Two graphene-based sensors cost about the same, but they do not perform the same: the rougher, more defective material detects NT-proBNP in artificial saliva at a lower concentration than pristine CVD graphene. Graphene-based materials are being investigated as sensing elements for detecting different analytes.

CVD graphene and graphene oxide are both used in biosensors, and the production costs of CVD graphene- and GO-based sensors are similar. The central comparison is between CVD graphene aptasensors and reduced GO aptasensors for detecting NT-proBNP, the gold standard biomarker for heart failure.

Both use commercial gold interdigitated electrodes with graphene or GO as the channel of a liquid-gated field-effect transistor. Both aptasensors demonstrate a dynamic range from ten femtograms per milliliter to one hundred picograms per milliliter. In artificial saliva, the limit of detection is one hundred femtograms per milliliter for rGO-FET and one picogram per milliliter for GFET.

A promising low-cost graphene biosensor uses a field-effect transistor channel modified with a target-specific aptamer. Aptamers attract attention as biosensor receptors because manufacturing is relatively low cost and stability is higher than for antibodies.

The sensing mechanism is electrostatic gating: the distance or number of charges between the graphene surface and the analyte or aptamer is modulated. The electrical signal can therefore represent a biochemical reaction. A major challenge is response variation.

A survey using more than five thousand measurements found that GFET sensor responses can vary by more than three hundred percent, even among devices produced in one batch. NT-proBNP is released into the bloodstream when heart muscles are damaged, and it can also be found in bodily fluids such as saliva.

That makes NT-proBNP a promising heart-failure marker for point-of-care diagnostics. Saliva is attractive because collection is fast and easy, without complex or invasive preparation. But saliva remains difficult because its NT-proBNP concentration can be lower than one picogram per milliliter.

The small size of NT-proBNP is comparable to the specific aptamer, which adds complexity to interpreting the field-effect-transistor signal. The technology therefore needs to reduce uncertainty when measuring trace analyte levels.

The study uses commercial interdigitated electrodes in contact with a graphene channel to build cost-effective field-effect-transistor biosensors. The new CVD GFET is compared with a reduced GO-FET developed previously.

Both devices measure NT-proBNP across a wide range, from one femtogram per milliliter to ten nanograms per milliliter, in buffer solution and dissolved artificial saliva. Artificial saliva is used as a model for possible interference from bodily fluids.

Both sensors are highly sensitive, but the reliable limit of detection as low as one hundred femtograms per milliliter in dissolved artificial saliva, corresponding to one picogram per milliliter in saliva, is observed only for rGO-FET. Two field-effect transistors are investigated: a GO monolayer ink device and CVD monolayer graphene transferred onto commercially available interdigitated electrodes.

These become the two material platforms for the comparison. The rGO-FET starts with graphene oxide diluted in a water and NMP mixture to zero point two milligrams per milliliter. The suspension is drop-cast onto gold electrodes modified with cysteamine and incubated for two hours.

The glass between the electrodes is activated by APTES to improve adhesion of GO monolayers. GO is then reduced with hydrazine vapor at eighty degrees Celsius for two hours, followed by thermal annealing at two hundred degrees Celsius for one hour.

For the CVD device, monolayer graphene on thirty-micrometer copper foil is transferred to the working electrodes using a wet-transfer method with PMMA support. The PMMA is spin-coated over the graphene and pre-baked at sixty degrees Celsius for five minutes.

The copper is etched first in a hydrochloric-acid, hydrogen-peroxide, and water mixture, then in ammonium persulfate solution for two hours. After washing, the graphene and PMMA are transferred onto the electrode and dried overnight. Boiled acetone and a boiled THF and water mixture remove the PMMA film, after which the graphene is rinsed with water and dried with nitrogen gas.

Figure one characterizes the two sensing films before electrical testing. AFM images show an intact CVD graphene surface, while the rGO appears as interconnected flakes; the height profiles make these surface structures visible across a two-micrometer distance.

Raman spectra further identify the films through their G and two-D features, with the graphene spectrum showing a pronounced two-D peak and the rGO spectrum showing stronger defect-related structure. The study aims to produce a monolayer film with both deposition approaches.

The transferred CVD monolayer graphene demonstrates an intact surface, while the GO film consists of interconnected individual flakes with an average size of several microns. The GO film has roughness of one point three plus or minus zero point one nanometers, more than two times higher than CVD graphene at zero point forty-six plus or minus zero point zero-three nanometers.

The substrate roughness also contributes to the measured surface structure. The peak-to-peak surface height difference is two point two plus or minus zero point five nanometers for graphene and five point five plus or minus one point three nanometers for GO.

During assembly in zero point zero one-times PBS, the rGO-FET and GFET chips are used to analyze the electrical response to NT-proBNP. The transconductance of bare devices is similar for both types. PBASE attachment affects the electrical properties of both devices and leads to p-type doping by the NHS groups.

Transconductance is estimated from the slope of the linear part of the p-type branch of the current-voltage curves. After aptasensor assembly, transconductance increases by only ten percent for GFET but by more than eighty percent for rGO-FET. The increase is associated with ionic redistribution in the Stern layer.

Figure two follows the aptasensor assembly through transfer curves, Dirac-point shifts, and a schematic of the electrical response. Panels a and b compare pristine, PBASE-treated, and aptamer-treated devices across the stated PBS conditions, while panel c summarizes the shifts for GFET and rGO-FET configurations.

The opposite Dirac-point responses after aptamer binding to PBASE, illustrated in panel d, matter because they indicate that surface immobilization alters charge and the electrical behavior differently in graphene and reduced graphene oxide. At high ionic strength, where the electrical double-layer thickness is small, the Dirac-point shift is almost negligible for CVD graphene.

A reliable signal is observed only in diluted PBS, while rGO-FET remains sufficiently sensitive in one-times PBS. The difference is attributed to electrostatic gating from the aptamer to semimetal graphene and semiconducting rGO. For rGO, trapped states in the bandgap are more sensitive to electrostatic gating, although they can produce higher noise.

NT-proBNP is measured in zero point zero one-times PBS with Tween to increase the Debye length. Stepwise concentration measurements reveal different Dirac-point-shift values but the same direction for GFET and rGO-FET. Transconductance does not change for the GFET aptasensor, consistent with earlier results for a photochemically immobilized GFET with an aptamer.

This lack of mobility effects supports the intact structure and absence of defect-associated trapped states in CVD graphene. For rGO-FET, both transconductance and Dirac-point shift are more pronounced because NT-proBNP binding affects electrostatic doping and direct doping to trapped states in rGO.

For CVD graphene, the shift is weak, begins at ten femtograms per milliliter, and rapidly saturates at higher concentrations. Figure three compares graphene and reduced-graphene-oxide aptasensors detecting NT-proBNP in diluted PBS and artificial saliva. Panels a and b show concentration-dependent transfer-curve changes and Dirac-point shifts in PBS, while panels c and d examine three concentrations in saliva-diluted PBS.

The similar shift direction in PBS, and the additional baseline shift caused by saliva’s ionic strength and pH, highlight why the measurement medium matters when interpreting these biosensor responses. After long-term storage under normal conditions, both aptasensor types show good selectivity, meaning low sensitivity, toward cTnI.

This agrees with results demonstrated previously. Unexpectedly, both aptasensors show higher sensitivity toward the proBNP peptide. Although NT-proBNP is part of prohormone proBNP, aptasensors generally do not show sensitivity toward proBNP.

The proposed explanation is that specific stacking of the aptamer on the graphene surface can increase sensitivity to proBNP. The authors also expect some degradation of sensing properties after long-term storage. Table 2 compares the analytical performance of aptasensors built with CVD GFETs and rGO-FETs.

Both platforms report a dynamic range from ten to the power of minus two to ten to the power of two picograms per milliliter, while the listed limits of detection are one and zero point one picograms per milliliter, respectively. The table also reports sensitivities of approximately zero point seven and two point five millivolts per decade, providing a concise basis for discussing their differing responses to NT-proBNP.

The CVD graphene FET biosensor uses a non-covalently linked aptamer for NT-proBNP detection and is compared with an rGO-based FET biosensor. The comparison shows that selecting a biosensor technology requires considering the sensing material, the analyte, and the sensing mechanism.

NT-proBNP is a small peptide that can interact with aptamers in different manners, and those interactions can result in large measurement errors. The aptamer-based assay can nevertheless be performed in diluted artificial saliva.

For point-of-care devices, materials with a larger bandgap and trapped states, such as rGO-FET, are preferred to increase sensitivity and decrease noise. The key lesson is that sensor performance depends on the material, the analyte, and the sensing mechanism together; for NT-proBNP point-of-care detection, rGO-FET offers the lower demonstrated detection limit, while CVD GFET shows less parameter variation.