High-Throughput Identification and Statistical Analysis of Atomically Thin Semiconductors

TL;DR

This paper introduces an automated photoluminescence microscopy method for high-throughput identification of monolayer TMD semiconductors, significantly accelerating research and enabling large-scale material property analysis.

Contribution

The authors developed a fully automated, high-throughput identification technique for TMD monolayers, reducing analysis time by four orders of magnitude compared to manual methods.

Findings

Measured over 2,400 monolayers and bilayers, enabling new statistical analyses.

Discovered correlation between photoluminescence intensity and monolayer size.

Observed significant brightness variation across different production batches.

Abstract

Transition metal dichalcogenides (TMDs) are layered two-dimensional semiconductors explored for various optoelectronic applications, ranging from light-emitting diodes to single-photon emitters. To interact strongly with light, such devices require monolayer TMDs, which exhibit a direct bandgap. These atomically thin sheets are typically obtained through mechanical exfoliation followed by manual identification with a brightfield optical microscope. While this traditional procedure provides high-quality crystals, the identification step is time-intensive, low-throughput, and prone to human error, creating a significant bottleneck for TMD research. Here, we report a simple and fully automated approach for high-throughput identification of TMD monolayers using photoluminescence microscopy. Compared to a manual search and verification, our methodology offers a four-orders-of-magnitude decrease in the time a researcher must invest per identified monolayer. This ability enables us to measure geometric and photoluminescence-intensity features of more than 2,400 monolayers and bilayers of WSe$_2$, MoSe$_2$, and MoS$_2$. Due to these large numbers, we can study and quantify material properties previously inaccessible. For example, we show that the mean photoluminescence intensity from a monolayer correlates with its size due to reduced emission from its edges. Further, we observe large variations in brightness (up to 10$\times$) from WSe$_2$ monolayers of different batches produced by the same supplier. Therefore, our automated approach not only increases fabrication efficiency but also enhances sample quality for optoelectronic devices of atomically thin semiconductors.