A self-powered humidity sensor for respiratory monitoring and energy harvesting

Abstract

The application provides a self-driven humidity sensor for breath monitoring and energy collection, which utilizes 1-butyl-3-methylimidazolium chloride modified halloysite nanotubes HNTs to significantly enhance the surface hydrophilicity and ionic conductivity, adopts a concave structure with patterned copper and aluminum electrodes to facilitate uniform film deposition and efficient interface charge transfer, and optimizes the sensor to realize an output voltage of 510 mV in a wide humidity range, with a response speed being 4 times that of pure HNTs, and voltage amplification is realized through series connection; by utilizing the high sensitivity and fast dynamic response characteristics, the sensor can accurately distinguish various human breath patterns and detect simulated apnea events, in combination with a machine learning classifier, the sensor realizes high-precision automated breath monitoring, and simultaneously has non-contact sensing and energy collection capabilities.

Description

Technical Field

[0001] This invention relates to the field of humidity sensor technology, and more specifically to a self-driven humidity sensor for respiratory monitoring and energy harvesting. Background Technology

[0002] Humidity sensors are crucial for monitoring environmental moisture and are widely used in industrial, agricultural, and everyday applications. Their role is particularly significant in healthcare: by detecting changes in humidity in exhaled breath, they enable non-invasive, real-time tracking of physiological states. Respiratory rate and pattern are key vital signs, and abnormalities can serve as early indicators of conditions such as sleep apnea, chronic obstructive pulmonary disease (COPD), or cardiac arrest. The near-saturated humidity of exhaled breath provides a convenient and non-invasive signal source for monitoring respiratory activity. While flexible electronics offer promise for wearable health monitoring, most existing systems still rely on external power sources, complicating integration, compromising wearability, and impacting comfort. Self-powered circuitry sensors, capable of directly harnessing energy from the human body or environment, offer a novel approach to wearable health monitoring platforms.

[0003] Various self-powered mechanisms have been explored for humidity sensing, including triboelectric, piezoelectric, and ion diffusion effects. However, these methods often have limitations, such as reliance on mechanical activation, slow response speed, or limited output stability. Recently, electrochemical humidity (ECH) sensors based on battery-like structures have emerged as a promising alternative, capable of generating voltage without external bias by utilizing humidity-dependent redox reactions. Despite some advancements in existing technologies, the widespread application of ECH sensors has been hampered by a trade-off between output performance and response speed, often limited by insufficient ionic conductivity in the sensing layer or slow water adsorption-desorption kinetics.

[0004] To address these challenges, researchers have explored various functional nanomaterials to enhance the performance of ECH sensors. Among them, halloysite nanotubes (HNTs) have attracted considerable attention due to their abundant natural reserves, high specific surface area, and rich hydrophilic groups, showing potential as humidity-sensitive materials. Previous studies have shown that HNT-based composites can significantly improve the humidity detection range and response characteristics of ECH sensors. However, the inherent ion transport and water absorption properties of unmodified HNTs are still insufficient to support the rapid and stable signal acquisition required for real-time respiratory monitoring. Summary of the Invention

[0005] This invention proposes a self-driven humidity sensor for respiratory monitoring and energy harvesting, based on ionic liquid (IL)-functionalized halloysite nanotubes (HNTs), wherein the HNTs are modified with 1-butyl-3-methylimidazolium chloride ([BMIM]Cl) to enhance hydrophilicity and ionic conductivity. Unlike conventional planar device structures, the concave structure design with patterned copper and aluminum electrodes creates a unique geometry that enables uniform thin-film coating, enhanced interfacial contact, and efficient charge transport. Benefiting from this unique architecture, the resulting sensor exhibits a wide detection range (11-98% RH), a high output voltage of 510 mV, and fast response / recovery times (4 s and 5 s, respectively), making it suitable for real-time respiratory pattern recognition.

[0006] Specifically, in a first aspect, the present invention provides a self-driven humidity sensor for respiratory monitoring and energy harvesting, comprising:

[0007] An insulating substrate with grooves;

[0008] Copper and aluminum electrodes are disposed on both sides of the groove;

[0009] And a humidity-sensitive material layer that fills the groove and covers part of the copper and aluminum electrodes, the humidity-sensitive material layer being coated with an ionic liquid-modified halloysite nanotube composite material.

[0010] Furthermore, the ionic liquid is 1-butyl-3-methylimidazolium chloride.

[0011] Furthermore, in the ionic liquid-modified halloysite nanotube composite material, the mass fraction of 1-butyl-3-methylimidazolium chloride is 5%-15%.

[0012] Furthermore, the distance between the copper electrode and the aluminum electrode is 800-900 μm.

[0013] Furthermore, the thickness of the moisture-sensitive material layer film is formed into a uniform film by controlling the concentration of the composite material solution and the coating amount. The concentration of the composite material solution is 50 mg / mL, and the coating amount is 10 μL.

[0014] Furthermore, the output voltage generated by the humidity-sensitive material layer at 98% relative humidity is 510mV.

[0015] Furthermore, the self-driven humidity sensor allows the hydrogen evolution reaction and oxygen reduction reaction to occur simultaneously at the cathode.

[0016] Furthermore, multiple self-driven humidity sensors are connected in series to amplify the output voltage.

[0017] Secondly, the aforementioned self-driven humidity sensor is used in respiratory monitoring devices. The self-driven humidity sensor is integrated into a mask or face shield to monitor different breathing patterns of the human body in real time, identify sleep apnea events, and make physiological state judgments.

[0018] Thirdly, the aforementioned self-driven humidity sensor is used in human-computer interaction devices. The self-driven humidity sensor realizes voice recognition, non-contact switch control, and coded communication functions by detecting changes in the humidity field.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1) The self-driven humidity sensor device features an innovative structure, using a concave structure for the first time. Existing technologies all use planar structures, which make it difficult to control the electrode spacing. Planar structures are also prone to solution leakage when sensitive materials are added, and their electrode-material interface mainly relies on two-dimensional planar contact, resulting in relatively low charge transfer efficiency. This invention is the first to fabricate a concave device structure, which allows for controllable electrode spacing and prevents leakage of sensitive materials, thus facilitating uniform thin film deposition and efficient interface charge transfer.

[0021] 2) This invention employs a direct physical blending method to prepare 1-butyl-3-methylimidazolium chloride-functionalized HNTs composite materials. The method is simple, easy to operate, low in cost, and can be mass-produced. Moreover, characterization data confirms that 1-butyl-3-methylimidazolium chloride not only adsorbs onto the surface of HNTs, but its cations and anions also embed into the interlayer of HNTs through electrostatic interactions, resulting in a 0.12° low-angle shift of the (001) crystal plane in the XRD pattern, an increase in interlayer spacing, and the formation of a stable organic-inorganic hybrid structure.

[0022] 3) Traditional self-driven humidity sensors typically have long response times, ranging from tens of seconds to hundreds of seconds, which is not conducive to human respiration detection. By modifying HNTs with 1-butyl-3-methylimidazolium chloride, their surface hydrophilicity and ionic conductivity are significantly enhanced, reducing the sensor response time to as short as 4 seconds. Utilizing its high sensitivity and rapid dynamic response characteristics, the sensor can accurately distinguish various human breathing patterns (normal, rapid, deep, and shortness of breath) and detect simulated apnea events.

[0023] 4) This invention conducted specific experiments for each potential reaction to verify that the reaction occurring at the cathode of the electrochemical self-driven humidity sensor is a simultaneous hydrogen evolution reaction and oxygen reduction reaction. Attached Figure Description

[0024] Figure 1(a) is a schematic diagram of the fabrication of the self-powered humidity sensor; (b) is a SEM image of the H@Cl-2 sample; (c) is a TEM image; (d) is a comparison of the water contact angles of HNTs and H@Cl-2 samples; (e) is the XRD pattern of HNTs and H@Cl-2 samples; (f) is the corresponding magnified local pattern; and (g) is the FTIR spectrum of HNTs and different H@Cl-based samples.

[0025] Figure 2 The sensing performance of the self-powered humidity sensor is shown in the following figures: (a) is a schematic diagram of the concave planar sensor structure; (b)-(e) are the dynamic voltage response curves of HNTs, H@Cl-1, H@Cl-2 and H@Cl-3 base sensors in the range of 11% to 98% relative humidity, respectively; (f) is a comparison of the steady-state voltage response of different sensors; (g) is the linear fit of the output voltage of H@Cl-2 sensor with respect to relative humidity (33-98% RH); (h) is the voltage output of H@Cl-2 sensor at 23% RH; and (i) is the response and recovery time of H@Cl-2 sensor at 98% RH.

[0026] Figure 3 This document provides a comprehensive characterization of the H@Cl-2 self-powered humidity sensor. The results include: (a) cyclic stability testing over 30 cycles at 75% RH; (b) long-term voltage stability testing over 20 hours at 75% RH; (c) gas selectivity testing for common interfering gases (200 ppm); (d) external load characteristics of the sensor at 98% RH; (e) the relationship between output power and load resistance; (f) performance testing of multiple sensors connected in series; (g) charging test using four sensors connected in series with different capacitors; (h) cyclic charge-discharge stability testing using a 22μF capacitor; and (i) a demonstration of the self-powered sensor illuminating a red LED.

[0027] Figure 4 For mechanism research and experimental verification, (ab) shows the sensor voltage output using symmetrical electrodes (Cu-Cu and Al-Al), (c) shows the polarity reversal test, (d) shows a schematic diagram of the sensing mechanism of the self-driven humidity sensor, (e) shows the Nyquist plot under different humidity levels, (f) shows the response of the hydrogen sensor during gas enrichment in a sealed chamber containing multiple sensors, (g) shows the dynamic response cycle of the sensor in 97.3% RH humid air (with O2) and pure N2 (without O2) environments, and (h) shows a comparison of steady-state output voltage under aerobic and anaerobic conditions at 97.3% RH.

[0028] Figure 5This is a multimodal human physiological sensing application of a self-powered humidity sensor. Among them, (a) is a schematic diagram of the application scenario of the self-powered humidity sensor, (b) is the real-time detection of different breathing modes, (c) is the monitoring of rapid breathing, (d) is a schematic diagram illustrating the working principle of the classification learner, (e) is the prediction accuracy of different algorithms for classifying multiple breathing modes, (f) is the prediction result obtained from the random forest algorithm, (g) is the identification of simulated sleep apnea events, (h) is the response to continuous coughing events, (i) is the syllable recognition capability, (j) is the finger distance detection, and (k) is the Morse code communication demonstration.

[0029] Figure 6 (a) is a photograph of the original HNTs suspension, and (b) is a photograph of the H@Cl-2 suspension;

[0030] Figure 7 SEM images of HNTs samples;

[0031] Figure 8 TEM images and corresponding elemental mapping diagrams of the H@Cl-2 sample;

[0032] Figure 9 The response and recovery times of HNTs sensors at 98% RH;

[0033] Figure 10 This is a schematic diagram of how to amplify the output voltage by connecting multiple sensors in series. Detailed Implementation

[0034] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0035] Example 1: Experimental Section

[0036] 1. Materials

[0037] Halloysite nanotubes (HNTs) were purchased from Guangzhou Runwo Materials Technology Co., Ltd. 1-Butyl-3-methylimidazolium chloride [BMIM]Cl was purchased from Maclean Biochemical Co., Ltd. Aluminum foil tape with a thickness of 0.06 mm and copper foil tape with a thickness of 0.06 mm were purchased from Shenzhen Wangxing Tape Co., Ltd.

[0038] 2. Preparation of H@Cl-based composite materials

[0039] Ionic liquid-modified HNTs composites were prepared by physical blending. The detailed experimental steps are as follows: First, a predetermined amount of HNTs powder was dispersed in deionized water to obtain a homogeneous HNTs suspension. Then, 0, 0.5, 1.0, and 1.5 mL of 1 mg / mL 1-butyl-3-methylimidazolium chloride [BMIM]Cl aqueous solution were added to the dispersion. The mixture was magnetically stirred for 30 minutes to ensure that the ionic liquid was fully modified onto the HNTs surface. Finally, a series of composite materials with [BMIM]Cl mass fractions of 0%, 5%, 10%, and 15% were obtained, and named HNTs, H@Cl-1, H@Cl-2, and H@Cl-3 composite materials, respectively. The synthesis parameters of the different [BMIM]Cl-modified HNTs sensitive materials are summarized in Table 1.

[0040] Table 1

[0041]

[0042] The concentration of [BMIM]Cl solution in Table 1 is 10 mg / mL.

[0043] 3. Preparation of a self-powered humidity sensor

[0044] The structure of the self-driven humidity sensor for respiratory monitoring and energy harvesting of the present invention is as follows: Figure 1 As shown in (a), it includes:

[0045] An insulating substrate with grooves;

[0046] Copper and aluminum electrodes are disposed on both sides of the groove;

[0047] And a moisture-sensitive material layer that fills the groove and covers part of the copper and aluminum electrodes.

[0048] The humidity-sensitive material layer is coated with halloysite nanotube composite material modified with ionic liquid; the ionic liquid is 1-butyl-3-methylimidazolium chloride; in the halloysite nanotube composite material modified with ionic liquid, the mass fraction of 1-butyl-3-methylimidazolium chloride is 5%-15%.

[0049] The thickness of the humidity-sensitive material film is achieved by controlling the concentration of the composite material solution and the coating amount to form a uniform film. The concentration of the composite material solution is 50 mg / mL and the coating amount is 10 μL. The output voltage generated by the humidity-sensitive material layer at 98% relative humidity is 510 mV.

[0050] The detailed production process is as follows:

[0051] First, a 15mm × 1mm × 1mm groove was formed in the center of a 20mm × 10mm × 2mm glass substrate using laser processing. Then, copper and aluminum strips were attached to opposite sides of the groove as the anode and cathode, respectively. The distance between the copper and aluminum electrodes was maintained at 800-900μm. Finally, a mixed solution (50mg / mL) of 10μL of HNTs and various H@Cl solutions was uniformly dropped into the groove between the copper and aluminum strips, and the mixture was dried in an infrared drying oven for 30 minutes to complete the fabrication of the self-powered humidity sensor.

[0052] 4. Characterization and Humidity Sensing Performance Testing

[0053] The microstructure and morphology of the humidity-sensitive material were characterized using field emission scanning electron microscopy (SEM, Zeiss Sigma 300) and transmission electron microscopy (TEM, FEITecnai G2 F20). Crystal structure was determined by X-ray diffraction (XRD, RigakuSmartLab S). Furthermore, surface wettability was assessed by measuring the water contact angle using an optical contact angle meter (ThetaFlex). Chemical functional groups were analyzed using Fourier transform infrared spectroscopy (FTIR, ThermoScientific Nicolet iS20).

[0054] A humidity testing platform was established based on the saturated salt solution method, where various saturated salt solutions provided a relative humidity (RH) range of 11%–98% in a closed environment. A high-precision digital multimeter (Keithley DMM 6500) was used to monitor the sensor's voltage response signal under different humidity conditions in real time. During the test, measurements were taken at 11% RH as a baseline, followed by measurements at 33%, 43%, 59%, 75%, and 98% RH to systematically evaluate the humidity sensing performance. Table 2 shows the relative humidity of the environment surrounding different saturated salt solutions.

[0055] Table 2

[0056]

[0057] Example 2: Results and Discussion

[0058] 1. Structural Analysis

[0059] First, the successful preparation of the H@Cl-based composite material was demonstrated by observing changes in the dispersion characteristics of the solution. For example... Figure 6As shown, (a) is a photograph of the original HNTs suspension, and (b) is a photograph of the H@Cl-2 suspension. The original HNTs remained well suspended for more than six hours, while the [BMIM]Cl-functionalized HNTs settled rapidly. This significant difference stems from the strong electrostatic interaction between the ionic liquid and the nanotubes. HNTs possess the characteristic of having a positively charged inner wall and a negatively charged outer wall. During the functionalization of HNTs with ionic liquids, [BMIM] dissociates from [BMIM]Cl... + Cations and Cl - Anions can generate a strong Coulombic attraction with oppositely charged sites on HNTs. This efficient electrostatic adsorption not only explains the observed aggregation behavior but also confirms the formation of a stable organic-inorganic hybrid structure, laying a solid foundation for enhancing humidity sensing performance.

[0060] Figure 7 SEM images of the original HNTs are shown, revealing a typical nanotube morphology. SEM images of the H@Cl-2 sample after modification with [BMIM]Cl are also shown. Figure 1 (b) showed no significant changes, indicating that the introduction of [BMIM]Cl did not disrupt the basic nanotube structure of HNTs. This was confirmed by TEM images ( Figure 1 Further observations in (c) revealed that HNTs possess a distinct hollow structure with clear contrast between light and dark regions, and the estimated lumen size is approximately 20 nm. Furthermore, the elemental distribution results ( Figure 8 The results showed that Al, Si, and O elements were uniformly distributed on the nanotubes, and N and Cl elements derived from the ionic liquid [BMIM]Cl were also detected. This confirms that the ionic liquid has been successfully modified onto the HNT surface. Surface wettability was characterized by water contact angle measurements. Figure 1 As shown in (d), the contact angle decreased from 17.5° for the original HNTs to 7.9° for the H@Cl-2 sample, indicating that the hydrophilicity was enhanced after ionic liquid modification. Figure 1 (e) shows the XRD patterns of the HNTs and H@Cl-2 samples. The characteristic diffraction peaks observed at 2θ = 12.20°, 19.94°, 24.73°, 35.05°, 38.29°, 54.52°, and 62.34° correspond to the (001), (100), (002), (110), (003), (210), and (300) crystal planes of HNTs, respectively. Notably, compared to HNTs, the (001) diffraction peak of the H@Cl-2 sample shifted to a lower angle by 0.12°, which is attributed to the [BMIM]Cl ionic liquid embedding into the interlayer space of HNTs, resulting in an increase in the (001) interlayer spacing. The corresponding magnified local image (( Figure 1The peak shift is clearly shown in (f). At the same time, the introduction of ionic liquid significantly enhances the hygroscopicity of the sample, resulting in a sharper (002) diffraction peak for H@Cl-2 than that for HNTs. Figure 1 (g) shows the FTIR spectra of HNTs and various H@Cl-based composites. In the spectrum of HNTs, 3694 cm⁻¹ -1 and 3622 cm -1 The absorption peaks at 1095 cm⁻¹ are attributed to the stretching vibrations of the inner surface hydroxyl groups and the structural hydroxyl groups (located between the silicon-oxygen tetrahedron and the aluminum-oxygen octahedron), respectively. -1 and 1033 cm -1 The strong absorption bands at 912 cm⁻¹ correspond to the stretching vibrations of the Si-O and Si-O-Si bonds, respectively, while the bands at 912 cm⁻¹... -1 The absorption band at 3153 cm⁻¹ is attributed to the bending vibration of Al-OH. With increasing amounts of ionic liquid introduced, the spectrum of H@Cl⁻ ...� at 3153 cm⁻¹... -1 An absorption peak is observed at 2965 cm⁻¹, originating from the C–H stretching vibration of the imidazole ring. -1 and 2873 cm -1 The peaks at 1569 cm⁻¹ represent the asymmetric and symmetric stretching vibrations of the methyl group, respectively. -1 The absorption at 1164 cm⁻¹ is attributed to the C=C stretching vibration of the imidazole ring. -1 The peak at this point corresponds to the CN stretching vibration within the ring. Furthermore, after introducing [BMIM]Cl, the peak at 3429 cm⁻¹... -1 A broad peak appeared nearby, with its intensity increasing significantly with increasing ionic liquid content. This peak is attributed to the OH stretching vibration of water molecules absorbed by [BMIM]Cl. These results confirm that the ionic liquid has been successfully loaded onto HNTs.

[0061] 2. Performance of the self-powered humidity sensor

[0062] Figure 2 (a) illustrates the unique concave planar structure of the proposed self-powered humidity sensor, which comprises copper and aluminum electrodes and an H@Cl-based composite material deposited within the cavity. This structural design facilitates efficient interfacial contact between the electrodes and the humidity-sensitive material. The humidity-sensing properties of the self-powered sensors functionalized with different [BMIM]Cl concentrations (0–15 wt%) were systematically evaluated using a saturated salt solution platform calibrated at 25°C. Figure 2 As shown in (b)-(e), the dynamic voltage response of each sensor was recorded over a wide relative humidity range (11-98% RH). Figure 2As shown in (b), the devices based on the original HNTs exhibited limited voltage output, remaining close to baseline levels (close to 1.8 mV) even at up to 59% RH, reflecting the inherent low humidity sensitivity and slow proton transport of unmodified HNTs. The introduction of [BMIM]Cl significantly enhanced the electrical output, with H@Cl-1 (5 wt% IL), H@Cl-2 (10 wt% IL), and H@Cl-3 (15 wt% IL) devices exhibiting progressively improved performance. Notably, the H@Cl-2 sensor achieved a maximum output voltage of approximately 510 mV at 98% RH, a significant improvement compared to the unmodified HNTs devices ( Figure 2 Significant progress has been made in (d). This enhancement is attributed to the synergistic effect of [BMIM]Cl, which not only improves surface hydrophilicity but also promotes ion transport. Comparative analysis of steady-state voltage response ( Figure 2 (f) further shows that the H@Cl-2 sensor exhibits the most linear behavior (R) in the 33-98% RH range. 2 =0.98, Figure 2 (g) This is crucial for the practical application of humidity sensors. Although the H@Cl-3 device exhibits a slightly higher voltage output under high humidity conditions, it shows signs of response saturation, likely due to excessive moisture absorption. With its optimal combination of high sensitivity, wide dynamic range, and excellent linearity, the H@Cl-2 sensor was selected as the best sensor for subsequent system testing. Figure 2 The (h) figure shows the real-time voltage response of the H@Cl-2 sensor when switching from 11% RH to 23% RH. A significant voltage output of approximately 4.6 mV was observed at 23% RH, confirming the sensor's effective operation over a wide humidity range from 11% to 98% RH. The sensor's dynamic response and recovery characteristics were further investigated at 98% RH, such as... Figure 2 As shown in (i), this sensor exhibits fast response and recovery times, with a response time of 4 s and a recovery time of 5 s, which is significantly shorter than the 19 s response time of the original HNTs-based sensor. Figure 9 This fast response characteristic is significantly competitive compared to existing self-powered humidity sensors.

[0063] Repeatability is a key parameter for practical sensor applications, and it was evaluated by performing 30 consecutive cycles of testing at 75% RH. Figure 3 (a)). The sensor exhibits excellent repeatability with a relative standard deviation (RSD) of 4.87%, indicating high reliability and stability of its electrical output. Long-term stability was investigated by monitoring the voltage output for over 20 hours at 75% RH. Figure 3(b)). The sensor maintained a stable output voltage of approximately 0.41 V for the first 10 hours, demonstrating robust short-term performance. Although a gradual drop in voltage to approximately 0.34 V was observed over the subsequent 10 hours, the sensor retained substantial output functionality, indicating acceptable operational durability over longer periods. Figure 3 (c) shows the voltage response of the H@Cl-2 sensor to 200 ppm of common interfering gases. Clearly, low voltage output is observed for other gases, which can be attributed to the unique mechanism of the self-driven humidity sensor, relying on a humidity-induced electrochemical reaction. Its power generation capability was evaluated by examining the sensor's performance at 98% RH under different external load resistances. Figure 3 (d) As the load resistance increases, the output voltage rises accordingly, while the current decreases. The corresponding output power reaches its maximum value of approximately 0.27 μW at the optimal load resistance of 200 kΩ. Figure 3 (e)).

[0064] This invention connects multiple self-driven humidity sensors in series to amplify the output voltage, such as... Figure 3 As shown in (f), the output voltage increases linearly with the number of series-connected devices, with the combined voltage of the five units being approximately 2.5 V. This result highlights the direct scalability of the sensor system, making it suitable for applications requiring higher output potentials. The superior humidity-driven power generation capability of the H@Cl-2 sensor offers great potential for practical applications, especially in self-powered systems. To demonstrate this potential, a simple energy harvesting and utilization device was constructed. Four H@Cl-2 sensor units were connected in series to amplify the output voltage, which was then used to charge a capacitor. The stored energy could then be released to power a small light-emitting diode (LED). The charging performance of this series array was evaluated at 98% RH using capacitors of varying capacitances (0.22, 22, 47, 100, 220, and 470 μF). The corresponding charging curves are shown in Figure 1. Figure 3 As shown in (g), a clear dependence of charging time on capacitor size is evident. As expected, smaller capacitors charge faster. Furthermore, the reliability of this energy storage process was verified through cyclic charge-discharge tests using a 22 μF capacitor. Figure 3 (h)). The sensor array exhibits excellent cycling stability with minimal performance fluctuations and a very low relative standard deviation (RSD) of only 0.48% over multiple cycles. Notably, the energy stored in a fully charged 22 μF capacitor is sufficient to instantaneously light up a commercially available red LED, such as... Figure 3 The photograph in (i) is shown. This demonstration verifies the feasibility of the self-powered H@Cl-2 humidity sensor in practical applications, including energy harvesting and powering low-power electronic devices.

[0065] 3. Sensing mechanism of self-powered humidity sensor

[0066] The main working principle of the self-driven humidity sensor is based on an electrochemical (galvanic cell) reaction. To this end, this invention prepares a control device with symmetrical electrodes. The device has two identical copper (Cu) electrodes ( Figure 4 (a) or a device with two aluminum (Al) electrodes Figure 4 (b) shows the lowest voltage output. The Al-Al electrode pair shows a slightly higher voltage output and a noisier baseline, attributed to the more active nature of aluminum. These results confirm that the voltage output of a self-driven humidity sensor requires two different metals. This was further validated by a polarity reversal test. Figure 4 (c)). After swapping the connection between the multimeter probe and the sensor terminal, the measured output voltage sign is reversed, which is a clear characteristic of the behavior of a galvanic cell. Figure 4 (d) is a schematic diagram of the sensing mechanism of the self-driven humidity sensor. Under low humidity conditions, only a few water molecules are adsorbed on the sensor surface, dissociating into a limited number of hydrogen ions (H+). + ) and hydroxide ions (OH) - Low ion concentration results in minimal voltage output, keeping the sensor off. As humidity increases, more water molecules are adsorbed and dissociated, while chloride ions (Cl- ions) from the ionic liquid 1-butyl-3-methylimidazolium chloride ([BMIM]Cl) are released. - The charge dissociates and participates in ion transport. The resulting increase in overall ionic conductivity promotes efficient charge transfer, enabling vigorous redox reactions to occur on the electrodes and generate a high output voltage, thereby switching the sensor to the on state.

[0067] To further investigate the electrical behavior of the sensor under different humidity levels, impedance spectroscopy analysis was performed. Nyquist plot ( Figure 4 (e) shows that the semicircle diameter decreases with increasing humidity, indicating enhanced ion conduction. The elongated tail at high humidity indicates that more ions are involved in the conduction process, which is consistent with the self-powered sensing mechanism.

[0068] Regarding electrochemical reactions, it is generally believed that aluminum acts as the anode, releasing electrons to form Al. 3+ Ions (Al → Al) 3+ +3e - However, for a precise cathode reaction (at the copper electrode), there are currently two main possible reaction pathways:

[0069] (i) Hydrogen evolution reaction (HER), in which protons from dissociated water accept electrons to form hydrogen gas (2H+). + + 2e - → H2),

[0070] (ii) Oxygen reduction reaction (ORR), in which dissolved oxygen is reduced in the presence of water (O2 + 2H2O + 4e-). - →4OH - ).

[0071] To resolve the ambiguity of this mechanism, this invention conducted specific experiments for each potential reaction. To confirm the HER, twelve self-powered humidity sensors were enclosed in a sealed chamber to accumulate the gas produced during the humidity-generating process. The atmosphere in the sealed chamber was monitored using a commercially available hydrogen sensor at different enrichment times (5, 30, and 55 minutes). Figure 4 As shown in (f), the response of the hydrogen sensor gradually increases with enrichment time, providing direct evidence for H2 generation and validating the HER pathway. To assess the involvement of oxygen, a dynamic testing platform was constructed. Dry air (containing O2) and pure nitrogen (without O2) were used as carrier gases, and a 97.3% RH environment was achieved through bubbling. The sensor's voltage output differed significantly under the two conditions: 0.518V in the presence of O2 and 0.489V in its absence. This confirms that ORR also participates in the cathode process, although its contribution is relatively small. Figure 4 (g)(h)). In summary, the operating mechanism is clearly described: the device operates as a humidity-activated galvanic cell. Humidity controls ion conduction within the [BMIM]Cl-modified HNT layer, thereby regulating the electrochemical reaction rate.

[0072] At the cathode, a mixed chemical reaction occurs, involving the coexistence of hydrogen evolution reaction and oxygen reduction reaction. In the self-driven humidity sensor of the present invention, the hydrogen evolution reaction and oxygen reduction reaction occur simultaneously at the cathode. This explanation of the dual-cathode approach advances the understanding of the mechanism of self-powered electrochemical humidity sensors and provides key experimental support for their future development.

[0073] Example 3: Utilizing the fast response and high output voltage of the self-powered humidity sensor of the present invention, the present invention demonstrates its multifunctional capabilities in physiological monitoring, non-contact sensing, and human-computer interaction. Figure 5 (a) schematically illustrates an application scenario for a self-driven humidity sensor. The sensor is initially integrated into a face mask for respiratory monitoring. For example... Figure 5 As shown in (b), it can clearly distinguish between slow, normal, and rapid breathing patterns, with the signal frequency gradually increasing and the amplitude decreasing accordingly. The sensor also successfully tracked pathologically high respiratory rates, accurately capturing breathing patterns exceeding 70 breaths per minute. Figure 5 (c) demonstrates its ability to monitor severe lung conditions.

[0074] To demonstrate the potential of sensors in intelligent diagnostics, a machine learning framework was integrated for automated respiratory pattern classification. For example... Figure 5 As shown in (d), the workflow includes feature extraction from raw sensor signals, supervised model training, and rigorous cross-validation. To validate this approach, ten volunteers were recruited. Each volunteer performed four different breathing patterns: slow, normal, fast, and rapid (extremely fast) breathing. Each volunteer performed ten trials in each pattern, resulting in a dataset of 400 samples (10 volunteers × 4 patterns × 10 trials). The voltage-time data from each 30-second sensor trial was used as the input feature vector for the classifier. This invention uses three different algorithms (Support Vector Machine (SVM), Random Forest (RF), and Linear Discriminant Analysis (LDA)) to train and evaluate classification performance. A 10-fold cross-validation method was used to split the dataset to ensure robustness and prevent overfitting. Validation results are summarized in... Figure 5 (e). The Random Forest (RF) algorithm demonstrated superior performance, achieving a significant prediction accuracy of 96.25% in distinguishing four breathing patterns. Figure 5 (f)). SVM and LDA also showed good accuracy, confirming the high quality and uniqueness of the features extracted by the sensor. These results clearly demonstrate that the self-powered humidity sensor signal of the present invention contains rich, algorithmically distinguishable information, enabling high-precision automated identification of complex physiological states.

[0075] Furthermore, the sensor reliably identified simulated apnea events, showing no response during the 15-second breath-hold period, while maintaining normal detection before and after this interval. Figure 5 (g) This confirms its potential in monitoring sleep apnea. In addition to breathing patterns, the sensor can also effectively characterize coughing events. Figure 5 The (h) data shows that the sensor's response amplitude increased significantly with consecutive coughs (single, double, and triple), which is attributed to the accumulated moisture generated during coughing.

[0076] The application of sensors can also be extended to voice and contactless interaction. In syllable recognition tests ( Figure 5 (i)), different signal peaks precisely correspond to the number of syllables in spoken words ("a", "china", "banana"). Furthermore, this sensor also has significant applications in non-contact sensing, where a finger can be brought close to the sensor (i). Figure 5The sensor (j) is used as a non-contact switch, where the response intensity varies inversely with the distance (2-8 mm) between the finger and the sensor, demonstrating the sensor's high spatial resolution in micro-humidity fields. Finally, this invention implements a Morse code communication system by encoding short and long exhalations as dots and dashes. The sensor successfully decoded the breathing pattern corresponding to the number "119" (j). Figure 5 (k) demonstrates its potential as an alternative to human-machine interfaces. These comprehensive demonstrations highlight the versatility of sensors in medical and health monitoring and interactive technology applications.

[0077] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A self-driven humidity sensor for respiratory monitoring and energy harvesting, characterized in that, include: An insulating substrate with grooves; Copper and aluminum electrodes are disposed on both sides of the groove; And a humidity-sensitive material layer that fills the groove and covers part of the copper electrode and aluminum electrode, wherein the humidity-sensitive material layer is an halloysite nanotube composite material modified by ionic liquid, which is an organic-inorganic hybrid composite material formed by 1-butyl-3-methylimidazolium chloride being embedded between halloysite nanotube layers through electrostatic interaction. The self-driven humidity sensor undergoes hydrogen evolution and oxygen reduction reactions simultaneously at the cathode, resulting in a higher output voltage in an oxygen-rich environment compared to an oxygen-free environment.

2. The self-driven humidity sensor according to claim 1, characterized in that, In the ionic liquid-modified halloysite nanotube composite material, the mass fraction of 1-butyl-3-methylimidazolium chloride is 5%-15%.

3. The self-driven humidity sensor according to claim 1, characterized in that, The distance between the copper electrode and the aluminum electrode is 800-900 μm.

4. The self-driven humidity sensor according to claim 1, characterized in that, The thickness of the humidity-sensitive material layer film is formed by controlling the concentration of the composite material solution and the coating amount to form a uniform film. The concentration of the ionic liquid-modified halloysite nanotube composite material solution is 50 mg / mL, and the coating amount is 10 μL.

5. The self-driven humidity sensor according to claim 1, characterized in that, The humidity-sensitive material layer generates an output voltage of 510mV at 98% relative humidity.

6. The self-driven humidity sensor according to claim 1, characterized in that, The self-driven humidity sensor has a detection range of 11-98% RH, an output voltage of 510mV, and response and recovery times of 4s and 5s, respectively.

7. The self-driven humidity sensor according to claim 1, characterized in that, The output voltage is amplified by connecting multiple self-driven humidity sensors in series.

8. The application of the self-driven humidity sensor according to any one of claims 1-7 in a respiratory monitoring device, characterized in that, The self-driven humidity sensor is integrated into a mask or face shield to monitor different breathing patterns in real time, identify sleep apnea events, and assess physiological state.

9. The application of the self-driven humidity sensor according to any one of claims 1-7 in a human-computer interaction device, characterized in that, The self-driven humidity sensor achieves voice recognition, non-contact switch control, and coded communication functions by detecting changes in the humidity field.

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