The development of highly sensitive biosensors has been significantly advanced by graphene nanostructures, particularly nanogrids, due to their remarkable surface area-to-volume ratio, which enhances biomolecule detection at ultra-low concentrations. This study introduces a scalable fabrication technique for graphene nanogrids integrated into field-effect transistor (FET) biosensors, specifically designed for sub-femtomolar detection of viral proteins. Through the optimization of pore size and distribution, the graphene nanogrid FET biosensors demonstrated high signal-to-noise ratios (SNR) and overcame challenges associated with non-specific antigen interference. The surface antigen was detected at 0.25 fM in serum, even in the presence of Hepatitis C. In addition to these advancements, structural analysis techniques, including XPS and TEM, were employed to observe the effects of lattice temperature and core structures on the electronic band gap, which directly influenced electron mobility. Lattice temperature effects were analyzed for their impact on sensitivity, revealing that optimized temperature control significantly improved detection performance, while precise adjustments in pore morphology and material composition reduced device non-linearity and minimized quantification errors. By operating in heterodyne mode (80 kHz–2 MHz) and utilizing a probabilistic neural network (PNN), the sensor mitigated Debye screening effects, achieving a 70 % increase in SNR, detecting 0.20 fM of Hepatitis B viral proteins with 60 % sensitivity and 6 % standard deviation, demonstrating potential for ultra-sensitive biomedical detection with enhanced electron mobility and reduced non-linearity.
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