ArticleJournal of molecular modeling2023
Identification of microbes using single-layer graphene-based nano biosensors.
Article in Journal of molecular modeling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
- Graphene-Based Materials for Bone Regeneration in Dentistry: A Systematic Review of In Vitro Applications and Material Comparisons.Nanomaterials (Basel, Switzerland) · 2025Review
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Authors and funding
2 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
contextGraphene based nano sensors have huge potential in an era of sensor technology. The objective of this study is to create a sensor by investigating the vibration responses of cantilever and bridged boundary conditioned single layer graphene sheets (SLGS) with various attached microorganisms on the tip and at the centre of the sheet. The Parvoviridae, Flaviviridae, and Polyomaviridae biological substances have been comprehensively investigated here. For the Parvoviridae, Polyomaviridae, and Flaviviridae categories of targeted microbes, the sizes are 21nm, 40nm, and 45nm, respectively. The Parvoviridae family has a maximum frequency of 1.87x10
methodsIn this research, the application of Single Layer Graphene (SLG) as a virus sensing device is explored. Atomistic finite element method (AFEM) has been used to carry out the dynamic analysis of SLG. Molecular dynamic analysis and simulations have been performed to see how SLG behaves when employed as sensors for biological entities and when they are exposed to bridged and cantilever boundary conditions. The frequency analysis was performed using ANSYS APDL software. SLG of various chirality has been utilised in the investigation. By altering the applied mass of a biological object, the difference in frequency observed. The idea behind mass detection employing nano biosensors is built on the concept that the stiffness of a biomolecule changes as its mass changes, making the resonant frequency extremely sensitive to that change. A shift in the resonance frequency results from a change in the associated mass on the graphene sheet. The main challenge in mass detection is estimating the variation in resonant frequency driven by the mass of the connected molecule. The SLG-based biosensor has a specific application in the early identification of diseases. The biosensor investigated in this article is novel, whereas the biosensors that are presently on the market operate using the ionization method. The simulations result shows SLG based biosensor's sensitivity considerably faster than an existing one.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.