A flexible bifunctional colorimetric gas sensor patch and a preparation method and application thereof

Abstract

The application discloses a flexible wearable bifunctional colorimetric gas sensor patch as well as a preparation method and application thereof, and belongs to the field of sensors. The bifunctional colorimetric gas sensor patch uses thymol blue and hydroxylamine sulfate as response materials, and is designed as a high-sensitivity, low-cost and wide-range sensor, which can simultaneously detect acetone gas in a range of 1-40 ppm and HCl gas in a range of 100-900 ppm. The color data collected by the sensor can be converted into gas concentration by using a deep neural network, so that the precise gas concentration detection function is realized, and real-time gas leakage monitoring and early warning can be realized on a site such as a chemical working site.

Description

Technical Field

[0001] This invention relates to the field of sensor technology, and more specifically to a flexible dual-function colorimetric gas sensor patch, its preparation method, and its application. Background Technology

[0002] With the continuous development of industry, the scale and production efficiency of chemical enterprises have improved. Many raw materials and finished products in the chemical industry are toxic, flammable, and explosive substances, and the production process involves numerous hazardous factors and poses significant risks. Therefore, due to equipment defects, management negligence, and improper operation, a high risk of accidents may occur. Once hazardous chemicals leak during production and storage, human life and the ecological environment will be threatened. Acetone is one of the common volatile organic compounds (VOCs) in industry, mainly used as a solvent in explosives, rubber, leather, paints, and other chemicals. Specifically, acetone is a hazardous chemical substance with toxic, flammable, and explosive properties. When the temperature exceeds its flash point of -20°C, a concentration of 2.5%-12.8% in air can easily cause an explosion or flash fire. Its vapor can affect the central nervous system, causing symptoms such as fatigue, dizziness, nausea, and vomiting; in severe cases, it may lead to convulsions and coma. Long-term exposure can also irritate the skin and respiratory tract, leading to health problems such as dermatitis, pharyngitis, and bronchitis. Because acetone is stored in industrial tanks, it poses a high risk of fire and explosion. Therefore, risk assessments of acetone leaks and their consequences in chemical plants, including leak source identification, leak volume prediction, and analysis of their environmental and human impacts, are of practical significance. Hydrogen chloride (HCl) gas is strictly regulated in many countries and regions worldwide due to its significant hazards. Major sources include the complete combustion of halogenated polymers, plant burning, emissions from absorption towers in semiconductor plants, and acid rain. According to safety standards, the tolerable safe exposure threshold for hydrogen chloride gas is 10 ppm. Even short-term exposure to a concentration of 35 ppm is sufficient to cause discomfort such as throat irritation. Exposure to concentrations in the 50-100 ppm range may be intolerable, leading to more severe respiratory discomfort and damage. Exposure to concentrations of 1300-2000 ppm can be fatal. Based on these hazards, monitoring of hydrogen chloride gas, especially at the ppm level, becomes particularly important.

[0003] Currently, various methods have been proposed for the detection of acetone and HCl gases, including gas chromatography, colorimetric sensors, resistive sensors, mid-infrared spectroscopy, plasma-assisted catalytic emission sensors, and fiber optic sensors. However, due to high cost, time-consuming procedures, lack of portability, or relatively low sensitivity, these technologies are not suitable for real-time and online monitoring. Among numerous gas detection methods, colorimetric sensors have gradually become one of the ideal gas detection devices due to their low cost, portability, and ease of fabrication. Because of their simple structure, colorimetric sensors do not require complex equipment support, facilitate rapid detection in different environments, and are low-cost, making them suitable for on-site and real-time monitoring. Donghyun Kim et al. developed an ion-pair dye with multichromatic behavior for a carbonyl-selective colorimetric sensor. This sensor can generate multiple color patterns under the influence of different carbonyl substances through different reactions of a single dye, thus achieving simple and effective analysis. So Hee Nah et al. developed a sensor array based on dye-doped photonic crystals, aiming to enhance the colorimetric detection of volatile organic compounds (VOCs). Wonhyeong Jang et al. developed a decoder for on-site monitoring of acid vapor—MOF-808-EDTA-Cu. By combining MOF-808 with Cu-EDTA, a proton-triggered colorimetric decoder is formed, which can effectively convert the anionic components of corrosive acids into visible colors, thereby enabling real-time monitoring and decoding of acid vapor.

[0004] In recent years, the demand for real-time gas monitoring in the industrial sector has been growing. To meet this demand, the combination of deep learning algorithms and sensor technology has formed a complete monitoring system. Summary of the Invention

[0005] In view of this, the present invention provides a flexible dual-function colorimetric gas sensor patch, its preparation method, and its application. The present invention utilizes thymol blue and hydroxylamine sulfate as response materials to design a highly sensitive, low-cost, and wide-range sensor capable of simultaneously detecting acetone gas in the range of 1-40 ppm and HCl gas in the range of 100-900 ppm. By employing a deep neural network, the color data collected by the sensor can be converted into gas concentration, achieving accurate gas concentration detection and enabling real-time gas leak monitoring and early warning in locations such as chemical plants.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A flexible wearable dual-function colorimetric gas sensor patch includes: a dual-function sensor, a hydrogen chloride sensor, a support layer, and an adhesive layer;

[0008] The dual-function sensor is disc-shaped, and the hydrogen chloride sensor is ring-shaped.

[0009] The diameter of the dual-function sensor is smaller than the inner diameter of the hydrogen chloride sensor, and the hydrogen chloride sensor is sleeved on the outside of the dual-function sensor, with the bottoms of both on the same plane.

[0010] The support layer is disposed below the dual-function sensor and the hydrogen chloride sensor;

[0011] The adhesive layer is disposed below the support layer.

[0012] Preferably, the dual-function sensor has a diameter of 6 mm and a thickness of 0.26 mm.

[0013] Preferably, the hydrogen chloride sensor has an inner diameter of 7 mm and an outer diameter of 8 mm.

[0014] Another object of the present invention is to provide a method for preparing the above-mentioned flexible wearable dual-function colorimetric gas sensor patch, comprising the following steps:

[0015] (1) Add deionized water and methanol to both beakers. Add hydroxylamine sulfate and thymol blue to one beaker, which is labeled beaker A. Add only thymol blue to the other beaker, which is labeled beaker B. Stir at room temperature until completely dissolved to form an indicator solution.

[0016] (2) Cut a filter paper disc, and use a pipette to draw the indicator solution in beaker A and drop it onto the surface of the filter paper disc to obtain a dual-function sensor for later use;

[0017] (3) Use a pipette to draw the indicator solution from beaker B and drop it onto the filter paper ring. Let it dry naturally at room temperature to obtain a hydrogen chloride sensor for later use.

[0018] (4) Add silica gel to beaker C and stir with a glass rod for 5 minutes to make the solution uniform. Place the back of the dual-function sensor and the hydrogen chloride sensor on a glass slide and pour on the silica gel. Use a spin coater to make the silica gel plane uniform in thickness. Mold in a drying oven. Take out the molded sensor and put it into a laser printer. Cut it according to the outer ring to obtain the molded sensor patch.

[0019] Preferably, in step (1), the methanol is AR grade with a purity of ≥99.5%, and the volume ratio of deionized water to methanol is 9:1.

[0020] Preferably, the amount of hydroxylamine sulfate in beaker A is 0-1.5 mmol, and the amount of thymol blue is 0-0.02 mmol; the amount of thymol blue in beaker B is 0-0.02 mmol.

[0021] Preferably, the stirring time in step (1) is 2 hours and the stirring speed is 200-400 rpm.

[0022] Preferably, the volume of liquid aspirated by the pipette in steps (2) and (3) is 5 μL;

[0023] In step (4), the drying temperature of the drying oven is 60℃ and the drying time is 2h.

[0024] Another object of the present invention is to provide the application of the sensor patch prepared by the above-mentioned flexible wearable dual-function colorimetric gas sensor patch in the detection of acetone and HCl gas leaks.

[0025] Specifically, the sensor patch is attached to workers' clothing, storage rooms, and transportation pipelines for visual leak detection. The specific detection method includes: the sensor has a dual-zone differential detection structure, with the outer ring selectively responding to HCl and the inner ring responding synergistically to both HCl and acetone. In a mixed gas environment, the HCl concentration is first calculated based on the color difference before and after the outer ring changes color, using a calibration curve. Then, based on the nonlinear coupling effect of the inner ring's color change on HCl and acetone, the HCl response value calculated by the outer ring is subtracted from the color difference of the inner ring in the mixed gas, thus establishing a nonlinear decoupling model of the multi-factor sensor. The color difference values ​​of the inner ring and outer ring are used as inputs to calculate and output the acetone concentration, thereby eliminating interactive interference and achieving simultaneous quantitative detection of hydrogen chloride and acetone. The detection range is: acetone gas 1-40ppm, HCl gas 100-900ppm.

[0026] As can be seen from the above technical solution, compared with the prior art, the present invention has the following beneficial effects:

[0027] The sensor of this invention exhibits excellent performance in the quantitative analysis of acetone and HCl gases. For acetone gas, it can accurately detect within a concentration range of 1-40 ppm with a response time of 110 seconds; while for HCl gas, it can detect within a concentration range of 100-900 ppm with a response time of 32 seconds.

[0028] The sensor of this invention exhibits extremely high selectivity and strong adaptability to changes in temperature and humidity, with changes in temperature and humidity having little impact on its detection results.

[0029] The sensor of this invention has excellent stability and can be stored continuously for up to 13 days under normal conditions without affecting its performance.

[0030] The sensor developed using this invention, combined with a host computer module, enables real-time monitoring of acetone and HCl gases in the environment, thereby effectively assessing the safety status of the environment and providing reliable technical support for safety management and early warning. The sensor's high sensitivity, wide detection range, and low cost make it a promising candidate for applications in environmental monitoring, industrial safety, and other fields. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0032] Figure 1 (a) Flowchart of sensor fabrication; (b) Flowchart of colorimetric sensing system monitoring.

[0033] Figure 2 (a) Physical image of the color-changing sensor disc; (b) Characterization of the color-changing sensor disc; (c) Schematic diagram of the reaction mechanism of acetone and HAS; (d) Schematic diagram of the color-changing mechanism of the sensor disc; (e) ΔE sensing response values ​​of 5 ppm acetone and 300 ppm HCl at different TB contents; (f) ΔE sensing response values ​​of 5 ppm acetone and 900 ppm HCl at different HAS contents.

[0034] Figure 3 (a) Physical image of the sensor changing color in 1-60 ppm acetone gas; (b) ΔE response value of the sensor in 1-60 ppm acetone gas; (c) ΔE response fitting curve of the sensor; (d) Dynamic response curve of the sensor in 5, 10, 15 and 20 ppm acetone gas; (e) Selectivity test of sensor mixture, with acetone, NO2, CO2, CH4, H2 and H2S injected sequentially; (f) Sensor response value under different humidity conditions in acetone gas; (g) Consistency test of color change response of different batches of sensors when the acetone concentration is 10 ppm.

[0035] Figure 4(a) Physical image of the sensor changing color in HCl gas at 300-1300 ppm; (b) ΔE response value of the sensor in HCl gas at 1-100 ppm; (c) ΔE response value of the sensor in HCl gas at 100-1300 ppm; (d) Fitting curve of the sensor in HCl gas at 100-900 ppm; (e) Dynamic response curve of the sensor in HCl gas at 300, 500, 700 and 900 ppm; (f) Response value of the sensor in HCl gas at different humidity levels; (g) Consistency test of color change response of different batches of sensors at 900 ppm HCl concentration.

[0036] Figure 5 (a) Real-time monitoring of the sensor via a colorimetric sensing system; (b) Predicted acetone concentration; (c) Predicted HCl concentration; (d) Schematic diagram of the sensor structure; (e) Diagram of dual-gas identification test; (f) Physical test diagram of sensor application in the wearable field.

[0037] Figure 6 (a) Comparison of responses between filter paper substrate and non-woven fabric substrate; (b) Effects of NO2, H2S, H2, CH4 and CO2 gases on sensor color response; (c) Color changes under different humidity levels. Figure 1 (d) Consistency testing of different sensors Figure 1 (e) Color changes under different humidity levels Figure 2 (f) Consistency testing of different sensors Figure 2 (g) Response test graphs under different temperature conditions; (h) Stability test graphs. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Example 1

[0040] Material selection

[0041] Thymol Blue (TB, ACS grade), Hydroxylamine Sulfate (HAS, ACS grade), Methanol (CH3OH, ≥99.5%), Smooth-On Ecoflex TM Silica gel (00-30), deionized water, thymol blue, hydroxylamine sulfate, and methanol were purchased from Shanghai Aladdin Biochemical Technology Co., Ltd. Non-woven fabric and filter paper were purchased from Zhejiang Jin Sanfa Group Co., Ltd. EcoflexTM The silicone was purchased from Beijing Tiantong Huayi Landscape Co., Ltd.

[0042] Sensor fabrication

[0043] First, add 18 mL of deionized water and 2 mL of methanol solution to two 50 mL beakers (A and B). Add hydroxylamine sulfate (0-1.5 mmol) and thymol blue (0-0.02 mmol) to beaker A, and add only thymol blue to beaker B. Stir each beaker at room temperature for 2 hours until completely dissolved to form an indicator solution. Then, cut one piece each of filter paper and non-woven fabric with a diameter of 6 mm and a thickness of 0.26 mm (non-woven fabric as a control). Use a pipette to drop 5 μL of the indicator solution from beaker A onto the surface of the filter paper and non-woven fabric, respectively. Finally, allow both moistened sensors to air dry at room temperature. Next, use a pipette to drop 5 μL of the indicator solution containing only thymol blue onto a filter paper ring with an inner diameter of 7 mm and an outer diameter of 8 mm, and allow it to air dry at room temperature. Add silica gel to beaker C and stir with a glass rod for 5 minutes to ensure a homogeneous solution. Place the disc and the back of the ring onto a glass slide, then pour silica gel on top and use a spin coater to ensure a uniform thickness. Place the slide in a 60°C oven for 2 hours to allow it to solidify. Remove the solidified sensor and place it in a laser printer. Cut along the outer ring to obtain the final sensor. Figure 1 As shown in (a).

[0044] Colorimetric testing

[0045] To systematically evaluate the performance of the colorimetric sensor in gas detection, this invention employs an image-based gas reaction detection system for testing. This system includes a sealed gas chamber with an internal volume of 900 mL, at the bottom of which a colorimetric gas sensor is integrated. Illumination sources are evenly distributed around the inner wall of the chamber to shield against potential interference from ambient light variations on image acquisition accuracy, ensuring consistent experimental conditions and reliable data. For gas concentration control, a precise gas flow control device was used to accurately control the concentrations of acetone and hydrogen chloride (HCl) gases within the chamber. During the experiment, a Logitech C1000S camera, combined with a color analysis algorithm, was used to extract and analyze color feature information from the sensor's sensing area in real time, detecting the current gas concentration and displaying it on a smart terminal. The sensor and camera were maintained at a distance of 10 cm to ensure image clarity and color accuracy. Figure 1 As shown in (b).

[0046] To simplify the image analysis process, image thresholding segmentation technology in the preprocessing stage effectively removes background information from non-sensor areas in the image, significantly improving the specificity and accuracy of color analysis. The CIE Lab color space recommended by the International Commission on Illumination (CIE) and its derived CIE DE2000 color difference calculation method were also adopted. ΔE, as the sensor's response output value, shows a high correlation with changes in gas concentration; therefore, ΔE can be considered an indicator of the colorimetric sensor's response intensity to acetone and hydrogen chloride, enabling quantitative assessment of gas concentration.

[0047] To achieve real-time monitoring of gas concentration changes within a gas chamber, a colorimetric sensing system monitoring interface was developed based on the Qt platform. The interface is divided into four parts: the first part displays the current sensor color in real-time, based on the camera's image; the second part performs image segmentation to extract the sensor from the background, improving color recognition accuracy; the third part performs concentration prediction, matching the acquired color data to output the current gas concentration value; and the fourth part displays a gas concentration change line graph, showing the gas concentration value output in the third part. This interface can continuously invoke algorithms for analysis and display gas concentration changes in real-time as a line graph. This real-time monitoring effectively detects gas concentration changes and provides data support for subsequent optimization and applications.

[0048] Material characterization and sensing mechanisms

[0049] like Figure 2 As shown in (a), this is a physical image of the sensor. Based on this, to further investigate its microstructural changes, the filter paper surface was characterized using scanning electron microscopy (SEM), as shown below. Figure 2 As shown in (b), the results revealed significant roughness and irregular microstructure on the treated filter paper surface. Compared to the original filter paper, treatment with thymol blue (TB) and hydroxylamine sulfate (HAS) solutions resulted in a marked structural change in the filter paper surface, specifically manifested as an uneven distribution of micron-sized particles. The particle packing density varied across different regions, with some areas exhibiting dense particle packing and others relatively loose packing. These particles were irregularly distributed on the filter paper fibers, with localized particle aggregation forming a relatively rough surface texture. The combined effect of particle packing and fiber interweaving created a high degree of microscopic inhomogeneity on the surface, significantly increasing the specific surface area of ​​the filter paper and thus enhancing its interaction with the external environment.

[0050] For the quantitative detection of acetone and HCl gas content, the sensing mechanism of acetone and HCl is explained below to ensure rapid and accurate detection of the target gases. Figure 2As shown in (c), acetone reacts with hydroxylamine sulfate to produce acetone oxime and sulfuric acid as byproducts. A key feature of this reaction is the release of sulfuric acid, which significantly lowers the pH of the reaction system, thereby triggering the subsequent optical response process. In this system, thymol blue is used as a pH-sensitive indicator. The thymol blue molecule contains multiple proton-acceptable sites, especially the phenolic hydroxyl and sulfonic acid groups, which can accept protons (H+) under different pH conditions. + This results in changes in structural configuration.

[0051] Specifically, under neutral conditions, thymol blue exists primarily in a deprotonated form, at which point the molecule appears yellow. However, as the pH of the system decreases to the acidic range, the concentration of hydrogen ions in the environment increases significantly, and thymol blue gradually undergoes a protonation reaction. The protonation process alters its intramolecular conjugated structure, thereby changing the molecule's absorption characteristics for visible light. With increasing protonation, the sensor exhibits a color change from yellow to pink. This change is as follows: Figure 2 As shown in (d), the transition of thymol blue from a neutral state to an acidic state is demonstrated, thereby providing a visual indication of changes in an acidic environment.

[0052] Besides the acetone reaction, the introduction of HCl gas also lowers the ambient pH, causing thymol blue to undergo a protonation reaction, thus changing the sensor color from yellow to pink. Figure 2 d). However, it is worth noting that sulfuric acid in this system is generated directly on the filter paper substrate, which gives the sensor an extremely low detection limit for acetone. In contrast, HCl gas is dispersed in the gas chamber and acts on the sensor surface; the sensor needs to absorb more HCl gas to achieve a significant color change.

[0053] Optimization of sensor conditions

[0054] To achieve a low-cost sensor with high sensitivity, low detection limit, and wide detection range for acetone and HCl gases, the effects of different concentrations of TB and HAS on sensor performance were investigated. Figure 2As shown in (e), the effect of different concentrations of TB (0, 0.005, 0.008, 0.01, 0.015, 0.02 mmol) on the color change of the sensor was tested. The experimental results showed that when the TB concentration was 0 mmol, the sensor did not show any color change in response to acetone and HCl. Color change occurred as the TB concentration increased. When the concentration was 0.01 mmol, the sensor had the largest response value (ΔE) to acetone. When the concentration was greater than 0.01 mmol, ΔE showed a decreasing trend. When the TB concentration was less than 0.01 mmol, there were not enough TB ​​molecules to fully express the pH change caused by the reaction between hydroxylamine sulfate and acetone gas. This made the sensor itself weak in sensing performance and ultimately showed a low ΔE value.

[0055] However, when the TB concentration exceeds 0.01 mmol, the sulfuric acid produced by the reaction is insufficient to cause color change in all TB molecules. For HCl gas, ΔE gradually increases with increasing TB content. When the TB concentration reaches 0.01, 0.015, and 0.02 mmol, the ΔE difference becomes relatively small and falls within the error range. Considering all these factors, this work selects 0.01 mmol of TB as one of the standards for sensor preparation.

[0056] The effects of different concentrations of HAS (0, 0.3, 0.6, 0.9, 1.2, 1.5 mmol) on the color change of the sensor were tested. Figure 2 As shown in (f), when the HAS content is 0 mmol, the sensor does not respond to acetone. The response value to acetone increases with increasing HAS content, reaching its maximum value at 0.6 mmol HAS. However, when testing the sensor's response to acetone and HCl, further increasing the HAS amount actually leads to a decrease in the ΔE value. This may be because when acetone gas interacts with filter paper loaded with a small amount of HAS, less sulfuric acid is produced, resulting in a less noticeable color change in TB, which weakens the sensor's response to acetone gas. When excessive HAS is added, the unreacted HAS will significantly affect the color difference measurement, causing the ΔE value to show a trend of first increasing and then decreasing. Therefore, in this work, a HAS content of 0.6 mmol was chosen as the standard for sensor preparation. Based on this, the sensitivity of filter paper and non-woven fabric substrates to these two gases was compared, such as... Figure 6 As shown in (a), 5 ppm of acetone gas and 900 ppm of HCl gas were tested. The response value (ΔE) of the filter paper substrate was higher than that of the non-woven fabric substrate, indicating that the filter paper substrate has stronger sensing performance. Therefore, filter paper was selected in this work to prepare a sensor with high sensitivity, low cost and wide detection range.

[0057] Sensor performance testing

[0058] The tests were conducted under experimental conditions of 24±5℃ and 65±4% relative humidity. The sensing performance of acetone gas was first tested. For example... Figure 3 As shown in (a), the color images of the sensor under different concentrations of acetone gas demonstrate the sensor's sensitivity to acetone gas. ΔE (color difference) is an important indicator for quantifying color changes and is commonly used to assess the degree of color difference in visual perception. When ΔE is less than 1.0, the color difference is small, and the color change is almost imperceptible to the naked eye; when ΔE is between 1 and 2, a slight color difference can be detected upon careful observation; and when the ΔE value is greater than 2, the color difference is significant and can be clearly identified by the naked eye. Through repeated tests, the ΔE response curves of the sensor under different acetone gas concentrations were obtained. Figure 3 b).

[0059] The results show that at a concentration of 1 ppm, the sensor's ΔE response value is approximately 1.3, which is within the range that can be detected by the naked eye. Furthermore, the sensor can clearly detect acetone gas in the concentration range of 1-40 ppm, and there is a correlation between the ΔE response value and the acetone concentration. When curve fitting is performed on the response of acetone gas in the concentration range of 0-40 ppm (…), Figure 3 c) exhibits a typical exponential growth pattern.

[0060] Specifically, the sensor's color response initially underwent a rapid change, followed by a gradual plateau. This behavior indicates that the sensor's response to acetone gas is non-linear, stabilizing after an initial rapid change, consistent with an exponential response mode. Furthermore, this work tested the dynamic sensing curves for different concentrations of acetone, such as... Figure 3 As shown in (d), it can be observed that the ΔE value does not change after 110 seconds from the moment the sensor comes into contact with acetone gas, so the response time of the sensor is 110 seconds.

[0061] To further evaluate the gas selectivity of the sensor, the effects of NO2, H2S, H2, CH4, and CO2 gases at concentrations of 5 ppm on the sensor's color response were tested. Figure 6 b). Experimental results show that the ΔE values ​​of these gases are all less than 0.5, having almost no effect on the color change of the sensor. This indicates that the interference from other gases is very limited when the sensor detects acetone. Finally, regarding the response of the mixed gas, 5 ppm of acetone gas was first injected, followed by 5 ppm of NO2, CO2, CH4, H2, and H2S. Figure 3 e). Analysis of the ΔE value change showed that the addition of other gases after the acetone gas reaction did not affect the sensor's color. This result further confirms that the sensor possesses excellent gas selectivity when detecting acetone gas.

[0062] In summary, the sensor of this invention exhibits rapid response and high selectivity to acetone gas, and shows minimal response to other gases in complex gas environments, demonstrating strong practical value. To facilitate application in environments such as chemical plants, this work tested the sensor's sensing capabilities under different humidity levels, such as (…). Figure 3 As shown in f), the ΔE response values ​​at concentrations of 5, 15, 25, and 35 ppm were tested, and physical images at different humidity levels are displayed. Figure 6 c) The response value under low humidity is slightly higher than that under high humidity, but the color difference deviation caused by humidity is within the sensor's test error range. Therefore, humidity has a relatively small impact on the sensor. This may be because the sulfuric acid content generated after the reaction of acetone gas with the sensor is basically the same and directly acts on the filter paper, resulting in a basically consistent color difference value after the sensor changes. This work also tested the ΔE response values ​​of six different sensors under 10ppm acetone gas, such as... Figure 3 As shown in (g), all sensors are at the same level and within the error range, and as can be seen from the physical image, they exhibit the same color change. Figure 6 d) demonstrates that the sensor has excellent consistency.

[0063] In this invention, the sensor's performance in responding to HCl was tested in detail. The experiment evaluated the sensor's color response capability to HCl gas within a concentration range of 0 to 1300 ppm. Figure 4 As shown in (a), the actual color changes of the sensor are illustrated in the range of 300 to 1400 ppm. Color changes and ΔE responses were also analyzed at relatively low concentrations (0 to 200 ppm). Figure 4 (b) The results show that the sensor exhibits a significant color change at an HCl concentration of 300 ppm. At a concentration of 100 ppm, the ΔE value is 1.5. Although the color change is not as pronounced as at higher concentrations, it is still perceptible upon close observation. Therefore, the visual detection limit of the sensor for HCl gas is 100 ppm. Figure 4 (c) This demonstrates the sensor's ΔE response to HCl across the entire concentration range, indicating that the sensor can effectively detect HCl gas from 0 to 900 ppm. The ΔE response maintains a good linear relationship with HCl concentration within the 0 to 900 ppm range, as shown in Figure 1. Figure 4 As shown in (d), this linear relationship helps to accurately identify and distinguish different concentrations of HCl gas, thereby detecting the current HCl concentration. To evaluate the sensor's dynamic response to different concentrations of HCl gas, its sensing performance was tested. Figure 4 e).

[0064] Experiments demonstrate that the sensor reacts rapidly upon contact with HCl gas, exhibiting a rapid color change that stabilizes within approximately 32 seconds, after which the ΔE value remains constant. Therefore, the sensor's response time is 32 seconds. This rapid response characteristic proves its effectiveness in real-time monitoring of HCl gas concentration changes. To meet the application requirements of chemical plants, the sensor's color change and ΔE response under different humidity conditions were studied, such as... Figure 4 As shown in (f), the results indicate that ΔE is slightly higher in low-humidity environments than in high-humidity environments. This may be due to the higher pH value under high-humidity conditions, which affects the sensor's response to HCl. However, at the same concentration, the maximum difference in ΔE between different humidity conditions is only 0.75, which is within the sensor's testing error range. Furthermore, through the physical diagram (…), Figure 6 e) Observations revealed that the color changes were essentially consistent under different humidity levels, indicating that the influence of humidity on the sensor is negligible. Furthermore, this study tested the ΔE response of six different sensors under 900 ppm HCl gas. Figure 4 g). The results show that the ΔE response values ​​of these sensors are all at the same level and within the error range. (Image of the actual device) Figure 6 f) This further confirmed the same color change, demonstrating the sensor's excellent performance in the consistency test. In this work, the sensor's stability was tested. First, as... Figure 6 As shown in (g), the sensor's response was tested under different temperature conditions (15-33℃). Specifically, 5 ppm acetone gas and 900 ppm HCl gas were used for testing. The results show that the sensor's performance remained consistent across different temperatures, demonstrating stable response to both gases, indicating that temperature changes within the normal temperature range (15-33℃) have no impact on the sensor's performance. Furthermore, a two-week long-term stability test was conducted. Figure 6 h). During this process, the sensor was stored in a light-proof, sealed environment to avoid interference from external environmental factors. The ΔE values ​​were measured for 5 ppm acetone gas and 900 ppm HCl gas, respectively, and the results showed that the sensor's response remained stable. As the test continued, the sensor's response performance began to decline until day 13, indicating that the sensor only exhibited a certain degree of performance degradation after reaching a certain usage period. This provides strong support for its reliability in practical applications.

[0065] Algorithm prediction

[0066] In this work, a multilayer perceptron (MLP) was used as the core algorithm to convert the sensor's color data into gas concentration values. For example... Figure 5As shown in (a), image segmentation techniques are first used to extract the sensor region in the gas chamber. Then, the color difference (ΔE) before and after the image color change is calculated using the CIEDE 2000 formula. This ΔE value corresponds to the gas concentration; therefore, the ΔE value and RGB data are used as input features. Next, the ΔE value is mapped to the gas concentration value through a trained MLP model, thereby achieving gas concentration prediction. During training, the dataset is divided into a training set and a validation set (9:1). The training set is used to update model parameters, and the validation set is used to evaluate the model's generalization ability. To prevent overfitting, dropout technology is used to reduce the network's excessive dependence on training data. The dropout rate is set to 0.2, meaning that 20% of neurons are randomly dropped during each training iteration, which helps enhance the model's generalization ability. Furthermore, cross-validation is used to evaluate the model's performance, ensuring consistency and stability across different data partitions, further reducing the risk of overfitting.

[0067] To improve monitoring efficiency, a Qt-based host computer system is used for monitoring. This system integrates algorithms for automatic camera control, image segmentation, color difference calculation, and real-time gas concentration prediction. The system can automatically acquire images of the gas chamber, perform color analysis, and use an MLP model to predict the concentration of acetone or HCl gas in real time. Compared with traditional gas detection methods, this method has advantages in high accuracy, non-invasiveness, and real-time monitoring. Although there are some challenges in terms of lighting changes and model generalization, through image preprocessing and appropriate model training, the system can effectively handle various application scenarios, achieving accurate gas concentration monitoring and is widely applicable to gas detection industries such as chemical plants.

[0068] The MLP algorithm prediction model can efficiently and non-contactly convert sensor color data (color difference ΔE value) into gas concentration values, thereby achieving accurate quantitative assessment of the gas content in the gas chamber. For example... Figure 5As shown in (b), practical tests were conducted on acetone gas, using five different color sensors to evaluate the model's generalization ability and prediction accuracy. Within the 0-40 ppm range, even with very small concentration gradients, acetone gas caused detectable color changes in the sensors, particularly below 10 ppm, where a color change from yellow to pink appeared on the sensor surface. This detectable gradual color difference allowed the MLP to capture subtle changes in the ΔE value and translate them into accurate concentration predictions. The maximum prediction error was 3.4 ppm after testing with five different color sensors. The results indicate that using the MLP algorithm for color difference-concentration mapping can highly sensitively predict low concentrations of acetone gas, thus showing potential applications in low-concentration leak monitoring and trace analysis. In contrast, due to the wider concentration range of HCl gas (0-900 ppm), the color changes in the sensors are not as pronounced as with acetone, and the training set for HCl is less detailed than that for acetone, resulting in larger errors when predicting high concentrations of HCl. Among the five sensors, the maximum error was 79 ppm (e.g., ...). Figure 5 (c) is shown.

[0069] Gas differentiation and application

[0070] This invention relates to a sensor structure based on silicone rubber, with a sensor disc and a sensor ring embedded on its surface. It aims to distinguish between acetone and hydrochloric acid (HCl) gases, while also meeting the needs of wearable applications. Because the filter paper has a microporous structure, the silicone rubber cannot penetrate it, thus not affecting the response of the sensor disc. Figure 5 As shown in (d), the central circular region of the sensor contains HAS, while the outer ring region does not. The difference in the reaction mechanisms of acetone and HCl with the sensor allows for the differentiation of these two gases. The central disc is used to detect the concentration of the two gases, while the outer ring is used to identify the type of gas. Figure 5 As shown in (e), when the sensor is exposed to acetone gas, the central circular region containing HAS changes from yellow to pink, while the outer ring region without HAS shows no color change. Conversely, when the sensor is exposed to HCl gas, both the central circular region and the outer ring region change from yellow to pink. These results demonstrate that the sensor structure can effectively distinguish between acetone and HCl gases based on their different reactivity characteristics, showcasing its broad application potential. Figure 5As shown in (f), the main structure of the sensor uses highly elastic silicone rubber as a substrate. The excellent chemical inertness and mechanical stability of silicone rubber significantly improve the device's anti-interference ability in complex environments. Furthermore, a layer of double-sided tape is adhered beneath the silicone layer, allowing the sensor to be directly attached to the skin or fabric surface for wearable deployment. In the experiment, the device was fixed to the subject's arm and exposed to acetone and HCl gases through the outer layer of clothing. Due to the specific colorimetric response of the sensing layer to these two harmful gases, the device exhibited a significant color change within a very short time, providing a convenient method for real-time, visual monitoring of harmful gases in wearable applications.

[0071] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0072] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for fabricating a flexible, wearable, dual-function colorimetric gas sensor patch, characterized in that, Includes the following steps: (1) Add deionized water and methanol to both beakers. Add hydroxylamine sulfate and thymol blue to one beaker (beaker A) and add only thymol blue to the other beaker (beaker B). Stir at room temperature until completely dissolved to form an indicator solution. The methanol is AR grade with a purity of ≥99.5%, and the volume ratio of deionized water to methanol is 9:

1. The amount of hydroxylamine sulfate in beaker A is 0-1.5 mmol, and the amount of thymol blue is 0-0.02 mmol. The amount of thymol blue in beaker B is 0-0.02 mmol. (2) Cut a filter paper disc, use a pipette to draw 5 μL of indicator solution from beaker A and drop it onto the surface of the filter paper disc to obtain a dual-function sensor for later use; the dual-function sensor has a diameter of 6 mm and a thickness of 0.26 mm; (3) Use a pipette to take 5 μL of indicator solution from beaker B and drop it onto a filter paper ring. Let it dry naturally at room temperature to obtain a hydrogen chloride sensor for later use. The inner diameter of the hydrogen chloride sensor is 7 mm and the outer diameter is 8 mm. (4) Add silica gel to beaker C and stir with a glass rod for 5 min to make the solution uniform. Place the back of the dual-function sensor and the hydrogen chloride sensor on the glass slide and pour on the silica gel. Use a spin coater to make the silica gel plane uniform in thickness. Dry in a 60℃ drying oven for 2 h to form the sensor. Take out the formed sensor and put it into a laser printer. Cut it according to the outer ring to obtain the formed sensor patch. The hydrogen chloride sensor is sleeved outside the dual-function sensor, and the bottoms of both are on the same plane.

2. The method for preparing a flexible wearable dual-function colorimetric gas sensor patch according to claim 1, characterized in that, In step (1), the stirring time is 2 hours and the stirring speed is 200-400 rpm.

3. The application of the sensor patch prepared by the method described in claim 2 in the detection of acetone and HCl gas leaks.

4. The application according to claim 3, characterized in that, Sensor patches are attached to workers' clothing, storage rooms, and transport pipelines for visual leak detection. The specific detection method includes: the sensor has a dual-zone differential detection structure, with the outer ring selectively responding to HCl and the inner ring responding synergistically to both HCl and acetone. In a mixed gas environment, the HCl concentration is first calculated based on the color difference before and after the outer ring changes color, using a calibration curve. Then, based on the nonlinear coupling effect of the inner ring's color change on HCl and acetone, the HCl response value calculated by the outer ring is subtracted from the color difference of the inner ring in the mixed gas, thus establishing a nonlinear decoupling model of the multi-factor sensor. The color difference values ​​of the inner ring and outer ring are used as inputs to calculate and output the acetone concentration, thereby eliminating interactive interference and achieving simultaneous quantitative detection of hydrogen chloride and acetone. The detection range is: acetone gas 1-40 ppm, HCl gas 100-900 ppm.

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