Broadband convolutional processing using band-alignment-tunable heterostructures

Broadband convolutional processing is critical to high-precision image recognition and is of use in remote sensing and environmental monitoring. Implementing in-sensor broadband convolutional processing using conventional complementary metal-oxide-semiconductor technology is, however, challenging because broadband sensing and convolutional processing require the use of the same physical processes. Here we show that a palladium diselenide/molybdenum ditelluride van der Waals heterostructure can provide simultaneous broadband image sensing and convolutional processing. The band alignment between type-II and type-III heterojunctions of the photovoltaic heterostructure is gate tunable, and the devices exhibit linear light-intensity dependence for both positive and negative photoconductivity, as well as linear gate dependence for the broadband photoresponse. Our in-sensor broadband convolutional processing improves recognition accuracy for multi-band images compared with conventional single-band-based convolutional neural networks. A palladium diselenide/molybdenum ditelluride van der Waals photovoltaic heterostructure can provide simultaneous broadband image sensing and convolutional processing.

Automated summary

In this study, we demonstrate a palladium diselenide/molybdenum ditelluride van der Waals photovoltaic heterostructure that can provide simultaneous broadband image sensing and convolutional processing. The band alignment of the heterojunctions is tunable, and the devices show linear relationships between light intensity and photoconductivity, as well as between gate voltage and broadband photoresponse. Our in-sensor broadband convolutional processing improves recognition accuracy for multi-band images compared with conventional single-band-based convolutional neural networks.