An Atomically Thin Optoelectronic Machine Vision Processor

Adv Mater. 2020 Sep;32(36):e2002431. doi: 10.1002/adma.202002431. Epub 2020 Jul 23.

Abstract

2D semiconductors, especially transition metal dichalcogenide (TMD) monolayers, are extensively studied for electronic and optoelectronic applications. Beyond intensive studies on single transistors and photodetectors, the recent advent of large-area synthesis of these atomically thin layers has paved the way for 2D integrated circuits, such as digital logic circuits and image sensors, achieving an integration level of ≈100 devices thus far. Here, a decisive advance in 2D integrated circuits is reported, where the device integration scale is increased by tenfold and the functional complexity of 2D electronics is propelled to an unprecedented level. Concretely, an analog optoelectronic processor inspired by biological vision is developed, where 32 × 32 = 1024 MoS2 photosensitive field-effect transistors manifesting persistent photoconductivity (PPC) effects are arranged in a crossbar array. This optoelectronic processor with PPC memory mimics two core functions of human vision: it captures and stores an optical image into electrical data, like the eye and optic nerve chain, and then recognizes this electrical form of the captured image, like the brain, by executing analog in-memory neural net computing. In the highlight demonstration, the MoS2 FET crossbar array optically images 1000 handwritten digits and electrically recognizes these imaged data with 94% accuracy.

Keywords: 2D materials; crossbar arrays; integrated circuits; neural networks; transition metal dichalcogenides.