Enhanced sensing response of the three dimensional MoS2 microstructure for NO2 gas detection at room temperature

As a promising sensing material, Molybdenum disulfide (MoS₂) nanosheets is being increasingly studied for Nitrogen dioxide (NO₂) gas sensing. However, the MoS₂ nanosheets is prone to the stacking effect that compromises the sensing performances. Here, the stacking effect is mitigated by engineering MoS₂ nanosheets into a three dimensional (3D) network microstructure, which was fabricated by method of electrostatically self-assembling of MoS₂/SiO₂ microspheres. The fabricated sensor based on 3D MoS₂ network observed a significantly improved response of 15% to 12.3 ppm NO₂, which is a 75-fold increase compared to the control sensor with pure MoS₂ nanosheets. In addition, the sensitivity of the sensor with 3D MoS₂ network was 6.15 times larger than that of the control sensor with pure MoS₂ nanosheets. The detection limit of our sensor was 0.297 ppm, lower than most of reported MoS₂-based NO₂ sensors. The enhanced sensitivity and dynamic response stem from the improved interaction between NO₂ molecules and MoS₂ network, thanks to its increased surface area per footprint of MoS₂ nanosheets compared to pure 2D MoS₂ film (single- or few-layer). This work presents a new approach to enhancing the performance of gas sensors based on 2D materials.

Introduction

NO₂ is a harmful gas pollutant that can pose a threat to environment and human health. The detection of NO₂ is widely applied in industrial production [1], air quality monitoring [2], and environmental monitoring [3]. In recent years, NO₂ detection with chemiresistive sensors has been widely investigated due to their low consumption and high accuracy [4]. Semiconductor metal oxides like TiO₂ [5], SnO₂ [6], ZnO [7], WO₃ [8], Co₃O₄ [9], and NiO [10] are commonly used in gas sensing due to their excellent thermal stability, surface properties, tunable structure, and diverse surface morphology. To improve sensor sensitivity, metal oxide heterojunctions like Sn₃O₄/SnO₂ [11], SnO₂/In₂O₃ [12], and ZnO/SnO₂ [13] are also utilized for NO₂ gas detection. However, metal oxide gas sensors require high temperatures (100°C–300°C) for optimal performance. The need for high temperature necessitates additional heating elements, leading to higher operating and maintenance cost.

Recently, carbon materials [14, 15], transition-metal sulphides [16–18] have been used to detect NO₂ for their ability to be used at room temperature. Because of the excellent electronic properties and high chemical stability, two dimensional materials such as graphene and its composites have attracted great attention for optoelectronic applications. Nevertheless, the zero bandgap and lower sensitivity limit their applications in gas sensing. MoS₂ has been widely used for gas sensors due to its tunable band gap, large surface area ratio, and various active sites [19–22]. MoS₂ grown by chemical vapor deposition method was used to detect NO₂, achieved a low limit of detection (LOD) of 1 ppm [23, 24]. To increase the sensing characteristics, MoS₂ nanoparticles such as flower-like nanospheres [11], nanoworms [25], nanoflakes [26] were used as the active materials. To overcome the disadvantage of fast electron-hole recombination caused by narrow bandgap of MoS₂ (–1.65 eV) [27], various MoS₂ compounds and doped MoS₂ were also explored and achieved different success. For example, the LOD of the sensor based on MoS₂/porous silicon nanowire heterojunctions reached 1 ppm [28]; By using MoS₂/SnO₂ compound as sensing material, Cui et al. fabricated a NO₂ sensor whose LOD was 0.5 ppm [29]; In 2022, Bharathi et al. decreased the LOD to 0.311 ppm by using edge activated Ni-MoS₂ nanosheets [30]. However, because MoS₂ is a layered material and it usually suffers from sheet stacking, which seriously debilitates its sensing performance.

In this work, we demonstrated a NO₂ sensor based on three dimensional MoS₂ network microstructure, which can significantly enhance the sensitivity of MoS₂-based NO₂ sensor. The 3D MoS₂ network microstructure was fabricated by using MoS₂/SiO₂ composite microspheres with a core-shell structure. The silicon dioxide (SiO₂) microspheres serve as the support substrate, which were uniformly wrapped with MoS₂ nanosheets on the spherical surface. This could prevent MoS₂ nanosheets from the stacking effect and maintain the excellent electrical properties of MoS₂ nanosheets. Furthermore, the formed 3D microstructure enhanced the interaction between NO₂ molecules and MoS₂ nanosheets, resulting in the improvement of the sensitivity and detection limitation of the sensor. This fabricated NO₂ sensor exhibits high sensitivity and low LOD (0.297 ppm) at room temperature. Our fabricated gas sensor with 3D MoS₂ network microstructure holds great potential for application potential in industrial production, monitoring under various conditions.

Sensor fabrication

The preparation process of MoS₂/SiO₂ composite microspheres is shown in Figure 1 the MoS₂/SiO₂ composite microspheres are fabricated by electrostatic self-assembly method. Specifically, 7 mL emulsion of SiO₂ microspheres (1.8 mg/mL, diameter is 1 μm, Da E Technology Co., Ltd.) and 30 μL Methacryloxyethyltrimethyl ammonium chloride (DMC) solution (concentration is 75%) were mixed and sonicated for 10 min. To make the SiO₂ microspheres positively charged, the mixture was kept in a water bath at 75°C for 1.5 h. Then, 1.6 mL MoS₂ nanosheet suspension (0.1 mg/mL, Beike 2D materials Co., Ltd.) is added to the positively charged SiO₂ microspheres emulsion, mixed and stirred for 1.5 h to make sure the MoS₂ nanosheets were completely and uniformly wrapped around the SiO₂ microspheres.

Figure 1

Figure 1. Preparation process of MoS₂/SiO₂ composite microspheres.

High resolution X-ray photoelectron spectroscopy (XPS, Thermo k alpha⁺, Thermo Fisher Scientific Inc.) was used to investigate the chemical nature of the MoS₂ nanosheets, as depicted in Figure 2. The XPS spectra revealed signals of Mo 3d_5/2 at 229.08 eV and Mo 3d_3/2 at 232.18 eV, indicating the presence of Mo⁴⁺ [31]. This was further supported by the signals of S 2p_3/2 and S 2p_1/2 peaks at approximately 161.88 eV and 163.08 eV, corresponding to the S^2- oxidation state of sulphur [32]. Additionally, peaks at 235.48 eV were attributed to Mo⁶⁺ in MoO₃ due to surface oxidation and adsorption [33], while the presence of the S 2 s peak at 226.0 eV suggested oxidation of sulphur.

Figure 2

Figure 2. High resolution XPS spectra of MoS₂ nanosheets (A) Mo 3d region and (B) S 2p region.

The SiO₂ microspheres were coated around with MoS₂ thin films as shown in the Figure 3A. The insert of Figure 3A shows the TEM image of typical MoS₂ nanosheet, whose size is about 1 × 1 µm, so that the surface of the SiO₂ microspheres should be encapsulated by about three nanosheets. As shown in the Figure 3B, the MoS₂ nanosheets were uniformly wrapped around the SiO₂ microspheres, forming a shell with thickness of 7.7 nm. The MoS₂ coating consist of approximately ten layers. The MoS₂ nanosheets did not exhibit significant stacking effects in the fabricated process of MoS₂/SiO₂ composite microspheres. Figures 3C–F is the energy dispersive spectrometers (EDSs) of the MoS₂/SiO₂ composite microspheres, while Figure 3G shows the corresponding TEM image of the EDSs. Figures 3C–F display the distributions of the Mo, S, Si, and O elements. The distribution patterns of Mo, S, Si, and O elements are similar and match the arrangement of the composite microspheres in TEM images (Figure 3G). It indicates that the MoS₂ nanosheets were uniformly wrapped around the SiO₂ microspheres. To confirm the existence of MoS₂ coating on SiO₂ microspheres, Raman spectroscopy of the composite microspheres is studied.

Figure 3

Figure 3. (A) (B) TEM images of MoS₂/SiO₂ composite microspheres; (C)-(G) TEM image and distribution of Mo, S, Si, and O elements of the MoS₂/SiO₂ composite microspheres.

Figure 4 shows the Raman spectra of MoS₂/SiO₂ microspheres and pure SiO₂ microspheres, measured by Raman microspectroscopy (LabRAM HR Evolution, HORIBA Jobin Yvon, France, lens parameters: ×50 objective, NA = 0.5). In the Raman spectra of pure SiO₂ microspheres (red solid curve), two broad peaks at 475.4 cm⁻¹ and 795.5 cm⁻¹ were observed. The peak at 475.4 cm⁻¹ should be due to the W₁ band (symmetrical Si-O-Si stretching modes) and the D₁ defect band of SiO₂. The peak at 795.5 cm⁻¹ should be assigned as W₂ band of SiO₂ [34]. For the MoS₂/SiO₂ microspheres (dark solid curve), There are two main feature peaks at 383.5 cm⁻¹ and 408.1 cm⁻¹ in addition to the two broad peaks at 475.4 cm⁻¹ and 795.5 cm⁻¹. These two peaks at 383.5 cm⁻¹ and 408.1 cm⁻¹ are due to in-plane $E_{2g}^1$ and the out-of-plane $A_{1g}$ vibration, respectively. The appearance of 383.5 cm⁻¹ and 408.6 cm⁻¹, as well as the weakening of broad peaks at 475.4 cm^-1 and 795.5 cm⁻¹, evidence effective coating of MoS₂ nanosheets on SiO₂ microspheres. In addition, the energy difference between $E_{2g}^1$ and $A_{1g}$ Raman peaks is 25.1 cm⁻¹, which indicated that multi-layer (>6 layers) MoS₂ nanosheets were coated on SiO₂ microspheres [26]. It is consistent with the MoS₂ coating thickness observed by TEM.

Figure 4

Figure 4. Raman spectra of MoS₂/SiO₂ composite microspheres and SiO₂ microspheres.

Figure 5A is the fabrication process of the resistive gas sensor based on 3D MoS₂ network. After 5 min of ultrasonic treatment, 4 μL of prepared MoS₂/SiO₂ composite microspheres suspension was dropped on the interdigitated electrodes (IDEs) by using a micro-syringe as shown in Figure 5A. After 6 hours of natural evaporation at room temperature, the composite microspheres were self-assembled and formed 3D MoS₂ network structure on the IDEs. Figure 5B shows the Scanning Electron Microscope (SEM, Ultra-55, Carl Zeiss AG) image of the formed 3D MoS₂ network structure. The MoS₂/SiO₂ composite microspheres were arranged into a 3D structure. As shown in the right insert in Figure 5B, the MoS₂ nanosheets were uniformly wrapped around the SiO₂ microsphere. The left insert of Figure 5B illustrates the cross section of the MoS₂ 3D network, which consists of more than 10 layers fabricated on the IDEs. The 3D structure appears uniform in Figure 5B.

Figure 5

Figure 5. (A) The fabrication process of the MoS₂/SiO₂ composite microspheres wrapped on the interdigitated electrodes. (insert: schematic diagram of 3D MoS₂ network structure) (B) SEM image of the 3D MoS₂ network microstructure (left insert: the cross section of the 3D MoS₂ network; right insert: magnified SEM image of microsphere).

As shown in the insert of Figure 5A, the SiO₂ microspheres serve as the support substrate, which could avoid the stacking of MoS₂ nanosheets and maintain the excellent electrical properties of MoS₂ nanosheets. The MoS₂ nanosheets (yellow region) wrapped around the SiO₂ microspheres (gray region) were interconnected to form a 3D network resistance. This 3D network provides a larger surface area per footprint of MoS₂ nanosheets compared to 2D single- or few-layer MoS₂ film, increasing the contact area between gas molecules and MoS₂ nanosheets to enhance the sensing response. However, the 3D network structure is not close-packed due to the uneven surface of the IDEs, resulting in a lower filling factor of microspheres and limiting the surface area per footprint of the MoS₂ film.

NO₂ sensing experiments and discussion

Figure 6 is the setup of NO₂ sensing experiment. Two individual flow controllers (MFC, Beijing Qixing Co., Ltd., China) were used to control the flow velocities of nitrogen and nitrogen dioxide. The concentrations of NO₂ could be controlled by controlling the flow rates of nitrogen and nitrogen dioxide separately. The prepared sample was placed into a chamber with gold electrodes, which connected to the interdigital electrode of the sample. The impedance change of the sample was monitored by the impedance analyzer (UCE, UC8002, China) and the data was transmitted to the computer for display and saved in real time. The whole gas sensing experiment was carried out at room temperature.

Figure 6

Figure 6. Experimental setup of NO₂ sensing measurement.

The sensing response (S) of the sample was calculated by Eq. 1 [25]:

$S\left(\%\right)=\frac{R_g-R_a}{R_a}\times 100\%(1)$

Where, $R_a$ and $R_g$ were the resistance value of the sample in pure N₂ and target gas, respectively.

Figure 7 shows the NO₂ sensing properties of MoS₂ nanosheets with 3D network microstructure. The resistance of the MoS₂ nanosheets with 3D network microstructure is 23.7 kΩ. The resistances of the sample decrease gradually with increasing NO₂ gas concentration at room temperature (from 12.2 to 18.3 ppm), as shown in Figure 7. The variation amplitude of the sensing response (S) increases gradually with increasing NO₂ gas concentration at room temperature (from 12.2 to 18.3 ppm). Figure 7B shows the sensing response of the sensor under different NO₂ gas concentrations. The red line is the linear fitting of the sensing response. The sensitivity is 0.806%/ppm, and the linearity coefficient is 0.997.

Figure 7

Figure 7. NO₂ Gas sensing properties of MoS₂ with 3D network microstructure: (A) the variation of actual sample’s response with different NO₂ gas concentrations mixed with dry N₂ at room temperature; (B) the response of the sensor under different NO₂ gas concentrations and its linear fitting.

For comparison, the NO₂ gas sensing characteristics of MoS₂ nanosheets from the same batch were studied. Figure 8 shows the NO₂ sensing characteristics of MoS₂ nanosheets without 3D network microstructure. The resistance of the pure MoS₂ nanosheets is 3703.8 kΩ, which is 156 times that of the sample with 3D network structure. As shown in the Figure 4, the 3D network microstructure has multiple connected MoS₂ films, which greatly increases the conductive paths and reduces the resistance of the MoS₂ 3D network microstructure sample. As expected, the pure MoS₂ sensor exhibit a similar trend for the response to NO₂ gas concentration at room temperature (from 12.3 to 18.4 ppm). However, the obtained sensitivity of 0.131%/ppm is remarkably lower as shown in Figure 8B. In another word, by employing the 3D MoS₂ network, the sensitivity of the sensor is improved by 6.15 times, compared to the control sensor using pure MoS₂ nanosheets. When the concentration of NO₂ was 12.2 ppm, the response of MoS₂ nanosheets with 3D network microstructure was up to 15%. It is 75 times larger than that of MoS₂ nanosheets sample (0.2%). The improvement in sensing performance is due to the 3D network microstructure, which greatly increases the contact area between MoS₂ nanosheets and gas molecules.

Figure 8

Figure 8. NO₂ gas sensing properties of MoS₂ nanosheets: (A) the variation of actual sample’s response with different NO₂ gas concentrations mixed with dry N₂ at room temperature; (B) the response of the sensor under different NO₂ gas concentrations and its linear fitting.

The limit of detection can be calculated using the following Eq. 2 [30],

$LOD=3\times \frac{Std.deviation}{Sensitivity}(2)$

where the Std.deviation is the standard deviation of the base line, 3 denotes that the value of the response is three times higher than the noise level of the sensor device. The calculated LOD of the sensor base on 3D MoS₂ network was 297 ppb, whereas the value for the sensor based on pure MoS₂ nanosheets was much larger, 727 ppb. The LOD of the sensor with 3D MoS₂ is 2.45 times lower than that of the control sensor with pure MoS₂.

Figure 9 shows the characterization of repeatability, stability and dynamic response of the sensor based on 3D MoS₂ network. As shown in Figure 9A, the NO₂ concentration was continuously changed between 0 ppm and 12.3 ppm at room temperature, the sensor keeps their original response without apparent degradation, which indicated that the sensor has good repeatability and stability. The response and recovery times of the sensor (detecting 12.3 ppm at room temperature) is investigated as shown in Figure 9B. The response (T_res) and recovery time (T_rec) of the gas sensor based on 3D MoS₂ network were 57 s and 204 s, respectively. This sensor exhibited a quicker dynamic response compared to MoS₂/SnO₂ sensor when exposed to a NO₂ concentration of 10 ppm level [29].

Figure 9

Figure 9. (A) the characterization of repeatability, stability of the sensor based on 3D MoS₂ network; (B) dynamic response of the sensor based on 3D MoS₂ network.

The sensing response is influenced by the concentration of charge carriers in the sensing materials. It can be proven through first principles that the adsorption of NO₂ gas on MoS₂ causes the Fermi level to shift downwards to the valence band, which leads to hole doping in MoS₂ [35]. The Eq. 3 shows the proposed chemical interaction mechanism:

$\text{Mo}{S}_2+N{O}_2\left(g\right)=\text{Mo}{S}_2+N{O}_2^{-}\left(ads\right)+h^{+}(3)$

In our experiment, when NO₂ is adsorbed, the resistance of both MoS₂-based sensors decreases, demonstrating a p-type sensing behavior. Both n-type and p-type MoS₂ sensors have been reported [24–30] with different reason such as intrinsic defects, vacancies, and extrinsic defects. In the XPS spectra (Figure 2A), the peak at 235.48 eV confirms the presence of Mo⁶⁺ in MoS₂ nanosheets, indicating that MoS₂ was partially oxidized. Previous works has revealed that partial oxidation can introduce p-type doping [36, 37] and the MoO_x layer between metal contacts and MoS₂ can lead to p-type MoS2 transistor behavior [38]. It should be the reason for the p-type sensing behavior of our samples.

The significantly improved performance of 3D MoS₂ network based sensor can be explained as follow. The SiO2 microspheres serve as the support substrate, which could efficiently prevent the MoS₂ nanosheets from sticking together, allowing for the maximum utilization of the extensive surface area of MoS₂ nanosheets. Assuming the MoS₂/SiO₂ composit microspheres assemble into a hexagonal close-packed (HCP) structure, the surface area of the 3D MoS₂ networks is increased by a factor of $2\sqrt{3}N\pi /3$ compared to the pure 2D MoS₂ sensing films, as shown in the following Eq. 4:

$\frac{{3NS}_{sphere}}{S_{Hex}}=\frac{3\times 4\pi r^2}{6\times \sqrt{3}{r}^2}=\frac{2}{3}\sqrt{3}N\mathrm{\pi }(4)$

where S_sphere is the superficial area of the MoS₂/SiO₂ sphere with a radia of r, S_Hex is the area of a regular hexagon footprintprint with a width equal to 2r, 3 denotes that three MoS₂/SiO₂ spheres can be accommodated within each regular hexagon footprint, and the N is the number of layers in the 3D HCP structure. This 3D MoS₂ network provides a larger surface area per footprint compared to 2D MoS₂ films, increasing the contact area between gas molecules and MoS₂ nanosheets to enhance the sensing response and reduce LOD.

Table 1 compares the performance of different NO₂ gas sensors utilizing MoS₂ at room temperature. As shown in Table 1, the sensor based on 3D MoS₂ network exhibits high responsivity in measuring a concentration of 12.3 ppm. In comparison to hollow MoS₂ spheres with a thickness of 700 nm [39], the MoS₂ film supported by SiO₂ can maintain a much thinner thickness of 7.7 nm. This helps prevent the stacking of molybdenum disulfide nanosheets and preserves its excellent electrical properties. Additionally, the self-assembly process forms up to 10 layers of a 3D connected network microstructure. As a result, our sensor can operate at room temperature and has a greater sensing response. It is worth noting that sensors based on MoS₂ Flakes or MoS₂/SnO₂ show higher responsivities [26, 29], but the response time is notably longer that could be a critical shortcoming for practical applications. Thanks to the special structural features of 3D MoS₂ network, our sensor demonstrates a visibly faster response time and moderate recovery time, while maintaining a satisfactory responsivity. Additionally, the limit of detection (0.297 ppm) is lower than the majority of NO₂ sensors utilizing MoS₂.

Table 1

Table 1. Performance of different type of NO₂ gas sensor based on MoS₂ operating at room temperature.

Conclusion

We demonstrated a NO₂ gas sensor operating at room temperature with excellent repeatability, low detection limit, and fast dynamic response. The sensor utilizes 3D MoS₂ network microstructure, which was made by the method of electrostatically self-assembling of MoS₂/SiO₂ microspheres upon drop casting. Compared to the pristine 2D MoS₂ nanosheets, the engineered 3D MoS₂ network possess larger surface area per footprint and hence more active sites that facilitate the interaction between NO₂ molecules and MoS₂ nanosheets. This leads to the significantly improved sensitivity and dynamic response in the NO₂ sensor with 3D MoS₂ network. At a NO₂ concentration of 12.2 ppm, the MoS₂ nanosheets featuring a 3D network microstructure exhibited a response rate of 15%. This was a remarkable 75-fold increase compared to the response of the pristine MoS₂ nanosheets sample. The detection limit of this sensor is 0.297 ppm, which is lower than the majority of NO₂ sensors utilizing MoS₂, as shown in Table 1. Additionally, this sensor exhibits fast response and recovery times of 57 s and 204 s, respectively. This high-performance NO₂ gas sensor has potential applications in industrial production and indoor air quality monitoring. This work presents a new approach to enhancing the performance of gas sensors based on 2D materials.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Author contributions

HC: Data curation, Formal Analysis, Investigation, Writing–original draft. SH: Investigation, Data curation, Writing–original draft. ZX: Investigation, Methodology, Writing–review and editing, Supervision. LY: Data curation, Investigation, Writing–original draft. JY: Supervision, Writing–review and editing, Funding acquisition, Conceptualization. YZ: Supervision, Writing–review and editing, Funding acquisition, Conceptualization, Data curation.

Funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. National Natural Science Foundation of China (12174156); Natural Science Foundation of Guangdong Province (2017A030313359 and 2021A1575012632); Science and Technology Project of Guangzhou (201803020023).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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