NIR-UV Dual-Mode Photodetector with the Assistance of Machine-Learning Fabricated by Hybrid Laser Processing

Abstract

Photodetectors are widely used in optoelectronic applications such as remote controlling, optical communication, and intelligent manufacturing. Multi-wavelength response capability can expand the application scenarios of a photodetector. However, responding to and recognizing multiple bands is still challenging for a photodetector. Here, we develop a dual-mode photodetector that can respond to and recognize near-infrared (NIR) and ultraviolet (UV) light with the assistance of a machine-learning model. A hybrid laser processing method was proposed to fabricate this photodetector based on the polyimide substrate. This method uses femtosecond laser and continuous wave laser to induce the formation of carbon and zinc oxide composite material in different forms. The femtosecond laser-processed area and the continuous wave laser-processed area realized stable NIR light detection and UV light detection, respectively. Recognition of the type of incident light was realized with the assistance of a machine-learning classification model. The proposed hybrid laser processing method combines the characteristics of two kinds of lasers and provides new insights into fabricating dual-mode photodetector. This photodetector could advance the development of dual-mode photodetection and has application potential in many fields like wearable devices and smart clothing.