Triboelectric Nanogenerator Enabled Body Sensor Network for Self

Aug 14, 2017 - Heart-rate monitoring plays a critical role in personal healthcare management. A low-cost, noninvasive, and user-friendly heart-rate mo...
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Triboelectric Nanogenerator Enabled Body Sensor Network for Self-Powered Human Heart-Rate Monitoring Zhiming Lin,† Jun Chen,‡ Xiaoshi Li,† Zhihao Zhou,† Keyu Meng,† Wei Wei,† Jin Yang,*,† and Zhong Lin Wang*,‡,§ †

Department of Optoelectronic Engineering, Chongqing University, Chongqing 400044, China School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States § Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 100083, China ‡

S Supporting Information *

ABSTRACT: Heart-rate monitoring plays a critical role in personal healthcare management. A low-cost, noninvasive, and user-friendly heart-rate monitoring system is highly desirable. Here, a self-powered wireless body sensor network (BSN) system is developed for heart-rate monitoring via integration of a downystructure-based triboelectric nanogenerator (D-TENG), a power management circuit, a heart-rate sensor, a signal processing unit, and Bluetooth module for wireless data transmission. By converting the inertia energy of human walking into electric power, a maximum power of 2.28 mW with total conversion efficiency of 57.9% was delivered at low operation frequency, which is capable of immediately and sustainably driving the highly integrated BSN system. The acquired heart-rate signal by the sensor would be processed in the signal process circuit, sent to an external device via the Bluetooth module, and displayed on a personal cell phone in a real-time manner. Moreover, by combining a TENG-based generator and a TENG-based sensor, an all-TENG-based wireless BSN system was developed, realizing continuous and self-powered heart-rate monitoring. This work presents a potential method for personal heart-rate monitoring, featured as being self-powered, cost-effective, noninvasive, and user-friendly. KEYWORDS: self-powered body sensor network, triboelectric nanogenerator, downy structure, power management circuit, heart-rate monitoring displayed.6,7 However, the current BSNs are mainly powered by a traditional power supply unit, such as batteries. Due to the limited lifetime and the potential environmental pollution issue of batteries, a self-powered working module is highly desired for the BSN for heart-rate monitoring.8,9 Here, in this work, a self-powered wireless BSN system was reported for cost-effective, noninvasive, and user-friendly human heart-rate monitoring. It is a systematical integration of a downy-structure-based triboelectric nanogenerator (DTENG), a power management circuit, a heart-rate sensor, a signal processing unit, and Bluetooth module for wireless data transmission. By harvesting human biomechanical energy, a maximum power of 2.28 mW was delivered from the wearable

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wing to the quickening rhythm of human life and work as well as the population aging, healthcare monitoring has drawn increasing attention for alerting unhealthy lifestyle and prevention of latent disease.1,2 Heart rate, a direct reflection of the health status of the human cardiovascular system, is one of the most widely used vital sensing signals for human healthcare monitoring and diagnosis. Various efforts have been committed to develop technologies for human heart-rate monitoring.3,4 Despite the potential and high performance, widespread usage of these techniques is possibly limited by structure complexity, fabrication of highquality materials, and reliance on external power sources.5 Recently, technologies based on the body sensor network (BSN), a network of associated sensor nodes on the human body, contributes largely to personalized health monitoring and assessment as well as disease diagnosis. As a consequence, it would be great to develop a heart-rate BSN platform, whereby real-time heart-rate signals could be collected, transmitted, and © 2017 American Chemical Society

Received: April 30, 2017 Accepted: August 14, 2017 Published: August 14, 2017 8830

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enhancing the electric output. Here, the copper films play dual roles of the triboelectric material and the electrode. Photographs of the inner downy structure and an as-fabricated D-TENG are, respectively, shown in Figure 1d,e. As discussed in the Experimental Section, the fabrication process of the DTENG is straightforward and compatible with possible largescale manufacturing. The operation of the D-TENG relies on relative sliding between the PTFE and copper thin films, in which a coupling between triboelectrification and electrostatic induction gives rise to alternating flow of electrons between electrodes.10−23 The electricity-generating process is elaborated through a basic functional unit in Figure 2. In the initial state, a physical contact between the PTFE and copper thin films will lead to a charge transfer at the interface due to a difference of the electron affinity between the two, which will result in a positively charged copper thin film and a negatively charged PTFE thin film (Figure 2a-I), and the insulating property of the PTFE allows a long-time retention of triboelectric charges. Once a displacement occurs due to the external mechanical excitation, the triboelectric charges are not compensated at the displaced areas, which will result in an electrical potential difference across the electrodes to drive the electrons flowing from the PTFE back electrodes to right electrodes and the freestanding copper layer (Figure 2a-II). This flow of electrons will last until the electric potential difference reaches zero (Figure 2a-III). Further relative sliding between the two triboelectric layers will result in a reversely built potential difference between the right electrodes and the PTFE’s electrodes, which will drive the electrons to flow back from the right electrodes and the freestanding copper layer to the PTFE’s electrodes, generating a reverse current in the external circuit (Figure 2a-IV). This is a full cycle of electricity generation progress for the D-TENG. In addition, to obtain a more quantitative understanding of the working principle of D-TENG, numerical calculations of the electric field potential distribution across the electrodes under open-circuit conditions are also simulated via finite element method,24−27 as demonstrated in Figure 2b, which is consistent with the experimental observation. To investigate the D-TENG for vibration energy harvesting, a first step was taken to study if the grid number depended on output performance. As schematically illustrated, the inner downy structure with various grid numbers of D-TENGs are presented in Figure S1, and it can be seen that the efficient triboelectric area of each grid decreases with the increase of the grid number due to the air gap increasing for the same volume. All the types of D-TENGs share a same device volume and maximum sliding displacement, and all the electrical measurements were acquired under a consistent mechanical excitation at the frequency of 10 Hz. To begin with, the short-circuit current of all the D-TENGs with various grids numbers are explored and displayed in Figure 3a, which reveals that all the D-TENGs are capable of delivering a stable electric output. The current amplitudes of the D-TENG increased with the elevation of the grid numbers from 2 to 4 owing to an increase of the effective sliding displacement. However, it is worth noting that the current amplitudes of D-TENGs decrease with the grid number from 5 to 8, which is mainly ascribed to the reduction of the effective contact area with increasing grid numbers, and the detailed reason is demonstrated in Figure S2 and Note 1 (Supporting Information). In Figure 3b, it indicates that open-circuit voltage follows a similar trend with the shortcircuit current, and a maximum value of 540 V can be achieved

D-TENG under natural human walking, which is capable of driving the entire BSN system. The heart-rate signal would be processed in the signal process circuit and transmitted via the Bluetooth module, which will finally be displayed on the personal cell phone for analysis of daily human heart-rate information. This work not only greatly advanced the TENG in a system level for wearable medical devices but also provided a superior solution for personal heart-rate monitoring.

RESULTS AND DISCUSSION The D-TENG holds a multilayer structure with acrylic as supporting backbone, as schematically shown in Figure 1a,b. It

Figure 1. Structural design of the downy-structured triboelectric nanogenerator (D-TENG). (a) Schematic illustration of the (a) process flow and (b) device structure of the D-TENG. (c) SEM image of the PTFE polymer nanowire array. Photograph of the (d) inner structure and (e) as-fabricated D-TENG.

consists of two basic functional units; one unit is composed of copper back-coated polytetrafluoroethylene (PTFE) thin films and copper thin films, which are stationary layers with one end being anchored onto the acrylic frame, leaving the other end freestanding. These two kinds of films are segmentally alternating on acrylic sheets to form a downy-like structure. The other unit is the acrylic sheet segmentally adhered on the front and back surface by the copper-coated PTFE and copper thin films as the freestanding triboelectric layers, which are finally connected to the outer frame with a stretchable rubber. Due to the innovatively designed inner downy structure, the restoring forces of the stationary layers make triboelectric layers contact fully, which is beneficial to increase the effective contact area between triboelectric layers and enhancing the electric output. This configuration is extremely sensitive to external mechanical excitation, and even a small disturbance will lead to a relative sliding between the triboelectric layers and generate power. Acrylic was selected as the structural material owing to its good strength, light weight, good machinability, and low cost. Furthermore, to enhance the triboelectrification, surface modification was performed on the PTFE thin films via an inductively coupled plasma (ICP) to create an aligned nanowire array, as shown by the scanning electron microscopy (SEM) image in Figure 1c, which is capable of largely increasing the effective contact area between triboelectric layers and 8831

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Figure 2. Electricity generation process of the D-TENG. (a) Two-dimensional schematic illustration and (b) finite element simulations showing the working principle of the D-TENG.

for D-TENGs with four grids. Furthermore, Figure 3c shows the charges generated by D-TENG with grid numbers from 2 to 8. It can be observed that the transferred charges remain almost constant with the open-circuit voltage. In addition, the optimized power for different grid numbers has been also measured, and the output power reaches the maximum with four grids. Given the above experimental observation, the DTENG with four grids is the optimized device structure with the highest output performance. Additionally the D-TENG exhibits good stability in device operation. As shown in Figure S3 (Supporting Information), there is no significant change in electrical output after about 10000 cycles. For a quantitative characterization of the output performance, the electric output of the D-TENG with four grids is systematically measured, as displayed in Figure 4. A frequency response was first measured for the D-TENG at vibrational frequencies from 6 to 10 Hz. The short-circuit currents are measured for the D-TENG with four grids, as shown in Figure 4a. Average peak current outputs are around 5.6 to 12 μA with the increase of frequency applied, and the open-circuit voltages are also demonstrated in Figure 4b and Figure S4 (Supporting Information), which indicated an increasing of the output voltage from 200 to 540 V with the elevation of the external vibration frequencies. Furthermore, the transferred charges of the D-TENG at different operating frequencies are shown in Figure 4c. It was found that the transferred charges increased proportionally from ∼115 to ∼306 nC with the increasing

frequencies. The conversion efficiency is introduced and defined as the ratio between the input mechanical energy and the generated electric energy, and the generated electrical energy obtained by the load reaches the maximum values at a certain resistance, which can be calculated as Eelectrical =

∫ I(t )2 ·R·dt

(1)

where I(t) is the instantaneous current at a certain resistance and R is the load resistance. Figure 4d shows the output current of the D-TENG with four grids at a load resistance of 80 MΩ and the corresponding energy on the load, which is calculated to be 0.39 mJ. For the input mechanical energy, it will be determined by the difference between potential energy at an initial position and final position (equilibrium point), which can be predicted by Emechanical =

1 ·k·x 2 2

(2)

where k is the spring constant of the rubber (k = 68.2 N/m) and x is its displacement. Thus, the efficiency is determined by the equation η = Eelectrical/Emechanical, and then the conversion efficiencies of D-TENG with four grids at different frequencies could be calculated, as shown in Figure 4e. The highest efficiency reaches 57.9% at the vibrational frequency of 10 Hz. It clearly demonstrates the capability of harvesting mechanical energy at a very high efficiency. To further investigate the 8832

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Figure 3. Electrical characterization of the D-TENG. Dependence of the (a) short-circuit current, (b) open-circuit voltage, (c) transfer change quantity, and (d) power of the D-TENG with different grid numbers under a consistent mechanical excitation of 10 Hz.

management circuit). As shown in Figure S7a (Supporting Information), the D-TENG can scavenge the inertia energy from natural human walking when it is equipped on the human body, and a total of 42 commercial light-emitting diode bulbs assembled in series can be lighted up simultaneously (see Supporting Information Video S1). In addition, the influencing factors of the output performance were also explored systematically when the D-TENG is worn on the arm, as demonstrated in Note 2 (Supporting Information). The output voltage of the TENG is affected by the acceleration of the sliding layer a, which is determined by the amplitude of human walking and the frequency of arm swinging. Figure S7b shows that the electric output varies with different frequencies of arm swinging under a consistent amplitude. It can be observed that the open-circuit voltages present an obvious increasing tendency with the increase of frequencies of arm swinging. Furthermore, a self-powered wireless body sensor network was developed based on the power-supplying system for heartrate monitoring. As shown in Figure 5b, the self-powered wireless BSN system consisted of a commercial heart-rate sensor, signal processing unit, a Bluetooth module for data transmission, as well as the power-supplying system. As the arm swung naturally during walking, the harvested human biomechanical energy is capable of driving the BSN independently in a real-time manner. As depicted in Figure 5c, the heart-rate signal acquired by the commercial sensor would be processed in the signal process circuit, which includes the AD module, microcontroller, and Bluetooth module. The AD module will convent the analog heart-rate signal into a digital signal. High precision 12-bit AD and appropriate sampling rate ensure the synchronous data acquisition with

output power of the D-TENG with four grids, the output current is also measured with the external load ranging from 1 KΩ to 1 GΩ. It remains stable when the resistance is smaller than 1 MΩ and then decreases due to the Ohmic loss. An optimum output power of 2.28 mW is delivered at a resistance of 80 MΩ, as shown in Figure S5a, and the power of D-TENGs at different frequencies versus external resistance plots is shown in Figure S5b (Supporting Information). Moreover, the DTENG with four grids is also investigated to charge a capacitor of 10 μF at different vibrational frequencies. Measured various voltage charging curves by the D-TENG are demonstrated in Figure 4f. As indicated, it takes 1.7, 2.6, and 3.9 s to charge the capacitor up to 6 V by the D-TENG at vibrational frequencies of 6, 8, and 10 Hz, respectively. It is noticed that the D-TENG delivered a high voltage but relatively low current output, resulting in a large output impedance and thus affecting its applicability as a power source. The electric output in an alternating current manner is also a concern for practical applications. In this regard, a power management circuit was developed to integrate with the DTENG to form a complete power-supplying system. Figure 5a illustrates the complete power-supplying system including a TENG, a power management circuit, and the commercial electronics. The power management circuit plays an important role for the power-supplying system, consisting of a transformer, a rectifier, and a low leakage energy storage capacitor, as demonstrated in Figure S6 (Supporting Information). It addresses the issue of the mismatch between the electrical outputs of the TENG and the power requirement for electronics and largely improves the storage efficiency (the right inset in Figure 5a is the photograph of the power 8833

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Figure 4. Electrical output performances of the D-TENG with a four grid inner downy structure. (a) Dependence of the short-circuit current of the D-TENG on the external vibration frequency from 6 to 10 Hz. (b) Dependence of the open-circuit voltage of D-TENG on the external vibration frequency from 6 to 10 Hz. (c) Transfer charge quantity of the D-TENG. (d) Output current at a load resistance of 80 MΩ and energy on the load resistance. (e) Electromechanical conversion efficiencies of D-TENG. (f) Measured various voltage charging curves of a 10 μF capacitor driven by the D-TENG.

capable of realizing health-monitoring purposes. By combining a TENG-based generator and a TENG-based sensor with the signal management circuit, an all-TENG-based wireless BSN system was presented, as illustrated in Figure 5e. The TENGbased generator will harvest human biomechanical energy to power external circuits such as signal management circuits, and the TENG-based sensor could acquire real-time heart-rate information, which is displayed chromatically in Figure 5f. It clearly elucidates the TENG-based sensor, management circuits, and recorded real-time heart-rate signal on a personal cell phone and oscilloscope, achieving the all-TENG-based wireless BSN system. Figure 5g shows the heart-rate signal acquired by the TENG-based sensor and commercial sensor, which is a photoelectric reflective analog sensor; it can be seen

abundant details. The microcontroller would receive the digital signals from the AD module for further data processing. Next, the processed digital signals were sent to the smart phone via the Bluetooth module. The detected heart-rate signal will be received and displayed in real time on a personal cell phone. Figure 5d is an enlarged view showing the whole software interface of the real-time acquired heart-rate signals. The red line on the interface clearly represents the runner’s heart-rate signal, and a value of 150 bpm was obtained spontaneously (see Supporting Information Video S2). We also developed a TENG-based sensor to detect the heartrate signal, which consists of a PTFE film and a copper film as the triboelectric layers working in single-electrode mode.3 It has features of being wearable, light weight, self-powered, and 8834

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Figure 5. Demonstrations of the integrated power-supplying system for driving and charging electronics. (a) System diagram of the complete power-supplying system. (b) Photograph showing that the integrated system was equipped onto a human arm. (c) Photograph showing the acquired heart-rate data were wirelessly transmitted to a cell phone in a real-time manner. (d) Enlarged view to show the whole software interface of the real-time acquired heart-rate signals. (e) Diagram of all TENG-based wireless BSN system. (f) Demonstration of an all-TENGbased wireless BSN system and the acquired real-time heart-rate information displayed on a personal phone. (g) Heart-rate signal acquired by a (I) TENG-based sensor and (II) commercial sensor.

CONCLUSION

that a typical characteristic pulse wave shape can be obtained from TENG-based sensor with three clearly distinguishable determinants: systolic peak (PS), point of inflection (Pi), and dicrotic wave (PD). The three parameters can be used to quantify the augmentation index and reflection index, which can accurately evaluate the physiological conditions of the human cardiovascular system. However, the commercial sensor cannot detect the clear and distinct related characteristics of the heart-rate signal. Due to the self-powered, wearable, integrated features, the system will be capable of implementing the lowcost, real-time, and noninvasive heart-rate monitoring, presenting a way to detect, evaluate, and reveal early stages of heart disease. A schematic illustration of self-powered wireless BSN system is also provided in Figure S10 (Supporting Information) to better show its commercial application potential.

To summarize, a triboelectric nanogenerator driven wireless BSN system was reported for noninvasive real-time human heart-rate monitoring. By effectively harvesting the inertia energy of human walking, a D-TENG delivered a maximum power of 2.28 mW with total conversion efficiency of 57.9% due to the innovatively designed inner downy structure, which can immediately and sustainably power the highly integrated wireless BSN system. Relying on the self-powered BSN, the acquired human heart-rate signals are first processed by a signal process circuit, wirelessly transmitted via Bluetooth, and finally displayed onto a personal cell phone for real-time heart-rate monitoring. This work presented a competent and costeffective solution to satisfy the increasing demands of cardiopathy patients for daily healthcare monitoring, which 8835

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AUTHOR INFORMATION

can be immediately and extensively adopted in a variety of applications and ultimately improve our way of living.

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected].

EXPERIMENTAL SECTION

ORCID

Fabrication of Nanowires on PTFE Surface. A 50 μm thick PTFE thin film was first washed with menthol, isopropyl alcohol, and deionized water, consecutively. To improve the triboelectrification, an inductively coupled plasma (SI500, SENTECH Instruments Corp.) reactive ion etching was performed to fabricate the aligned nanowires on the PTFE surface. O2, Ar, and CF4 gases were injected into the ICP chamber with a flow rate of 10, 15, and 30 sccm. Plasma with a large density was produced by a power source of 400 W. Another power source of 100 W was applied in order to accelerate the plasma ions. The PTFE nanowires were obtained after an etching process for 40 s. Fabrication of the D-TENG. The D-TENG mainly consists of two parts: two freestanding triboelectric layers and two pairs of downy structure stationary layers. On one hand, the freestanding triboelectric layers were first made by shaping a piece of acrylic sheet with dimensions of 90 mm × 70 mm × 2 mm as a substrate by using a laser cutter. Then, the copper-coated PTFE and copper thin film with same dimensions of 65 mm × 20 mm were segmentally adhered to the front and back surface of the acrylic sheets. On the other hand, downy structure stationary layers were first made by cutting the acrylic sheet into a 110 mm × 70 mm × 2 mm rectangle by the laser cutter. Then, one edge of the PTFE films and copper thin film with the same dimensions of 65 mm × 30 mm were fixed on the acrylic plates in an alternating manner. To integrate, the freestanding triboelectric layers were sandwiched by two pairs of downy structure stationary layers, followed by a final connection to the top of the acrylic framework with a piece of elastic rubber. Electrical Measurement. The D-TENG was mounted onto an electrodynamic shaker (Labworks ET-139) to study the output performances at different vibrational frequencies. The shaker was driven by an amplifier (LabworkPa-13) and a functional generator (Tektronix AFG3021) with pure sinusoidal signal output. The output voltage was acquired by a programmable electrometer (Keithley model 6514). The output current was measured via a low-noise current preamplifier (Stanford Research System model SR570).

Jun Chen: 0000-0002-3439-0495 Jin Yang: 0000-0002-6606-8310 Zhong Lin Wang: 0000-0002-5530-0380 Author Contributions

Z.L. and J.C. contributed equally to this work. Notes

The authors declare no competing financial interest.

ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China (Nos. 51675069, 51475060), and graduate scientific research and innovation foundation of Chongqing, China (Grant No. CYB17017). REFERENCES (1) Niu, S.; Wang, X.; Yi, F.; Zhou, Y. S.; Wang, Z. L. A Universal Self-Charging System Driven by Random Biomechanical Energy for Sustainable Operation of Mobile Electronics. Nat. Commun. 2015, 6, 8975. (2) Zhong, J.; Zhang, Y.; Zhong, Q.; Hu, Q.; Hu, B.; Wang, Z. L.; Zhou, J. Fiber-Based Generator for Wearable Electronics and Mobile Medication. ACS Nano 2014, 8, 6273−6280. (3) Yang, J.; Chen, J.; Su, Y.; Jing, Q.; Li, Z.; Yi, F.; Wen, X.; Wang, Z.; Wang, Z. L. Eardrum-Inspired Active Sensors for Self-Powered Cardiovascular System Characterization and Throat-Attached AntiInterference Voice Recognition. Adv. Mater. 2015, 27, 1316−1326. (4) Pu, X.; Li, L.; Song, H.; Du, C.; Zhao, Z.; Jiang, C.; Cao, G.; Hu, W.; Wang, Z. L. A Self-Charging Power Unit by Integration of a Textile Triboelectric Nanogenerator and a Flexible Lithium-Ion Battery for Wearable Electronics. Adv. Mater. 2015, 27, 2472−2478. (5) Rendon-Morales, E.; Prance, R. J.; Prance, H.; Aviles-Espinosa, R. Non-Invasive Electrocardiogram Detection of in vivo Zebrafish Embryos Using Electric Potential Sensors. Appl. Phys. Lett. 2015, 107, 193701. (6) Pirbhulal, S.; Zhang, H.; Mukhopadhyay, S. C.; Li, C.; Wang, Y.; Li, G.; Zhang, Y. T. An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks. Sensors 2015, 15, 15067−15089. (7) Hao, Y.; Foster, R. Wireless Body Sensor Networks for HealthMonitoring Applications. Physiol. Meas. 2008, 29, R27. (8) Trung, T. Q.; Lee, N. E. Flexible and Stretchable Physical Sensor Integrated Platforms for Wearable Human-Activity Monitoringand Personal Healthcare. Adv. Mater. 2016, 28, 4338−4372. (9) Khan, Y.; Ostfeld, A. E.; Lochner, C. M.; Pierre, A.; Arias, A. C. Monitoring of Vital Signs with Flexible and Wearable Medical Devices. Adv. Mater. 2016, 28, 4373−4392. (10) Zhu, G.; Chen, J.; Zhang, T.; Jing, Q.; Wang, Z. L. Radial Arrayed Rotary Electrification for High Performance Triboelectric Generator. Nat. Commun. 2014, 5, 3426. (11) Zhu, G.; Pan, C.; Guo, W.; Chen, C. Y.; Zhou, Y.; Yu, R.; Wang, Z. L. Triboelectric-Generator-Driven Pulse Electrodeposition for Micropatterning. Nano Lett. 2012, 12, 4960−4965. (12) Yang, J.; Chen, J.; Yang, Y.; Zhang, H.; Yang, W.; Bai, P.; Wang, Z. L. Broadband Vibrational Energy Harvesting Based on a Triboelectric Nanogenerator. Adv. Energy Mater. 2014, 4, 1301322. (13) Chen, J.; Zhu, G.; Yang, W.; Jing, Q.; Bai, P.; Yang, Y.; Wang, Z. L. Harmonic-Resonator-Based Triboelectric Nanogenerator as a Sustainable Power Source and a Self-Powered Active Vibration Sensor. Adv. Mater. 2013, 25, 6094−6099. (14) Yang, J.; Chen, J.; Liu, Y.; Yang, W.; Su, Y.; Wang, Z. L. Triboelectrification-Based Organic Film Nanogenerator for Acoustic

ASSOCIATED CONTENT S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.7b02975. Schematic illustration of the inner downy structure with various grid numbers in a D-TENG (Figure S1); illustration of the efficient triboelectric area of the inner downy structure (Figure S2); cyclic test investigating the stability of the D-TENG (Figure S3); relationship between frequency and electrical output of as-fabricated TENG with four grids (Figure S4); measured output power of the D-TENG versus external load resistance (Figure S5); diagram of the power management circuit (Figure S6); harvesting energy from natural vibration of human walking (Figure S7); theoretical model of metalto-dielectric sliding mode (Figure S8); mechanical spring mass-damper model (Figure S9); schematic illustration of self-powered wireless body sensor network (Figure S10) (PDF) Video S1: triboelectric nanogenerator harvesting vibration energy from human walking (AVI) Video S2: self-powered heart-rate monitoring system (AVI) 8836

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