Self-Powered Polyaniline/Si NIR Photodetectors for Waste Classification: Fabrication, Optimization, and Application

Rapid rise in the population and urbanization has led to increased waste generation, creating significant challenges for efficient waste management. Although recycling remains effective, manual sorting of diverse materials limits the scalability. In this study, we report the fabrication and optimization of polyaniline (PANI) interlayer-based photodetectors with varying film thicknesses by using plasma-enhanced chemical vapor deposition (PECVD). PANI films were characterized via UV–vis spectroscopy, FTIR, XPS, and AFM. Devices were tested under varying solar light intensities and a broad wavelength range (351–1600 nm). The photodetector with a 200 nm PANI layer exhibited the best performance, achieving a responsivity of 1.013 A/W, detectivity of 1.34 × 1011 Jones, and EQE of 114.2% under self-powered operation. We propose the use of this device for waste classification, shifting from conventional reflected NIR signal analysis to examining transmitted near-infrared (NIR) wavelengths through waste samples. Our results show that photocurrent, responsivity, and EQE from the PANI/n-Si heterojunction can reliably distinguish material types. This work demonstrates the potential of self-powered NIR photodetectors to enable automated, scalable, and efficient waste classification systems.