Rational Design for Optimizing Hybrid Thermo-triboelectric Generators Targeting Human Activities

Abstract

Despite the rise in Internet of Things devices and mobile electronics, devising an energy harvester with sufficient time-averaged power remains a challenge when targeting human activities. Here, we report a hybrid thermo-triboelectric generator targeting human motion with systematic optimization strategies in frequency feature-size variable spaces. The device consists of bismuth telluride (Bi2Te3) tiles with polydimethylsiloxane (PDMS) layers filled in between, thereby harvesting both thermal energy and triboelectricity from human touch. Detailed heat transport analyses reveal that optimal operational frequency for thermoelectrics may be tuned on the basis of the insulation property of PDMS. Meanwhile, triboelectricity exhibits strong feature-size dependence when PDMS is interfaced with high-dielectric thermoelectric materials. The analyses establish the design guidelines for a hybrid energy harvester that outperforms the simple physical addition of constituent energy harvesters and demonstrates an average power of 3.27 mu W/cm(3), which is feasible to power potential applications operated by human touch at 2.5 Hz.