Modeling and Simulation of 2D Transducers Based on Suspended Graphene-Based Heterostructures in Nanoelectromechanical Pressure Sensors

Graphene-based two-dimensional (2D) heterostructures exhibit excellent mechanical and electrical properties, which are expected to exhibit better performances than graphene for nanoelectromechanical pressure sensors. Here, we built pressure sensor models based on suspended heterostructures of graphene/h-BN, graphene/MoS<sub>2</sub>, and graphene/MoSe<sub>2</sub> by using COMSOL Multiphysics finite element software. We found that suspended circular 2D membranes show the best sensitivity to pressures compared to rectangular and square ones. We simulated the deflections, strains, resonant frequencies, and Young's moduli of suspended graphene-based heterostructures under the conditions of different applied pressures and geometrical sizes, built-in tensions, and the number of atomic layers of 2D membranes. The Young's moduli of 2D heterostructures of graphene, graphene/h-BN, graphene/MoS<sub>2,</sub> and graphene/MoSe<sub>2</sub> were estimated to be 1.001 TPa, 921.08, 551.11, and 475.68 GPa, respectively. We also discuss the effect of highly asymmetric cavities on device performance. These results would contribute to the understanding of the mechanical properties of graphene-based heterostructures and would be helpful for the design and manufacture of high-performance NEMS pressure sensors.

Authors

Institutions

Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2024-10-19
DOI
https://doi.org/10.1021/acsami.4c11941
Citations
14
Primary Topic
Graphene research and applications
Type
article
Field-Weighted Citation Impact
1.64

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling and Simulation of 2D Transducers Based on Suspended Graphene-Based Heterostructures in Nanoelectromechanical Pressure Sensors

Xuge Fan, Quan Liu, Jie Ding, Chang He et al.
14 citations
ACS Applied Materials & Interfaces
Graphene research and applications
1.64
article

Modeling and Simulation of 2D Transducers Based on Suspended Graphene-Based Heterostructures in Nanoelectromechanical Pressure Sensors

Xuge Fan, Quan Liu, Jie Ding, Chang He, Wendong Zhang
article en
14 citations

Abstract

Graphene-based two-dimensional (2D) heterostructures exhibit excellent mechanical and electrical properties, which are expected to exhibit better performances than graphene for nanoelectromechanical pressure sensors. Here, we built pressure sensor models based on suspended heterostructures of graphene/h-BN, graphene/MoS<sub>2</sub>, and graphene/MoSe<sub>2</sub> by using COMSOL Multiphysics finite element software. We found that suspended circular 2D membranes show the best sensitivity to pressures compared to rectangular and square ones. We simulated the deflections, strains, resonant frequencies, and Young's moduli of suspended graphene-based heterostructures under the conditions of different applied pressures and geometrical sizes, built-in tensions, and the number of atomic layers of 2D membranes. The Young's moduli of 2D heterostructures of graphene, graphene/h-BN, graphene/MoS<sub>2,</sub> and graphene/MoSe<sub>2</sub> were estimated to be 1.001 TPa, 921.08, 551.11, and 475.68 GPa, respectively. We also discuss the effect of highly asymmetric cavities on device performance. These results would contribute to the understanding of the mechanical properties of graphene-based heterostructures and would be helpful for the design and manufacture of high-performance NEMS pressure sensors.

ACS Applied Materials & InterfacesVol. 16(43)
Beijing Institute of Technology (CN), North University of China (CN), National Institute of Measurement and Testing Technology (CN), Advanced Research Institute (US)
National Natural Science Foundation of China, Beijing Institute of Technology, Beijing Municipal Natural Science Foundation, Young Scientists Fund, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 12%
Graphene research and applications
1.64
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.