Graphene field-effect transistors (GFETs) are suitable building blocks for high-performance electrical biosensors, because graphene inherently exhibits a strong response to charged biomolecules on its surface. However, achieving ultralow limit-of-detection (LoD) is limited by sensor response time and screening effect. Herein we demonstrate that the detection limit of GFET biosensors can be improved significantly by decorating the uncovered graphene sensor area with carbon dots (CDs). The developed CDs-GFET biosensors used for exosome detection exhibited higher sensitivity, faster response and three orders of magnitude improvements in the LoD compared with nondecorated GFET biosensors. A LoD down to 100 particles/μL was achieved with CDs-GFET sensor for exosome detection with the capability for further improvements. The results were further supported by atomic force microscopy (AFM) and fluorescent microscopy measurements. The high performance of CDs-GFET biosensors will aid the development of an ultrahigh sensitivity biosensor platform based on graphene for rapid and early diagnosis of diseases.
Graphene field-effect transistor (GFET) biosensors exhibit high sensitivity due to a large surface-to-volume ratio and the high sensitivity of the Fermi level to the presence of charged biomolecules near the...
Glial
fibrillary
acidic protein (GFAP) is a discriminative blood
biomarker for many neurological diseases, such as traumatic brain
injury. Detection of GFAP in buffer solutions using biosensors has
been demonstrated, but accurate quantification of GFAP in patient
samples has not been reported, yet in urgent need. Herein, we demonstrate
a robust on-chip graphene field-effect transistor (GFET) biosensing
method for sensitive and ultrafast detection of GFAP in patient plasma.
Patients with moderate–severe traumatic brain injuries, defined
by the Mayo classification, are recruited to provide plasma samples.
The binding of target GFAP with the specific antibodies that are conjugated
on a monolayer GFET device triggers the shift of its Dirac point,
and this signal change is correlated with the GFAP concentration in
the patient plasma. The limit of detection (LOD) values of 20 fg/mL
(400 aM) in buffer solution and 231 fg/mL (4 fM) in patient plasma
have been achieved using this approach. In parallel, for the first
time, we compare our results to the state-of-the-art single-molecule
array (Simoa) technology and the classic enzyme-linked immunosorbent
assay (ELISA) for reference. The GFET biosensor shows competitive
LOD to Simoa (1.18 pg/mL) and faster sample-to-result time (<15
min), and also it is cheaper and more user-friendly. In comparison
to ELISA, GFET offers advantages of total detection time, detection
sensitivity, and simplicity. This GFET biosensing platform holds high
promise for the point-of-care diagnosis and monitoring of traumatic
brain injury in GP surgeries and patient homes.
The performance of graphene devices is often limited by defects and impurities induced during device fabrication. Polymer residue left on the surface of graphene after photoresist processing can increase electron scattering and hinder electron transport. Furthermore, exposing graphene to plasma-based processing such as sputtering of metallization layers can increase the defect density in graphene and alter the device performance. Therefore, the preservation of the high-quality surface of graphene during thin-film deposition and device manufacturing is essential for many electronic applications. Here, we show that the use of self-assembled monolayers (SAMs) of hexamethyldisilazane (HMDS) as a buffer layer during the device fabrication of graphene can significantly reduce damage, improve the quality of graphene, and enhance device performance. The role of HMDS has been systematically investigated using surface analysis techniques and electrical measurements. The benefits of HMDS treatment include a significant reduction in defect density compared with as-treated graphene and more than a 2-fold reduction of contact resistance. This surface treatment is simple and offers a practical route for improving graphene device interfaces, which is important for the integration of graphene into functional devices such as electronics and sensor devices.
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