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<p>Graphene, a two-dimensional material known for its exceptional stiffness and low weight, exhibits resonant frequencies that facilitate the detection of mass changes on the order of zeptograms. However, extensive research has been conducted on carbon-based nanomaterials, particularly graphene sheets, the majority of studies have predominantly focused on single mass detection. As is well-known, real systems often involve the identification of materials containing a large number of particles per sample. This paper investigates the application of graphene in the development of mechanical nano-sensors capable of detecting minuscule entities, such as viruses and gas molecules, through measurable alterations in their resonant frequency. This study analytically develops a non-local continuum model to explore the effects of multiple masses attached to a graphene sheet on its frequency response. Additionally, the finite element method is employed to analyze this system, allowing for a comparative assessment of the results obtained from both analytical modeling and finite element analysis. The research focuses on graphene sheets with randomly distributed masses on their surfaces, examining how variations in aspect ratio, length, and mass quantity influence frequency changes. The findings contribute to the understanding of graphene-based nanosensors and their potential applications in biosensing and diagnostics, particularly in the context of rapid detection methods for viral pathogens such as SARS-CoV-2.</p>

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Development of a non-local continuum model and finite element modeling for multi-mass detection on single-layered graphene sheets: implications for enhanced nanosensor performance

  • 期刊论文

  • 发表日期：

    2026年1月3日

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  • Mobina Mohammadi,
  • Javad Payandehpeyman,
  • Mojtaba Mazaheri

摘要

Graphene, a two-dimensional material known for its exceptional stiffness and low weight, exhibits resonant frequencies that facilitate the detection of mass changes on the order of zeptograms. However, extensive research has been conducted on carbon-based nanomaterials, particularly graphene sheets, the majority of studies have predominantly focused on single mass detection. As is well-known, real systems often involve the identification of materials containing a large number of particles per sample. This paper investigates the application of graphene in the development of mechanical nano-sensors capable of detecting minuscule entities, such as viruses and gas molecules, through measurable alterations in their resonant frequency. This study analytically develops a non-local continuum model to explore the effects of multiple masses attached to a graphene sheet on its frequency response. Additionally, the finite element method is employed to analyze this system, allowing for a comparative assessment of the results obtained from both analytical modeling and finite element analysis. The research focuses on graphene sheets with randomly distributed masses on their surfaces, examining how variations in aspect ratio, length, and mass quantity influence frequency changes. The findings contribute to the understanding of graphene-based nanosensors and their potential applications in biosensing and diagnostics, particularly in the context of rapid detection methods for viral pathogens such as SARS-CoV-2.