A Light-Powered Triboelectric Nanogenerator Based on the Photothermal Marangoni Effect
Chongxian Liu1, Dongjie Jiang2,3, Guiqiang Zhu1
1State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, No. 15 North Third Ring Road, Beijing 100029, People's Republic of China.
Abstract:
The photothermal Marangoni effect enables direct light-to-work conversion, which is significant for realizing the self-propulsion of objects in a noncontact, controllable, and continuous manner. Many promising applications have been demonstrated in micro- and nanomachines, light-driven actuators, cargo transport, and gear transmission. Currently, the related studies about photothermal Marangoni effect-induced self-propulsion, especially rotational motions, remain focused on developing the novel photothermal materials, the structural designs, and the controllable self-propulsion modes. However, extending the related research from the laboratory practice to practical application remains a challenge. Herein, we combined the photothermal Marangoni effect-induced self-propulsion with the triboelectric nanogenerator technology for sunlight intensity determination. Photothermal black silicon, superhydrophobic copper foam with drag-reducing property, and triboelectric polytetrafluoroethylene film were integrated to fabricate a triboelectric nanogenerator. The photothermal-Marangoni-driven triboelectric nanogenerator (PMD-TENG) utilizes the photothermal Marangoni effect-induced self-propulsion to realize the relative motion between the triboelectric layer and the electrode, converting light into electrical signals, with a peak value of 2.35 V. The period of the output electrical signal has an excellent linear relationship with the light intensity. The accessible electrical signal generation strategy proposed here provides a new application for the photothermal Marangoni effect, which could further inspire the practical applications of the self-powered system based on the photothermal Marangoni effect, such as intelligent farming.
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