Line-Scan Hyperspectral Imaging Microscopy with Linear Unmixing for Automated Two-Dimensional Crystals Identification

Abstract

Two-dimensional (2D) materials exhibit unique optical properties when controlled to atomic thickness, and show large potential for applications in optoelectronics, photodetectors, and tunable excitonic devices. Current characterization techniques, including conventional optical microscopy, atomic force microscopy (AFM), and Raman spectroscopy are time-consuming and labor-intensive for studying large-scale samples. To realize the rapid identification of monolayer and few-layer crystals in the "haystack" of hundreds of flakes appearing in the exfoliation process, line-scan hyperspectral imaging microscopy combined with linear unmixing was developed to identify 2D molybdenum disulfide (MoS2) and hexagonal boron nitride (hBN) samples. A complete hyperspectral measurement and analysis, including single-band analysis, pixel-level spectral analysis and image classification was performed on MoS2 and hBN flakes with mono- and few-layer thickness. The characteristic spectra were extracted and analyzed via linear unmixing calculations to reconstruct the distribution images. The abundance maps showed the spatial distribution of these flakes with flake positions output, realizing an automatic identification of target flakes. This work shows a rapid and robust method for the determination of abundance maps of 2D flakes distributed over macroscopic areas.