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Abstract

In the present research work, RF sputtered SnO₂ thin film overcast with NiO as a catalyst has been exploited to design SO₂ gas sensors. NiO nanoclusters of varying thickness on the film’s surface of SnO₂ as a catalyst. Microstructural analysis of pristine SnO₂ thin film depicted porous and cracked surface morphology and regular and homogeneous distribution of grains was observed for SnO₂ thin film integrated with NiO catalyst. The gas sensing response of prepared thin films was explored against various gases such as sulfur dioxide (SO₂), liquified petroleum gas (LPG), Methane, Acetone, and carbon dioxide (CO₂). SnO₂ thin film gas sensor having thin 10 nm NiO nanoclusters exhibited an enhanced sensing response of ~54. The sensor produces a response time of 75 s and a recovery time of 60 s, respectively at a lower 180 °C operating temperature. A gas-sensing method for an improved fast-sensing response has been presented following the addition of a catalyst for the NiO/SnO₂ gas sensor. This work demonstrates the first systematic optimization of NiO nanocluster thickness (6–14 nm) on SnO₂ thin films, revealing that 10 nm NiO nanoclusters provide optimal surface roughness and dual-mechanism sensing and achieve 2.16 times higher sensing response than state-of-the-art Ag-doped WO₃ sensors while operating at 220 °C lower temperature.

Graphical Abstract

Keywords

2D-thin films gas sensor

Introduction

The development of effective and sensitive gas sensors has been a continuous endeavor by the scientific community. Regulation and precise detection of hazardous gases, including H₂, NO₂, SO₂, CO, H₂S, etc., are the major current challenges in front of the research community under the environmental protection policy. Many studies are being conducted to create particular gas sensors with effective response characteristics. However, limited work has been reported on the detection of SO₂, which contributes to acid rain and whose repeated exposure can cause permanent pulmonary impairment. Therefore, there is an utmost requirement for developing an efficient sensor for SO₂ gas. Amongst diverse gas sensors, gas sensors based on the conductometric principle with semiconducting metal oxides as sensing layers are most preferred for efficient and easy detection of several gases like H₂, NO₂, NH₃, H₂S, CO₂, etc.

The most extensively used semiconducting metal oxides investigated as effective gas sensing materials are WO₃, ZnO, TiO₂, SnO₂, In₂O, NiO, and others because of their high sensitivity, cheap fabricating costs, the potential for miniaturization, and simplicity of related electronics.^1,2 The most researched among these are tin oxide (SnO₂) thin films and nanostructure-based gas sensors due to their quick reaction times, excellent chemical stability, and capacity to detect all types of gases (oxidizing as well as reducing) with great sensitivity, without being poisonous, and low cost.^3–6 However, there hasn’t been much work done in the advancement of SO₂ gas sensors using conductometric techniques. Shimizu et al. observed a maximum sensing response of the sensor of ~25 for SO₂ gas (800 ppm) using an Ag-doped WO₃ semiconductor gas sensor with a temperature operating at 400 °C.⁷ Han et al. reported the detection of H₂S via photoactivation and photothermal activation of MXene/PbS sensor.⁸ Few reports are also available on SO₂ gas detection using electrochemical techniques. Liang et al. combined NASICON with V₂O₅ doped TiO₂ electrode and observed a sensitivity of ~170 EMF/mV towards 50 ppm of SO₂.⁹ Li et al. and Bukun et al. exploited an electrochemical technique for SO₂ detection and recorded sensor response of 5.4 × 10⁻¹¹ A/ppm at room temperature and 0.2 units for 200 °C as an operating temperature, respectively.^10,11 Ni-doped MoS₂ nanocomposite sensors synthesized via a hydrothermal method demonstrated enhanced SO₂ detection at room temperature, supported by DFT-based insights into adsorption behavior.¹² Previous studies on SO₂ gas sensors based on the conductometric detection principle using metal oxide semiconductors reveal either a poor detecting response or a high working temperature (⩾400 °C).^7–11 Therefore, efforts are still being made to create an effective SO₂ gas sensor throughout the world. The first condition is by fabricating an adequate sensing layer having the desired morphological characteristics or by incorporating a catalyst or going for a second condition, which is using dopants into the sensing layer to obtain enhanced sensing response. Furthermore, it is reported in the literature for other toxic gases that incorporating a semiconducting dopant into the sensing layer and making either p-n or n-n heterojunction modulates the depletion region after interaction with the target gas, which results in an enhanced sensing response.^3,4 In this regard, NiO is a desirable (p-type) material well recognized for its chemical stability, along with its outstanding optical and electrical characteristics, and as an excellent gas sensing material. The interaction of SO₂ gas with different nano-clustered catalyst/SnO₂ thin film sensors was studied, and NiO was discovered to be the best catalyst when loaded over SnO₂ in a dotted nanocluster form. for detection of SO₂ gas.¹³

Recent advancements in gas sensing technology have increasingly focused on heterostructure-based materials due to their superior sensing performance compared to single-component sensors. Alam et al. comprehensively reviewed the development of chemoresistive-based heterostructure gas sensor technology, highlighting their enhanced sensitivity, selectivity, and stability while identifying future opportunities and challenges in this rapidly evolving field.¹⁴ The fundamental principles and applications of mixed-dimensional van der Waals heterostructures in gas sensing have been extensively explored by Goel et al., who demonstrated how these unique structures enable improved charge transfer mechanisms and enhanced sensing capabilities through engineered interfaces.¹⁵ Complementing these findings, Liu et al. investigated 1D/2D heterostructures, emphasizing their synthesis methodologies and applications in both photodetectors and sensors, showcasing the versatility of dimensionally engineered materials.¹⁶ Nosovitskiy et al. provided insights into the latest advances in semiconductor gas sensing materials and structures, particularly focusing on breath analysis applications and the development of sophisticated algorithms for enhanced detection capabilities.¹⁷ Furthermore, Ma et al. reviewed recent progress in graphene-based humidity sensors with particular emphasis on structural design considerations, demonstrating the critical role of material architecture in sensor performance.¹⁸ The practical implementation of these advanced sensing technologies has been demonstrated by Nguyen and Lee, who developed chemical sensor devices specifically for monitoring hazardous gases in semiconductor manufacturing processes, bridging the gap between fundamental research and industrial applications.¹⁹ These collective studies underscore the importance of heterostructure engineering and dimensional control in developing next-generation gas sensors with enhanced performance characteristics.

However, the work presented earlier was limited to a specific thickness (10 nm) of NiO catalyst only. According to research in the literature, the catalyst layer’s thickness has a significant influence on the gas-detecting capabilities of the sensor. As a result, optimizing the catalyst thickness of layers is crucial for producing an improved sensing response to a certain target gas. Therefore, for the current study, the variation in gas sensing response has been investigated for the diverse catalyst NiO thickness scattered over the SnO₂ sensing layer in dotted nanoclusters in shape. Different sensing mechanisms have been explored for the sensing response changes with catalyst thickness variation for NiO/SnO₂ sensors.

Experimental

Thin films of SnO₂ have been deposited with a metal tin target (99.99% purity) within a controlled ambiance of argon and oxygen gas by the RF sputtering technique. All the parameters used for SnO₂ deposition have been tabulated in Table 1.

Table 1.

SnO₂ and NiO film deposition parameters for the sensor.

Sample/sensor	SnO₂	NiO
Target	Sn	Ni
Pressure (mT)	10	20
T-S distance (cm)	6.5	6.5
RF power (W)	150	40
Argon (%)	50	60
Oxygen (%)	50	40

SnO₂ thin film deposition was done on the Pt/Ti inter-digital electrodes pattern silicon substrate (description of the fabrication of Pt/Ti is mentioned elsewhere¹³) for sensing applications and silicon substrate for other characterizations. RF sputtering technique is used for the incorporation of NiO catalysts with varying thicknesses (6–14 nm) have been incorporated over the thin film surface of SnO₂ using the shadow masking technique, having a pore size of 50 microns shadow mask. The deposition characteristics are compiled in Table 1, where the SnO₂ thin film layer was maintained at 90 nm in thickness. SnO₂ thin film thickness and deposition parameters for obtaining enhanced sensing response have been taken from the previous report.¹³ Deposition parameters were obtained in depositing NiO catalyst using the RF sputtering technique. NiO/SnO₂ samples have been coded as N1 (6 nm), N2 (8 nm), N3 (10 nm), N4 (12 nm), N5 (14 nm) for varying thickness of NiO catalyst above the SnO₂ thin film surface. For comparison, under the ideal conditions, a bare SnO₂ thin film sensor has also been created; the bare sample is coded as N0.

Veeco Dektak 150 surface profiler measures the gas sensor thickness of deposited thin films. The MIRAJ TESCAN scanning electron microscope was used to examine the crystallinity of SnO₂ thin films. The optical characteristics of the sensors were investigated by a UV-visible spectrometer (Perkin Elmer, Lambda 35). SO₂ gas sensing properties of the prepared sensors were tested in-house developed GSTC “Gas Sensing Test Chamber.” A flowchart detailing the material preparation and sensor fabrication steps provides a clearer and more intuitive representation of the process and is shown in Figure 1.

Figure 1.

Flowchart representing the fabrication process.

Results and discussions

Structural analysis

The XRD patterns of NiO and SnO₂ targets are shown in Figure 2. The diffraction peaks for NiO correspond to the (111), (200), (220), (311), and (222) planes, consistent with the cubic phase of NiO (JCPDS No. 47-1049).²⁰ For SnO₂ sharp and well-defined peaks are observed at (110), (101), (200), (211), (220), (002), (310), (112), (301), (202), and (321) planes, which are indexed to the tetragonal rutile structure of SnO₂ (JCPDS No. 41-1445).²¹ The absence of impurity peaks indicates high purity.

Figure 2.

XRD profiles of NiO and SnO₂ target.

Microstructural analysis

The microstructural properties of the prepared thin films were depicted using SEM micrographs as shown in Figure 3. Figure 3(a) illustrates the formation of a porous nanostructure with minute cracks on the surface of the pristine SnO₂ thin film. SEM images of annealed SnO₂ thin films with NiO catalyst integration are displayed in Figure 3(b). The microstructure of SnO₂ thin film integrated with NiO catalyst exhibits uniformity and homogenous distribution of grains. The targeted gases may reach a considerable surface area of the SnO₂ thin film through these cracks, which helps achieve a good sensing response.

Figure 3.

(a) SEM image of annealed SnO₂ thin film, (b) annealed SnO₂ thin film integrated with NiO catalyst.

Gas sensing analysis

Studies of the sensing response of bare-SnO₂ (N0) and all heterostructures gas sensors (N1, N2, N3, N4, N5) were carried out by varying the temperature from 100 °C to 300 °C, and the obtained change in sensor response concerning 100 ppm SO₂ gas is shown in Figure 4.

Figure 4.

Temperature-dependent changes in the sensing response of NiO/SnO₂ heterostructure sensors with different NiO cluster thicknesses when SO₂ gas is exposed at 100 ppm.

Every sensor exhibits the typical sensing response, which rises with substrate temperature, achieves its highest value at the operating temperature (T_OPT), and subsequently decreases with temperature (Figure 4). Observed behavior is a result of the target SO₂ gas not having the least amount of energy to react with the sensing layer at lower temperatures (T_OPT), which is what causes it. However, at T_OPT this energy is maximum, leading to twin mechanisms (1) Fermi energy control, and (2) spill over mechanism which results in high sensing response. At a temperature greater than the operating temperature (>T_OPT), the desorption and the adsorption rate of targeted gas becomes higher due to which the sensing response further reduces. The max observed sensing response of the N0 sample was about 1.33 at T_OPT = 220 °C. After the integration of NiO clusters (NI, N2, N3, N4, and N5 samples), the operating temperature (T_OPT) was reduced to 180 °C, and the sensing response increased by roughly one order of magnitude (Figure 4). Obtained results indicate the significance of the NiO modifier over the SnO₂ thin film which has resulted in enhanced sensing response at lower operating temperature. Table 2 tabulates the sensing response, recovery times, and operating temperature of all NiO/SnO₂ sensors (N0, N1, N2, N3, N4, and N5) towards SO₂ gas at 100 ppm. The observed enhancement in sensing response on integrating NiO is attributed to both: (i) mechanism of fermi energy control that leads to space charge region modulation formed between the interfaces of NiO (p-type) as well as SnO₂ (n-type) sensing layers and (ii) spillover mechanism which accelerates the decomposed species of target gas molecules on uncovered SnO₂ surface. These mechanisms have been discussed in the later sections.

Table 2.

Illustrates parametric optimization for the current gas sensor.

Thickness of thin film base layer (SnO₂)	Thickness variation of dopant (NiO)	Optimized operating temperature (°C)	PPM gas	Response time (s)	Recovery time (s)	Sensing response
90 nm	No modifier (N0)	220	100	47	27	1.3
	6 nm (N1)	180	100	86	152	5.7
	8 nm (N2)	180	100	161	145	9.1
	10 nm (N3)	180	100	75	60	54
	12 nm (N4)	180	100	217	215	21
	14 nm (N4)	180	100	182	88	14

It can be seen that as NiO modifier thickness increases to 10 nm (N3 sample), the sensing response also increases to ~54. But on further increasing the thickness of NiO clusters (>10 nm) the sensing response decreases continuously. This might be explained by considering that the 10 nm thin NiO clusters (N3) sample exhibits the optimal roughness that leads to enhanced desorption and adsorption of target SO₂ gas on sensing layer. It is reported that if the surface roughness is very low or very high the sensing response is poor.²² With further increasing thickness of the catalyst thickness (>10 nm) for N4 and N5 samples, the surface roughness is seen to be increasing but the quick desorption of gas may be responsible for decreasing the sensing response for these sensors. However, no change in the operating temperature (180 °C) is observed for all NiO/SnO₂ sensors.

In Figure 5, the resistance changes of the sensor N3, as a function of ambient air temperature (R_a). R_a values are significantly correlated with the semiconducting properties of the metal oxides (SnO₂ and NiO) and decrease with increasing temperature for all sensor setups. R_a stables at a specific temperature due to NiO clusters over the surface of the SnO₂ thin film. When the SO₂ gas entered testing chamber, we noticed a significant change in R_a and was again stable when the SO₂ gas was exhausted.

Figure 5.

Resistance (R_a) variation for NiO/SnO₂ heterojunction sensor as a function of temperature, different NiO nanocluster thicknesses were seen in the air.

Figure 6(a) and (b) show the side view of the resulting NiO and SnO₂ hetero-junction that shows the depletion region, as well as the diagrammatic representation of the heterojunction formed at the meeting point of p-type NiO clusters and n-type SnO₂ thin film. As a result of the formation of a depletion region at the interface across n-type SnO₂ and p-type NiO, the concentration of electrons in the conduction band of the SnO₂ thin film drastically decreases and the sensor resistance (R_a) value rises. Additionally, NiO clusters hasten the process through which oxygen from the surrounding environment is adsorbed on the surface of SnO₂ thin films, causing the electron concentration in the SnO₂ conduction band to continue to drop.²³ When compared to bare SnO₂ (N0) sensors, NiO/SnO₂ sensors (N1, N2, N3, N4, N5) have more oxygen adsorbed, which results in a higher resistance (R_a) value. R_a value continuously rises as NiO cluster thickness increases from 6 to 10 nm. According to the measurements, the expansion of the space charge area at the NiO/SnO₂ interface and increased oxygen adsorption on the exposed surface of the SnO₂ film are both responsible for the rise in R_a. The channel thickness and, consequently, the cross-sectional area of the channel for electron conduction in the SnO₂ layer continues to be reduced as the breadth of the space charge region widens (Figure 5(a)). On the other hand, the increased absorption of ambient oxygen causes the SnO₂ thin layer to trap additional electrons. As a result, with the increasing thickness of NiO clusters, a rise in the initial sensor resistance (R_a) for NiO/SnO₂ heterostructure. It’s significant to note that with further increasing the NiO nanoclusters thickness (>10 nm), the value of R_a starts decreasing from 9.4 to 5.6 MΩ at T_OPT = 120 °C (N4 and N5 samples). The decrease in R_a for N4 and N5 samples may be attributed to the seeping of NiO clusters through the underneath SnO₂ thin film for higher thickness (>10 nm in the present case. According to the results of the current investigation, this might improve conductivity and lower sensor resistance (R_a).^24,25 The apparent hump in the R_a readings at temperatures of about 160 °C is caused by the conversion of adsorbed molecular oxygen (O₂⁻) to atomic oxygen (2O⁻; Figure 4).^24,25 More electrons are trapped over the surface of SnO₂, giving a result of improved adsorption and subsequent conversion of O₂⁻ to 2O⁻ at moderate temperature, raising the value of R_a at comparatively lower temperatures (~160 °C).

Figure 6.

Schematic diagram of the prepared NiO/SnO₂ heterojunction showing space charge region and effective channel thickness in SnO₂ thin film (a) before and (b) after exposure to SO₂ gas.

When the sensors were exposed to 100 ppm of SO₂ gas, all NiO/SnO₂ heterostructure sensors showed variations in sensor resistance (R_g) at different temperatures. When exposed to SO₂ gas while running at their operational temperature, all of the NiO/SnO₂ heterostructure sensors (NI, N2, N3, N4, and N5) show a substantial reduction in sensor resistance from R_a to R_g. In contrast, the R_a to R_g fluctuation for NiO/SnO₂ sensors is greater than the equivalent change in resistance for bare-SnO₂ sensors (N0). In comparison to other sensors (N1, N2, N4, and N5), the sensor resistance change (R_a = 12.0 M to R_g = 206 k) for sample N3 under SO₂ exposure of 100 ppm gas at T_OPT = 180 °C was found to be the largest. The predicted sensing method for the SO₂ gas detection using NiO/SnO₂ sensors is as follows. The interaction between the gas molecules of SO₂ and NiO nanoclusters, which produces the volatile SO₃ gas species,²⁶ is described in equation (1):

$NiO + 4 {SO}_{2} (g) \to NiS + 3 {SO}_{3} (g) (spilled)$ (1)

On the surface of the exposed SnO₂, at T_OPT = 180 °C, these explosive SO₃ gas species react with adsorbed atomic oxygen species (O⁻). As anticipated by equation (2), the species undergoes a transition into molecules of O₂ and SO₂ gas, which releases the electrons that have been stored into the SnO₂ conduction band. The depletion/space-charged region generated at the contact site of the NiO/SnO₂ sensor structure diminishes as a consequence of the Fermi energy control mechanism (which converts NiO into NiS) and the consequent overflow of targeted gas molecules that are not connected, thus lowering resistance (R_g)²⁷:

${SO}_{3} (g) (spilled) + O^{-} (absorbed) \to {SO}_{2} + O_{2} + e^{-}$ (2)

Due to the interaction that exists between the surface layer of the exposed SnO₂ sensor and the emitted molecules of SO₂ gas, more stored electrons are released to participate in SnO₂ layer conduction, lowering the R_g and increasing the sensing response. Figure 6 demonstrates the space charge region and effective channel thickness in SnO₂ thin film integrated with NIO catalyst before and after exposure to SO₂ gas.

This results in an increase in the optimum thickness of the conducting channel and a decrease in the region of depletion in the SnO₂ layer (at the NiO/SnO₂ junction). Resistivity of the sensor decreased significantly from R_a to R_g as a result of coming into contact with the SO₂ gas. This makes it easier for electrons to easily travel through the SnO₂ layer.²⁴

During the time of recovery, the SO₂ gas vents off from the gas sensing chamber, and fresh air is inserted. When fresh dry air interacts with the sensor surface, NiS gets converted back into NiO as given in equation (3)²⁸:

$NiS + \frac{3}{2} O_{2} \to NiO + {SO}_{2}$ (3)

Also, the oxygen gas molecules get absorbed from the atmosphere onto the SnO₂ surface and become O⁻ species depending on the ambient temperature (T_OPT = 180 °C). Thus, the sensor resistance again increases from R_g to R_a during the recuperation phase. Since the surface layer roughness of the NiO modifier is very crucial for obtaining the enhanced interaction of SO₂ gas molecules, this interaction is maximum for NiO nanoclusters having 10 nm thickness due to the higher value of surface roughness. As a result, it is hypothesized that the N3 sample has the largest concentration of spilled-over species, and as a result, the N3 sample has the strongest sensing response owing to the maximum fluctuation in resistance R_a values to R_g values.

Figure 7(a) and (b) display the response and recovery time at different operating temperatures of all developed gas sensors (N0, N1, N2, N3, N4, N5) towards SO₂ gas (100 ppm). After adding the NiO modifier to the SnO₂ thin film surface layer, an increase in the values of response and recovery time was seen (Figures 6(b) and 7(a)).¹⁵ Due to the conversion of NiO into NiS upon contact with SO₂ gas, the Fermi energy control mechanism predominates for NiO/SnO₂ sensors. This is a protracted process, and hence, the response time for all NiO/SnO₂ sensors is higher than for bare SnO₂ sensors. As with the bare-SnO₂ sensor, recovery time is likewise poor. All sensor structures’ response and recovery periods decrease as temperature increases because gas molecules adsorb and desorb more quickly at higher temperatures. The response and recovery time obtained for the other NiO/SnO₂ gas sensor designs are determined to be much shorter than the response and recovery time obtained for sensor N3, which is found to give response and recovery times of 75 and 60 s. This might be a result of the high surface roughness produced by the sensor N3, which causes more gas molecules to be trapped on the rough surface and lengthens the reaction time.

Figure 7.

(a) Variation in sensor response time. (b) Recovery time of all the fabricated sensors (N0, N1, N2, N3, N4, and N5).

Figure 8 demonstrates the gas sensor N3 structure’s transient response to temperature. It is observed that when exposed to SO₂ gas at 100 ppm, the resistance values of the sensor fluctuate most when the operating temperature (T_OPT) is 180 °C. When temperature rises, adsorption and desorption rates rise as well, resulting in reduced variance in sensor resistance when exposed to SO₂ gas molecules.

Figure 8.

Transient response structure of (10 nm) NiO/SnO₂ sensor obtained at various temperatures towards SO₂ gas at 100 ppm.

In Figure 9, the selectivity transient of the N3 sensor structure towards other toxic and harmful gases like LPG, methane, acetone, and CO₂ at 1000 ppm gas concentration, along with the SO₂ at 100 ppm. Operating temperature of 180 °C, which has been optimized for the sensor, N3 displays the best sensing response towards 100 ppm SO₂ gas and exhibits poor response towards other interfering gases (Figure 9). Equation (4) has been used to estimate the selectivity parameter (β) of the N3 sensor for other interfering gases:

$β = \frac{S_{interferring}}{S_{target}}$ (4)

Figure 9.

Selectivity study of (10 nm) NiO/SnO₂ sensor (N3) with various gasses that interfere at 1000 ppm at an operating temperature of 180 °C.

The sensing reaction to SO₂ gas (100 ppm) is known as $S_{target}$ , while the response to equivalent interfering gases, such as CO₂, LPG, methane, and acetone, at 1000 ppm concentration at the operating temperature T_OPT = 180 °C, is stated as $S_{interferring}$ . Figure 10 illustrates the enhanced sensing response of various gases, including SO₂, LPG, methane, acetone, and CO₂. The maximum sensing response was experienced against SO₂ gas. Table 2 summarizes the parametric optimization, sensing response, recovery time, and operating temperature of all NiO/SnO₂ sensors (N0, N1, N2, N3, N4, and N5) towards SO₂ gas at 100 ppm for the current gas sensor. Table 3 demonstrates a comparison on the grounds of lower operating temperature, higher response, and competitive response/recovery times.

Figure 10.

Variation of the (10 nm) NiO/SnO₂ sensor structure’s selectivity parameter for various interfering gases.

Table 3.

Comparison table for lower operating temperature, higher response, and competitive response/recovery times.

Sensor material	Operating temperature (°C)	Response	Response time (s)	Recovery time (s)	Detection limit	References
Ag-doped WO₃	400	25	–	–	800 ppm	Shimizu et al.⁷
NASICON/V₂O₅-TiO₂	–	170 mV/EMF	–	–	50 ppm	Liang et al.⁹
Nano-Au assembly	RT	5.4 × 10⁻¹¹ A/ppm	–	–	–	Li et al.¹⁰
NiO/SnO₂ (this work)	180	54	75	60	100 ppm	Present study

Conclusion

The sensing response properties of the NiO/SnO₂ thin film-heterostructure sensor of all the developed structures have been investigated for detecting the SO₂ gas (100 ppm). The optimal thickness of NiO nanoclusters in the NiO/SnO₂ heterostructure sensor has been established to be 10 nm to obtain the increased sensing response (54) with a shorter reaction time (75 s) and rapid recovery time (60 s) at a lower operating temperature (180 °C). It is discovered that during the contact of SO₂ gas with the NiO/SnO₂ heterojunction structure (10 nm modifier), the maximum modulation of the space charge region took place at the interface of p-type modifiers with n-type SnO₂ thin film. This alteration in the space charge area drastically changed the sensor resistance (from R_a and R_g). The selectivity of the developed gas sensor against SO₂ gas also proves to be excellent compared with various other exposed gases.

Footnotes

The authors are thankful to the Department of Electronics and Communication,Chandigarh University,and Semi-conductor Laboratory,Mohali for providing support and permission to work in the laboratory.

ORCID iDs

Divya Bajpai Tripathy

Anjali Gupta

Ethical considerations

In the present study,no animal and human are involved and the manuscript doesn’t require ethical approval.

Consent to participate

The study carried out in the present manuscript is a novel work and didn’t involve any data from any individual and doesn’t require consent from any individual.

Author contributions

Shubham Choudhary: conceptualization. Manish Deshwal: data curating. Payal Patial: methodology. Nupur Aggarwal: formal analysis. Naveen Kumar: supervision. Divya Bajpai Tripathy: reviewing,editing,and co-supervision. Anjali Gupta: reviewing,editing,and co-supervision.

Funding

The authors received no financial support for the research,authorship,and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Data availability statement

Data will be made available on request.

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