Solution ion luminescence induced by the triboelectric-discharge effect for rapid and intuitive detection of sweat ions

Abstract

Sweat ion detection is a non-invasive health monitoring technique widely used in areas, such as sports monitoring, disease diagnosis, and drug treatment assessment. State-of-the-art technologies, such as ion-selective electrode analysis, chromatography, and spectroscopy, usually rely on specific biomaterials, large equipment, or highly skilled operators, limiting their lifespan and application scenarios. To address these challenges, this work proposed a triboelectric-discharge effect-enabled, visualized sweat ion detection solution with the merits of a simple design, user-friendliness, real-time monitoring, reusability, self-powering, with no need for additional materials. The visible light of ion luminescence with various ionic information can be excited by inducing triboelectric discharge between a metal tip and the sample solution. The species and concentrations of ions were identified by the colors and eigen-peaks of the luminescence. Additionally, the effectiveness of this method was further verified by testing artificial sweat doped with lithium ions and varying concentrations of potassium ions, demonstrating its potential for sweat ion analysis and health assessment in a rapid and intuitive way.

---

Introduction

With societal and technological advancements, human health care has become an area of increasing emphasis. To enhance the effectiveness of health care, physiological signal sensors are extensively studied and applied to monitor signals from various tissues or organs of the human body, such as muscle movement, blood glucose concentration, and neural signal transmission.^1–7 These diverse wearable or implantable sensors, interconnected through wireless networks, amalgamate signals from various body regions into a cohesive whole, playing a pivotal role in disease prevention and monitoring human physiological states, known as the body area network (BAN).^8–13 Among them, sweat is a key biomarker that contains information on electrolyte concentration, metabolites, and other factors, revealing the metabolism, electrolyte balance, and overall health status of the human body.^14–20 Current sweat ion detection solutions, such as ion-selective electrode analysis, chromatography, mass spectrometry, and spectroscopy, require expensive, specialized, and relatively large equipment, along with professional research analysts, making them impractical for portable and real-time sensing.^20–24 Although emerging wearable sweat sensors partially address these challenges, they usually rely on specific biological materials, such as enzymes and ion-selective membranes, limiting their ability to identify a single specific type of ion and reducing their lifespan.^20,25–28 Besides, the sensing results are often presented as non-human-readable signals (currents or voltages), which are unintuitive and require intricate circuit design for decoding.

Triboelectric discharge (TD), an emerging technology for sensing and wirelessly transmitting physical signals in a self-powered manner, offers the benefits of ease of operation, a simple design, with no need for an additional power supply. It has drawn growing interest recently.^29–31 With the coupled mechanism of triboelectrification, electrostatic induction, and breakdown discharge, the energy released during the TD process can generate electromagnetic (EM) waves and optical signals, implying various external environmental factors.^31–41 More importantly, the detailed elements and corresponding energy levels can also be obtained by analyzing the eigen-peaks of the emitted light in real-time, demonstrating a potential intuitive sweat ion detection method. However, previous work on TD mainly focuses on phenomena occurring in gaseous environments, while research on liquid solutions remains largely unexplored.

Therefore, this work proposes a self-powered, miniature solution ion detection (SID) device based on triboelectric discharge between a conductive tip and a conductive liquid solution (TDTS) for real-time, portable, and wireless analysis of sweat ions (Fig. 1). During the TDTS process, optical and EM signals containing various material information of the ion solution are generated and transmitted wirelessly. By analyzing the optical spectrum, typical sweat ion types (Na⁺, K⁺, Li⁺, Ca²⁺) and concentrations can be identified in real time. Furthermore, since the eigen-peaks of these ions are distributed in the visible light band, the emission light displays different colors, enabling solution ion visualization without the requirement of batteries, auxiliary circuits, or sensors. Additionally, this method can be reused without being affected by multiple tests. Practically, the hand-motion-induced TDTS emits discharge-induced light, which can be collected and analyzed by a portable spectrometer to determine the ion types and concentrations in the sweat solution. This TDTS-based method successfully detected sodium and other ions in artificial sweat. In conclusion, this solution enables the visualization of sweat ions and facilitates rapid sweat ion analysis in a self-powered, wireless, intuitive and real-time way, with potential applications in health monitoring, BAN, and material detection.

Fig. 1 The scheme and mechanism of TDTS-SID. (a) Potential demonstration of TDTS-SID, where hand motion-driven ion luminescence contains sweat ion information, which can be received by a portable spectrometer and transformed into a detectable spectrum. (b) Mechanism and working process of ion luminescence in TDTS.

Results and discussions

Mechanism of ion luminescence in TDTS

Similar to the conventional TD between solid tips, the TDTS can also effectively convert the input mechanical energy into an EM wave and optical signal. During the operation of the ion luminescence in TDTS, the metal tip and the conductive ion solution are connected to the two separate electrodes of a triboelectric nanogenerator (TENG). When the two triboelectric layers of the TENG move towards each other, charges with opposite polarities accumulate on the solution droplet and metal tip, respectively, due to the coupling effect of triboelectrification and electrostatic induction. The accumulated charges result in a strong electric field between the metal tip and the solution droplet, with the highest strength around the tip because of its small curvature. Once the electric field strength exceeds the threshold breakdown value, a breakdown discharge occurs between the solution droplet and the metal tip, accompanied by a luminous discharge phenomenon. During this discharge-induced luminescence, the end of the discharge arc near the tip exhibits an optical emission phenomenon similar to that produced by air discharge, while the other end demonstrates an optical emission phenomenon resulting from the ion species present in the solution (Fig. 1b(i)).

Considering the details of this TD process, it can be assumed that the metal electrode is the cathode, and the ion solution is the anode. Under the electric field generated by the TENG, electrons emitted from the cathode and free electrons in the gas are accelerated, collide with the gas molecules in the air, and finally reach the solution. During the collision process, if the kinetic energy of the electron (eEx) of these electrons exceeds the energy required for the transition of the electrons in gas molecules from the initial energy level E₀ to a higher energy level E_m, as given by eqn (1), the electrons are excited from the ground state to an excited state, known as excitation.

eEx > E_m − E₀ = W_e (1)

where W_e is the excitation energy of the corresponding gas molecule, x is the mean free path of the free electron, and E is the electric field intensity. However, gas molecules remain in an excited state for a very short duration (approximately 10⁻⁶ s). Subsequently, the excited electron transitions from the higher energy level (E_m) and falls back to a lower energy state (E₁), emitting optical energy in the form of , as given by eqn (2). The emitted light is shown by the purple region in Fig. 1b(ii) and (iii).where h is Planck's constant, c is the speed of light, and λ is the wavelength of the emitted photon. Thus, the emitted light in the air contains information about the gas molecules. Similarly, when the electrons reach the surface of the ion solution, the accelerated electrons or induced current excite the ions and molecules in the solution. The ions in the solution are excited by collisions. Subsequently, these excited states are relaxed to the ground state, emitting photons of specific wavelengths. This process is shown in Fig. 1b(iv).

The measurement principle of TDTS-SID

To quantitatively observe and analyze this ion luminescence, a fixed experimental platform was designed (Fig. 2a). This platform consists of a sliding freestanding TENG (SFT-TENG), coaxial cable, liquid chamber, black box, optical fiber probes, and spectrometer. The SFT-TENG converts the mechanical input into a high-voltage output with a low current. Through a coaxial cable that effectively improves the interference immunity and decreases the energy loss, two SFT-TENG electrodes connect with a top metal tip and the bottom electrode of the liquid chamber. The liquid chamber is made of black resin with good opaque and insulating properties. After adding the ion solutions, the liquid directly connects with the bottom metal electrode to form a conductor. Upon the mechanical triggering of SFT-TENG, an electric field forms between the metal tip and the charged liquid, with the strongest electric field at the sharp part of the tip. When this electric field is larger than the threshold breakdown value, the breakdown discharge occurs between the metal tip electrode and the liquid electrode (Fig. 2b). The induced optical signal, resulting from gas discharge and solution ion luminescence (discussed in Fig. 1b), can be observed and received through an observation hole next to the liquid chamber. Unlike the conventional TD between solids, where the wavelength of the emitted light is determined solely by the gas molecules (Fig. 2c(i)), luminescence appears around the solution surface during TDTS to illustrate the information of ions from the solution (Fig. 2c(ii)). To further quantitively analyze the ion luminescence spectrum, an optical fiber is placed at the observation hole to collect the emission signal, which is then transmitted to the spectrometer. Both the liquid chamber and optical probe are housed in a black box to minimize environmental interference.

Fig. 2 The measurement principle and system of TDTS-SID. (a) The measurement platform of TDTS-SID. (b) Block diagram of the liquid–metal triboelectric-discharge path. (c) Photograph of the triboelectric discharge effect-induced luminescence between (i) the metal–metal electrode and (ii) the metal–liquid electrode. (d) Equivalent circuit model of the liquid–metal triboelectric discharge path. (e) Liquid–metal triboelectric discharge ion luminescence spectra measured continuously eleven times with an integration time of 7.2 ms by a spectrometer. (f) Liquid–metal triboelectric discharge ion luminescence spectra of positive (dark blue) and negative (orange) discharge with an integration time corresponding to the half-movement cycle of SFT-TENG.

The equivalent circuit of this metal–liquid discharge path is shown in Fig. 2d. The TENG part is equivalent to a voltage source V_i series connected with a capacitor C_T. The coaxial cable is modeled as an electrical conductance G₀ parallel to a capacitor C₀. The triboelectric discharge unit, comprising a metal–liquid interface, is equivalent to a capacitor C_B in initial status and then transitions to a resistor R_d in series with an inductor L_d. Before discharge, resistance R₀ and inductance L₀ are also present in the discharge path. Apart from the coaxial cable, the resistance and inductance in the discharge path mainly come from the ion solution characteristics and the setup between the metal tip and the liquid electrode. The ion solution is equivalent to a resistor, with resistance mainly determined by the ion concentration. A lower ion concentration results in higher resistance, making the breakdown more difficult and consuming more energy in the triboelectric discharge process, which leads to weaker light intensity.

Throughout a complete working cycle, the SFT-TENG generates an alternating voltage output due to the varying input mechanical trigger directions. In these two different directions, the liquid electrodes carry charges of two different polarities, while the corresponding metal electrodes carry charges of opposite polarities. To describe this discharge process, the direction of the metal–liquid TD is defined as the current direction, with the liquid electrode serving as the reference point. Consequently, the TD from the liquid electrode to the metal electrode is defined as the positive discharge and that from the metal electrode to the liquid electrode as the negative discharge (Fig. S1†).

For each SFT-TENG working cycle, the charge Q₀ generated by TENG is stable under the same input force and moving distance. Besides, the relationship between the initial output voltage and the generated charge is given by eqn (3):

When the total generated charges Q₀ exceed the released charges in each discharge, multiple discharges occur within a half-working cycle. This process can be observed by the triboelectric-discharge-effect-induced EM wave signals (Fig. S2†). The SFT-TENG was connected with a breakdown discharger, and an antenna was connected to an oscilloscope to detect the emitted EM wave signal. During two complete working cycles of SFT-TENG, multiple EM pulses can be detected in each half-working cycle, demonstrating the multiple discharges. Additionally, the released charges in each TD process can also be measured by charge steps through a wired measurement circuit (Fig. S3a†), where the amount of the released charge can be calculated by the difference in charge mutations each time. Assuming the released charges in one breakdown discharge process in Q_n (n = 1, 2, 3, …, N), the voltage output of SFT-TENG after n times release (V_n) can be calculated by eqn (4):

When the V_n remains above the threshold breakdown value as defined by Paschen's law, the breakdown discharge continues. To accurately control the discharge distance, the metal-based breakdown discharger with two sharp tips is positioned 50 μm apart. By maintaining a stable input mechanical force and adjusting the acceleration, the transferred charge remains nearly constant (Fig. S3b and c†). The results obtained by adjusting the series-connected resistors R₀ and R_d in the equivalent circuit are shown in Fig. S3d and e.† It can be noted that as the series resistance increases, the energy released per breakdown decreases while the total number of breakdowns increases.

With a similar mechanism and working process, the phenomenon of multiple discharges also occurs in TDTS. Similarly, charge transitions occur in each discharge, accompanied by EM waves and luminescence. The intervals between each luminescence event are shorter than the minimum time distinguishable by the human eye (16–25 ms), making each single luminescence difficult to observe and differentiate. Herein, optical fibers and a spectrometer are used to analyze the ion luminescence spectrum. The half-working cycle of SFT-TENG is approximately 420 ms, and the integration time of the spectrometer is set to 7.2 ms. After continuously measuring around 80 ms, the multiple-discharge-induced luminescence is also observed (Fig. 2e), with 6 discharges occurring during this time. Due to the variability in discharge duration and luminescence persistence, integrating all luminescence energy from a single discharge is challenging. However, the time and released energy in every single discharge exhibit some randomness. The total generated charges and luminescence duration in each half-working cycle of SFT-TENG remain stable. To quantitively analyze the luminescence signal, the integration time of the spectrometer is set to the half-moving cycle period of SFT-TENG.

The TDTS spectra in a sodium-lithium mixed solution during the positive and negative discharge were measured and are shown in Fig. 2f. The measured wavelength ranges from 200 nm to 1100 nm. Here, the ultraviolet (UV) band spans 200 to 400 nm, the visible band covers 400 to 800 nm, and the infrared (IR) band extends from 800 nm to 1100 nm. The characteristic peaks of the spectral signal are across these regions. According to the atomic emission spectrum, the characteristic peak of sodium ions is at 588.68 nm, and that of lithium ions is at 669.78 nm. The reason for a higher value of the characteristic peak of sodium is due to its greater concentration in the mixed solution. Other characteristic peaks, highlighted in gray boxes, mainly originate from air molecules and the solution. By analyzing the position and relative intensity of these peaks, the species and relative concentration of ions can be determined, suggesting a potential portable ion detection method. In addition, the comparison of the waveforms of positive and negative discharge reveals differences in the energy intensity distribution, and most peak energy is concentrated in the UV region between 200 nm and 300 nm in the positive discharge case.

Major influential factors of TDTS-SID

The major influential factors of the TDTS-SID mainly include the ion types and the concentration of the tested solution, output of SFT-TENG, discharge distance, and test environment (temperature and humidity). To quantitatively study the effects of these key factors, experiments were designed to control the other influential factors. This experiment (with the setup shown in Fig. 2a) maintained a temperature of 24 °C and humidity between 60% and 65%. The tested ion solution is sodium chloride solution.

First, the luminescence spectra from the positive and negative discharge were analyzed by adjusting the concentration of the sodium solution from 0.0001 mol L⁻¹ to 4.67 mol L⁻¹, as shown in Fig. 3a and b, respectively (zoomed-in figures are displayed in the ESI as Fig. S4†). Generally, the light intensity of the positive discharge was higher than that of the negative discharge at the same concentration. As the concentration of the sodium solution increased, the light intensity gradually increased for both discharge types. At low concentrations (<0.1 mol L⁻¹), almost no light emission appeared in the 200–300 nm range for both positive and negative discharge. However, it can be noticed that more photons are emitted in this spectral interval with the increasing concentration. Overall, the emission intensity in positive discharges was much higher than in negative discharges, with the spectral energy of emission light being more concentrated in the 200–300 nm UV region for positive discharge. Besides, the relationship between the light intensity and concentration of sodium ions was revealed in both discharges (Fig. 3c). The light intensity of characteristic peaks is increased with the increasing sodium ion concentration, while the light intensity of positive discharges remains higher than that of the negative discharges. Furthermore, a notable improvement in light intensity was observed when the ion concentration exceeded 0.1 mol L⁻¹. Thus, when other variables are strictly controlled, the concentration of the measured ions can be assessed.

Fig. 3 The major influential factors of TDTS-SID. (a and b) The spectra of TDTS-SID in sodium chloride solutions with different concentrations in (a) positive and (b) negative discharge cases. (c) Relationship between the light intensity of the characteristic peaks of sodium ion (588.68 nm) and solution concentration in positive and negative discharges. (d and e) The spectra of TDTS-SID in sodium chloride solutions with different applied input voltages in (d) positive and (e) negative discharges. (f) The relationship between the light intensity of the characteristic peaks of sodium ion (588.68 nm) and input voltage of the SFT-TENG in positive and negative discharges. (g and h) The spectra of TDTS-SID in sodium chloride solutions with different discharge distances in (g) positive and (h) negative discharges. (i) The relationship between the light intensity of the characteristic peaks of sodium ion (588.68 nm) and discharge distance between the metal tip and the surface of ion solution in positive and negative discharges.

Second, the relationship between the emission light intensity and the energy input from SFT-TENG was carefully investigated with a well-fixed concentration of the sodium solution (1 mol L⁻¹). The output of the SFT-TENG was adjusted by regulating the pressure in a linear motor, allowing for the testing of the emission light spectra at 6 different voltage levels during both positive and negative discharges (Fig. 3d and e). As the voltage input of TENG increased, the emission light intensity of all characteristic peaks increased correspondingly, indicating that higher input energy/voltage/charge from the SFT-TENG leads to increased light emission. The relationship between the emission light intensity and applied voltage for both discharge cases is presented in Fig. 3f. Consequently, as the energy input increases, the characteristic peaks become more prominent.

Third, the discharge distance was studied with a fixed sodium ion concentration of 1 mol L⁻¹. In this experiment, the electrostatic force causes the liquid surface to contact with the metal tip before discharging since the metal tip and ion solution carry opposite charges. In this case, the discharge does not occur, and no luminescence is generated. Thus, to ensure the occurrence of TDTS, the actual distance must be smaller than that for static discharge. Herein, a discharge distance of 0 mm is defined as the minimal required discharge distance at which the discharge can occur and an optical signal can be detected. With this standard, by gradually adjusting the discharge distance from 0 mm to 1 mm, the detected spectra for positive and negative discharges are shown in Fig. 3g and h, respectively. As indicated by the measured spectra, with the increasing discharge distance, the energy distribution of the ion luminescence changed, with more emission light energy concentrated near or within the IR region (wavelength >750 nm). In addition, the light intensity of ion luminescence first increases to a certain point and then gradually decreases to a lower value, as shown in Fig. 3i, which illustrates the relationship between the light intensity and discharge distance for positive and negative discharges. Thus, an appropriate input voltage plays a significant role in enhancing the effective detection of characteristic peaks.

Ion species detection of TDTS-SID

To differentiate various metal ions, 4 common metal ions found in human sweat were tested, including sodium (Na⁺), calcium (Ca²⁺), lithium (Li⁺), and potassium (K⁺). These metal ion solutions were prepared with a concentration of 1 mol L⁻¹. Under controlled conditions involving the applied voltage, discharge distance, and environmental factors, the spectra for positive discharge are shown in Fig. 4a, with the light intensity normalized to highlight the eigen-peaks. More importantly, the luminescence of these ions can be easily distinguished by naked eyes. Specifically, the different ions (Na⁺, Li⁺, Ca²⁺, K⁺) emitted various colors (bright yellow, carmine red, brick red, and lilac) under TDTS-SID, showing a visible and intuitive metal ion detection method for users, as shown in Fig. 4b.

Fig. 4 The study of ion species detection of TDTS-SID. (a) The spectra of ion luminescence for different species of metal ions. (b) Photograph of the TDTS-SID of sodium, lithium, calcium, and potassium ions (scale bar: 200 μm). (c) The spectra of ion luminescence of mixed solutions of sodium, lithium, and potassium ions with different ratios. (d) The relationship between the light intensity ratio and mixed solutions with different proportions of sodium and lithium ions.

The spectra of mixed solutions were examined (Fig. 4c), including a 1 mol per L sodium ion solution combined with 1 mol per L lithium-ion solution in ratios of 1 : 1, 1 : 2, 1 : 5, and a mixed solution of 1 mol per L sodium ion solution and 1 mol per L lithium-ion solution and 1 mol per L potassium ion solution in a 1 : 1 : 1 ratio. All eigen-peaks were detected, as shown in the highlighted regions (Fig. 4c). Furthermore, ions with higher concentrations exhibit greater emission light intensity, suggesting a potential method for analyzing ion types, concentrations, and ratios. Using this method, the ratio between the light intensity of characteristic peaks of sodium ions and lithium ions was calculated, implying a higher sodium-to-lithium ion ratio, which corresponds to a higher light intensity ratio (Fig. 4d).

Portable spectrometer

To detect the ion-luminescence-induced optical signals in a portable and flexible way, a handheld spectrometer was designed. As shown in Fig. 5a, the TENG part and metal needle are connected using copper wires shielded by insulation coats. For spectral analysis, a mini-spectrometer chip (Hamamatsu C12880MA) was employed as the charge-coupled device (CCD) array due to its high sensitivity and ultra-compact size. This CCD array is an integrated circuit that can sense the input optical image and convert it to digital signals. Controlled by a microcontroller (STM32F103C8T6) operating at a 3.3 V digital power supply, these digital signals can be processed to obtain the spectra. The compact design of the sensor, measuring 20.1 × 12.5 mm, accommodates the optical input path of the Hamamatsu C12880MA chip, ensuring portability. The overall circuit block diagram is shown in Fig. S5.†

Fig. 5 The design of the portable spectrometer and TDTS-SID-enabled sweat metal ion detection. (a) The schematic of the working principle of the portable spectrometer. (b) Photograph of the portable spectrometer. (c) The sweat collection and testing process of TDTS-SID-enabled spectral analysis. (d) The TDTS-SID-induced spectra of the testing results of artificial sweat solution in the positive and negative discharge cases. (e) The TDTS-SID-induced spectrum of the solution with added lithium ions to artificial sweat in the positive discharge case, where the characteristic peaks of sodium and lithium ions can be detected. (f) The TDTS-SID-induced spectrum of the solution with gradually added potassium ions to artificial sweat in the positive discharge case, where the characteristic peaks of sodium and potassium ions can be detected, and higher concentrations of potassium ions show higher light intensity.

The high resolution of 15 nm for the sensor enables a clear distinction of discharge spectra generated by different metal ions in human sweat. Encased in a 3D-printed box made from polylactic acid (PLA) via fused filament fabrication (FDM) technology, the device is lightweight and portable, suitable for a wide range of application scenarios. The STM32F103C8T6 microcontroller captures the sensor's signal, which is transmitted to a computer via Bluetooth or serial port for further analysis. The spectral data is subjected to feature extraction, including peak locations, peak values, mean values, and variances. The photographs of the CCD array chip and portable spectrometer are shown in Fig. 5b. Therefore, the spectra of the ion luminescence can be detected by this portable spectrometer in real time. By analyzing the eigen-peaks, the metal ion species can be detected.

Artificial sweat ion detection by TDTS-SID

Metal ions in sweat can reveal the health and metabolic status. For example, sodium and potassium ions are common indicators of hyponatremia, hydration, and cystic fibrosis. Lithium ions are used in therapeutic drug monitoring (TDM) for mood stabilization in psychiatric disorders.^42,43

A potential sweat collection method is illustrated in Fig. 5c, where the human sweat can be harvested using microchannels. By directly triggering the TDTS-SID between the metal electrode and the collected sweat, ion species can be detected by identifying the characteristic peaks in the spectrum. Although the concentration of the common ions, such as potassium, is typically around dozens of mmol L⁻¹, the characteristic peaks can be identified, but the light intensity remains constant. One method is to concentrate the sweat by heating and evaporating the water content in the sweat to increase the ion concentration. This allows for the estimation of metal ion concentration by analyzing the light intensity of characteristic peaks under consistent conditions.

To verify this sweat metal ion analyzing method, an SFT-TENG with relatively stable output, spectrometer, and standard artificial sweat was applied in the experiment. The spectra of the TDTS in artificial sweat in positive and negative discharges are shown in Fig. 5d, where the characteristic peak of sodium ions is highlighted. Subsequently, lithium ions, which monitor drug metabolism, were added to the artificial sweat. The added lithium ions can be identified in the TDTS spectra (Fig. 5e). In addition, to study the influence of metal ions on light intensity, the artificial sweat with varying concentrations of potassium ion solution was concentrated to 15 times its original strength by heat evaporation. The results are shown in Fig. 5f, where the light intensity of sodium ions remained constant, while the light intensity of potassium ions gradually increased with higher concentrations. Therefore, by analyzing the ratio between the light intensity of these characteristic peaks, early detection of diseases like hypokalemia becomes possible. Compared with other sweat ion detection studies (details shown in Table S1†), the TDTS-SID-based sweat ion detection method shows significant advantages in reusability and adaptable device design, with the capability of simultaneous detection of multiple ions, which address the challenges of single ion detection, need of specific detection materials, non-reusable, and high cost. Furthermore, the sensing signal is presented in optical form, allowing a more intuitive display of the preliminary detection results without complex instruments. However, the TDTS-SID-based sweat ion detection method can only be applied to detect metal cations, such as K⁺, Na⁺, Ca²⁺, Li⁺, etc. Additionally, compared with similar studies, the sensitivity and accuracy of this proposed method still need to be further enhanced, especially at low ion concentrations.

Conclusion

In this work, we propose and investigate a solution-ion luminescence phenomenon induced by the triboelectric-discharge effect. With the coupled mechanism of triboelectrification, electrostatic induction, and breakdown discharge between the conductive solution and the metal electrode, the optical signal that contains the information of ion type and concentration is emitted from the discharge near the liquid surface. By analyzing the spectra of these optical signals, the information that corresponds to different eigen-peaks can be decoded. The spectra of ion luminescence were quantitively studied using a black box-based experimental platform, focusing on major influential factors, including input voltage, discharge distance, ion type and concentration. In addition, we studied the mixed ion solutions, revealing that ions with higher concentrations exhibit greater light intensity. Furthermore, the artificial sweat with different doped ions was tested, demonstrating its potential for sweat ion detection in a rapid, intuitive, and self-powered way.

Experimental section

Fabrication and measurement of SFT-TENG

An acrylic plate is applied as the SFT-TENG substrate. Above the substrate, two copper tapes are attached, serving as electrodes. A coaxial wire is connected with these two electrodes for further signal and energy transmission. Afterwards, an FEP film, as the tribo-negative layer, is attached to the top of the acrylic plate and copper electrodes. Besides, an NBR block is applied as the tribo-positive layer. Driven by a linear motor, this SFT-TENG can generate stable output. A programmable electrometer (Keithley model 6514) is applied to measure the transferred charge in the breakdown discharge process of the SFT-TENG.

Measurement of optical signal induced by the triboelectric discharge effect

An optical fiber is placed at the observation hole to collect the optical signal induced by the TDTS-SID. This optical fiber is further connected with a spectrometer (Ocean Insight Maya 2000 Pro High-Sensitivity Spectrometer) to record the spectra of optical signals induced by TDTS-SID.

Measurement of EM signal induced by the triboelectric discharge effect

A monopole antenna is connected to an oscilloscope (Keysight DSOX2014A) to detect the emitted wireless EM signal. The oscilloscope is set in trigger mode with the rising edge trigger at a 1.5 V trigger level.

Data availability

The data supporting this study are included within the article and/or ESI.†

Author contributions

H. W. and Y. Z. conceived the idea. H. W., J. F., X. S., and H. T. discussed the results and prepared the manuscript. H. W., J. F., and H. T. set up the experiments and performed the optical signal measurements. H. W. and J. F. analyzed the experimental results and studied the working principle. X. S. designed the handheld spectrometer. H. W., J. F., and X. S. designed and completed the demonstrations. R. G. and C. C. assisted with the signal measurements. G. Z., B. Z., and Z. S., contributed to the demonstrations. X. X., G. X., K. Y., and Z. Z. provided discussions and assisted in the preparation of the manuscript.

Conflicts of interest

The authors declare that they have no conflict of interest.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (project no. 52275560), the Guangdong Natural Science Foundation Outstanding Youth Fund (project no. 2023B1515020074), the Guangzhou-HKUST (GZ) Joint Funding Project (Grant No. 2024A03J0466), and the Guangdong Basic and Applied Basic Research Foundation (2023A1515110643). It was also supported by the RGC Senior Research Fellow Scheme (SRFS2122-5S04) and the Hong Kong Polytechnic University (1-CD44). We thank the Materials Characterization and Preparation Facility (GZ) (MCPF (GZ)) of HKUST-GZ for their technical support.

References

1. J. Kim, A. S. Campbell, B. E.-F. de Ávila and J. Wang, Wearable biosensors for healthcare monitoring, Nat. Biotechnol., 2019, 37, 389–406,  DOI:10.1038/s41587-019-0045-y.
2. Z. Lou, L. Wang, K. Jiang, Z. Wei and G. Shen, Reviews of wearable healthcare systems: Materials, devices and system integration, Mater. Sci. Eng., R, 2020, 140, 100523,  DOI:10.1016/j.mser.2019.100523.
3. B. Zhang, et al., A three-dimensional liquid diode for soft, integrated permeable electronics, Nature, 2024, 628, 84–92,  DOI:10.1038/s41586-024-07161-1.
4. M. Wang, et al., A wearable electrochemical biosensor for the monitoring of metabolites and nutrients, Nat. Biomed. Eng., 2022, 6, 1225–1235,  DOI:10.1038/s41551-022-00916-z.
5. J. Tu, et al., A wireless patch for the monitoring of C-reactive protein in sweat, Nat. Biomed. Eng., 2023, 7, 1293–1306,  DOI:10.1038/s41551-023-01059-5.
6. J. Min, et al., An autonomous wearable biosensor powered by a perovskite solar cell, Nat. Electron., 2023, 6, 630–641,  DOI:10.1038/s41928-023-00996-y.
7. W. Gao, et al., Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis, Nature, 2016, 529, 509–514,  DOI:10.1038/nature16521.
8. B. Chu, W. Burnett, J. W. Chung and Z. Bao, Bring on the bodyNET, Nature, 2017, 549, 328–330,  DOI:10.1038/549328a.
9. M. Fotouhi, et al., A lightweight and secure two-factor authentication scheme for wireless body area networks in health-care IoT, Comput. Netw., 2020, 177, 107333,  DOI:10.1016/j.comnet.2020.107333.
10. S. Javaid, S. Zeadally, H. Fahim and B. He, Medical Sensors and Their Integration in Wireless Body Area Networks for Pervasive Healthcare Delivery: A Review, IEEE Sens. J., 2022, 22, 3860–3877,  DOI:10.1109/JSEN.2022.3141064.
11. S. Niu, et al., A wireless body area sensor network based on stretchable passive tags, Nat. Electron., 2019, 2, 361–368,  DOI:10.1038/s41928-019-0286-2.
12. J. Li, et al., Thin, soft, wearable system for continuous wireless monitoring of artery blood pressure, Nat. Commun., 2023, 14, 5009,  DOI:10.1038/s41467-023-40763-3.
13. Y. Luo, et al., Technology Roadmap for Flexible Sensors, ACS Nano, 2023, 17, 5211–5295,  DOI:10.1021/acsnano.2c12606.
14. M. Bariya, H. Y. Y. Nyein and A. Javey, Wearable sweat sensors, Nat. Electron., 2018, 1, 160–171,  DOI:10.1038/s41928-018-0043-y.
15. A. Childs, et al., Diving into Sweat: Advances, Challenges, and Future Directions in Wearable Sweat Sensing, ACS Nano, 2024, 18, 24605–24616,  DOI:10.1021/acsnano.4c10344.
16. N. Brasier, et al., Towards on-skin analysis of sweat for managing disorders of substance abuse, Nat. Biomed. Eng., 2024, 8, 925–929,  DOI:10.1038/s41551-024-01187-6.
17. J. Wang, et al., Epidermal wearable optical sensors for sweat monitoring, Commun. Mater., 2024, 5, 77,  DOI:10.1038/s43246-024-00518-z.
18. D. S. Yang, R. Ghaffari and J. A. Rogers, Sweat as a diagnostic biofluid, Science, 2023, 379, 760–761,  DOI:10.1126/science.abq5916.
19. J. Choi, R. Ghaffari, L. B. Baker and J. A. Rogers, Skin-interfaced systems for sweat collection and analytics, Sci. Adv., 2018, 4, eaar3921,  DOI:10.1126/sciadv.aar3921.
20. N. Davis, J. Heikenfeld, C. Milla and A. Javey, The challenges and promise of sweat sensing, Nat. Biotechnol., 2024, 42, 860–871,  DOI:10.1038/s41587-023-02059-1.
21. S. Wang, et al., Wearable Sweatband Sensor Platform Based on Gold Nanodendrite Array as Efficient Solid Contact of Ion-Selective Electrode, Anal. Chem., 2017, 89, 10224–10231,  DOI:10.1021/acs.analchem.7b01560.
22. M. M. Delgado-Povedano, M. Calderón-Santiago, F. Priego-Capote and M. D. Luque de Castro, Study of sample preparation for quantitative analysis of amino acids in human sweat by liquid chromatography–tandem mass spectrometry, Talanta, 2016, 146, 310–317,  DOI:10.1016/j.talanta.2015.07.066.
23. M. M. Delgado-Povedano, L. S. Castillo-Peinado, M. Calderón-Santiago, M. D. Luque de Castro and F. Priego-Capote, Dry sweat as sample for metabolomics analysis, Talanta, 2020, 208, 120428,  DOI:10.1016/j.talanta.2019.120428.
24. S. Demuru, B. P. Kunnel and D. Briand, Real-Time Multi-Ion Detection in the Sweat Concentration Range Enabled by Flexible, Printed, and Microfluidics-Integrated Organic Transistor Arrays, Adv. Mater. Technol., 2020, 5, 2000328,  DOI:10.1002/admt.202000328.
25. M. Parrilla, R. Cánovas, I. Jeerapan, F. J. Andrade and J. Wang, A Textile-Based Stretchable Multi-Ion Potentiometric Sensor, Adv. Healthcare Mater., 2016, 5, 996–1001,  DOI:10.1002/adhm.201600092.
26. H. Y. Y. Nyein, et al., A Wearable Electrochemical Platform for Noninvasive Simultaneous Monitoring of Ca2+ and pH, ACS Nano, 2016, 10, 7216–7224,  DOI:10.1021/acsnano.6b04005.
27. P. Pirovano, et al., A wearable sensor for the detection of sodium and potassium in human sweat during exercise, Talanta, 2020, 219, 121145,  DOI:10.1016/j.talanta.2020.121145.
28. I. Shitanda, et al., Wearable Ion Sensors for the Detection of Sweat Ions Fabricated by Heat-Transfer Printing, ACS Sens., 2023, 8, 2889–2895,  DOI:10.1021/acssensors.3c01027.
29. H. Wang, J. Fu, J. Wang, L. Su and Y. Zi, Tribophotonics: An emerging self-powered wireless solution toward smart city, Nano Energy, 2022, 97, 107196,  DOI:10.1016/j.nanoen.2022.107196.
30. J. Fu, et al., Optical Emission from Triboelectric Gas Discharge toward Self-Powered Gas Sensing, Adv. Opt. Mater., 2023, 11, 2202697,  DOI:10.1002/adom.202202697.
31. H. Wang, et al., A paradigm shift fully self-powered long-distance wireless sensing solution enabled by discharge-induced displacement current, Sci. Adv., 2021, 7, eabi6751,  DOI:10.1126/sciadv.abi6751.
32. C. Xu, et al., On the Electron-Transfer Mechanism in the Contact-Electrification Effect, Adv. Mater., 2018, 30, 1706790,  DOI:10.1002/adma.201706790.
33. Z. L. Wang, On Maxwell's displacement current for energy and sensors: the origin of nanogenerators, Mater. Today, 2017, 20, 74–82,  DOI:10.1016/j.mattod.2016.12.001.
34. P. F. Wilson and M. T. Ma, Fields radiated by electrostatic discharges, IEEE Trans. Electromagn. Compat., 1991, 33, 10–18,  DOI:10.1109/15.68245.
35. Q. Zhang, et al., Human body IoT systems based on the triboelectrification effect: energy harvesting, sensing, interfacing and communication, Energy Environ. Sci., 2022, 15, 3688–3721,  10.1039/D2EE01590K.
36. H. Wang, et al., A general self-powered wireless sensing solution based on triboelectric-discharge effect, Nano Energy, 2023, 105, 107982,  DOI:10.1016/j.nanoen.2022.107982.
37. H. Wang, et al., A flexible lightweight self-powered wireless metal detector enabled by triboelectric discharge effect, Device, 2023, 1(6), 100127,  DOI:10.1016/j.device.2023.100127.
38. J. Fu, et al., Deep-learning assisted biomimetic self-powered wireless electronic noses system enabled by triboelectric discharge, Nano Energy, 2024, 121, 109156,  DOI:10.1016/j.nanoen.2023.109156.
39. S. Liu, S. An, X. Zhou, J. Wang and X. Pu, A self-powered, process-oriented wireless sensor with high discharge signal density, Device, 2024, 2(9), 100437,  DOI:10.1016/j.device.2024.100437.
40. L. Liu, et al., Deep-learning-assisted self-powered wireless environmental monitoring system based on triboelectric nanogenerators with multiple sensing capabilities, Nano Energy, 2024, 132, 110301,  DOI:10.1016/j.nanoen.2024.110301.
41. J. Si, et al., Long-distance multifunctional wireless sensing platform for identifying and ranging, Nano Energy, 2023, 109, 108267,  DOI:10.1016/j.nanoen.2023.108267.
42. S. Pedraza-Sanabria, S. Dodd, L. F. Giraldo-Cadavid, K. Whittingham and R.-H. Bustos, Existing and Emerging Technologies for Therapeutic Monitoring of Lithium: A Scoping Review, J. Clin. Psychopharmacol., 2024, 44, 291–296,  DOI:10.1097/jcp.0000000000001835.
43. F. Criscuolo, F. Cantù, I. Taurino, S. Carrara and G. D. Micheli, A Wearable Electrochemical Sensing System for Non-Invasive Monitoring of Lithium Drug in Bipolar Disorder, IEEE Sens. J., 2021, 21, 9649–9656,  DOI:10.1109/JSEN.2020.3009538.

---

Footnotes

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4ta09239b

‡ All authors contributed equally to this work.

---