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. 2023 May 19;15(10):2375.
doi: 10.3390/polym15102375.

Polyvinylidene Fluoride/Aromatic Hyperbranched Polyester of Third-Generation-Based Electrospun Nanofiber as a Self-Powered Triboelectric Nanogenerator for Wearable Energy Harvesting and Health Monitoring Applications

Affiliations

Polyvinylidene Fluoride/Aromatic Hyperbranched Polyester of Third-Generation-Based Electrospun Nanofiber as a Self-Powered Triboelectric Nanogenerator for Wearable Energy Harvesting and Health Monitoring Applications

Ramadasu Gunasekhar et al. Polymers (Basel). .

Abstract

Flexible pressure sensors have played an increasingly important role in the Internet of Things and human-machine interaction systems. For a sensor device to be commercially viable, it is essential to fabricate a sensor with higher sensitivity and lower power consumption. Polyvinylidene fluoride (PVDF)-based triboelectric nanogenerators (TENGs) prepared by electrospinning are widely used in self-powered electronics owing to their exceptional voltage generation performance and flexible nature. In the present study, aromatic hyperbranched polyester of the third generation (Ar.HBP-3) was added into PVDF as a filler (0, 10, 20, 30 and 40 wt.% w.r.t. PVDF content) to prepare nanofibers by electrospinning. The triboelectric performances (open-circuit voltage and short-circuit current) of PVDF-Ar.HBP-3/polyurethane (PU)-based TENG shows better performance than a PVDF/PU pair. Among the various wt.% of Ar.HBP-3, a 10 wt.% sample shows maximum output performances of 107 V which is almost 10 times that of neat PVDF (12 V); whereas, the current slightly increases from 0.5 μA to 1.3 μA. The self-powered TENG is also effective in measuring human motion. Overall, we have reported a simpler technique for producing high-performance TENG using morphological alteration of PVDF, which has the potential for use as mechanical energy harvesters and as effective power sources for wearable and portable electronic devices.

Keywords: PVDF; electrospinning; hyperbranched polyester; triboelectric nanogenerator.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
(a). Schematic explanation of preparation and electrospinning of P-Ar.HBP-3 solution followed by TENG fabrication: (i). preparation of P-Ar.HBP-3 blend solution, (ii). solution blending by constant magnetic stirring, (iii). electrospinning process, (iv). SEM image of electrospun nanofiber and (v). fabricated TENG device. (b). Schematic illustration of triboelectric mechanism.
Figure 2
Figure 2
(a). XRD pattern and (b). FTIR spectra of PVDF fibers as well as P-Ar.HBP-3 (0 to 40 wt.%) blended nanofibers. (c). Computed β-phase content variability in P-Ar.HBP-3 (0 to 40 wt.%) blended nanofibers, and (d). Mechanism of β-phase formation in P-Ar.HBP-3 nanofiber.
Figure 3
Figure 3
(a,a′). Surface morphologies of neat PVDF (16 wt.%), (b,b′). Surface morphologies of P/HBP-3 (10 wt.%) nanofibers, respectively. (c,d). EDS and elemental mapping of P-Ar.HBP-3 (10 wt.%) nanofiber, respectively. (e). Map spectrum of elements in P-Ar.HBP-3 (10 wt.%) nanofiber and (fh). Energy-dispersive spectral images of carbon, fluorine and oxygen elements, respectively.
Figure 4
Figure 4
(ad). Time-dependent VOC and ISC graphs of PVDF and P-Ar.HBP-3/PU (10 wt.%)-based TENG under constant frequency of 1 Hz and load of 10 N, respectively. (e,f). Output performances (VOC and ISC) of P/PU and P-Ar.HBP-3/PU (10 wt.%)-based TENG device as a function of load 5–10 N). (g). Rectified voltage of P-Ar.HBP-3/PU (10 wt.%)-based TENG (h). P-Ar.HBP-3/PU (10 wt.%)-based TENG device energy storage with various capacitors (2.2–22 μF) with charging cycles. (i). Circuit diagram for LED application. (j,k). Images of 12 LEDs before and after connecting P-Ar.HBP-3/PU (10 wt.%)-based TENG.
Figure 5
Figure 5
Real-time monitoring of P-Ar.HBP-3/PU (10 wt.%)-based TENG: (a). Sensitivity efficiency under various physical deformations of the sensor (tapping, twisting, bending, and folding), (b). Sensor’s performance when used as a finger ring, (c). Detection of punching intensity, (d). Sensitivity of the joint-bending when the sensor is placed at elbow flexion, (e). Smart chair health care, (f). Detecting and differentiating the intensities of slow and fast coughing pattern while the sensor is used on mouth mask, (gi). Motion detection and differentiation (hand moment, leg moment, walk and jump) when the sensor is placed on pocket, knee and shoe insole, respectively for human health motion applications.

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