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Article

Carbon Nanofibers Synthesized at Different Pressures for Detection of NO2 at Room Temperature

by
Nikita I. Lapekin
1,
Pavel B. Kurmashov
1,
Tatyana V. Larina
2,
Yurii A. Chesalov
2,
Dmitry S. Kurdyumov
1,
Arina V. Ukhina
3,
Evgene A. Maksimovskiy
4,
Arcady V. Ishchenko
2,
Vitalii I. Sysoev
4 and
Alexander G. Bannov
1,*
1
Department of Chemistry and Chemical Engineering, Novosibirsk State Technical University, 630073 Novosibirsk, Russia
2
Boreskov Institute of Catalysis, Siberian Branch of Russian Academy of Sciences, 630090 Novosibirsk, Russia
3
Institute of Solid State Chemistry and Mechanochemistry, Siberian Branch of Russian Academy of Sciences, 630128 Novosibirsk, Russia
4
Institute of Inorganic Chemistry, Siberian Branch of Russian Academy of Sciences, 630090 Novosibirsk, Russia
*
Author to whom correspondence should be addressed.
Chemosensors 2023, 11(7), 381; https://doi.org/10.3390/chemosensors11070381
Submission received: 30 March 2023 / Revised: 29 June 2023 / Accepted: 5 July 2023 / Published: 7 July 2023
(This article belongs to the Special Issue Carbon Nanomaterials and Related Materials for Sensing Applications)
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Abstract

:
In this paper, room-temperature chemiresistive gas sensors for NO2 detection based on CVD-grown carbon nanofibers (CNFs) were investigated. Transmission electron microscopy, low-temperature nitrogen adsorption, and X-ray diffraction were used to investigate the carbon nanomaterials. CNFs were synthesized in a wide range of pressure (1–5 bar) by COx-free decomposition of methane over the Ni/Al2O3 catalyst. It was found that the increase in pressure during the synthesis of CNFs induced the later deactivation of the catalyst, and the yield of CNFs decreased when increasing pressure. Sensing properties were determined in a dynamic flow-through installation at NO2 concentrations ranging from 1 to 400 ppm. Ammonia detection was tested for comparison in a range of 100–500 ppm. The obtained sensors based on CNFs synthesized at 1 bar showed high responses of 1.7%, 5.0%, and 10.0% to 1 ppm, 5 ppm, and 10 ppm NO2 at 25 ± 2 °C, respectively. It was shown that the obtained non-modified carbon nanomaterials can be used successfully used for room temperature detection of nitrogen dioxide. It was found that the increase in relative humidity (RH) of air induced growth of response, and this effect was facilitated after reaching RH ~35% for CNFs synthesized at elevated pressures.

1. Introduction

One of the most harmful air pollutants, nitrogen dioxide (NO2), is well known to be harmful to human health. For instance, it may result in lung cancer, asthma, and respiratory infections [1,2,3,4]. Nitrogen dioxide reacts with water on moisture-exposed tissues forming nitric acid, which is highly corrosive and dangerous. It can pass through the upper respiratory tract with little effect and then react with water in the lungs, causing severe tissue damage. Toxicity depends on both the concentration of the gas and the duration of exposure, but short-term exposure to high concentrations tends to be more harmful than longer-term exposure to low concentrations [5]. Thus, the monitoring of NO2 in the air is a priority for occupational and life safety [6].
One of the reliable ways to determine the nitrogen dioxide concentration is using chemiresistive gas sensors, the resistance of which changes with NO2 content in air [7]. Today, commercial sensors based on semiconductors are widely used, but the operation of such sensors is associated with many problems, for example, their high power consumption, which is due to the need to heat the sensing layer above 250–300 °C [8,9,10]. The drawbacks of traditional semiconductor-based gas sensors can be solved by the application of nanomaterials as active layers for the sensors making it possible to operate at room temperature [11]. Surface acoustic wave sensors are also used for NO2 detection [12,13], but the chemiresistive sensors are considerably cheaper.
There are a lot of nanomaterials and composites applied for NO2 detection at room temperature, such as ZnO [14,15], CuO-ZnO [16], Co3O4-ZnO [17], SnO2-NiO [18], In2O3@GO [19], SnO [20], gallium oxyselenides [21], transition metal carbides/nitrides and their composites (MXenes) (such as Mo2TiC2Tx/MoS2 [22], TiO2/Ti3C2 [23], Ti3C2Tx/TiO2/rGO [24]), etc. Special attention is paid to carbon nanomaterials because of the great variety of modifications [25,26,27,28]. In particular, carbon nanomaterials, such as single-walled carbon nanotubes (SWCNTs) [29,30], multiwalled carbon nanotubes (MWCNTs) [31,32], double-walled carbon nanotubes (DWCNTs) [33], as well as carbon nanofibers (CNFs) [34,35,36,37] are already investigated for NO2 detection.
Carbon nanofibers, being a by-product of catalytic decomposition of methane (or other hydrocarbons) for hydrogen synthesis, are of greater interest for applications in sensing due to their relatively low cost, higher yield compared to SWCNTs and MWCNTs, almost no need for purification [34], and easier process of production [38,39]. This material can be produced both in the form of powder and granules, which is determined by the content of the active components (nanoparticles of transition metals) of the catalyst and type of reactor (fluidized bed, vibrofluidized bed, and fixed bed) [40,41]. At the same time, there is no data reported on the application of CVD-grown CNFs, synthesized at pressures above 1 bar, for gas sensing. There is only one paper devoted to the creation of NO2 gas sensors based on granulated carbon nanofibers synthesized at atmospheric pressure [34]. For the synthesis of CNFs, it is important to control the synthesis parameters (e.g., temperature and pressure inside the reactor) since changes in parameters will make it possible to obtain carbon material with different disorder degree, texture characteristics (specific surface area, pore size, nanofiber length, etc.). All these characteristics will reflect on the sensing behavior. Such studies have not been carried out before. The impact of pressure on the growth of CNFs and the sensing behavior of materials is a novel and relatively cheap approach to modify the characteristics of sensors. Usually, the sensor response can be modified via chemical modification [42,43] of carbon nanomaterials, but the control of pressure needs no additional chemical reagents and does not lead to a decrease in the yield of material compared to chemical treatment.
This work is the first one devoted to the creation of room-temperature nitrogen dioxide sensors based on CNFs synthesized at different pressures (1–5 bar) over 90%Ni/Al2O3 catalyst using the CVD technique. The sensing behavior of CNFs for the detection of nitrogen dioxide in a range of 1–400 ppm NO2 was investigated. Ammonia detection at room temperature was also studied for comparison. Thermodynamic characteristics of the NO2 adsorption process were also calculated in order to predict the adsorption mechanism. The distinctive feature of this paper is the use and investigation of three different CNF materials synthesized at various pressures. This technique can be considered as a novel way for modification of adsorption behavior of sensing material by means of increasing the pressure of growth of the CNFs.

2. Materials and Methods

2.1. Synthesis of CNFs and Characterization Techniques

Carbon nanofibers were synthesized by catalytic decomposition of methane in the flow through installation BTRS-Jr (Autoclave Engineers, Houston, TX, USA) at pressures above 1 bar. The catalyst containing 90% Ni/10% Al2O3 was used for the growth of CNFs at the temperature of 535 °C and pressure ranges from 1 to 5 bar. The technique of preparation of Ni/Al2O3 catalyst was described in [44] in detail. Briefly, the catalyst was obtained by solution combustion technique. The authors dissolved the nitrates (Ni(NO3)∙6H2O and Al(NO3)∙9H2O) in 100 mL of deionized water and added the hexamethylenetetramine (HTMA) as fuel with a fuel excess coefficient of 1 (φ = 1). The solution was heated to 100 °C for dehydration, and further ignition of the mixture using the gas burner with the subsequent formation of catalytic nanoparticles was carried out. The catalyst was placed in a vertical reactor of BTRS-Jr (Autoclave Engineers, USA) installation, and CNFs were grown at 1 bar (the sample was named “CNFs-1”), 3 bar (“CNFs-3” sample) and 5 bar (“CNFs-5” sample) at 535 °C.
The following methods were used for the characterization of synthesized carbon nanomaterials.
Transmission electron microscopy (TEM) was used to estimate the morphological features of the obtained CNFs using JEM-2200FS (Jeol, Tokyo, Japan) with an accelerating voltage of 200 kV and lattice resolution of 1 Å. For TEM investigation, the samples were preliminary ultrasonicated in ethanol solution and deposited onto a carbon sheet supported on a copper grid.
Low-temperature nitrogen adsorption was used for the characterization of the porosity of CNFs using Quantachrome NOVA 1000e installation. The samples were preliminarily degassed in a vacuum at 300 °C at 6 h in order to remove the adsorbed compounds. Isotherms of adsorption and desorption were taken at a 77 K of temperature and in the range of relative pressure of nitrogen of 0.005–0.995. The Brunauer–Emmett–Teller (BET) method was used to determine the specific surface area.
X-ray diffraction (XRD) was used to determine the crystallite size of CNFs and traces of catalyst using a D8 Advance diffractometer (Bruker, Mannheim, Germany). The crystallite size of CNFs, Ni, was determined using Rietveld analysis in TOPAS 4.2 software (Bruker AXS).
The features of disorder degree of the CNFs were determined by Raman spectroscopy on a T64000 (Horiba Jobin Yvon, Longjumeau, France). The 514 nm Ar+ laser was used as the Raman excitation source. The power of radiation reaching the sample was 0.2 mW. The degree of disorderliness of the carbon materials (degree of defectiveness) was estimated from the ratio of the intensities of D and G peaks.

2.2. Sensors Preparation Technique

Figure 1 shows the flowchart of the technique used for the sensor preparation. The active layer of the gas sensor was obtained by drop-casting of the CNF sample in the thick dielectric substrate. The dielectric substrate made of several layers of glass fabric soaked with epoxy resin (textolite) with thin copper contacts on the edges of one side was mechanically polished with abrasive paper down to 600 grids and cleaned with ethanol solution. The suspension of CNFs (particles with a size below 100 µm were used) was prepared by their dispersion in ethanol solution in the ultrasonic bath (UZV-3/200, RELTEK, Russia) at the power 85 W for 20 min (frequency was 22 kHz). CNFs (0.03 g) were dispersed in 5 mL of ethanol. During droplet application on the heated (80 °C) substrate, the film (5 × 5 mm) was formed, partially covering the copper contacts.

2.3. Gas Sensing Procedure

The setup for the detection of the hazardous gas in the air is shown in Figure 2.
The setup included flows of analytes and carrier gas (synthetic air containing 21 vol.% O2, 79 vol.% N2). The mixture of nitrogen dioxide in air (i.e., 500 ppm NO2 in air), a mixture of ammonia and air (i.e., 5000 ppm NH3 in air) were used as model gases for the investigation of CNF-based sensors.
The total flow rate fed into the test chamber was 100 mL/min. The concentration of the analyte in the system was achieved by adjusting the ratio of gas flows from the cylinders using mass flow controllers.
The measurement technique included the following steps. First, the system was purged with a carrier gas (synthetic air) for 10 min with a flow rate of 100 mL/min in order to clean the system from the residual analyte molecules. After that, the sensor was placed in the cell with two copper electrodes and heated inside to 70 °C and kept for 10 min in a 100 mL/min flowing of synthetic gas to carry out the desorption of compounds from the surface of the sensor and decrease the level of relative humidity (RH) inside the cell up to 1 ± 0.1%. The testing of sensors was performed in dry air (1%) and at higher relative humidity using an additional line with wet synthetic air fed into the chamber.
Then, the system was cooled down for 20 min at a flow rate of 1000 mL/min to decrease the temperature inside the cell to room temperature (25 ± 2 °C). The next step consisted of measuring the baseline of 60 min in synthetic air (100 mL/min) followed by 10 min cycles of analyte/air mixture fed alternated by 10-min-cycles of synthetic air.
The changes in resistance of the sensors were recorded using a Keithley 2401 source meter (Keithley Instruments, Inc., Cleveland, OH, USA) at a voltage bias of 0.1 V. Data acquisition was performed by KickStart software (Tektronix, Inc., Beaverton, OR, USA).
To evaluate the behavior of the sensors to NO2 and NH3 gases, the relative response of the sensors was calculated as the ratio between the change in sensor resistance (ΔR) during the contact with the analyte and the initial resistance (R0) in air, using the following equation:
∆ R R 0 = R − R 0 R 0 · 100 % ,
where R is the electrical resistance of the sensor when exposed to analyte, Ω; R0 is the initial electrical resistance of the sensor when exposed to carrier gas (air), Ω.

3. Results

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/gcat (CNFs-1), 12.0 g/gcat (CNFs-3) and 10.1 g/gcat (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 cm3/g. CNFs-1 synthesized at 1 atm showed 108 m2/g specific surface area, and further increase in pressure led to a decrease of the latter to 101 m2/g with the subsequent growth at 5 atm to 129 m2/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/gcat to 10.1 g/gcat, the specific surface area decreases at 3 atm and then begins to increase to grow to 21 m2/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/Al2O3 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 NO2 at concentrations above 100 ppm.
The response to NO2 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 (R2 = 0.972). The power c in the same type of equation for CNFs-3 and CNFs-5 was 0.24752 (R2 = 0.975, a = 9.496, b = −8.287) and 0.28614 (R2 = 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 NH3 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 NH3 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 NH3 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 NO2 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 NH3.
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 NO2. 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 NO2 ranged from −14.1 to −27.5% and 0.5–1.9% to NH3. As can be seen, the sensors based on CNFs taken without any treatment possess a better response to NO2 compared to NH3 (Table 4). Since the content of surface functional groups has high importance for NH3 detection in carbon nanomaterials [52,62], the CNF samples showed a relatively low ΔR/R0, typical for non-functionalized carbon nanomaterials [63,64].
Because of the high response to 100 ppm NO2, it can be indirectly suggested that the sensors are also capable of detecting lower concentrations of NO2. To confirm this, the obtained sensors were tested in a lower range of 1–50 ppm NO2 (Figure 7).
The obtained sensors demonstrated a good response towards 1–50 ppm of NO2 (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 NO2 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 NO2 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] (R2 = 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 NO2 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/Al2O3 catalyst obtained by coprecipitation technique and synthesized at 1 atm and 550 °C, has also shown the physical nature of NO2 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 m2/g compared to 110 m2/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 NO2 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 NO2 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 NO2 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 H3O+) 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, NO2 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 NO2 (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., NO2) 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.

4. Conclusions

The obtained results showed the high potential of the COx-free method for the synthesis of carbon nanofibers for NO2 detection at room temperature. Pristine CNF-based sensors demonstrated a response of 1.7% to 1 ppm NO2. It was found that CNFs were more sensitive toward NO2 compared to NH3. The increase in the rate of CNF formation at 1 atm leads to the formation of strongly curved nanofibers, which is apparently shown using Raman spectroscopy by the highest I(D)/I(G) ratio. The CNFs with higher curvature degrees possessed higher concentrations of defects since these regions are under strain, and this explains the highest disorder degree and sensitivity of the sensor based on CNFs synthesized by methane decomposition at 1 atm. The modified Langmuir isotherm was more suitable for fitting the response data and showed the physical adsorption as dominating mechanism of interaction of nitrogen dioxide with the surface of CNFs. The investigated CNFs can be considered as suitable active materials for all-carbon gas sensors operating at room temperature. It was found that an increase in the pressure of the catalytic decomposition of methane led to a decrease in the response to NO2. The sensor response was found to be enhanced by humidity for all CNFs, which is caused by the strong donation of protons from water molecules. The humidity-enhanced response was detected for CNFs synthesized at pressures higher than atmospheric pressure. This feature of CNFs could be a benefit for operating sensors in wet air or other gas mixtures with high humidity.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/chemosensors11070381/s1, Figure S1: SEM images of the CNFs on the substrate: CNFs-1 (a,b), CNFs-3 (c,d), CNFs-5 (e,f).; Figure S2. The impact of concentration of NO2 to response of CNF films (RH = 1%).

Author Contributions

Conceptualization, P.B.K., A.G.B. and N.I.L.; methodology, A.G.B., A.V.I., A.V.U., E.A.M. and D.S.K.; investigation, N.I.L., T.V.L., V.I.S., A.V.I., A.V.U., E.A.M., D.S.K., Y.A.C. and P.B.K.; writing—original draft preparation, A.G.B., N.I.L., P.B.K., T.V.L. and Y.A.C.; supervision, A.G.B. All authors have read and agreed to the published version of the manuscript.

Funding

The work was supported by the Russian Federation Ministry of Science and Higher Education (state research target, project no. FSUN-2023-0008).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The experiments were performed using facilities of the Shared Research Center “National Center of Investigation of Catalysts” at Boreskov Institute of Catalysis. The Raman spectra were registered using the equipment of the Center of Collective Usage “VTAN” in the ATRC department of Novosibirsk State University.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Chemosensors 11 00381 g001 550
Figure 1. Sensors preparation technique.
Figure 1. Sensors preparation technique.
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Figure 2. Setup for testing of sensors in a dynamic regime at room temperature.
Figure 2. Setup for testing of sensors in a dynamic regime at room temperature.
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Figure 3. TEM-micrographs of CNFs-1 (a–c); CNFs-3 (d–f); CNFs-5 (g–i).
Figure 3. TEM-micrographs of CNFs-1 (a–c); CNFs-3 (d–f); CNFs-5 (g–i).
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Figure 4. XRD patterns of CNFs-1 (a); CNFs-3 (b); CNFs-5 (c) (Cu Kα radiation).
Figure 4. XRD patterns of CNFs-1 (a); CNFs-3 (b); CNFs-5 (c) (Cu Kα radiation).
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Figure 5. Raman spectra of CNFs (λ = 514 nm).
Figure 5. Raman spectra of CNFs (λ = 514 nm).
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Figure 6. Response of obtained CNFs to 100–400 ppm of NO2 (a) and 100–500 ppm of NH3 (b) at room temperature (25 ± 2 °C, RH = 1%); SEM images of CNFs on the substrate: CNFs-1 (c), CNFs-3 (d), CNFs-5 (e).
Figure 6. Response of obtained CNFs to 100–400 ppm of NO2 (a) and 100–500 ppm of NH3 (b) at room temperature (25 ± 2 °C, RH = 1%); SEM images of CNFs on the substrate: CNFs-1 (c), CNFs-3 (d), CNFs-5 (e).
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Figure 7. Response of obtained CNFs to 1–50 ppm of NO2 and at room temperature (25 ± 2 °C) and RH = 1%.
Figure 7. Response of obtained CNFs to 1–50 ppm of NO2 and at room temperature (25 ± 2 °C) and RH = 1%.
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Figure 8. Effect of relative humidity on the NO2 response at room temperature: CNFs-1 (a); CNFs-3 (b); CNFs-5 (c); long-term stability sensor curve at 1.5 ppm NO2 at 1% RH; An example of the long-term stability curve of the CNFs-1 sample in dry air (RH = 1%) is shown in (d).
Figure 8. Effect of relative humidity on the NO2 response at room temperature: CNFs-1 (a); CNFs-3 (b); CNFs-5 (c); long-term stability sensor curve at 1.5 ppm NO2 at 1% RH; An example of the long-term stability curve of the CNFs-1 sample in dry air (RH = 1%) is shown in (d).
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Table
Table 1. Characterization of obtained CNFs.
Table 1. Characterization of obtained CNFs.
SampleSpecific Flow Rate of Methane, L/(h∙gcat)Pressure, atmYield of CNFs, g/gcatSpecific Surface Area, m2/gAverage Pore Size, nmTotal Pore Volume, cm3/g
CNFs-190.01268.310810.30.28
CNFs-390.0312.010110.70.27
CNFs-590.0510.112912.40.40
Table
Table 2. I(D)/I(G) ratio of CNFs.
Table 2. I(D)/I(G) ratio of CNFs.
SampleI(D)/I(G)
CNFs-12.00
CNFs-31.69
CNFs-51.84
Table
Table 3. Response to nitrogen dioxide of the sensors based on CNFs as an active layer at room temperature and RH = 1%.
Table 3. Response to nitrogen dioxide of the sensors based on CNFs as an active layer at room temperature and RH = 1%.
SampleAnalyteΔR/R0, %R25° *, Ω
100 ppm200 ppm400 ppm
CNFs-1NO2−14.1−23.2−27.5603
CNFs-3NO2−7.3−15.2−20.3830
CNFs-5NO2−12.4−21.6−26.3447
* R25°—Resistance of active layer in air at room temperature.
Table
Table 4. Response to ammonia of the sensors based on CNFs at room temperature and RH = 1%.
Table 4. Response to ammonia of the sensors based on CNFs at room temperature and RH = 1%.
SampleAnalyteΔR/R0, %
100 ppm250 ppm500 ppm
CNFs-1NH30.51.21.9
CNFs-3NH30.61.51.9
CNFs-5NH30.81.62.1
Table
Table 5. Response of sensors based on CNFs at room temperature and RH = 1%.
Table 5. Response of sensors based on CNFs at room temperature and RH = 1%.
SampleAnalyteΔR/R0, %
1 ppm5 ppm10 ppm25 ppm50 ppm
CNFs-1NO2−1.7−5.0−10.0−15.5−20.2
CNFs-3−0.4−1.3−2.6−6.0−11.0
CNFs-5−0.4−1.3−3.2−8.7−14.8
Table
Table 6. Summary of isotherm fitting parameters for obtained CNFs.
Table 6. Summary of isotherm fitting parameters for obtained CNFs.
IsothermCNFs-1CNFs-3CNFs-5
R2Qm, %K, Pa−1nR2Qm, %K, Pa−1nR2Qm, %K, Pa−1n
Freundlich0.911n/a10.010.290.961n/a3.950.450.949n/a5.470.44
Langmuir0.98827.340.531.000.98322.380.1510.99129.5930.171
Modified Langmuir 0.98927.530.530.980.98322.930.150.960.99327.190.151.20
Table
Table 7. Enthalpy of NO2 adsorption on films of CNFs at room temperature.
Table 7. Enthalpy of NO2 adsorption on films of CNFs at room temperature.
IsothermCNFs-1CNFs-3CNFs-5
ΔH, eVΔH, eVΔH, eV
Freundlich0.1180.0710.087
Langmuir0.0330.0960.092
Modified Langmuir0.0330.0960.096
Table
Table 8. Performance of NO2 sensor based on CNFs and a comparison with published data.
Table 8. Performance of NO2 sensor based on CNFs and a comparison with published data.
Active Layer of SensorNO2 Concentration, ppmΔR/R0, %Temperature, °CReference
WS2/CNFs10.02.1125 (RT)[71]
CNFs10.01.6325 (RT)
CNFs1.02.0025 (RT)[72]
CNFs10.03.0025 (RT)[35]
TiO2-carbon black10.02.5050[73]
CNFs (CNFs-1 sample)10.010.0025 (RT)This work
Table
Table 9. Response time of sensors at various concentrations (RH = 1%, room temperature).
Table 9. Response time of sensors at various concentrations (RH = 1%, room temperature).
SampleResponse Time, s (at Various NO2 Concentrations)
1 ppm10 ppm50 ppm
CNFs-1504525477
CNFs-3465517507
CNFs-5465520480
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Lapekin, N.I.; Kurmashov, P.B.; Larina, T.V.; Chesalov, Y.A.; Kurdyumov, D.S.; Ukhina, A.V.; Maksimovskiy, E.A.; Ishchenko, A.V.; Sysoev, V.I.; Bannov, A.G. Carbon Nanofibers Synthesized at Different Pressures for Detection of NO2 at Room Temperature. Chemosensors 2023, 11, 381. https://doi.org/10.3390/chemosensors11070381

AMA Style

Lapekin NI, Kurmashov PB, Larina TV, Chesalov YA, Kurdyumov DS, Ukhina AV, Maksimovskiy EA, Ishchenko AV, Sysoev VI, Bannov AG. Carbon Nanofibers Synthesized at Different Pressures for Detection of NO2 at Room Temperature. Chemosensors. 2023; 11(7):381. https://doi.org/10.3390/chemosensors11070381

Chicago/Turabian Style

Lapekin, Nikita I., Pavel B. Kurmashov, Tatyana V. Larina, Yurii A. Chesalov, Dmitry S. Kurdyumov, Arina V. Ukhina, Evgene A. Maksimovskiy, Arcady V. Ishchenko, Vitalii I. Sysoev, and Alexander G. Bannov. 2023. "Carbon Nanofibers Synthesized at Different Pressures for Detection of NO2 at Room Temperature" Chemosensors 11, no. 7: 381. https://doi.org/10.3390/chemosensors11070381

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