Deformable, resilient, and mechanically-durable triboelectric nanogenerator based on recycled coffee waste for wearable power and self-powered smart sensors

Maximizing resource recycling and finding renewable energy sources are important for a sustainable environment considering the development and consumption of electronic products with the advancement of the internet of things and artificial intelligence technologies. Herein, an economic and environment-friendly triboelectric nanogenerator derived from the discarded coffee ground waste (CG-TENG) is developed to serve as a light-weight and shape-adaptive energy source and self-powered sensitive sensor (CG-TENG sensor). The coffee ground, embedded into the silicone rubber elastomer, is first used as the metal-free electrode feedstock to minimize waste generation. Based on the triboelectrification and electrostatic induction, the shape-adaptive CG-TENG, as wearable power, is capable of harvesting surrounding energy from human motions and extreme deformations, exhibiting excellent stretchability and mechanical durability. The generated electricity can be stored in the conductive coffee ground-derived capacitors to drive portable electronics, which is beneficial for building completely green power systems using coffee waste. Furthermore, the self-powered CG-TENG sensor with optimized structure endows its ultra-high sensitivity for sensing human physiological signals, monitoring motions, emulating gestures, as well as for developing smart tactile epidermal controller and intelligent vending coaster, paving the way for building large-scale energy-efficient artificial sensors and eco-environmental wearable electronics towards humanoid robotics and human-machine interfaces.

Automated summary

In this study, an economic and environment-friendly triboelectric nanogenerator using discarded coffee ground waste as electrode feedstock was developed. The generator is capable of harvesting energy from human motion and extreme deformations for driving portable electronics, and can also be used for developing intelligent interactions between humans and smart devices.