Mitigating Permittivity–Charge Cross-Sensitivity in Biomolecular Sensing: Electrostatic Decoupling and Feedforward Biasing in an Asymmetric Dual-Gate a-IGZO FET
Year: 2026
Type: preprint
Abstract: Permittivity-based biomolecular identification is inherently ambiguous in real-world sensing environments because analyte charge also influences the measured electrical response. Different combinations of charge and permittivity can produce similar electrical responses, so a change in the measured response cannot be uniquely attributed to permittivity. This work combines electrostatic decoupling through device engineering with charge-conditioned feedforward biasing to mitigate this cross-sensitivity and recover both analyte properties through direct drain-current readings from a single transistor. We provide a proof of concept through technology computer-aided design (TCAD) simulations of an asymmetric dual-gate, dual-nanogap amorphous indium– gallium–zinc oxide (a-IGZO) transistor. Gate-insulator dielectric engineering and nanogap optimization establish complementary drain-current responses, with the bottom gate pre-dominantly sensing analyte charge and the top gate predominantly sensing permittivity. Feedforward biasing further suppresses residual charge interference in the top-gate response. First, the bottom-gate drain current provides an estimate of analyte charge. This estimate and a preliminary top-gate current reading are used to select the voltage for the final top-gate measurement. The drain current measured at that voltage then determines permittivity. Three sequential current readings thus provide permittivity-based biomolecular identification without prior knowledge of analyte charge, alongside complementary charge measurement. Mean charge and permittivity extraction errors remain below 1.8% and 0.6%, respectively, across the calibration and independent test datasets. Abstract Figure
Institution: Islamic University of Technology
Language: English
Subfield: Analytical Chemistry
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7223150123