Identification of microbes using single-layer graphene-based nano biosensors

Area of Science:

• Nanotechnology
• Materials Science
• Biosensing

Background:

• Graphene-based nanosensors offer significant potential for advanced sensor technology.
• Investigating vibration responses of single-layer graphene sheets (SLGS) with attached microorganisms is crucial for developing novel sensors.
• Specific viruses like Parvoviridae, Flaviviridae, and Polyomaviridae were studied based on their size and mass.

Purpose of the Study:

• To develop a graphene-based nanosensor for detecting microorganisms and viruses.
• To analyze the vibration responses of single-layer graphene sheets under different boundary conditions and with attached biological substances.
• To evaluate the performance of armchair single-layer graphene sheets compared to chiral ones.

Main Methods:

• Utilized the atomistic finite element method (AFEM) for dynamic analysis of single-layer graphene (SLG).
• Performed molecular dynamic simulations to assess SLG behavior as a sensor under cantilever and bridged boundary conditions.
• Conducted frequency analysis using ANSYS APDL software, varying the mass of attached biological objects.

Main Results:

• Frequency response is inversely proportional to the mass of attached microorganisms; higher mass leads to lower frequency.
• Armchair single-layer graphene sheets exhibit superior performance compared to chiral SLG.
• Mimivirus (3.0041 Zg) showed the lowest frequency, indicating a clear mass-dependent frequency shift.

Conclusions:

• Graphene-based nanosensors are highly sensitive to the mass of attached biological entities, enabling microorganism detection.
• The developed SLG biosensor demonstrates significantly faster sensitivity than existing ionization-based methods.
• This novel biosensor holds promise for the early identification of diseases through virus detection.