased temperature, and the interactions between the molecules and surface become stronger. Under this condition, the molecules can be chemisorbed on the surface, which can explain the high responses in the sensing experiment. The adsorption energy of SO2 is the largest of the three gases, which shows that the adsorption of SO2 is the strongest; it is firmly absorbed and difficult to desorb.

The three gases all behave as charge donors. The charge transfer of SO2 is more than twice than that of SOF2, and for SO2F2, it is only 0.008 e. This finding indicates that SO2 can provide more electrons to the surface and that the surface has a better sensitivity to SO2.

The highest occupied molecular orbital (HOMO) energy level and lowest unoccupied molecular orbital (LUMO) energy level of the three gas molecules and of the anatase (101) surface are calculated according to molecular orbital theory. By analyzing the HOMO and LUMO, whether the gases easily interact with the anatase (101), surface can be estimated. E1 and E2 are defined as follows:

E1=|EHOMO(TiO2)ELUMO(gas)|E2=|ELUMO(TiO2)EHOMO(gas)|E1

If E1 is small, the charge is more easily transferred to the gas molecules from the surface. If E2 is small, the charge is more easily transferred to the surface from the gas molecules. The calculated EHOMO, ELUMO, E1, and E2 are listed in Table 2.

SystemEHOMO/eVELUMO/eVE1/eVE2/eV
TiO2−7.257−5.093//
SO2−8.000−4.6692.5872.917
SOF2−8.536−3.0724.1853.453
SO2F2−9.145−2.6284.6284.062

Table 2.

Energy frontier molecular orbital and the energy difference.

Both the E1 and E2 of SO2 are smaller than those of the other two gases. This finding shows that SO2 easily interacts with the anatase (101) surface and that the charge transfer is also the easiest between them. SO2F2 interacting with the surface is relatively difficult. Here, we also find that the anatase (101) surface is more sensitive to SO2 than to SOF2, and the sensitivity of the surface to SOF2 is better than that to SO2F2.

The energy gap of the adsorption structure can be calculated through the energy levels of the HOMO and LUMO defined as Eg:

Eg=|EHOMOELUMO|E2

The energy gap width determines how much energy an electron needs to jump into the LUMO from the HUMO. The wider the gap, the more energy is required and the more difficult it is for electrons to transfer between the valence band (VB) and the conduction band (CB). Table 3 shows the energy gaps. The adsorption of SO2 on the anatase (101) surface reduces the energy gap width and improves the electron transfer of the surface. However, the adsorption of SOF2 and SO2F2 cannot do so. Therefore, TNTAs are much more responsive to SO2 gas than to SOF2 and SO2F2.

SystemEHOMO/eVELUMO/eVEg/eV
TiO2−7.257−5.0932.164
TiO2-SO2−7.134−5.6071.527
TiO2-SOF2−7.208−5.0532.155
TiO2-SO2F2−7.204−5.0472.156

Table 3.

Energy gaps of the adsorption structures and structures without adsorption.

The molecular structures of the gases are also analyzed based on valence bond theory (VBT) combined with molecular orbital theory. A three-center four-electron pi bond exists in the SO2 molecule, and the pi bond contains five orbitals that are hybridized by a 3p orbital, two 3d orbitals in the S atom, and a 3p orbital in each O atom. This finding indicates that the pi bond consists of some 3d orbitals. Four electrons occupy the two lower orbitals (i.e., HOMO and HOMO-1) of the pi bond, and the middle orbital of the pi bond is unoccupied (LUMO). However, the d-p pi bond exists between the S atom and the O atom in the SOF2 and SO2F2 molecules. The S atom in SOF2 has one lone pair of electrons, but not the SO2F2. Therefore, the SO2F2 molecule is more stable than the SOF2 molecule. Moreover, the activities of the gas molecules can be compared by obtaining the difference between EHOMO and ELUMO. Table 4 shows ΔE, which is defined as ΔE =.ELUMO (gas)EHOMO (gas). Based on the VBT analysis and the data in Table 4, the pi bond in SO2 is more active than the d-p pi bond in SOF2 and SO2F2. Moreover, SO2 is easy to interact with the anatase (101) surface.

GasSO2SOF2SO2F2
ΔE/eV3.3305.4646.517

Table 4.

Difference between HOMO and LUMO.

To investigate the influence of adsorbed gas molecules on the electronic property of the anatase (101) surface, the total density of states (TDOS) of the adsorption system and the projected density of states (PDOS) of adsorbed gas molecules calculated using MS are given in Figure 5. The Fermi level is aligned at zero. As shown in Figure 5, when the molecules of the three gases are adsorbed on the surface, the Fermi levels of those still on top of the VB change little. This finding indicates the formation of a depletion region on the surface, and only a few charge carriers are present in this region. Therefore, the surface presents high resistivity.

Figure 5.

The TDOS of adsorption systems and the PDOS of adsorbed gas molecules.

The TODSs of the SOF2 and SO2F2 adsorption systems remain nearly unchanged compared with the system without adsorption, which indicates that the adsorbed SOF2 and SO2F2 induce little change to the electronic property of the (101) surface. An unapparent density peak of around 2.8 eV exists in the PDOS of SOF2. On the other hand, the adsorbed SO2 induces noticeable change to the electronic property of the (101) surface. The SO2 adsorption introduces an impurity state near the CB, as shown in Figure 6, resulting in a narrowing of the band gap (which changes from 2.161 to 1.527 eV). The unoccupied impurity state is a surface state of the anatase (101) surface, which can capture or release electrons or form a composite center, improving the conductive performance of the surface. The PDOSs of p orbitals that contribute to the impurity state and the orbitals that contain the 3p orbital of the S atom and the 2p orbital of the O atom (near the surface in Figure 4) are shown in Figure 7.

Figure 6.

Band structure of the TiO2-SO2 adsorption system.

Figure 7.

PDOS of the p orbitals of impurity state.

2.1.2. Preparation and surface characterization of intrinsic TiO2 nanotubes

The present study generated a TNTA by an anodic oxidation method using a two-electrode system [1]. A platinum metal piece was used as cathode, whereas a titanium piece was used as anode. The experimental processes are as follows: first, 0.5-mm-thick Ti foil (area of 0.8 cm × 2.0 cm and purity of 99.94%) was burnished with sandpaper, soaked in 30% HCl solution, and heated to 80°C for 20 min to remove the surface oxidation layer [1]. Then, the Ti pieces were cleaned by washing with deionized water. The clean Ti pieces acted as the anode, whereas the platinum pieces acted as the cathode in the two-electrode electrochemical electrolysis pool. Between the two electrodes, a constant 20 V of anodic oxidation was applied continuously for 2 h. The electrolyte concentration was 0.1 M HF solution, and the electrolyte pH value was tested using a Model 3000 pH meter [1]. Magnetic stirring was applied to ensure the uniformity of the Ti electrode surface electric current and temperature in the oxidation process and reduce the influence of the double electric layer between the electrolyte and electrode interface [1]. After the reaction, the TNTA was cleaned by washing with deionized water, dried in air heated from 2°C/min to 500°C in a muffle furnace for 1 h, and then removed after the temperature dropped to room temperature [1].

Figure 8 shows the scanning electron microscopy (SEM) images of the TNTAs. As observed from the SEM images, the TNTAs are highly ordered and directionally grown, the pipe diameter of which is about 80 nm, length is about 300 nm, and thickness is about 10 nm. The main effect of having an ordered structure is to further improve the area’s effective adsorption area. The schematic diagram of TNTAs is shown in Figure 9.

Figure 8.

SEM images of TNTAs: (a) side view, (b) front view, (c) front amplification view.

Figure 9.

Schematic diagram of TNTAs.

Figure 10 shows the X-ray diffraction spectrum diagram of the TNTAs. The strong (101) facet peak of anatase (A in the figure) exists at 2θ = 25.3°, and the weak strong (110) facet peak of rutile exists at 2θ = 27.4° (R in the figure). These findings indicate that TNTAs are mainly anatase, and a small amount of the rutile phase is observed.

Figure 10.

X-ray diffraction pattern of TNTAs.

2.1.2.1. Gas-sensing experiments of intrinsic TiO2 nanotubes sensors

Figure 11 presents the detection test device for the TNTA sensor response measurement of the SF6 decomposition products [1]. Shown in the figure are the following: (1) quartz glass tube; (2) thermal resistance probe; (3) carbon nanotube sensors; (4) ceramic heating slices; (5) vacuum form; (6) vacuum pump; (7) vent ducts; (8) terminals; (9) AC regulator; (10) temperature display apparatus; (11) impedance analyzer; (12) gas flow meter; and (13) inlet ducts [1].

Figure 11.

Detection test device for the TNTA sensor response measurement of SF6 decomposition products.

The tested gases are SO2, SOF2, and SO2F2, which have a concentration of 50 μL/L, and N2 is used as the carrier gas [26]. The response R% is defined as the relative variation of the sensor’s resistance: (RgR0)/R0, where Rg is the resistance of the sensor to the relevant gas, and R0 is pure N2 [26]. The factors that influenced the response are analyzed comparatively, and the sensing mechanism of the temperature characteristic curves is explained based on the simulation results.

The responses of TNTAs to the 50 μL/L gases are shown in Figure 12. At 20°C, the response of SO2 is slightly higher than that of SOF2 and SO2F2, and the responses of SOF2 and SO2F2 are both small. When the temperature is above 120°C, the response of SO2 is much higher than that of the two gases. The response of SOF2 is slightly higher than that of SO2F2. This phenomenon matches the simulated findings. Therefore, the study concludes that the response R% depends on the impurity state introduced by the adsorbed gas molecule, and the band structure influences by the impurity state.

Figure 12.

Temperature characteristic curves of the responses of 50 μL/L gases.

The sensing mechanism of temperature characteristic curves is analyzed first.

When the temperature is low, the adsorbed gas molecules can provide a number of electrons to the semiconductor surface or reduce the band gap of the semiconductor; the thermal excitation of the semiconductor remains weak. The electron depletion region of the surface remains, and the electron concentration variation is small. All sensing responses are low when the temperature is low. Conversely, when the temperature increases, thermal excitation begins to play a main role, and more electrons in the valence band exit to the conduction band, producing more hole electron pairs and greatly increasing the electron concentration. The adsorption of the three gases then provides electrons onto the semiconductor surface, introduces the impurity states, and reduces the band gap. Thus, more excited electrons enter into the CB from the VB, and their sensing response becomes higher.

The reason for the changes in the temperature characteristic response of SO2, as shown in the curve in Figure 12, is discussed. The gas response at a high temperature is positively related to the concentration of thermally excited electrons and the adsorption amount of gas molecules. The adsorption amount increases when the temperature increases. However, if the temperature is too high, the thermal motions of the gas molecules become aggressive and a number of adsorbed gas molecules break away from the surface, decreasing the adsorption amount. The electrons produced by thermal excitation grow exponentially with the increasing temperature. Thus, the temperature characteristic response increases with the increasing temperature at first and then remains nearly unchanged.

The responses of SO2 and SOF2 are then compared. When the temperature is about 200°C, the response of SOF2 is much lower than that of SO2, and it is not sensitive to the varying temperature. The impurity state introduced by SO2 has a great impact on the band structure and the SO2 has a higher response because the impurity state introduced by SOF2 has little effect on the band structure. The thermal excitation is weak, and only a few electrons are exit to the CB through the impurity states under 20°C. Therefore, the impurity states of SO2 and SOF2 have little effect on the band structure. However, TSO2 provides more electrons to the surface, and the response of SO2 is slightly high.

Finally, the responses of SOF2 and SO2F2 are compared. SOF2 provides more electrons to the surface than SO2F2, but the responses of the two gases are both small because the impurity states induced by the two adsorbed gases have little influence on the band structure. The electron depletion region on the surface also influences the low responses. Considering the comparative analysis of SO2 and SOF2, it can be concluded that, if the impurity state introduced by adsorbed gas has a greater impact on the band structure, the electrons provided by adsorbed gas will have a relatively large influence on the response at low temperatures.

When the temperature is high, the response of SOF2 is slightly higher than that of SO2F2. The unapparent density peak around 2.8 eV in the PDOS of SOF2 has a certain effect on the band structure, and some electrons in the VB exit to the CB, which promotes the response.

The difference between the responses to 50 μL/L SOF2 and SO2F2 is not obvious in Figure 12; thus, we discuss the concentration response curves of SOF2 and SO2F2 at 200°C in Figure 13. In Figure 13, with increased concentration, the increase in SO2F2 response is relatively larger than that of the SOF2 response because the impurity state introduced by the increase in SOF2 has a greater impact on the band structure.

Figure 13.

Response curves of SOF2 (a) and SO2F2 (b) when the concentration varies at 200°C.

2.2. Pt-doped TiO2 nanotubes sensors

The adsorptions of SO2, SOF2, and SO2F2 on Pt-modified anatase (101) surface are calculated, the effect of modified Pt on the adsorption behavior of gas molecules is analyzed, and the sensing mechanism of Pt-modified TNTA is also explained clearly [27]. In this study, we improve the sensing mechanism of Pt-modified TNTA and provide a theoretical basis for the detection of SF6 decomposition components using the TNTA gas sensor [1, 28].

2.2.1. Investigation of gas-sensing simulation of Pt-doped TiO2 nanotubes

2.2.1.1. Adsorption models and calculation methods

Figure 14 shows the adsorption structures of SO2, SOF2, and SO2F2 on the perfect (101) surface of Pt-modified anatase [1]. The adsorption parameters are shown in Table 5. Comparing the parameters in Table 5 [1] with the parameters in references [29, 30], we observed that the modified Pt atom has a slight influence on the adsorptions of the three gases on the perfect surface near the Pt atom [1]. The energy values of the three gases adsorbed on the anatase perfect surface are all still <0.6 eV. The charges in the adsorptions are still transferred from the molecules to the surface, which reveals that the three adsorptions are physisorptions [1]. This finding indicates that the adsorption performance of the perfect (101) surface of the Pt-modified anatase to the three gases is nearly unchanged [1]. Figure 15 shows the DOS of the three adsorption structures [1]. We observed that the DOS is also nearly unchanged, and the state density near the Fermi level is mainly determined by the modified Pt atom. However, when the three gas molecules adsorb on the perfect (101) surface of the Pt-modified anatase, the conductivity of the surface is improved [1, 29].

Figure 14.

Adsorption structures of SO2, SOF2, and SO2F2 on the perfect (101) surface of Pt-modified anatase.

Figure 15.

TDOSs of the adsorption structures of SO2, SOF2, and SO2F2 on the perfect (101) surface of Pt-modified anatase and PDOSs of the three gases in these structures.

Adsorption siteStructureAdsorption energyCharge transferBond distance
Perfect surface of the Pt-modified anatase surfaceSO2–TiO2(a)−0.36060.09202.471
SOF2–TiO2(b)−0.28110.04702.803
SO2F2–TiO2(c)−0.06920.01102.841

Table 5.

Adsorption parameters of the three gases adsorbed on the perfect (101) surface of Pt-modified anatase.

2.2.1.2. Adsorption parameters and analysis

Figure 16 shows the adsorption structures of SO2, SOF2, and SO2F2 on the modified Pt atom [1]. The adsorption parameters are shown in Table 6 [1]. When SO2 is adsorbed, two situations, which depend on the initial structure, occur. One is the physisorption structure shown in Figure 16a whose adsorption energy is −0.2394 eV. The other is the chemisorption structure shown in Figure 16b whose adsorption energy is −1.1009 eV. When SOF2 is adsorbed, the physisorption and chemisorption situations occur. The chemisorption structure is shown in Figure 16c The Pt atom has a stronger adsorption to the S atom in SOF2 than the O or F atom [1]. Thus, the SOF2 molecule is more easily chemisorbed on the Pt atom with the S atom, rather than physisorbed with the O or F atom [1].

Adsorption siteStructureAdsorption energyCharge transferBond distance
Adsorbed on the modified Pt atomSO2–TiO2(a)−0.2394−0.1152.329
SO2–TiO2(b)−1.1009−0.2922.363
SOF2–TiO2(c)−0.9416−0.0752.263
SO2F2–TiO2(d)−0.06300.0202.425

Table 6.

Adsorption parameters of the three gases adsorbed on the modified Pt atom of Pt-modified anatase.

Figure 16.

Adsorption structures of SO2, SOF2, and SO2F2 on the modified Pt atom of Pt-modified anatase.

When SO2F2 is adsorbed, the adsorptions are mainly physisorptions, such as the structure shown in Figure 16d In addition, in a few initial structures, one S–F bond of SO2F2 may break and SO2F2 would be chemisorbed on the Pt atom. Figure 17 shows the DOS of the three gases adsorbed on the Pt atom [1]. The adsorbed gas molecules contributed to the state density near the Fermi level, which changes the electronic distribution of the area around the modified Pt atom and influences the conductivity of this area [1].

Figure 17.

TDOSs of the adsorption structures of SO2, SOF2, and SO2F2 on the modified Pt atom of Pt-modified anatase and PDOSs of the three gases in these structures.

Considering that the actual size of the modified Pt nanoparticle is larger than a single gas atom, and the conductivity of the nanoparticle is good and stable, we assume that the adsorptions of the gas molecules on the surface of the nanoparticle have a slight influence on the conductivity of the nanoparticle [1]. The main effect of the nanoparticle is the catalytic decomposition of some gas molecules [1]. We also calculated the adsorptions of SO2, SOF2, and SO2F2 on the Pt (200) surface to verify this finding. The adsorption structures are shown in Figure 18 [1]. In Figure 18a and b [1], we observed that SO2 and SOF2 form stable adsorption structures on the Pt (200) surface with the S atoms, which are similar to the structures on the single Pt atom of the anatase (101) surface. Figure 18c [1] is the stable adsorption structure of SO2F2 on the Pt (200) surface, which is different from the structure shown in Figure 17d [1], in that one S–F bond of SO2F2 breaks, as shown in Figure 18c [1], and SO2F2 is chemisorbed on the Pt (200) surface. The Pt (200) surface supplies more electrons than a single Pt atom of the anatase (101) surface and the S–F bond more easily breaks. Thus, we conclude that, when adsorbed on the Pt nanoparticles of the TNTA surface, the SO2F2 gas molecules are more easily catalytically decomposed by the Pt nanoparticles than the SOF2 molecules.

Figure 18.

Adsorption structures of SO2, SOF2, and SO2F2 on the Pt (200) surface.

Figure 19 [1] shows the adsorption structures of SO2, SOF2, and SO2F2 on Pt and anatase. The adsorption parameters are shown in Table 7. From Table 7 [1], we observed that the values of the adsorption energies of the three gases adsorbed on this site are relatively large, which indicates chemisorption [1]. The adsorption energy of SO2F2 is the largest and that of SOF2 is the smallest. When SO2 is adsorbed, the S atom of the SO2 molecule bonds with the Pt atom, and one O atom of the SO2 molecule bonds with the titanium (Ti) atom, as shown in Figure 19a [1]. When SOF2 is adsorbed, the S atom of the SO2 molecule also bonds with the Pt atom and one O atom of the SO2 molecule bonds with the Ti atom, as shown in Figure 19b [1]. When SO2F2 is adsorbed, one S–F bond of SO2F2 breaks down. The S and F atoms bond with the Pt atom, with one O atom of the SO2F2 molecule bonding with the Ti atom, as shown in Figure 19c.

Figure 19.

Adsorption structures of SO2, SOF2, and SO2F2 on both Pt and anatase.

Adsorption siteStructureAdsorption energyCharge transferBond distance
Adsorbed on Pt and anataseSO2–Pt–TiO2(a)−1.4215−0.27002.155
SOF2–Pt–TiO2(b)−0.8405−0.19302.273
SO2F2–Pt–TiO2(c)−1.6862−0.71102.003

Table 7.

Adsorption parameters of the three gases adsorbed on both of Pt and anatase.

Figure 20 [1] shows the DOS of the three gases adsorbed on Pt and anatase. We observed that the adsorbed gas molecules contributed to the state density near the Fermi level, which also changes the electronic distribution of the area around this adsorption site. Considering the actual effect of Pt nanoparticles, we assume that this adsorption site is more active and the adsorptions of gas molecules on this site effectively connects the Pt nanoparticle surface and the anatase (101) surface, which may improve the conductivity performance of this area [1].

Figure 20.

TDOSs of the adsorption structures of SO2, SOF2, and SO2F2 on both of Pt and anatase and PDOSs of the three gases in these structures.

2.2.2. Preparation and surface characterization of Pt-doped TiO2 nanotubes

The Pt-doped TiO2NTs based on intrinsic TiO2NTs were prepared using constant current method to deposit the Pt nanoparticles onto the TiO2NT surface. Intrinsic TiO2NTs were prepared through anodic oxidation [31], and a conventional three-electrode system with constant potential method is used to dope Pt nanoparticles into TiO2NTs. In the three-electrode system, the intrinsic TiO2NTs serve as the working electrode with a geometric area of 4.0 cm2. The Ag/AgCl electrode is the reference electrode, and platinum electrode functions as the counter electrode. An electronic pulse signal was produced in the constant current control mode of the Shanghai Chen Hua CHI660D electrochemical analyzer. The electrolyte was an aqueous solution of H2PtCl6⋅6H2O (1 g/L) and H3BO3 (20 g/L) at 50°C (pH = 4.4). After numerous exploratory experiments, the optimal parameters determined for the constant current method are as follows: current density of 0.1 mA/cm2, and doping times of 10, 20, 30, and 40 s. In the deposition process, a magnetic stirrer is used to ensure that the liquid has a stable metal ion concentration.

Figure 21 shows the cyclic voltammetry curve of the four types of sensors with different amounts of doped Pt in 1.0 mol/L NaOH solution. Curves (a) to (d) correspond to the doping times of 10, 20, 30, and 40 s, respectively. During electrochemical deposition, Pt4+ in the electrolyte is reduced to Pt, as described in [32]; the sizes of the curve areas were compared to determine the amount of deposited Pt metal. The humps between −1.0 and 0.8 V in the four curves shown in Figure 21 correspond to the hydrogen absorption and dehydrogenation processes of the Pt ions in NaOH solution [33]. The hump in curve (a) is not evident, and the humps in curves (b) to (d) are significant. Based on the size of each curve surrounding the area, we concluded that the amount of deposited Pt nanoparticles on the TiO2NT surface is proportional to deposition time.

Figure 21.

Cyclic voltammetry curve of sensors with different amounts of doped Pt in 1.0 mol/L NaOH.

Figure 22 shows the SEM images of intrinsic and Pt-doped TiO2NTs. Figure 22a shows the intrinsic TiO2NTs, and Figure 22b–e presents the Pt-doped TiO2NTs with deposition times of 10, 20, 30, and 40 s. The white objects around or above the tube wall in Figure 22 are Pt nanoparticles. The SEM images show that the amount of Pt deposition increases with the deposition time. At 10 s, less Pt nanoparticles are deposited, and at 30 s, the Pt nanoparticles have moderate sizes and are uniformly distributed. At 40 s, more Pt nanoparticles are deposited, and large tracts of these nanoparticles block the mouth of TiO2NTs, as shown in Figure 22e.

Figure 22.

SEM images of intrinsic and Pt-doped TiO2NTs.

Figure 23 shows that the intrinsic and Pt-doped TiO2 NTs have strong anatase (101) crystal plane peak at 2θ = 25.3° (A in Figure 23). Pt (111) and (200) crystal surface peaks at 2θ = 40.5 and 46° were observed in the XRD patterns of the Pt-doped TiO2 NTs.

Figure 23.

XRD patterns of Pt-doped TiO2NTs.

However, no such peaks are found for the intrinsic TiO2 NTs. This result shows that the constant potential method is useful when Pt nanoparticles are doped on TiO2 NTs.

2.2.3. Gas-sensing experiments of Pt-doped TiO2 nanotubes sensors

The performance of gas-sensitive metal oxide material is significantly influenced by working temperature. Therefore, the gas-sensing responses of the sensors with different amounts of doped Pt were investigated under different operating temperatures for SOF2, SO2F2, and SO2 gases. The optimal operating temperatures of the sensors were also determined.

The prepared Pt-doped sensors were placed into the test device (Figure 11). The sensor surface was then controllably heated. In this experiment, the sensor gas-sensing characteristics of the sensors for SOF2, SO2F2, and SO2 gases at 100 ppm from 20 to 220°C were examined. The results are shown in Figure 24.

Figure 24.

Sensitivity of sensors with different amounts of doped Pt with varying working temperatures.

Figure 24 shows the resistance sensitivity curves of the sensors with different amounts of doped Pt for SOF2, SO2F2, and SO2. The figure shows that the gas response value of the sensor (i.e., resistance change rate, R%) increases with increasing sensor surface temperature. The optimal sensor operating temperature is approximately 160°C. When the temperature reaches 100–160°C, the largest response value is observed. As the temperature increases, the sensor response value begins to dramatically decrease. When the temperature reaches 200°C, the response value becomes small. The optimal operating temperatures and selectivity of the four sensors for the three decomposition component gases vary, as shown in Table 8.

Doping timeOptimal temperatureSensitivity
SO2SOF2SO2F2
10 s160°C−53.3%−24.2%−5.4%
20 s150°C−33.9%−22.1%−19.2%
30 s130°C−13.8%−19.1%−50.6%
40 s100°C−6.7%−5.1%−10.7%

Table 8.

Sensitivity of Pt-doped sensors for 100 ppm SO2, SOF2, and SO2F2 at their optimum temperatures.

The optimal operating temperature is 160, 150, 130, and 100°C at 10, 20, 30, and 40 s doping time, respectively. These results show that with increasing doping time, the optimal working temperature of the sensor decreases. In addition, at the optimal temperature, the sensor with 10 s of doping time is the most sensitive to SO2 at −53.3% but has the weakest response to SO2F2 at −5.4%. The sensor with 20 s of doping time is most sensitive to SO2 at −33.9% but has weakest response to SO2F2 at −19.2%. The sensor with 30 s of doping time is most sensitive to SO2F2 at −50.6% but has weakest response to SO2 at −13.7%. The SOF2 gas response values of these three sensors remained almost unchanged. The sensor with 40 s of doping of time has significantly low responses for the three gases.

Compared with the intrinsic TiO2NT sensor, the doped Pt nanoparticles alter the sensor surface microstructure and charge distribution. When the sensor surface temperature is higher than its optimum working temperature, the Pt nanoparticles improve the chemical desorption rate on the sensor surface. This result indicates that the desorption rate of a gas molecule is higher than its adsorption rate, and that the density of the gas molecule adsorbed onto the surface decreases, such that the response value of the sensor rapidly decreases. However, most parts of the tube mouth of the 40 s sensor are blocked by Pt nanoparticles; thus, the gas-sensing response value is highly reduced.

According to the experimental methods and procedures mentioned above, the four kinds of sensors function at their optimal operating temperatures. Their gas-sensing property curves are tested under SO2, SOF2, and SO2F2 gases at 25, 50, 75, and 100 ppm. The change rate of the sensor resistance (gas-sensing response value) was calculated at various concentrations. The linear relationship between the change rate of the sensor resistance and gas concentration was examined. Using the linear fit curve, we can also estimate the concentration of the gas using the sensor response value. After multiple experiments, the gas-sensing response values of the four sensors were found to increase with the experiment gas concentration, but for one kind of gas. Therefore, in the following section, only the 30 s sensor is considered, and its gas-sensing response curves were obtained at different gas concentrations. The experimental data of the remaining three sensors were obtained using the linear fit curve.

2.2.3.1. Gas-sensing properties of sensors with different amounts of doped Pt to SO2 gas

Figure 25a shows that sensor with 30 s of doping time has resistance change rates of −2.0, −7.0, −10.0, and −13.8% for the SO2 gas at 25, 50, 75, and 100 ppm, respectively. Figure 25b shows that sensor with 10 s doping time has response values of −10.7, −25.6, −36.0, and −53.2% for the four SO2 concentrations. For the sensor with 20 s of doping time, the response values are −3.2, −13.4, −22.3, and −33.9% for the four SO2 concentrations. Meanwhile, for the sensors with 40 s of doping time, response values are −0.8, −3.5, −5.0, and −6.7% for the four SO2 concentrations. The sensitivities are shown in Table 9. The linear fit function and linear correlation coefficient are shown in Figure 25b.

Figure 25.

Response of four sensors with different amounts of doped Pt to varying concentrations of SO2. (a) Gas-sensing response curves of 30 s sensor for different concentrations of SO2 gas at 130°C. (b) Linear relationship between sensor response and gas concentration.

ConcentrationSO2
10 s20 s30 s40 s
100 ppm−53.2%−33.9%−13.8%−6.7%
75 ppm−36.0%−22.3%−10.0%−5.0%
50 ppm−25.6%−13.4%−7.0%−3.5%
25 ppm−10.7%−3.2%−2.0%−0.8%

Table 9.

Sensitivity of Pt-doped 30 s sensor to different concentrations of SO2 at optimal working temperature.

2.2.3.2. Gas-sensing properties of sensors with different amounts of doped Pt for SO2F2 gas

Figure 26a shows the gas-sensing response curve of the sensor with 30 s doping time for SO2F2 at 25, 50, 75, and 100 ppm and 130°C. The resistance change rate is −3.5, −16.1, −32.1, and −50.6% for the different tested SO2F2 concentrations. Figure 26b shows that sensor with 10 s of doping time has response values of −0.9, −2.1, −3.9, and −5.4% for the different SO2F2 concentrations. The sensor with 20 s of doping time has response values of −1.1, −7.8, −11.5, and −19.1% for the different SO2F2 concentrations. The sensor with 40 s doping time has response values for −0.9, −3.0, −7.2, and −10.9% to the different SO2F2 concentrations. The sensor sensitivities are shown in Table 10. The linear fit function and linear correlation coefficient are shown in Figure 26b.

Figure 26.

Response of four sensors with different amounts of doped Pt to varying concentrations of SO2F2. (a) Gas-sensing response curves of 30 s sensor for different concentrations of SO2F2 gas at 130°C. (b) Linear relationship between sensor response and gas concentration.

ConcentrationSO2F2
10 s20 s30 s40 s
100 ppm−5.4%−19.1%−50.6%−10.9%
75 ppm−3.8%−11.5%−32.1%−7.2%
50 ppm−2.1%−7.8%−16.1%−3.0%
25 ppm−0.9%−1.1%−3.5%−0.9%

Table 10.

Sensitivity of Pt-doped 30 s sensor to different concentrations of SO2F2 at optimal working temperature.

2.2.3.3. Gas-sensing properties of sensors with different amounts of doped Pt for SOF2 gas

Figure 27 shows that the sensor with 30 s of doping time has a resistance change rates of −1.1, −6.3, −10.0, and −19.1% for SOF2 gas at 25, 50, 75, and 100 ppm, respectively. Figure 27b shows that the sensor with 10 s doping time has response values of −3.2, −8.7, −15.8, and −24.9% for the four SOF2 concentrations. The sensor with 20 s doping time has response values of −2.0, −8.2, −14.2, and −22.3% for the four SOF2 concentrations. The sensor with 40 s doping time has response values of −0.8, −2.0, −3.9, and −5.3% to four SOF2 concentrations. The linear fit function and linear correlation coefficient are shown in Figure 27b.

Figure 27.

Responses of sensors doped with different amounts of Pt to varying concentrations of SOF2. (a) Gas-sensing response curves of 30 s sensor for different concentrations SOF2 gas at 130°C. (b) Linear relationship between sensor response and gas concentration.

Figure 28 shows a comparison chart for the gas-sensing responses of the four sensors for SO2, SOF2, and SO2F2 gases at 100 ppm and at their optimal working temperatures. The responses of the intrinsic TiO2NT sensor for these decomposition gases are discussed in Ref. [30]. With increasing doping amount, the sensor response for SO2 decreases and follows the trend: intrinsic (−73.5%) > 10 s (−53.3%) > 20 s (−33.9%) > 30 s (−13.8%) > 40 s (−6.7%). When the doping amount increases, the sensor response for SO2F2 increases and follows the trend: intrinsic (−4.1%) < 10 s (−5.4%) < 20 s (−19.2%) < 30 s (−50.6%) >> 40 s (−10.9%). The responses of the 10, 20, and 30 s sensors for SOF2 gas are nearly identical; however, response of the 40 s sensor for SOF2 dramatically decreases.

Figure 28.

Gas-sensing response of sensor with different amounts of doped Pt to SF6 decomposition components.

Figure 28 shows that the R% values of the Pt-doped TiO2 nanotube for the three SF6 decomposition gases are negative. This result indicates that the resistance of the Pt-doped TiO2 nanotube sensor tends to decrease. Based on a known response mechanism, the three measured gases serve as reducing gases or as electron-donating gases. The reaction occurs as follows: R+Oads → ROads+e

where R is the SF6 decomposition component gas (i.e., SO2, SOF2, and SO2F2), and Oads is the adsorbed oxygen ion on the sensor surface.

The results show that the reducing function and electron donating effect of SO2 gas are the most prominent in the micro-oxidation reduction reaction (i.e., most likely to lose electrons). SO2 is followed by SOF2, while SO2F2 is the weakest. The selectivity of the sensor is highest for SO2 gas. Therefore, the order of gas-sensing response of the intrinsic sensor for the three tested gases follows: SO2 (−74.6%) > SOF2 (−7.8%) > SO2F2 (−5.5%) [34].

The doped Pt significantly affects the gas-sensing response of the TiO2NT sensor for the SO2, SOF2, and SO2F2 gases, and thus, the selectivity of the sensor changes.

Pt serves as an oxygen storage point by constantly providing Oads to the TiO2NT sensor surface. The noble metal doping specifically reduced the activation energy of the reaction O2+2e→2O. Thus, the optimal working temperature also decreases, and the reaction rate and gas sensitive effects are enhanced. Meanwhile, the catalyst particles existing on the surface of the TiO2-sensitive body has better affinity interactions with the target gases. Therefore, these gases will be more attached to the sensor surface at a lower temperature. The catalyst particles are embedded on the surface of the sensitive body. When the adhesion concentration of the measured gas on the catalyst particles surface reaches a certain value, these gases will “overflow” from the catalyst particles toward the surface of the sensitive body, and further react with the adsorbed oxygen ions. Ultimately, the sensitivity of this gas sensor increases, and the sensor response accelerates.

SO2, SOF2, and SO2F2 gases are specifically discussed. Sulfides have a certain degree of toxicity to noble metal catalysts, and the level of toxicity is associated with the valence elements and molecular structure. The decreasing toxicity of the three experimental gases follows the order of SO2 > SOF2 > SO2F2; S6+ within a certain range is non-toxic [35]. Therefore, once the strong toxicity of SO2 accumulates, the Pt-doped sensor would be poisoned. The sensor poisoning follows a specific process. First, SO2 is physically adsorbed on the active center of the catalyst, and then, redox reaction occurs between SO2 and the active ingredient. Ultimately, the reaction produces alkylene sulfide and other sulfides, which block the active sites. In this complex series of processes, the activity of the catalyst decreases [35]; in addition, the sensitivity of the sensor is significantly improved with the nearly non-toxic SO2F2 gas.

2.3. Au-doped TiO2 nanotubes

2.3.1. Investigation of gas-sensing simulation of Au-doped TiO2 nanotubes

Intrinsic anatase TiO2 (101) surface model was optimized in Dmol3 module shown in Figure 29a, b while Au-doped anatase TiO2 (101) surface model after optimization was exhibited in Figure 29c and d.

Figure 29.

Views of intrinsic and Au-doped anatase TiO2 (101) surface models from different angles.

In Figure 30 [1], density of states (DOS) of intrinsic and Au-doped anatase (101) surfaces as well as the doped Au atom was compared. As can be concluded, Au-doping could reduce band gap of TiO2, to some extent [1]. To obtain more precise values, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) were calculated, and band gap of Au-doped anatase (101) surface was 1.906 eV, less than 1.932 eV, band gap of intrinsic anatase (101) surface [1]. The decrease of band gap made it easier for electrons to transfer from valence band to conduction band. In addition, Au-doping enhanced the DOS below Fermi level and increased density of electrons, providing more electrons which were possible to transfer to conduction band [1].

Figure 30.

DOS of intrinsic and Au-doped anatase TiO2 (101) surface.

Gas molecules approach Au-doped anatase TiO2 (101) surface by different atoms, shown in Figure 31. Considering structure features of SO2F2 that S atom is inside the tetrahedron made of O and F atoms, two conditions that SO2F2 approaches Au-doped anatase TiO2 (101) surface by O and F atoms were taken into consideration.

Figure 31.

Adsorption structures of three gas molecules on Au-doped anatase TiO2 (101) surface.

Table 11 [1] shows adsorption parameters of gases adsorbed on Au-doped anatase TiO2 (101) surface. As can be found, when SO2 molecule approaches Au atom by O or S atoms, adsorption parameters are close to each other, while similar condition occurs when SOF2 approaches Au atom. When SO2F2 approaches Au atom by O atom, the adsorption energy and charge transfer are obviously smaller than those of the other condition that SO2F2 approaches Au atom by F atom, which indicates that it is easier for SO2F2 to adsorb on Au atom by F atom.

Gas moleculesAdsorption structureAdsorption energy Ea/eVCharge transfer Q/eAdsorption distance d
SO2-S
-O
−0.657
−0.571
−0.156
−0.182
2.601
2.419
SOF2-S
-O
-F
−0.238
−0.363
−0.593
0.067
0.042
−0.006
2.657
2.636
2.656
SO2F2-O
-F
−0.071
−0.200
0.009
0.039
2.667
2.924

Table 11.

Adsorption parameters of gases adsorbed on Au-doped anatase TiO2 (101) surface “-S”, “-O” and “-F” represent that gas molecules approach adsorption surface by S, O and F atoms, respectively.

By comparison of adsorption energy, it can be concluded that, whatever figure gas molecules approach adsorption surface by, adsorption energy of SO2 is the largest, about 2–3 times that of SOF2 and SO2F2 [1]. It can also be found from the view of charge transfer that, electrons transfer from adsorption surface to SO2 molecule, the opposite direction of electron transfer in SOF2 and SO2F2 adsorption processes [1]. The phenomenon can be explained by the strong oxidizing ability of SO2. In addition, SO2 adsorption possesses larger absolute value of charge transfer in adsorption process than SOF2 and SO2F2 adsorption processes.

Figures 3234 showed the total density of states (TDOS) of adsorption system and partial density of states (PDOS) of adsorbed gas molecules, SO2, SOF2, and SO2F2, respectively. “SO2-O-TiO2” represents that SO2 approaches anatase TiO2 (101) surface by O atom, and the like.

Figure 32.

TDOS of adsorption systems and PDOS of adsorbed SO2.

Figure 33.

TDOS of adsorption systems and PDOS of adsorbed SOF2.

Figure 34.

TDOS of adsorption systems and PDOS of adsorbed SO2F2.

In order to investigate the effect of Au-doping on gas-sensing properties of TiO2 (101) surface, simulation results were compared with those of gas molecules adsorbed on intrinsic TiO2 (101) surface [1]. Detailed calculation and results of adsorption on intrinsic TiO2 (101) surface were included in the published reference [1, 3639]. It should be noted that, in reference [32], SO2 and SOF2 molecules were adsorbed on intrinsic anatase TiO2 (101) surface by O atom, while SO2F2 approached adsorption surface by F atom [1]. Therefore, the comparisons of adsorption parameters are mainly based on calculation results when gas molecules approached surface by the same atom [1]. In this paper, more approaching figures of gas molecules adsorbed on TiO2 (101) surface are involved [1].

As can be concluded from the adsorption parameters, adsorption energy and charge transfer increased obviously after SO2 molecule was adsorbed on Au-doped anatase TiO2 (101) surface than intrinsic anatase TiO2 (101) surface, while adsorption distance changed slightly [1]. More importantly, Au-doping changed the direction of charge transfer, causing the resistivity of adsorption system changing from decrease to increase [1]. As for SOF2, adsorption energy increased by one-third while charge transfer and adsorption distance kept almost unchanged [1]. It can be judged that adsorption ability of SOF2 on Au-doped surface slightly increased compared with that of SOF2 on intrinsic surface [1]. After SO2F2 was adsorbed on Au-doped anatase TiO2 (101) surface, adsorption distance became smaller, while adsorption energy and charge transfer became larger compared with the adsorption on intrinsic anatase TiO2 (101) surface. It can also be found that absolute values of adsorption energy and charge transfer became larger when three molecules were adsorbed on Au-doped TiO2 (101) surface with adsorption distance almost unchanged compared with the adsorption on intrinsic surface. That is to say, Au-doping improved adsorption performance of intrinsic anatase TiO2 (101) surface to SO2, SOF2, and SO2F2 [1]. When SO2 molecule was adsorbed on Au-doped adsorption surface by S atom, adsorption energy was 0.657 > 0.6 eV, so the process belonged to chemical adsorption, while adsorption energy was 0.571 eV when SO2 molecule was adsorbed by O atom, slightly smaller than 0.6 eV, which can be considered close to chemical adsorption. Adsorption energies of SOF2 and SO2F2 molecules adsorbed on Au-doped adsorption surface were much smaller than 0.6 eV, belonging to physical adsorption [1].

TDOS of adsorption systems and gas molecules was compared, too [1]. Reference [41] shows TDOS of adsorption systems and PDOS of gas molecules adsorbed on intrinsic anatase TiO2 (101) surface. By comparing with adsorption on intrinsic anatase TiO2 (101) surface, an obvious TDOS peak did not appear above Fermi level when SO2 was adsorbed on Au-doped anatase TiO2 (101) surface [1]. As can be concluded, SO2 molecule contributed less electrons to conduction band, leading to increase of adsorption system’s resistivity, which is consistent with the above analysis based on adsorption parameters. Au-doping changed variation tendency of adsorption system’s resistivity when SO2 was adsorbed on anatase TiO2 (101) surface [1].

Compared with adsorption of SOF2 on intrinsic anatase TiO2 (101) surface, SOF2 made obvious contribution to DOS near Fermi level when it was adsorbed on Au-doped anatase TiO2 (101) surface, which increased the amount of electrons in conduction band. From macroscopic view, resistivity of adsorption system dropped more severely and resistance declined more wildly as well in the adsorption process [1]. That is to say, Au-doping improved the sensitivity of anatase TiO2 (101) surface to SOF2, to some extent.

As far as SO2F2, adsorption of SO2F2 molecule did not contribute much to the DOS near Fermi level when SO2F2 was adsorbed on intrinsic anatase TiO2 (101) surface, that is, SO2F2 provided almost no electrons for conduction band of adsorption system [1]. When SO2F2 was adsorbed on Au-doped anatase TiO2 (101) surface, however, obvious DOS peaks appeared above Fermi level, and SO2F2 supplied more electrons to conduction band of adsorption system. Macroscopically, sensitivity of Au-doped anatase TiO2 (101) surface to SO2F2 increased obviously compared with intrinsic anatase TiO2 (101) surface [1].

Based on the above analysis of adsorption parameters and density of states, it can be concluded that, resistance’s variation tendency of Au-doped anatase TiO2 (101) surface after the adsorption of SO2 is decreasing, different from intrinsic anatase TiO2 (101) surface [1]. Resistance of Au-doped anatase TiO2 (101) surface dropped more, and the sensitivity increased slightly after SOF2 adsorption, while resistance of Au-doped anatase TiO2 (101) surface dropped severely, and the sensitivity increased obviously after SO2F2 adsorption [1].

2.3.2. Preparation and surface characterization of Au-doped TiO2 nanotubes

To prepare the Au-TNTA, the intrinsic TiO2 nanotubes were first fabricated, and then, Au was deposited onto the TiO2 nanotubes using the deposition-precipitation method. The intrinsic TNTAs used in this paper were prepared by the anodic oxidation method [1, 38], and NaOH was selected as the precipitating agent. Firstly, the pH of the 1.01 × 10−3 mol/L HAuCl4 solution was adjusted to 9 using NaOH solution [1]. Then, the intrinsic TiO2 nanotubes were subsequently added to the above solution, resulting in the pH value decreasing. At the moment, a little more NaOH solution was needed to maintain the pH value at 9. Next, the resulting suspension was stirred for 2 h at 70°C to allow the Au to be supported on the carrier sufficiently. During the process, the suspension became pale purple gradually, and the pH value remained at 9 after cooling. TiO2 nanotubes were picked out, washed, filtered, dried at room temperature and calcined for 4 h at 100°C to finally obtain the Au-TiO2 nanotube sensors [1, 39].

As for the reasons for keeping the pH at 9, the selection of a pH value of 8–9 is in agreement with several previous experimental investigations [1, 4045]. A number of groups have proven that the selection of pH leads to different geometries of TiO2 [1, 45], and the pH of an aqueous solution dramatically affects the particle size of Au [1, 43]. Though a finite value for the size cannot be deduced from the activity, since the electronic factors depend on the interaction with the support, the morphology of the particle or the chemical state of the gold, there is general agreement that the activity increases as the particle size decreases [1, 44]. Hence, the pH value of the solution has significant influence on the catalytic activity. A low pH causes a big Au particle, while a high pH causes a low Au deposition amount. The optimum pH aims to not only cause Au to be completely precipitated, but also leads to an appropriate diameter [1, 45]. Ivanova et al. have proven that when the pH value is above 8, the main species of Au in the solution is transformed from AuCl4 to Au(OH)4, leading to a smaller particle diameter. In order to remove Cl ions completely [1, 46], we chose a pH of 9.

The sample morphology was analyzed by scanning electron microscopy (SEM). The SEM images were obtained by JEOLJSM7000 field emission SEM equipment operated at 10 kV [1].

Figure 35 [1] shows SEM images of the pore size distribution of films composed of (a) intrinsic TiO2 nanotubes and aggregates and (b) the Au nanoparticles distribution of Au-TiO2 prepared by the deposition-precipitation method. The surfaces of the films were observed before and after Au deposition [1]. It is obvious that the morphology of the TiO2 films is significantly changed after the Au nanoparticle modification. The adopted fabrication method results in the formation of tubular TiO2 of 25 nm in diameter [1]. After the Au deposition treatment, the diameter of the tubes remains about the same. However, on the Au-TiO2 surface, the pipes are covered with Au nanoparticles of a dozen nanometers in size, aggregating at the pipe orifices [1]. The SEM images confirm that the formed films, whether composed of intrinsic or Au-TiO2, are homogeneous with a uniform distribution of pores or Au nanoparticles, respectively, as expected [1].

Figure 35.

(a) SEM image of the intrinsic TiO2 nanotubes. (b) SEM image of the Au-TiO2 nanotubes.

The crystal structures of the obtained intrinsic TiO2 and Au-TiO2 nanotubes were analyzed by X-ray diffraction, measured on an X’pert Pro (PANalytical, The Netherland) using Cu Kα radiation (λ = 0.15405 nm) at 40 kV, 35 mA. The wide-angle XRD patterns were collected at a scanning speed of 10°/min over the 2θ range of 20°–100°. Figure 36 [1] gives the XRD patterns of the products prepared by the deposition-precipitation treatment. Previously, Varghese et al. observed both the anatase and rutile phases of TiO2 by annealing treatment in ambient oxygen [1, 47, 48]. In our study, the labels A at 25.3° are observed in intrinsic, as well as in Au-doped TiO2, indicating that the crystal phases of TiO2 are both anatase according to previous structural characterizations [1, 49], for which it can be confirmed that, in these preparation conditions, the TiO2 nanotubes adopt an anatase crystal structure, while a rutile structure is not observed. The labels T and Au represent the reflections from the titanium substrate and different Au crystallographic forms. It is clearly seen from Figure 36 [1] that characteristic gold peaks come into existence in XRD analysis observed at 38.2° (111), 44.2° (200), 64.3° (220) and 98.1° (400), respectively. The main Au (111) characteristic peak suggests that approximately 10-nm gold nanoparticles are coated onto the anodized TiO2 nanotubes on the basis of the Scherer formula [1, 50].

Figure 36.

XRD of Au-TiO2 nanotubes.

Meanwhile, a certain amount of 200, 220 and 400 Au particle crystal forms do exist [1]. There is a popular belief that the characteristics of a metal oxide semiconductor are greatly affected by the doped metal or metalloid, which would also influence the operating temperature in a sensing application further. Therefore, it is necessary to investigate the gas-sensing response of Au-TiO2 NTAs to SF6 decomposed components (i.e., 50 ppm SOF2, SO2F2 and SO2) in an operating range of 20–200°C in order to find out the optimum operating temperature [1].

2.3.3. Gas-sensing experiments of Au-doped TiO2 nanotubes sensors

Figure 37 [1] depicts the curves of the resistance changes’ rate (i.e., the response value) of Au-doped and intrinsic TiO2 NTAs to SO2, SOF2 and SO2F2 at different operating temperatures. The response value of the intrinsic TiO2 nanotubes to SF6 decomposed components increases as the surface temperature rises, reaching saturation around 180°C, which is considered the optimum operating temperature. In the case of Au-TiO2, the resistance response increases with increasing operating temperature before 110°C, following the typical behavior of an oxide semiconductor [1]. However, the resistance response dramatically drops down when the temperature exceeds 110°C. Hence, the optimum operating temperature of the Au-TiO2 nanotubes sensor is taken as 110°C. A comparison of Au-doped and intrinsic TiO2 indicates that Au-doping reduces the working temperature of TiO2 NTAs along with obvious changes in the temperature characteristic curve [1].

Figure 37.

Sensor responses for 50 ppm SO2 (black dots), SOF2 (red dots) and SO2F2 (green dots), respectively, for the intrinsic (short dashed lines, in the range of 20–240°C) and Au-doped TiO2 (solid lines, in the range of 20–200°C) nanotubular films at different working temperatures.

The performance of the intrinsic TiO2 nanotube sensors maintaining its response value after it reaches 180°C might be attributed to the dynamic equilibrium of the gas adsorption and desorption rate on the sensor’s surface in the meantime [1]. As for Au-TiO2, the Au nanoparticles change the microscopic structure and charge distribution of the surface, and the doped Au results in a promoted chemical desorption rate when the temperature surpasses 110°C, causing the oxygen desorption rate to be faster than its adsorption rate [1]. As a result, the oxygen chemisorption density on the surface decreases, leading to a rapid drop of the response value [1, 51].

The gas-sensing response curves of SO2, SOF2 and SO2F2 for Au-TiO2 NTAs were recorded at different concentrations (i.e., 25, 50, 75, 100 ppm) under the optimal operating temperature (110°C) [1]. The results were linearly fit to investigate the linear relationship between the sensor’s resistance change and the gas concentration. Therefore, the concentration of target gases in real power equipment could be estimated through the linear relationship acquired by these sample gases [1].

2.3.3.1. Sensing performances of Au-TiO2 NTAs for SO2

As Figure 38 [1] shows, the resistance change rates of the Au-TiO2 nanotube gas sensor for SO2 at 25, 50, 75 and 100 ppm are −2.14, −8.73, −15.76 and −23.75%, respectively. The linear relationship between the sensor’s resistance change rate and the SO2 concentration is fitted as y = −0.287x + 5.37 with a linear correlation coefficient (R2) of 0.997 [1].

Figure 38.

(a) Au-TiO2 NTAs’ response to different concentrations of SO2 at the 110°C working temperature. (b) Linear relationship between the sensor’s response value and the SO2 concentration.

2.3.3.2. Sensing performances of Au-TiO2 NTAs for SOF2

Figure 39 [1] exhibits the sensing response curves of the Au-TiO2 nanotube sensor for SOF2 at different concentrations under 110°C. From Figure 39a, the resistance change rates that correspond to 25, 50, 75 and 100 ppm of SOF2 are separately −3.00, −9.97, −18.42 and −28.37%. After linear fitting, the linear function is calculated to be y = −0.338x + 6.197, as shown in Figure 39b, with R2 equaling 0.991. It can be concluded that, within a certain range of concentrations, a linear relationship between the resistance change rate of the Au-TiO2 nanotube sensor and the SOF2 concentration is also displayed [1].

Figure 39.

(a) Au-doped TiO2 NTAs’ response to different concentrations of SOF2 at the 110°C working temperature. (b) Linear relationship between the sensor’s response value and the SOF2 concentration.

2.3.3.3. Sensing performances of Au-TiO2 NTAs for SO2F2

Resistance change rates of Au-TiO2 nanotube gas sensor for SOF2 with different concentrations at 25, 50, 75 and 100 ppm are, respectively, −4.04, −19.58, −30.93 and −42.31%, as shown in Figure 40a. The linear fitting relationship is y = −0.503x + 7.138 and the linear correlation coefficient R2 equals 0.991 [1].

Figure 40.

(a) Au-doped TiO2 NTAs response to different concentrations of SO2F2 at the 110°C working temperature. (b) Linear relationship between the sensor’s response value and the SO2F2 concentration.

Figure 41 [1] shows the gas-sensing response comparison chart of intrinsic and Au-doped TiO2 NTAs at their optimum operating temperatures for 50 ppm SF6 decomposed gases, that is, SO2, SOF2 and SO2F2, where the gas-sensing properties of intrinsic TiO2 NTAs have been discussed in [1, 52]. The responses of intrinsic and Au-doped TiO2 NTAs both exhibit a negative behavior, that is, the resistances of intrinsic and Au-doped TiO2 NTAs decrease after introducing these gases.

Figure 41.

Sensor responses of Au-doped and intrinsic TNTA for SF6 decomposition components.

The gas-sensing response values of the intrinsic TiO2 nanotube sensor are SO2 (−74.6%) > SOF2 (−7.82%) > SO2F2 (−5.52%), while for the Au-TiO2 nanotube sensor is SO2F2 (−19.95%) > SOF2 (−9.97%) > SO2 (−8.73%). It is worth noting that the experimental results in our study are statistically significant, the values of which are at the average level according to dozens of experiments [1]. Obviously, the response value of SO2F2 dramatically increases, while SO2 is reduced, and the response of SOF2 remains constant. The selective detection of SO2F2 was actually achieved in our experimental research by the modification of Au nanoparticles at the appropriate operation temperature [1]. Hence, the Au-TiO2 NTAs are potential substrates for the SO2F2 detection application. Furthermore, combined Au-doped and intrinsic TiO2 arrays are promising substrates for SF6 decomposition component detection [1].

Acknowledgments

Parts of this chapter are reproduced from Refs. [2728] with Elsevier’s permission and from Refs. [1, 37] under the terms of their respective Creative Commons licenses.

© 2017 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License, which permits use, distribution and reproduction for non-commercial purposes, provided the original is properly cited.

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Ju Tang, Xiaoxing Zhang, Song Xiao and Fuping Zeng (June 7th 2017). Application of TiO2 Nanotubes Gas Sensors in Online Monitoring of SF6 Insulated Equipment, Nanomaterials Based Gas Sensors for SF6 Decomposition Components Detection, Xiaoxing Zhang, Ju Tang, Song Xiao, Fuping Zeng, Cheng Pan, Yingang Gui, IntechOpen, DOI: 10.5772/intechopen.68328. Available from:

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