We developed an arginine-responsive biosensor by integrating cascade enzymatic reactions into nanochannels functionalized with weak polyelectrolytes, which serve as "reactive signal amplifiers." This approach enhances device performance and broadens the detectable analyte range by generating high local analyte concentrations. The nanofluidic biosensor operates rapidly (<5 minutes) with a low detection limit of 3 μM.
View Article and Find Full Text PDFIn this study, we investigate the integration of the enzyme creatinine deiminase into solid-state nanopore walls through electrostatic assembly for the development of creatinine sensors. In these asymmetric single nanochannels, ionic transport is determined by the surface charge inside the channel, resulting in diode-like behavior that rectifies ionic current. The efficiency of such rectification depends on the surface charge density.
View Article and Find Full Text PDFSolid-state nanochannels have emerged as a promising platform for the development of ionic circuit components with analog properties to their traditional electronic counterparts. In the last years, nanofluidic devices with memristive properties have attracted special interest due to their applicability in, for example, the construction of brain-like computing systems. In this work, an asymmetric track-etched nanofluidic channel with memory-enhanced ion transport is reported.
View Article and Find Full Text PDFHerein, we present a novel approach to quantify ferritin based on the integration of an Enzyme-Linked Immunosorbent Assay (ELISA) protocol on a Graphene Field-Effect Transistor (gFET) for bioelectronic immunosensing. The G-ELISA strategy takes advantage of the gFET inherent capability of detecting pH changes for the amplification of ferritin detection using urease as a reporter enzyme, which catalyzes the hydrolysis of urea generating a local pH increment. A portable field-effect transistor reader and electrolyte-gated gFET arrangement are employed, enabling their operation in aqueous conditions at low potentials, which is crucial for effective biological sample detection.
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