Abstract

Zinc oxide (ZnO), as a typical piezoelectric semiconductor, has gained significant attention in the field of wearable electromechanical coupling. However, the presence of an intrinsic screening effect becomes a bottleneck in developing high-performance ZnO-based piezoelectric devices. To address this limitation, we propose the formation of p-n homojunction by La doping in ZnO nanorods (NRs) as well as discrete structural design to improve their electrical output and flexibility. The enhanced performance and the mechanism behind it are explored and revealed in terms of morphology, structure, built-in electric field, depletion layer width, and junction capacitance, respectively. Benefitting from the excellent electromechanical coupling performance of the developed devices, different human motions can be recognized and classified with the aid of machine learning. These findings provide a new insight into the impact of doping on the output performance of piezoelectric semiconductor devices, thus facilitating advancements in piezoelectric device design and application exploration.

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