Flexible perovskite solar cell-driven photo-rechargeable lithium-ion capacitor for self-powered wearable strain sensors. (June 2019) - Li, Chao; Cong, Shan; Tian, Zhengnan; Song, Yingze; Yu, Lianghao; Lu, Chen; Shao, Yuanlong; Li, Jie; Zou, Guifu; Rümmeli, Mark H.; Dou, Shixue; Sun, Jingyu; et al.
Abstract: Next-generation wearable electronics is expected to be self-powered by conformable energy storage devices that can provide energy output whenever needed. The emerging energy harvesting and storage integrated system in a flexible assembly, in this respect, has offered a promising solution. Nevertheless, daunting challenges pertaining to the insufficient energy density, limited overall efficiency and low output voltage of the prevailing integrated power sources still exist. Herein, we report a flexible perovskite solar cell (PSC)-driven photo-rechargeable lithium-ion capacitor (LIC) that hybridizes energy harvesting and storage for self-powering wearable strain sensors. Such flexible PSC-LIC module manages to deliver an overall efficiency of 8.41% and a high output voltage of 3 V at a discharge current density of 0.1 A g −1 . It could still harvest a remarkable overall efficiency exceeding 6% even at the high current density of 1 A g −1, outperforming state-of-the-art photo-charging power sources. Accordingly, thus-derived, self-powered strain sensor readily manifests precise and continuous data recording of physiological signals without any external power connections, thereby realizing the synergy of energy harvesting, storage, and utilization within one smart system. This multi-field-coupled, function-integrated platform is anticipated to offer significant benefits toward practical self-powered wearable electronics. Graphical abstract: Image 1 Highlights: Constructing a PSC-LIC-sensor integrated system with conformal and self-powered functionality. Achieving a record high overall efficiency (8.41%) by PSC-LIC module in the realm of flexible integrated power sources. Realizing a self-powered sensor for continuous data acquisition of physiological signals in practical scenarios.