3.1. Characterization of CNFs
TEM micrographs of CNFs (
Figure 3) showed the formation of cup-stacked cone (or so-called fishbone structure [
45,
46]) nanofibers with a diameter of 40–150 nm. Since the catalyst composition was the same for all samples, there is no difference in the structure of CNFs, and it is typical for materials synthesized over Ni-containing catalysts [
47]. The increase in pressure induced the later deactivation of the catalyst; however, the yield of CNFs decreased when increasing pressure. The formation of catalyst by solution combustion also induced the growth of nanofibers with smaller diameters (20–30 nm). The average diameter of CNFs was 44.9 ± 5.5 nm (CNFs-1), 78.5 ± 6.4 nm (CNFs-5), and 61.46 ± 3.4 nm. The data show that the lower diameter of CNFs was formed at 1 atm pressure of methane catalytic decomposition.
One considering the yield of CNFs, it is clearly seen that this value decreased when increasing pressure, e.g., 268.3 g/g
cat (CNFs-1), 12.0 g/g
cat (CNFs-3) and 10.1 g/g
cat (CNFs-5) (
Table 1). According to low-temperature nitrogen adsorption, all CNF samples consisted of mesopores fully without the contribution of other types of pores. The average pore size increases when increasing pressure from 10.3 nm to 12.4 nm. The total pore volume grows from 0.28 to 0.40 cm
3/g. CNFs-1 synthesized at 1 atm showed 108 m
2/g specific surface area, and further increase in pressure led to a decrease of the latter to 101 m
2/g with the subsequent growth at 5 atm to 129 m
2/g. This is also surprising and indicates the complex mechanism of the formation of carbon nanofibers at a pressure higher than 1 atm. According to data on the yield, which dropped when increasing pressure from 268.3 g/g
cat to 10.1 g/g
cat, the specific surface area decreases at 3 atm and then begins to increase to grow to 21 m
2/g compared to the CNFs-1 sample.
XRD patterns of CNFs are presented in
Figure 4. The samples were almost fully represented by the phase of graphite (
P63/mmc space group) with the strong (002) reflection typical for a majority of carbon nanomaterials [
48,
49]. All samples contained nickel phase additionally (
Fm3m space group), since the nickel oxide is reduced by hydrogen (formed as a result of methane decomposition), and the growth of nanofibers begins on nickel catalytic nanoparticles. The size of Ni crystallites is hard to be calculated because of its low concentration and high error of the calculation. Since the growth of CNFs was carried over the Ni/Al
2O
3 catalyst, the content of the latter is low (below the detection limit of the technique), and there are no reflections related to the alumina phase in the XRD patterns.
Raman spectra of CNFs are shown in
Figure 5.
The bands about 1595 and 1355 cm
−1 were observed in the spectra of all samples in the spectral region of the first order (1200–1600 cm
−1). The band around 1590 cm
−1 (G (Graphite) band) corresponds to the vibrational mode with the E2g symmetry of the ideal graphite lattice. The band around 1350 cm
−1 (D or Defective Band) is absent in the spectra of single-crystal graphite and HOPG (highly oriented polycrystalline graphite). The D band corresponds to the vibrational mode with the A1g lattice symmetry of graphite. The appearance of the defective band in the spectra of carbon materials is associated with the disordered structure. The increase in its intensity relative to the intensity of the G band is associated with an increase in the number of defects in the graphite structure [
50]. The D/G ratio of intensities is given in
Table 2.
It is shown that the defectiveness of CNFs changes when increasing pressure, and initially, it begins to decrease when pressure exceeds 1 bar. Then, it grows slightly during the pressure rising from 3 to 5 bar. It can be explained by complex behavior of CNF growth under pressure above 1 bar, since each increase in pressure prolongs the lifetime of catalyst. The increase in pressure brings no changes in the type of defects in CNFs, but it has an effect on diameter of CNFs and length consequently. The increase in pressure led to decrease in yield of CNFs as a result of decrease in conversion of methane. Probably, there is an impact of pressure on the rate of carbon formation on the catalyst, which is high enough for 1 atm and begins to decrease when increasing pressure. The increase in this rate of carbon formation at 1 atm leads to formation of strongly curved nanofibers which is apparently shown by Raman spectroscopy and the highest I(D)/I(G) ratio. The diameter of nanofibers in CNFs-1 was the lowest one (44.9 ± 5.5 nm) compared to two other samples, and this factor along with high growth rate induces higher curvature of CNFs and defectiveness. The CNFs with higher curvature degree possessed higher concentration of defects, since these regions are under strain. Such an effect was discussed in [
51] using single-walled carbon nanotubes as the model object.
3.2. Gas Sensing Properties
Figure 6 shows the response of sensors based on CNFs. They possess a high response towards NO
2 at concentrations above 100 ppm.
The response to NO
2 grows stronger until reaching 250 ppm, after which it had a smaller change when increasing concentration. This effect was also found in [
33,
52,
53] and is typical for different types of carbon nanomaterials. Usually, the higher concentration of analyte brings the system closer to the filling of adsorption sites, and further change in concentration makes a small effect on sensor response. The resistance change vs. concentration of nitrogen dioxide can be considered as non-linear. For example, response curve of CNFs-1 might be fitted with
y = a + b ·
xc function with a = 211.438, b = −221.99, c = 0.01918 (R
2 = 0.972). The power c in the same type of equation for CNFs-3 and CNFs-5 was 0.24752 (R
2 = 0.975, a = 9.496, b = −8.287) and 0.28614 (R
2 = 0.978, a = 5.098, b = −4.578), respectively, showing that the pressure increase making the response behavior relatively closer to power function relation.
The testing of gas sensors for NH
3 detection was also carried out for comparison since this is a different type of gas in terms of its interaction with the surface of carbon nanomaterials [
54]. The maximum response of CNFs to NH
3 was low enough and less than 3%, which is typical for non-functionalized carbon nanomaterials [
55,
56]. The higher concentrations of ammonia were taken because of the low sensitivity of CNFs to the latter. It was impossible to measure resistance without high noise and the error below 50–100 ppm NH
3 in air. So it can be indirectly concluded that the obtained sensors are selective to adsorb the nitrogen dioxide compared to ammonia.
It is well known that mostly carbon nanomaterials act as p-type semiconductor materials due to the defects acting as charge transfer centers [
57]. The negative slope of the NO
2 resistance vs. concentration relation is associated with a decrease in the resistance of the CNFs during its adsorption. This is due to the fact that the adsorption of electron acceptor compound as nitrogen oxide on the surface of sample causes transfer of electrons from the nanofibers, which increases the concentration of holes and increases the conductivity. Conversely, the increase in sensor resistance during ammonia adsorption by CNFs is caused by the electron donating nature of ammonia, adsorption of which reduces the concentration of charge carriers (holes, namely) leading to a decrease in conductivity. At the same time the investigated CNF samples contain not so much centers of ammonia interacting with surface compared to other carbon materials (e.g., graphene [
58], graphene oxide [
59], graphite oxide [
60], functionalized carbon nanotubes [
61] etc.) and this explains their low response to NH
3.
Further, the impact of pressure on the sensing behavior of CVD-grown CNFs will be discussed. Increasing the pressure in the catalytic decomposition of methane promoted the formation of CNFs with different specific surface areas and disorder degrees, resulting in reduced response to NO
2. SEM images of CNFs on the substrate were shown in
Figure 6c–e indicating the coverage of the surface of textolite with aggregated carbon nanofibers. SEM images with higher magnification are presented in
Supplementary Materials. The response of CNF-based films is given in
Table 3.
The sensor CNFs-1 showed the best response to the analytes due to the highest disorder degree, estimated using Raman spectroscopy (I(D)/I(G) = 2.0). The response to 100–400 ppm NO
2 ranged from −14.1 to −27.5% and 0.5–1.9% to NH
3. As can be seen, the sensors based on CNFs taken without any treatment possess a better response to NO
2 compared to NH
3 (
Table 4). Since the content of surface functional groups has high importance for NH
3 detection in carbon nanomaterials [
52,
62], the CNF samples showed a relatively low ΔR/R
0, typical for non-functionalized carbon nanomaterials [
63,
64].
Because of the high response to 100 ppm NO
2, it can be indirectly suggested that the sensors are also capable of detecting lower concentrations of NO
2. To confirm this, the obtained sensors were tested in a lower range of 1–50 ppm NO
2 (
Figure 7).
The obtained sensors demonstrated a good response towards 1–50 ppm of NO
2 (
Table 5), but the data had no correlation with data on the specific surface area of obtained CNFs. The increase in the surface area did not lead to an increase in response. On the contrary, the highest response was observed for the CNFs-1, obtained at 1 atm. In spite of the sensors are shown recovery during the carrier gas feeding, purging after 1 ppm of NO
2 did not lead to recovery of resistance. This is presumably due to the thermodynamic stability of the system in which the carrier gas was fed, and the dimensions of the testing chamber do not lead to a shift of the equilibrium to a desorption state fully.
3.3. Adsorption Isotherms
The response of CNF-based sensors depending on NO
2 concentration (
Figure S2 in
Supplementary Materials) was treated with different adsorption isotherms used to understand the behavior of sensing material under contact with nitrogen oxide. Langmuir [
30,
65] and Freundlich [
66,
67] isotherms were used to fit the experimental data; the explanation of the equations was given in
Supplementary Materials. The fitting data of curves of response using different isotherm theories are shown in
Table 6.
Fitting parameters shown in
Table 6 show that experimental data can be treated with the best fit using modified Langmuir isotherm [
68] (R
2 = 0.989–0.993) and classical linear Langmuir isotherm [
69]. The results of the calculation of adsorption energy (
Table 7; calculation equations were presented in
Supplementary Materials) showed the physical behavior of adsorption of NO
2 by all CNFs’ samples since the enthalpy of adsorption was below 1 eV [
70].
The enthalpy of adsorption increased for the set from CNFs-1 to CNFs-5 samples. Previously, we have found that the granulated carbon nanofiber material, synthesized over Ni/Al
2O
3 catalyst obtained by coprecipitation technique and synthesized at 1 atm and 550 °C, has also shown the physical nature of NO
2 adsorption [
34]. However, the enthalpy of adsorption in [
34] was 2–5 times of magnitude higher compared to CNFs studied in this paper. Apparently, this is caused by the higher disorder degree of CNFs investigated in this paper (according to Raman spectroscopy I(D)/I(G) was 1.69–2.0 compared to 0.98 for granulated CNF in [
34]). This is given at an assumption that the surface area of CNFs studied and granulated CNFs reported in [
34] seems to be similar (101–129 m
2/g compared to 110 m
2/g for granulated CNF studied in [
34]). The Langmuir constant K in the modified Langmuir equation was 0.15–0.53, and it was considerably higher than reported in [
34] (K = 0.03), showing the stronger interaction of the surface of CNFs with nitrogen dioxide molecules.
A comparison of response data of the CNF-based sensors for NO
2 detection to literature data is shown in
Table 8. Considering that the obtained materials were non-modified and used in pristine form, our CNFs are effective and prospective for NO
2 detection at room temperature.
3.4. Humidity
The effect of relative humidity on the sensing behavior of CNFs is an important factor to consider in the design and optimization of gas sensors based on these materials. The effect of relative humidity on the sensor response was studied (
Figure 8).
It was found that the increase in RH induced a growth of response. There is almost no effect of humidity at RH = 10–35%. After reaching an RH of ~35%, the response begins to increase with increasing RH (−3.6% at 1.5 ppm NO
2 and RH = 70% compared to −1.3% at RH = 30% at the same concentration of nitrogen dioxide). This effect confirms the data reported in [
74,
75]. The increase in humidity leads to an increase in the concentration of charge carriers caused by the donation of protons (H
+ or H
3O
+) from water in air. The Grotthus-type mechanism is usually used to explain the donation of protons in humidity-enhanced sensors [
76,
77]. The growth of RH makes the moving of protons better, including an enhancement of sensing performance [
77]. According to the data obtained, the effect of humidity becomes higher with an increase in the pressure of CNF synthesis. The humidity-enhanced response of the CNFs-5 sample is probably caused by the higher specific surface area and average pore size of these CNFs. It is interesting that the most defective CNFs-1 sample showed a less humidity-dependent response, indicating the insignificant role of defectiveness in the transport of protons and their absorption by the sample. This effect could be attributed to the saturation of the surface sites of the CNFs with water molecules that leads to a higher concentration of charge carriers and a more efficient sensing response. Moreover, it is clearly seen in
Figure 8 that the degree of recovery enhances with increasing RH. For example, at 1.5 ppm, NO
2 CNFs-5 sample shows 3%, 16%, and 44% of recovery at RH 10%, 30%, and 70%, respectively.
The humidity tests showed that even if CNFs were synthesized at a pressure higher than 1 atm, these samples showed a huge humidity-enhanced response. This feature of materials could be a benefit for operating sensors in wet conditions or other gas mixtures with high humidity level.
3.5. Response Time
The response time of sensors (time until reaching 90% of maximum sensor response at a certain concentration was analyzed for three main concentrations within a range of 1–100 ppm NO
2 (
Table 9).
The response time was slightly higher than that of sensors based on carbon nanomaterials or graphite-related materials [
78] and lower compared to various semiconductor-based sensors [
79,
80]. The difference in response time is caused not only by the type of sensing material but also by the design of the testing chamber, the flow rate of air, and the type of testing setup. The time of exposure at which the measurement is carried out and the concentration also contributes to the determination of response time. The effect of these factors on response time can be observed in the long-term stability test. An example of the long-term stability curve of the CNFs-1 sample in dry air (RH = 1%) is shown in
Figure 8d. As can be seen, the low concentration of analyte (i.e., NO
2) leads to the absence of saturation of the sensor.
Interestingly an increase in relative humidity made the response faster (as shown by the shape of the curve in
Figure 8). For example, the response time of the CNFs-1 sample at 10 ppm and RH = 70% was 395 s compared to 525 s (RH = 1%).
It is worth noting that there is no direct correlation between the response time of the sample. The second important characteristic is recovery time, but it is not possible to precisely analyze this value since the recovery was incomplete and the point of 90% of recovery shifts for each concentration.
Overall, the response time of the CNFs-based sensor is comparable to that of other types of sensors and can be optimized by adjusting the testing conditions and the design of the sensing chamber. The long-term stability of the sensor is also affected by these factors, as well as the concentration of the analyte and the type of sensing material used. Further research is needed to fully understand the mechanisms behind the response time and stability of CNF-based sensors and to optimize their performance for practical applications. The increase in pressure during the synthesis of CNFs can be considered as one of the ways to modify the sensing behavior of materials for NO2 detection.