A Crossbar GFET Platform with bioADC Integration for Multiplexed, Energy-Efficient Biosensing

Tyler Bodily, Min Suk Lee, Anirudh Ramanathan, Akshay Paul, Abhijith Karkisaval-Ganapati, Yuchen Xu, Oscar Vazquez-Mena, Gert Cauwenberghs

Confirmation: I have read and agree with the IEEE BSN 2025 conference submission's policy on behalf of myself and my co-authors.

Keywords: graphene field-effect transistor (GFET), multiplexed biosensor, low-power sensing, ion-sensitive FET

TL;DR: A low-power, multiplexed GFET array integrated with a neural interface SoC is demonstrated for scalable, real-time biosensing and future wearable diagnostics.

Abstract:

We present platform technology consisting of a scalable, low-power graphene field-
effect transistor (GFET) array integrated with a custom neural
interface system-on-chip (NISoC) for multiplexed biosensing.
The platform features a 10×10 GFET crossbar architecture
with high-density channel integration and side-gated liquid
sensing, enabling simultaneous detection of multiple bioana-
lytes in a compact footprint. Electrical characterization un-
der varying phosphate-buffered saline (PBS) concentrations
confirms stable Dirac point behavior and sensitivity to ionic
strength, highlighting the system’s electrostatic responsiveness.
Integration with a low-power bioADC-based NISoC supports
both current- and voltage-clamp operation, achieving sub-
μW/channel power consumption. Current-clamp mode offers
enhanced energy efficiency, critical for continuous monitoring
in wearable applications.

A streamlined graphene transfer process and dielectric-
isolated crossbar design ensure reproducible device
performance across the array. The platform is being
developed for surface functionalization with DNA aptamers
to enable multiplexed biomarker detection in physiological
fluids. These advancements position the system for real-time
monitoring of health, stress, or disease markers in digital health
and athletic performance settings. This work demonstrates a
promising direction for next-generation wearable biosensors
with low-power, high-density, and real-time signal acquisition
capabilities.

Track: 2. Sensors and systems for digital health, wellness, and athletics

NominateReviewer: Ratnesh Lal [e-mail]

Submission Number: 131