A natural-light-enabled self-powered system simultaneously monitoring wind speed, humidity, and irradiance in multiple channels

Abstract

The self-powered internet of things (IoTs) is in high demand which eliminates batteries with limited lifetime and after-use environmental contaminations. Triboelectric nanogenerators can reveal environmental information through their charge transfer behavior, however, the signal pre-amplification is necessary consuming relatively high external energies and the sensing channels are greatly restricted by the limited information dimensions of the electrical outputs. Herein, we developed a fully-self-powered, natural-light-enabled sensing paradigm by integrating polymer network liquid crystals (PNLCs) triggered by rotary freestanding sliding TENGs (RFS-TENGs), color filters and optical fibers, where the friction-modulated natural light instead of the tribo-charge serves as the information carrier without the necessity of pre-amplification of the tribo-charge signal. Compared with previous TENG enabled self-powered sensors, the developed paradigm significantly expands the dimensions of sensed information, enabling simultaneous monitoring of multiple environmental factors including irradiance, wind speed, and humidity. Through the wavelength divisions of the sunlight via color filters, the self-powered sensing can be performed in multiple channels. Experimental validation in an indoor-simulated oceanic atmospheric boundary layer demonstrates the independence of the sensing under different channels, and ultrahigh sensing accuracies of 98.3%, 97.3%, and 96.7% for irradiance, wind speed, and humidity monitoring, respectively.