Development of low-temperature SnO2–Au gas sensors for H2S detection in food freshness monitoring

Kee-Ryung Parkab, Jinhyeong Kwon*ac and Hyeunseok Choi*a
aResearch Institute of Sustainable Development Technology, Korea Institute of Industrial Technology (KITECH), Cheonan, 31056, Republic of Korea. E-mail: jhs0909k@kitech.re.kr; hchoi@kitech.re.kr
bKorea National Institute of Rare Metals, Korea Institute of Industrial Technology (KITECH), Incheon, 21655, Republic of Korea
cLaser-processed Nanomaterials Engineering Lab., Korea Institute of Industrial Technology (KITECH), Cheonan, 31056, Republic of Korea

Received 9th July 2024 , Accepted 24th August 2024

First published on 27th August 2024


Abstract

Tin Oxide (SnO2) is widely used in chemiresistive applications due to its favorable electrical properties, high reliability, and enhanced sensitivity towards various gases. However, its high operating temperature limits its application in energy-efficient and compact modules. This study presents a novel SnO2–Au 0.5 wt% chemiresistive gas sensor, optimized to operate at a low temperature of 200 °C, with high sensitivity (270.231, Ra/Rg) for 10 ppm H2S gas. The sensor has been integrated into a handheld device to evaluate beef freshness by detecting H2S gas emissions. The results demonstrate the sensor's potential to revolutionize the food industry by providing a quick, reliable, and non-invasive method for assessing meat quality, ensuring food safety, and reducing waste.


Introduction

Maintaining a fresh food supply system is one of the essential factors for a sustainable society.1 The United Nations Environment Program (UNEP) has reported that improper storage and inefficient logistics led to the wastage of approximately 17% of all globally produced food.2 This wastage not only affects food availability for those experiencing starvation but also contributes to increased greenhouse gas emissions during transportation and production.3 Modern electronic technologies offer potential solutions to deal with the issue.4 For example, food status indicators/sensors could provide real-time information to ensure optimal consumption of food.5,6 However, existing products encountered limitations such as complex manufacturing processes, sophisticated gas sensing system setups, expensive analytic instruments, and immobility. Furthermore, conventional gas sensor systems are not suitable for the different types of food species such as crops, fish, fruits, and meats.

Protein-containing foods emit various gases including ammonia (NH3), trimethylamine (TMA), hydrogen sulfide (H2S), among others, during decomposition.7–9 These gases serve as important indicators of food freshness and quality. Among them, H2S gas is particularly significant due to its harmful effects and distinct odor, making it a crucial target for food freshness detection.10 Consequently, researchers have focused extensively on developing gas sensor systems capable of detecting H2S with high sensitivity and specificity.11,12 Metal oxides such as CuO,13 Fe2O3,14 In2O3,15 SnO2,16,17 TiO2,18 WO3,19,20 and ZnO21–24 have been widely applied in gas sensor technology. These materials are favored due to their due to their cost-effectiveness, straightforward synthesis methods, fine gas-detecting capabilities, and long-term stability. However, a major limitation of metal oxide-based gas sensors is their high operating temperatures, often exceeding 300 °C, which are necessary to overcome activation energy barriers.25 This requirement poses challenges for practical applications, especially in scenarios where low power consumption and safety are critical.

To address these challenges, it is essential to develop advanced gas sensors that can operate at lower temperatures while maintaining sensitive and selective detection of target gas molecules. Tin dioxide (SnO2) is a promising candidate in this regard due to its desirable electrical properties, high chemical stability, reliability, and non-toxicity.26,27 Recent studies have shown that SnO2-based sensors can be engineered to achieve improved performance at lower temperatures, making them suitable for a wider range of applications, including food safety monitoring. For example, Liu et al. have fabricated an ethanol gas sensor using hydrothermally synthesized SnO2–Au microspheres.28 The ethanol sensor based on SnO2–Au microspheres exhibits a three-fold higher response value, good reversibility, and fast on/off performance at 240 °C compared to a conventional SnO2 gas sensor. Feng et al. also synthesize mesoporous SnO2–Au nanospheres using non-toxic, renewable, and inexpensive plant polyphenols.29 These nanospheres, with a uniform diameter of 120 nm and high surface areas, serve as the active material for a TMA gas sensor operating at 50 °C. Although these studies achieve significant gas detection performance, the researchers do not disclose the temperature and quantitative yield of the material synthesis.

In this study, we synthesize SnO2–Au hollow nanofibers through a combination of electrospinning and calcination processes. The electrospinning technique enables the creation of Sn-based nanofibers with large-area, uniform structures in significant quantities. Additionally, the subsequent calcination process enhances the surface areas of the SnO2-based nanofibers by generating hollow nanostructures. The optimized SnO2–Au nanostructure, when used as an H2S chemiresistive gas sensor, exhibits remarkable sensitivity, selectivity, and excellent repeatability at an operating temperature as low as 200 °C. Furthermore, we design and apply the sensor in a food freshness monitoring device to assess the freshness of beef. The device operates by measuring the concentration of H2S, a key indicator of freshness, and seamlessly relays the results through a smartphone app. Through a series of experiments evaluating the freshness of beef, the developed tool demonstrates its efficacy in determining the freshness level with precision. We expect that the food freshness monitoring system developed in this study will contribute to improving the food supply chain and reducing food waste in the future.

Results and discussion

Fig. 1(a) illustrates the electrospinning process used to synthesize Sn/Au-containing nanofibers. The jetting solution consists of dimethylformamide (DMF), ethanol, deionized water, Sn/Au metal precursors, and polyvinylpyrrolidone (PVP) additive. The inset figures exhibit the smooth surface morphology and scalable productivity of the as-spun Sn/Au nanofibers, respectively. Subsequently, a calcination process is performed at 600 °C on the as-spun nanofibers, during which Sn4+ ions react with oxygen and Au3+ ions acquire electrons, resulting in the formation of SnO2–Au nanofibers as shown in Fig. 1(b). Simultaneously, the inner structure of the nanofibers releases chloride species, PVP, and other components, resulting in SnO2–Au hollow-structured nanofibers.30 To obtain the proper surface morphologies of the SnO2–Au nanofibers, the Au precursor ratio in the jetting solution is systematically controlled from 0, 0.1, 0.5, 1, 2, to 5 wt%. Fig. 1(c) exhibits the morphological evolution of SnO2 nanofibers with increasing Au contents, synthesized via electrospinning, as visualized through SEM images: (i) SnO2, (ii) SnO2–Au 0.1 wt%, (iii) SnO2–Au 0.5 wt%, (iv) SnO2–Au 1 wt%, (v) SnO2–Au 2 wt%, and (vi) SnO2–Au 5 wt%. Image (i) depicts pristine SnO2 nanofibers with a continuous fibrous structure and a diameter of approximately 200 nm. As Au content increases from 0.1 wt% to 5 wt%, notable structural changes are observed in images (ii) to (vi). In the image (ii) with 0.1 wt% Au, the nanofibers show the initial surface roughness and slight structural modifications. Image (iii) with 0.5 wt% Au reveals prominent hollow nanostructures with defined porous surfaces due to the Kirkendall effect. Image (iv) with 1 wt% Au shows further hollow structure development and slight aggregation. In the image (v) with 2 wt% Au, more significant aggregation and chunkier formations appear. Finally, image (vi) with 5 wt% Au shows distinct clusters, with nanofibers losing their fibrous nature and demonstrating significant morphological aggregation. This transition from smooth fibers to hollow and aggregated forms illustrates the impact of increasing Au content on SnO2 nanofibers.
image file: d4tc02901a-f1.tif
Fig. 1 Schematic process of the fabrication of SnO2–Au hollow nanostructures. (a) The electrospinning creates as-spun nanofibers, containing Sn/Au metal precursors with other ingredients. The as-spun nanofibers show a smooth surface (left inset) and large-area scalability (right inset). (b) The calcination process at 600 °C turns as-spun nanofiber to the SnO2–Au hollow nanostructure. (c) SEM images illustrating the morphological evolution of SnO2 nanofibers with increasing Au content: (i) pristine SnO2 nanofibers, (ii) SnO2–Au 0.1 wt% with initial surface roughness, (iii) SnO2–Au 0.5 wt% showing prominent hollow structures, (iv) SnO2–Au 1 wt% with slight aggregation, (v) SnO2–Au 2 wt% showing significant aggregation, (vi) SnO2–Au 5 wt% forming distinct clusters and losing fibrous nature.

Further surface analysis reveals the inner structure, element distribution, and surface chemistry of the synthesized SnO2–Au 0.5 wt% hollow nanofibers. A high-resolution TEM image in Fig. 2(a-i) displays porous structures with rough surfaces for the SnO2–Au hollow nanofibers. This suggests that the SnO2–Au 0.5 wt% hollow nanofibers provide large surface areas and sufficient gas interaction sites. Fig. 2(a-ii) shows the observed lattice distances of SnO2 and Au, with the (101) plane of SnO2 and the (111) plane of Au matching lattice distances of 2.63 nm and 2.36 nm, respectively.31 The selected area electron diffraction (SAED) pattern exhibits a polycrystalline structure for the SnO2–Au 0.5 wt% hollow nanofibers in Fig. S1 (ESI), displaying several significant ring patterns corresponding to the (101), (110), and (211) planes for SnO2, and the (111) plane for Au. XRD analysis in Fig. 2(b) shows the crystal structure and phases of the SnO2–Au hollow nanofibers, with all diffraction peaks in the spectrum corresponding to specific crystal planes of SnO2 and Au. Specifically, the observed peaks at approximately 26.58°, 33.87°, 37.95°, and 51.77° are indexed to the (110), (101), (200), and (211) planes of the tetragonal crystal structure for SnO2 (JCPDS card no. 01-071-0652). The two peaks at approximately 38.18° and 44.37° correspond to the (111) and (200) planes for the metallic cubic phase of gold (JCPDS card no. 01-089-3697). This result indicates that the SnO2–Au hollow nanofibers have been properly synthesized through electrospinning and the subsequent calcination process without impurity phases.32 Fig. 2(c) presents the energy-dispersive X-ray spectroscopy (EDS) element mapping image of the SnO2–Au 0.5 wt% hollow nanofibers, revealing the even dispersion of Sn, O, and Au elements within the hollow structured nanofibers, along with the uniform distribution of Au nanoparticles on the SnO2 hollow nanofibers. Additionally, Fig. 2(d) displays the results of an X-ray photoelectron spectroscopy (XPS) survey, investigating the surface chemical state of each element in the SnO2–Au 0.5 wt% hollow nanofibers. The Sn element exhibits two distinct peaks, Sn 3d5/2 and Sn 3d3/2, with binding energies of 486.18 eV and 494.63 eV, respectively, indicating the presence of Sn4+ in SnO2.33 The identified oxygen peak is located at 530.50 eV, consisting of two different inner peaks: 529.98 eV for the absorbed O species and 531.12 eV for the O2− species. While existing literature suggests that the XPS peaks of Au are located at 83.53 eV and 87.23 eV, our study observes specific peaks for Au 4f5/2 and Au 4f7/2 at 83.43 eV and 87.08 eV, respectively.34 These results imply that the synthesized SnO2–Au 0.5 wt% hollow nanofibers exhibit proper chemical stability without inadequate chemical bindings.


image file: d4tc02901a-f2.tif
Fig. 2 Characterizations on the synthesized SnO2–Au 0.5 wt% hollow nanofiber. (a) TEM analysis reveals (i) the rough and hollow surface structure of the synthesized SnO2–Au nanofiber. (ii) The confirmed lattice distances indicate the main components of the structures are SnO2 (red) and Au (yellow). (b) XRD result also confirms the synthesized SnO2–Au 0.5 wt% hollow nanostructure has been properly crystallized after the calcination process. (c) EDS mapping image shows the Au contents are widely dispersed on the SnO2 nanostructure. (d) XPS results represent the synthesized SnO2–Au 0.5 wt% hollow nanofibers have appropriate chemical stability.

The synthesized SnO2–Au hollow nanofibers are adopted for gas sensor applications, utilizing their high surface areas, morphologies, and chemical stabilities. These characteristics enable the porous and hollow structured sensing materials to facilitate the diffusion of the target gas, ultimately enhancing the sensing properties while simultaneously reducing response and recovery times.35,36 The synthesized SnO2–Au hollow nanofibers can be used for chemiresistive gas sensor applications, leveraging their high surface areas, morphologies, and chemical stabilities. These characteristics enable the porous and hollow structured sensing materials to facilitate the diffusion of the target gas, ultimately enhancing the sensing properties while simultaneously reducing response and recovery times. Additionally, since SnO2 is widely used for H2S gas sensing, we aim to design a gas sensor specifically for H2S detection. Fig. 3(a) illustrates the fabrication of a H2S gas sensor module with predefined electrode patterns and a ceramic package using SnO2–Au hollow nanostructures. The H2S gas sensor modules are verified to confirm the optimal gas sensing response performances with varying compositions of the SnO2–Au hollow nanostructures and different operating temperature conditions, as shown in Fig. 3(b). As the amount of Au added to the SnO2 increases, the gas response value generally tends to increase. However, when over 1 wt% of Au is added, the response value decreases. This is likely because the nanostructures cluster together, resulting in a reduced surface area, as observed in the SEM images. Consequently, the most outstanding response value for H2S gas is obtained with SnO2–Au 0.5 wt% nanostructures. Fig. S2 (ESI) exhibits the gas sensing properties with various compositions of the SnO2–Au hollow nanostructures at different operating temperatures. The H2S gas response properties of the SnO2–Au 0.5 wt% gas sensor at various operating temperatures are shown in Fig. 3(c). As the operating temperature increases, the H2S gas response steadily rises. However, above 200 °C, the gas response slightly declines. Fig. S3 (ESI) shows gas response trend graphs at different operating temperatures from room temperature to 250 °C for the SnO2–Au 0.5 wt% gas sensor. The declined sensing response beyond the optimum operating temperature in conventional metal oxide sensors can be attributed to two factors. Firstly, in the n-type material of SnO2, the thickness of the depletion layer changes, which depends on the carrier concentration of adsorbed oxygen species on the surface.37,38 Within the temperature range of 100 °C to 300 °C, O2− species convert to O by consuming an electron: O2− + e → 2O. As the temperature exceeds 300 °C, O converts back to O2− by consuming another electron: O + e → O2−, resulting in a rapid increase in resistance at higher temperatures.39,40 Secondly, the adsorption/desorption reactions on the active sites are spontaneous and exothermic processes, characterized by negative Gibbs free energy.39,40 However, if the sensing temperature exceeds the desired range, the desorption of adsorbate gas molecules accelerates without allowing sufficient surface reaction time.39 While this kinetic process ensures faster recovery time, it leads to reduced responses to the target gas due to insufficient reaction time. Noble metal-added metal oxides facilitate easier absorption and diffusion of oxygen species on the surface.41,42 As a result, an electron-depleted layer forms at the interface, referred to as the spillover effect. This phenomenon enables the rapid diffusion and adsorption of oxygen ions onto the metal oxide surface, significantly enhancing sensor sensitivity and reducing the operating temperature.41,43 Nevertheless, it is also worth noting that an excessive amount of noble metal content in metal oxide gas sensors can lead to side effects. Excessive noble metals can chemically interact with gases, causing alterations in gas adsorption and reduction characteristics. These combined factors can impact the overall performance of the sensor, compromising its desired sensing properties.44 Therefore, the optimum operating temperature for the SnO2–Au 0.5 wt% gas sensor is 200 °C, at which it exhibits the highest response value of 270.231 (Ra/Rg) for 10 ppm of H2S gas. The gas sensing mechanism, illustrated as a band diagram of the SnO2–Au 0.5 wt% gas sensor at an operating temperature of 200 °C in both air and H2S conditions, is shown in Fig. S4 (ESI).45 Fig. 3(d) indicates gas sensing properties of the SnO2–Au 0.5 wt% gas sensor with various H2S gas concentrations. The H2S gas concentration is designed to gradually decrease from 10 ppm to 0.5 ppm, and it is confirmed that measurements can be accurately taken even at the minimum range of 0.5 ppm. Note that the theoretical limits of detection (LoD) for the SnO2–Au 0.5 wt% gas sensor can be estimated as approximately 0.3 ppm.46 Therefore, the counted LoD is close to its minimum H2S detectable range of 0.5 ppm. The gas sensing repeatability of the SnO2–Au 0.5 wt% gas sensor is verified in Fig. 3(e). The H2S gas sensing properties show good stability during the 15-cycle gas sensing test with a 10 ppm H2S gas concentration. Fig. S5 (ESI) also demonstrates the stability of the measurement values. Various gas injection tests, including H2S (10 ppm), C2H5OH (50 ppm), NH3 (200 ppm), CH3COCH3 (20 ppm), and NO2 (50 ppm), validate the gas selectivity of the SnO2–Au 0.5 wt% gas sensor at 200 °C in Fig. 3(f). It demonstrates significant gas sensing selectivity of 270.231 (Ra/Rg) against H2S gas, while other gases show weak activity. Additionally, mixed gas injection tests further indicate the excellent gas selectivity of the SnO2–Au 0.5 wt% gas sensor in complex environments This test is designed to flow reference gases such as CH3COCH3, NO2, NH3, and C2H5OH in the first stage. Afterward, the gas sensor system injects H2S gas into the sensor. At the final stage, the mixed gases, containing H2S and other reference gas are being flowed simultaneously. As depicted in Fig. S6 (ESI), there are no reactivity signals in the first stage. The gas reaction occurs when the H2S gas is being injected. Obviously, a similar gas detection signal is observed during both H2S and other reference gas injection conditions in the final stage. Therefore, the fabricated SnO2–Au 0.5 wt% gas sensor exhibits outstanding gas sensitivity, selectivity, and repeatability for H2S gas at 200 °C.


image file: d4tc02901a-f3.tif
Fig. 3 Gas sensing performances of the fabricated SnO2–Au Chemiresistive gas sensor (a) fabrication process of H2S gas sensor module using SnO2–Au hollow nanostructures. (b) Gas sensing response performance with varying Au compositions and operating temperatures. The SnO2–Au 0.5 wt% nanostructures show the highest response at 200 °C. (c) H2S gas response properties of SnO2–Au 0.5 wt% sensor at different temperatures. (d) Gas sensing properties with varying H2S concentrations, showing accurate measurements down to 0.5 ppm. (e) Repeatability test for 10 ppm H2S over 15 cycles, demonstrating good stability. (f) Gas selectivity test at 200 °C, showing significant selectivity for H2S over other gases.

To validate the practical application of the SnO2–Au 0.5 wt% gas sensor for monitoring food freshness, we implement the sensor in a handheld device. For our study, we use 10 grams of beef as a reference marker to observe and confirm the release trends of H2S gas, which is indicative of food spoilage. The reference markers are stored separately under two different temperature conditions: room temperature (30 °C) and refrigerator temperature (4 °C) for 72 hours. Fig. 4(a) illustrates the visual states of the reference markers over time under these storage conditions. At 30 °C, the reference marker exhibits a noticeable dark brown discoloration and a dried surface within just 24 hours. In stark contrast, the reference marker stored at 4 °C shows minimal changes in appearance, even after 72 hours. Fig. 4(b) presents the measured H2S gas responses from the two differently stored reference markers. Consistent with the visual observations, the reference marker kept at 30 °C demonstrates a gradual and steady increase in H2S gas emission, signifying the progression of beef spoilage. In contrast, the sample stored at 4 °C maintains a stable and low level of H2S gas, confirming its relatively fresh state. To establish a baseline for the H2S gas levels, we set the maximum value observed from the sample stored in the refrigerator for 72 hours at approximately 1.05. This value serves as a reference point to differentiate between fresh and spoiled states in practical applications of the handheld device. By utilizing historical food spoilage data, including H2S emission levels, temperature, and time, we further refine the accuracy of our freshness monitoring device. Through the analysis of this collected data, the device compares real-time H2S gas readings with historical patterns, providing a more reliable assessment of food quality. Fig. 4(c) illustrates the assembly structure of the handheld device. It consists of the SnO2–Au gas sensor module, a 3D-printed exterior case, a microcontroller unit (MCU), and other components. (Movie S1, ESI) A detailed description of the circuit components and design of the handheld device is provided in the Experimental Section. Fig. 4(d) and Movie S2 (ESI) demonstrate the working scenario of the handheld food freshness device, which detects whether the beef is good or bad. The handheld device, in conjunction with a smartphone application, promptly alerts the status of the food by displaying indicators for the good or bad condition of the target sample on the smartphone.


image file: d4tc02901a-f4.tif
Fig. 4 Food freshness monitoring by using SnO2–Au 5 wt% gas sensor. (a) The visual appearance changes of the beef with different storage temperatures of 30 °C and 4 °C for up to 72 hours. (b) A real-time H2S Gas sensing trend of the beef with different storage temperatures. (c) The inner structure of the hand-held device. (d) Application of the sensor for the hand-held device to detecting food freshness for (i) fresh beef and (ii) spoiled beef. Note that the H2S gas sensing results (and visual appearance) corresponds to the popped smartphone image.

Conclusions

In this study, we successfully synthesize SnO2–Au hollow nanofibers using electrospinning and calcination processes, demonstrating large surface areas, favorable morphologies, and high chemical stability. The chemiresistive gas sensing properties of these SnO2 nanofibers, with various Au contents (0–5 wt%), are evaluated for H2S detection. Among these, the SnO2–Au 0.5 wt% hollow nanofiber is identified as the most effective material, exhibiting high sensitivity, selectivity, repeatability, and rapid response/recovery times at an operating temperature of 200 °C. The practical application of the SnO2–Au 0.5 wt% gas sensor is demonstrated by integrating it into a handheld device designed for food freshness monitoring. This device successfully assesses the freshness of beef stored under different conditions by detecting H2S emissions, providing real-time feedback through a smartphone app. By offering a reliable, non-invasive, and efficient method for detecting meat spoilage, this innovation could contribute to sustainable food management practices and the reduction of food waste in society.

Experimental section

2.1. Materials

SnCl4·5H2O, HAuCl4·3H2O, ethanol, N,N-dimethylformamide (DMF), and poly(vinylpyrrolidone) (PVP; Mw = 1[thin space (1/6-em)]300[thin space (1/6-em)]000) were purchased from Sigma-Aldrich, USA. All chemicals were used without further purification.

2.2. Preparations of SnO2–Au hollow nanofibers

Firstly, we dissolved 0.45 g of Sn and different Au precursors (0, 0.1, 0.5, 1, 2, and 5 wt%) and PVP in 3 mL ethanol and 3 mL DMF with 1 g of DI water. The solution was then stirred at room temperature at 500 rpm for 4 h. Sn and Au precursor/PVP nanofibers synthesized with the solution by electrospinning a constant DC voltage of 19 kV applied between a stainless-steel collector and a syringe needle (27 gauge) with a feeding rate of 0.3 mL h−1. The as-spun Sn and Au precursor/PVP nanofibers were calcined at 600 °C for 2 h at a ramping rate of 3 °C min−1 in air ambient to obtain SnO2–Au hollow nanofibers followed by Kirkendall effect.

2.3. Material characterizations

The synthesized materials were characterized using scanning electron microscopy (SEM, S-4800, Hitachi High-Technologies, Co., Tokyo, Japan), X-ray diffractometry (XRD, D/MAX-2500-PC, Rigaku International Co., Tokyo, Japan) with Cu Kα X-ray source (λ = 1.5418 Å) at 2θ, high resolution transmission electron microscopy (HR-TEM, JEM-2100 F, JEOL Ltd., Tokyo, Japan), high-angle annular dark-field scanning tunneling electron microscopy (HAADF-STEM), selected-area electron diffraction (SAED), energy dispersive X-ray spectroscopy (EDS), and X-ray photoelectron spectroscopy (Theta Probe XPS, ThermoFisher Scientific, Waltham, MA, USA) with a base pressure of 4.8 × 10−9 mbar using a monochromatic Al Kα X-ray source ( = 1486.6 eV).

2.4. Fabrication of gas sensor module

A 5 × 5 mm2 SiO2/Si wafer with pre-defined interdigitated electrodes (IDEs) was used as the substrate. Each electrode has a length of 3 mm and a width of 20 μm, with a gap distance of 20 μm between the electrodes. Synthesized SnO2–Au hollow nanofibers were dispersed in ethanol, with 100 mg of nanofibers in 1 mL of ethanol. This suspension was drop-cast onto the electrode substrate, followed by drying at 60 °C to remove the ethanol. The assembled device, including a gas sensor module enclosed in a ceramic package, was then placed into a 3D-printed exterior case (Fig. 4(c)).

2.5. Chemiresistive gas sensor performance measurement

Firstly, 100 mg of SnO2–Au nanofibers were dispersed in 1000 μL of ethanol. The 3 μL of SnO2–Au dispersed solution was then drop casted on the prepared SiO2 sensor substrate with Au electrodes followed by drying of the ethanol solvent. The gas sensing tests were carried out using a company (GMC 1200, ATOVAC, Yongin, Korea) gas sensor measurement system equipped with a data acquisition system (2450 Sourcemeter, Keithley, Solon, OH, USA). The resistance was calculated by the recorded current from applied constant DC voltage of 3 V. The gas concentration was controlled by changing the mixing ratio of nitrogen and H2S (10 ppm in nitrogen) with fixed oxygen of 21% using mass flow controller (Model 5850E, Brooks Instrument, Hatfield, PA, USA) between 0.5 and 10 ppm. Nitrogen and oxygen were used as the carrier gas at a fixed flow rate of 500 sccm. The operating temperature was controlled from room temperature to 250 °C using a ceramic heater. The gas sensor performance was measured for 600 seconds with dried air and for 200 seconds with the target gas, respectively. A schematic of the gas sensor system is illustrated in Fig. S7 (ESI). Various analyte gases (CH3COCH3, NO2, C2H5OH, and NH3) were exposed to envisage the gas selectivity of the sensor as a function of different concentration. The response was used to characterize the sensor performance using the equation response = Ra/Rg, where Ra and Rg are the electrical resistance of the sensor under dry air and the concentration of H2S gas, respectively.

2.6. Preparation of food reference sample

We performed an experiment to assess the fresh beef. We placed two pieces of 10 g beef in a glass container and stored them under two different temperature conditions of 30 °C and 4 °C. We measured the sensing characteristics of each beef sample at four different time points: 0, 24, 48, and 72 hours after storage.

2.7. Hand-held device for food freshness detecting

A hand-held device for food freshness detecting was developed with the proposed H2S gas sensor. This device consists of air suction fan unit, circuit board with Wi-Fi module (LOLIN D32 V1.0.0 ESP-32 WiFi-Bluetooth), smart phone apps and the gas sensor module. The device was designed with the SnO2–Au the gas sensor module, ceramic heater, circuit board (with controller unit and commutation module), and a micro fan in its inside. In detail, inlet/outlet hole assemblies played the flow directions for the target gas molecules. Also, the sensor module is comprised of an alumina crucible measuring 1 × 1 × 1 cm3, which houses a circular ceramic heater with a diameter of 5 mm and a sensor element affixed to the ceramic heater. The device is capable of communicating with other devices via Wi-Fi, and can accurately assess the stability of beef within seconds using an app that is directly installed on Android phones. A lithium-ion battery was assembled to provide a power supply.

Author contributions

K. Park developed main idea of research and conducted the experiments. K. Park and J. Kwon wrote the manuscript in consultation with H. Choi. K. Park and J. Kwon revised the manuscript. H. Choi supervised the project and made the hand-held device as the application example of the sensor.

Data availability

The data supporting this article have been included as part of the ESI.

Conflicts of interest

The authors declare no conflict of interest.

Acknowledgements

This work was supported by the Big Issue Project (PEO24030) from Korea Institute of Industrial Technology and the Industrial Technology Innovation Program (no. 20023014) funded by the Ministry of Trade, Industry and Energy (MOTIE, Korea)

References

  1. S. Corrado, C. Caldeira, M. Eriksson, O. J. Hanssen, H.-E. Hauser, F. van Holsteijn, G. Liu, K. Östergren, A. Parry, L. Secondi, Å. Stenmarck and S. Sala, Global Food Secur., 2019, 20, 93–100 CrossRef PubMed .
  2. M. He, X. Zhu, S. Dutta, S. K. Khanal, K. T. Lee, O. Masek and D. C. W. Tsang, Bioresour. Technol., 2022, 344, 126395 CrossRef CAS PubMed .
  3. E. A. Mohareb, M. C. Heller and P. M. Guthrie, Environ. Sci. Technol., 2018, 52, 5545–5554 CrossRef CAS PubMed .
  4. C. Dincer, R. Bruch, E. Costa-Rama, M. T. Fernández-Abedul, A. Merkoçi, A. Manz, G. A. Urban and F. Güder, Adv. Mater., 2019, 31, 1806739 CrossRef PubMed .
  5. N. Khansili, G. Rattu and P. M. Krishna, Sens. Actuators, B, 2018, 265, 35–49 CrossRef CAS .
  6. H. Yousefi, H.-M. Su, S. M. Imani, K. Alkhaldi, C. D. M. Filipe and T. F. Didar, ACS Sens., 2019, 4, 808–821 CrossRef CAS PubMed .
  7. A. E.-D. A. Bekhit, B. W. B. Holman, S. G. Giteru and D. L. Hopkins, Trends Food Sci. Technol., 2021, 109, 280–302 CrossRef CAS .
  8. D. M. G. Preethichandra, M. D. Gholami, E. L. Izake, A. P. O'Mullane and P. Sonar, Adv. Mater. Technol., 2023, 8, 2200841 CrossRef CAS .
  9. S. Jiang and Y. Liu, TrAC, Trends Anal. Chem., 2020, 126, 115877 CrossRef CAS .
  10. K. Wu, W. Zhang, Z. Zheng, M. Debliquy and C. Zhang, Appl. Surf. Sci., 2022, 585, 152744 CrossRef CAS .
  11. A. Mirzaei, S. S. Kim and H. W. Kim, J. Hazard. Mater., 2018, 357, 314–331 CrossRef CAS PubMed .
  12. D. Li, Y. Tang, D. Ao, X. Xiang, S. Wang and X. Zu, Int. J. Hydrogen Energy, 2019, 44, 3985–3992 CrossRef CAS .
  13. N. Wang, W. Tao, X. Gong, L. Zhao, T. Wang, L. Zhao, F. Liu, X. Liu, P. Sun and G. Lu, Sens. Actuators, B, 2022, 362, 131803 CrossRef CAS .
  14. H. Wang, Y. Luo, K. Li, B. Liu, L. Gao and G. Duan, Chem. Eng. J., 2022, 427, 131631 CrossRef CAS .
  15. N. Liu, Y. Li, Y. Li, L. Cao, N. Nan, C. Li and L. Yu, ACS Appl. Mater. Interfaces, 2021, 13, 14355–14364 CrossRef CAS PubMed .
  16. K.-R. Park, H.-B. Cho, J. Lee, Y. Song, W.-B. Kim and Y.-H. Choa, Sens. Actuators, B, 2020, 302, 127179 CrossRef CAS .
  17. J. Tang, H. Wang, W. Dong, H. Yang, X. Wang, X. Guo and D. Zeng, Ceram. Int., 2024, 50, 14151–14160 CrossRef CAS .
  18. R. Kou, H. He, Y. Lu, H. Wang, J. Xu, Y.-Y. Song and Z. Gao, Chem. Eng. J., 2023, 476, 146546 CrossRef CAS .
  19. Y. Gui, K. Tian, J. Liu, L. Yang, H. Zhang and Y. Wang, J. Hazard. Mater., 2019, 380, 120876 CrossRef CAS PubMed .
  20. Z. Zhang, M. haq, Z. Wen, Z. Ye and L. Zhu, Appl. Surf. Sci., 2018, 434, 891–897 CrossRef CAS .
  21. G. Li, H. Zhang, L. Meng, Z. Sun, Z. Chen, X. Huang and Y. Qin, Sci. Bull., 2020, 65, 1650–1658 CrossRef CAS PubMed .
  22. H. Yuan, S. A. A. A. Aljneibi, J. Yuan, Y. Wang, H. Liu, J. Fang, C. Tang, X. Yan, H. Cai, Y. Gu, S. J. Pennycook, J. Tao and D. Zhao, Adv. Mater., 2019, 31, 1807161 CrossRef PubMed .
  23. K.-R. Park, R. N. Kim, Y. Song, J. Kwon and H. Choi, Materials, 2022, 15, 399 CrossRef CAS PubMed .
  24. I. Kortidis, H. C. Swart, S. S. Ray and D. E. Motaung, Results Phys., 2019, 12, 2189–2201 CrossRef .
  25. W. Yang, L. Feng, S. He, L. Liu and S. Liu, ACS Appl. Mater. Interfaces, 2018, 10, 27131–27140 CrossRef CAS PubMed .
  26. Y. Masuda, Sens. Actuators, B, 2022, 364, 131876 CrossRef CAS .
  27. H. Park, J.-H. Kim, D. Vivod, S. Kim, A. Mirzaei, D. Zahn, C. Park, S. S. Kim and M. Halik, Nano Today, 2021, 40, 101265 CrossRef CAS .
  28. Y. Liu, X. Li, Y. Wang, X. Li, P. Cheng, Y. Zhao, F. Dang and Y. Zhang, Sens. Actuators, B, 2020, 319, 128299 CrossRef CAS .
  29. B. Feng, Y. Wu, Y. Ren, Y. Chen, K. Yuan, Y. Deng and J. Wei, Sens. Actuators, B, 2022, 356, 131358 CrossRef CAS .
  30. L. Li, X. Yin, S. Liu, Y. Wang, L. Chen and T. Wang, Electrochem. Commun., 2010, 12, 1383–1386 CrossRef CAS .
  31. L. Guo, Z. Shen, C. Ma, C. Ma, J. Wang and T. Yuan, J. Alloys Compd., 2022, 906, 164375 CrossRef CAS .
  32. D. Xue, Z. Zhang and Y. Wang, Mater. Chem. Phys., 2019, 237, 121864 CrossRef CAS .
  33. W. Jiang, Y. Pang, L. Gu, Y. Yao, Q. Su, W. Ji and C.-T. Au, J. Catal., 2017, 349, 183–196 CrossRef CAS .
  34. W. Liu, X. Si, Z. Chen, L. Xu, J. Guo, L. Wei, G. Cheng and Z. Du, J. Alloys Compd., 2022, 919, 165788 CrossRef CAS .
  35. J.-H. Lee, Sens. Actuators, B, 2009, 140, 319–336 CrossRef CAS .
  36. C.-L. Zhu, H.-L. Yu, Y. Zhang, T.-S. Wang, Q.-Y. Ouyang, L.-H. Qi, Y.-J. Chen and X.-Y. Xue, ACS Appl. Mater. Interfaces, 2012, 4, 665–671 CrossRef CAS PubMed .
  37. Y.-F. Sun, S.-B. Liu, F.-L. Meng, J.-Y. Liu, Z. Jin, L.-T. Kong and J.-H. Liu, Sensors, 2012, 12, 2610–2631 CrossRef CAS PubMed .
  38. A. Dey, Mater. Sci. Eng.: B, 2018, 229, 206–217 CrossRef CAS .
  39. L. Bizhou, F. Jia, B. Lv, Z. Qin, P. Liu and Y. Chen, Mater. Res. Bull., 2018, 106, 403–408 CrossRef .
  40. C. Li, P. G. Choi and Y. Masuda, J. Hazard. Mater., 2023, 455, 131592 CrossRef CAS PubMed .
  41. H. Ji, W. Zeng and Y. Li, Nanoscale, 2019, 11, 22664–22684 RSC .
  42. J.-Y. Kim, J.-H. Lee, J.-H. Kim, A. Mirzaei, H. Woo Kim and S. S. Kim, Sens. Actuators, B, 2019, 299, 126965 CrossRef CAS .
  43. S. Mohammad-Yousefi, S. Rahbarpour and H. Ghafoorifard, Mater. Chem. Phys., 2019, 227, 148–156 CrossRef CAS .
  44. E. A. Nunes Simonetti, T. Cardoso de Oliveira, Á. Enrico do Carmo Machado, A. A. Coutinho Silva, A. Silva dos Santos and L. de Simone Cividanes, Ceram. Int., 2021, 47, 17844–17876 CrossRef CAS .
  45. L.-Y. Zhu, L.-X. Ou, L.-W. Mao, X.-Y. Wu, Y.-P. Liu and H.-L. Lu, Nano-Micro Lett., 2023, 15, 89 CrossRef CAS PubMed .
  46. R. Makole, Z. P. Tshabalala, H. C. Swart, L. Coetsee-Hugo, N. Leshabane and D. E. Motaung, Mater. Today Commun., 2024, 38, 108426 CrossRef CAS .

Footnote

Electronic supplementary information (ESI) available: SAED analysis results of the SnO2–Au 0.5 wt%. (Fig. S1); H2S gas sensing characteristics of SnO2–Au hollow nanostructures with different Au contents ratios. (Fig. S2) Gas sensing characteristics of SnO2–Au 0.5 wt% gas sensor to H2S gas in the range from 500 ppb to 10 ppm with different operating temperature. (Fig. S3) Band diagram of the SnO2–Au 0.5 wt% gas sensor. (Fig. S4); Sensitivity stability over 15 cycles of H2S measurement tests. (Fig. S5) Mixed gas sensing performance of the SnO2–Au 0.5 wt% gas sensor. (Fig. S6) Schematic of the gas sensing systems. (Fig. S7) Performance comparison data of the SnO2-based H2S gas sensors. (Table S1) A showcase of handheld device with its structure. (Movie S1) A working scenario of the handheld food freshness device. (Movie S2). See DOI: https://doi.org/10.1039/d4tc02901a

This journal is © The Royal Society of Chemistry 2024