arrow
Return

Statistically Resolving Thickness-Dependent Electrical Characteristics in Multilayer-MoS2 Transistors

delete2026-04-03
delete0
delete
OA
AI
S
S. W. Ricky Lee
S
Sumin Hong
M
Minho Park
S
Seongju Kim
S
Sanghoon Baek
S
Seonguk Yang
C
Chang-Soo Lee
S
Sang-Hoon Bae
J
Joonki Suh
Y
Yongwoo Lee *
H
Haksoon Jung *
J
Jimin Kwon *
DOI:10.1002/adfm.202532204delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
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 MoS2 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.
Keywords:
automatic flake detection
optical classification
single-flake transistors
transition metal dichalcogenides (TMDs)
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Advanced Functional Materials cover
Advanced Functional Materials
IF:
19
Papers:
3.4W
Citations:
32.1W

Organization

H
hanbat national university
Scholars:
135
Papers: 73
Citations: 0
H
hanyang university
Scholars:
2.8W
Papers: 2.7W
Citations: 36
U
unist
Scholars:
253
Papers: 87
Citations: 0
W
washington university in st. louis
Scholars:
672
Papers: 290
Citations: 1
K
Korea Advanced Institute of Science and Technology
Scholars:
3.4K
Papers: 1.3K
Citations: 254
T
tds innovation
Scholars:
1
Papers: 1
Citations: 0
U
ulsan national institute of science and technology
Scholars:
1.3K
Papers: 476
Citations: 2
researcher View more organizations