Breathing is a rhythmic activity of the human body, and its frequency and strength depend on the level of the body’s activity. The main purpose of breathing is to provide oxygen to the body and remove carbon dioxide^[1,2]. The humidity, concentration, flow rate, and pressure of breathing are important indicators for disease diagnosis, treatment and prognosis evaluation, as well as pulmonary function projects in medicine and other fields^[3-5]. Wearable devices such as wearable humidity sensors, can easily conform to and integrate with human skin, machines, and other curved surfaces, which enable rapid, continuous, and noninvasive capture of the breathing state^[6-10].

At present, the research on flexible humidity sensors mainly focuses on resistive and capacitive types^[11-15]. Among them, the resistive humidity sensors have widely been studied due to their simple fabrication and easy integration. The resistive humidity sensors display a resistance-change signal when the sensing material interacts with water molecules^[13,16]. Various moisture-sensitive materials have been explored to date, such as graphene oxide (GO)^[17], carbon nanotubes^[18], two-dimensional materials^[19], and porous membranes^[16]. For example, Xuet al.^[20] reported a humidity sensor based on supramolecular graphene modified with sodium naphthalene-1-sulfonate and silver nanoparticles. Their sensor has a high sensitivity to humidity and a fast response and recovery time (≤1 s). However, GO prepared by Hummer's method requires strong acid-corrosion resistance and a complex modification process, which greatly increases the cost and power consumption of the sensor. A recent humidity sensor based on a two-dimensional MoS₂ field-effect transistor requires a high gate operating voltage (80 V) and a complex preparation process; therefore, this sensor also increases the power consumption and incurs a high manufacturing cost^[21]. Although these materials have interesting structural and electronic properties, high sensitivity, and fast response time, their production costs remain excessively high and the fabrication processes are complex. Therefore, high-performance humidity sensors fabricated from cheap materials through simple processes are in great demand.

BiOBr is one of the important bismuth oxide halide compounds. It is a ternary V–VI–VII semiconductor compound with tetragonal crystal structure. The layered structure of BiOBr is composed of tetragonal [Bi₂O₂]²⁺ plates sandwiched between two Br ion plates. This inherent layered structure gives these materials fascinating optical, mechanical and electrical properties. At the same time, BiOBr can be prepared by various methods, such as hydrothermal^[22], liquid-phase exfoliation^[23], self-sacrifice template^[24], which is considered to be an efficient material in a wide range of application. Here, we report a single-crystal BiOBr nanostructures synthesized using sonochemical methods under mild conditions. This method is simple and the reaction is completed at room temperature. Additionally, the synthesized BiOBr nanosheets have excellent humidity-sensing performance and ultrahigh selectivity. The fabricated humidity sensor based on BiOBr delivered a high humidity sensitivity (I_g/I₀ = 550%) from 40% to 100% RH and response/recovery time: 11 and 6 s, respectively, and showed an excellent humidity selectivity of BiOBr. The sensor can also detect the respiratory rate and gas volume of the human body. The prepared face masks have a large-scale application in the diagnosis of pulmonary function.

The raw materials of the pure metals bismuth (Bi, 99.99%, ≥150 mesh) powder and hydrogen peroxide (H₂O₂, 30%) are commercially available and were obtained from Sigma-Aldrich. The hydrobromic acid (HBr) was purchased from Sinopharm Chemical Reagent Co., Ltd. Home-made deionized water (DI H₂O) was used for all experiments.

Fig. 1 shows the preparation of BiOBr nanostructures from the source material (Bi powder) via the sonochemical strategy under environmental conditions. In a typical experiment, 1 mmol Bi powder was added into the mixture solution with 5 mL H₂O₂ and 10 mL H₂O to form the suspension solution by stirring at a speed of 400 r/min. Then, 1 mL 1 M HBr was added into the suspension solution, and followed ultrasonic treatment at a frequency of 40 kHz for 2 h. The resultant products were collected by centrifugation and washed with H₂O for three times. Finally, the precipitate was dried under ambient conditions.

A 60 nm Au interdigital pattern was first deposited on the PET substrate by photolithography and thermal evaporation, and a flexible interdigital electrode was prepared, as shown inFigs. 2(a)–2(e). The prepared BiOBr was then dispersed in ethanol solution by ultrasound, and the prepared BiOBr ethanol solution was spin coated on the electrode at 300 r/min. Finally, the equipment was baked on a hot plate at 80 °C for 10 min to add BiOBr materials and electrodes.

Powder X-ray diffraction (XRD, D8 Advance, Bruker, Germany) was utilized to evaluate the phase compositions under Cu Kα X-ray radiation (λ = 1.5406 Å). The microstructure and morphology of as-prepared samples were observed under a field emission scanning electron microscope (FESEM, S-4800, Hitachi, Japan) and high-resolution transmission electron microscopy (HRTEM, JEM-2100F, JEOL, Japan) equipped with energy dispersive X-ray spectroscopy (EDX, Quantax-STEM, Bruker, Germany). The compositions and valence band of the product were analyzed by X-ray photoelectron spectroscopy (XPS, Scientific K-Alpha, Thermo, USA), with a reference of C 1s peak at 284.6 eV. The photoluminescence was tested on a spectrometer (Fluromax-4P, Horiba Jobin Yvon, France) that was excited at 350 nm.

The successful preparation of BiOBr was characterized through SEM, X-ray diffraction, TEM, IR, and XPS. Panels a and b ofFig. 3 displays SEM images of the Bi powder and BiOBr nanostructures, respectively. As shown in the images, the sonochemical strategy successfully incorporated the Bi powder into BiOBr nanosheets. After a statistical analysis of the particles in the SEM images, the approximate size range of the synthesized BiOBr nanostructures was determined as 0.5–1.5μm (seeFig. 3(b), an enlarged view ofFig. 3(c)). The X-ray diffraction pattern of BiOBr (Fig. 3(d)) is consistent with JCPDS card No. 09-0393. The Raman spectrum of the BiOBr nanosheets is shown inFig. 3(e). The spectral peaks at 57.4, 90.6, 112.1, and 160.5 cm^–1 excited by 532 nm light were assigned to BiOBr. Furthermore, square nanostructures were observed in the TEM images. The HRTEM images (Fig. 3(f)) displayed clear lattice fringes with an interplanar spacing of 0.28 nm, corresponding to the (110) plane of BiOBr.

The elemental valence states and chemical compositions on the surfaces of the BiOBr nanosheets were analyzed using XPS. The measured XPS spectra (Fig. 4(a)) confirm the presence of only Bi, O, and Br elements in both samples. The peaks located at 159.1 and 164.4 eV in the Bi 3b spectrum of the BiOBr nanosheets (Fig. 4(b)) correspond to Bi 4f 5/2 and Bi 4f 7/2, respectively. Furthermore, the spin-orbit splitting energy between these two peaks is 5.3 eV, which indicates that normal Bi³⁺ resided on the nanosheet surfaces. However, the overall spectral distribution of the nanosheets shifted toward higher binding energies than those of pure Bi, indicating a high oxidation state of Bi in the nanosheets. According to previous studies, new peaks appear when the binding energies of 160.1 and 165.4 eV are raised by the higher valence of Bi5⁺. The peaks at 69.2 and 70.6 eV inFig. 4(c) correspond to Br 3d_5/2 and Br 3d_3/2, respectively. The O1s spectrum of the BiOBr sample (Fig. 4(d)) is broad and asymmetric and could be fitted to two peaks. The peaks appearing at high and low binding energies were assigned to surface-adsorbed oxygen and lattice oxygen components in the sample, respectively.

A BiOBr-based flexible humidity sensor was fabricated and its performance was characterized at 40% RH and 25 °C (Fig. 5(a)).Fig. 5(b) plots the sensitivities of the BiOBr humidity sensor as functions of time at different RH (0%–100%). The relative current of the sensor decreased over the humidity range 0%–30% and increased over the humidity range 50%–100% because our test was performed in an air environment with 40% RH. The humidity-dependent relative current variations of the sensor are clarified inFig. 5(c). As the humidity increased from 0% to 100% RH, the relative current of the sensor increased to 1200%. This indicates that our sensor is highly sensitive to humidity.

In addition, the response and recovery time are important parameters of a humidity sensor in practical applications such as respiratory monitoring. In this work, we measured the time required for the sensor to reach equilibrium (95% of the maximum change) between 40% and 90% RH. During the measurement, the resistance change was measured while alternately moving the sensor between two humidity environments. The response and recovery time of the sensor were 10 and 6 s, respectively (Fig. 5(d)). We also characterized the cyclic stability of the device (Fig. 5(e)). When the humidity changed repeatedly between 40% and 90% RH, the response signal of the sensor fluctuated only slightly, indicating strong cycle performance and stability. Moreover, during respiration detection, the humidity sensor is directly interfered with by gas, so high selectivity for humidity is essential. The electrical response of the humidity sensor in the atmosphere of ethanol, acetone and ammonia gas. During the test, the relative humidity of the environment is controlled to be 40% and the gas concentration is 100 ppm. The test results are shown inFig. 5(f). It can be seen that when the humidity sensor works at room temperature, its relative current basically does not change in the presence of ethanol, acetone, and ammonia. This indicates that the humidity sensor can be used as a highly selective humidity sensor.

Given the excellent humidity performance and fast response time of the humidity sensor, we incorporated the sensor into an intelligent mask that detects human respiration in real time. As shown inFigs. 6(a) and6(b), our smart mask is composed of sensors installed in a breathing valve. When the mask is worn, the user’s breathing is detected in a relatively closed space. As the current of the sensor increases or decreases with each breath, we can monitor the changing intensity and frequency of the respiration by monitoring the magnitude and number of peaks, respectively.Fig. 6(c) compares the relative current changes of the sensor during deep and normal breathing. The intensity was much higher during deep breathing than during normal breathing. This implies that the sensor can detect the vital capacity. Additionally, the current of the smart mask increased and decreased in synchrony with the breathing pattern, so the changes in respiratory rate can be monitored through the number of peaks. As shown inFigs. 6(d)–6(f), our smart mask can monitor breathing at different frequencies (slow, normal, and fast) in real time. These results show that our intelligent mask can measure the respiratory status of the human body and help medical diagnoses of lung disease.

We have developed a high-performance flexible humidity sensor that is based on a sensitive material composed of BiOBr single-crystal biological nanostructured nanosheets. The material is prepared using a simple, low-cost sonochemical method suitable for large-scale production and demonstrates excellent humidity properties, with a humidity sensitivity of 550% (I_g/I₀) from 40% to 100% RH, response and recovery time 11 and 6 s, respectively, and excellent selectivity for humidity. In experimental demonstrations, the sensor successfully detected human respiration patterns. This cost-effective flexible humidity sensor has potential applications in the diagnosis and treatment of respiratory diseases; for instance, as a wearable respiratory monitoring device for infection reduction and health monitoring.