Validation of devices for characterization of hybrid 3D printed embroidery TENG for energy harvesting
DOI:
https://doi.org/10.25367/cdatp.2022.3.p1-8Keywords:
Hybrid nanogenerator, flexible filament, 3D printing, embroidery, tapping characterization, conductive, multifilament, hybrid yarn,Abstract
A textile-based triboelectric nanogenerator (TENG) is an energy harvesting flexible and lightweight device that converts mechanical energy to electrical energy. This work presents characterization of a novel hybrid 3D printed embroidery TENG for energy harvesting. The digital embroidery part is done on Brother Embroidery Machine PR670E with polyester multifilament conductive hybrid thread (CleverTex) with a linear thread resistance of 280 Ω/m. This embroidery thread is fully compatible with the standard textile embroidery process. The thread is highly suitable for embroidery due to its very good mechanical properties and no loop formation during embroidery. These features make the thread especially suitable for high production quality. It could be used as needle thread or bobbin thread. For the preparation of the embroidery part, the polyester multifilament conductive hybrid thread is used as needle thread with 100% polyester Madeira thread as bobbin thread. These threads have non-toxic, non-skin irritation properties, which makes them suitable for smart wearable energy harvesting applications. Furthermore, these threads are coated with silicone-paraffin emulsions that improve their running during the embroidery process. Among the possible stitch types (satin, fill, prog. fill, piping, motif, cross, concentric circle, radial, spiral, flexible spiral, stippling, net fill, zigzag net fill, and decorative fill), fill stitch with medium stitch density and 4.5 lines per mm has been used to develop this energy harvesting sample. The 3D printed textile fabric is prepared with extremely flexible filament with a tensile elongation at break of 1400%. The output voltage is 200 V and 103 V for tapping and friction characterization, respectively
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Copyright (c) 2022 Hasan Tahir, Benny Malengier, Carla Hertleer, Lieva Van Langenhove
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