Automated system for the detection of 2D materials using digital image processing and deep learning

Abstract

The unique properties of two-dimensional materials for light emission, detection, and modulation make them ideal for integrated photonic devices. However, identifying if the films are indeed monolayers is a time-consuming process even for well-trained operators. We develop an intelligent algorithm to detect monolayers of WSe2, MoS2 and h-BN autonomously using Digital Image Processing and Deep Learning with high accuracy rate, avoiding human interaction and any additional characterization tests. We demonstrate an autonomous detection algorithm for TMDC’s and h-BN monolayers with high accuracy of 99.9% with a total processing time of 9 minutes per 1cm2.