journal article·2026-06Open access

Statistically Resolving Thickness‐Dependent Electrical Characteristics in Multilayer‐MoS 2 Transistors

Sanghyun Lee, Sumin Hong, Minho Park, Seongju Kim, Sanghoon Baek, Seonguk Yang, Chang‐Soo Lee, Sang‐Hoon Bae, Joonki Suh, Yongwoo Lee, Haksoon Jung, Jimin Kwon

Advanced Functional Materials· Volume 36· Issue 45

Abstract

ABSTRACT Atomically thin 2D semiconductors enable excellent electrostatic control even in highly scaled transistors with few‐nanometer gate lengths. The electrical characteristics of 2D transistors can vary significantly with the number of layers, yet how device behavior evolves with channel thickness remains statistically unexplored. This limitation mainly arises from the difficulty of obtaining large numbers of single‐crystal flakes with well‐controlled thickness and fabricating devices. Here, we demonstrate the thickness‐dependent electrical characteristics of single‐flake MoS 2 transistors correlating optical observables with the monolayer (ML) numbers. The optical intensity serves as an indicator of flake thickness for identifying the number of MLs, while algorithm‐based filtering of blurry edges and non‐uniform intensities enables the selection of high‐quality flakes. The filtered flakes are subsequently grouped into distinct thickness clusters based on their optical intensity distributions. The resulting thickness clusters are validated by atomic force microscopy, yielding flakes spanning 3–8 MLs. Automated device layout generation allows the electrical characterization of 1615 transistors selected from over 120000 flakes, providing insight into thickness‐dependent charge carrier injection and transport behavior. Our findings offer a statistically grounded framework linking flake thickness to electrical characteristics and demonstrate the utility of readily accessible optical microscopy for accelerating 2D semiconductor device research.
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Research context

OpenAlex topics: 2D Materials and Applications · Nanowire Synthesis and Applications · Electronic and Structural Properties of Oxides

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Graduate School of Semiconductor Materials and Devices Engineering Ulsan National Institute of Science and Technology (UNIST) Ulsan Republic of Korea

Department of Electrical Engineering Ulsan National Institute of Science and Technology (UNIST) Ulsan Republic of Korea

Department of Creative Convergence Engineering Hanbat National University Daejeon Republic of Korea

Department of Biomedical Engineering Hanyang University Seoul Republic of Korea

Department of Chemical and Biomolecular Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea

TDS Innovation Daejeon Republic of Korea

Department of Mechanical Engineering and Materials Science Washington University in St. Louis St. Louis Missouri USA

School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea

Funding

National Research Foundation of Korea

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