Automatic detection of multilayer hexagonal boron nitride in optical images using deep learning-based computer vision.

ABSTRACT: Computer vision algorithms can quickly analyze numerous images and identify useful information with high accuracy. Recently, computer vision has been used to identify 2D materials in microscope images. 2D materials have important fundamental properties allowing for their use in many potential applications, including many in quantum information science and engineering. One such material is hexagonal boron nitride (hBN), an isomorph of graphene with a very indistinguishable layered structure. In order to use these materials for research and product development, the most effective method is mechanical exfoliation where single-layer 2D crystallites must be prepared through an exfoliation procedure and then identified using reflected light optical microscopy. Performing these searches manually

SUBMITTER: Ramezani F 

PROVIDER: S-EPMC9884302 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature