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Updated: Oct 16, 2026

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Published on: October 23, 2018
Decoupled Channel and Contact Modulation in α-In2Se3/ZrO2/Hf0.5Zr0.5O2 Dual-Ferroelectric Field-Effect Transistor
Jee Hwan Lee1,2,3, Jung Um Park1,2,3, Won Woo Lee1,2,3
1Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon16419, Republic of Korea.
Abstract:
Ferroelectric field-effect transistors (FeFETs) utilizing either a ferroelectric dielectric (FeD) or a ferroelectric semiconductor (FeS) are highly promising for neuromorphic computing. While integrating FeD with emerging FeS could provide new degrees of freedom for synaptic plasticity, direct integration inevitably suffers from unintended electrostatic coupling and a lack of independent polarization control. Here, we demonstrate a structurally decoupled dual-ferroelectric field-effect transistor (Dual-FeFET) based on an α-In2Se3/ZrO2/HZO heterostructure, in which a ferroelectric dielectric and a ferroelectric semiconductor are integrated into a single transistor while retaining independent functional roles. The inserted ZrO2 interfacial layer mitigates unintended polarization coupling between HZO and α-In2Se3, enabling two orthogonal memory operations: gate-bias-induced HZO polarization switching globally modulates the carrier density of the α-In2Se3 channel, whereas drain-bias-induced α-In2Se3 polarization switching predominantly modulates the drain-side Schottky barrier near the contact region. Dual-mode PFM, Hall-bar analysis, temperature-dependent transport measurements, and ZrO2-thickness-dependent control experiments support the largely decoupled modulation of channel transport and contact injection. By sequentially exploiting these two modulation modes, the Dual-FeFET extends the conductance dynamic range and improves the linearity of synaptic potentiation compared with conventional single-mode FeFET operation. The device exhibits robust nonvolatile memory characteristics with stable endurance over 105 cycles and retention up to 105 s. When implemented in convolutional neural network simulations for CIFAR-10 image recognition, the Dual-FeFET-based synapses achieve an accuracy of 89.2%, approaching the ideal software accuracy of 96.5% and outperforming conventional single-FeFET-based synapses (74.1%). These results demonstrate that structural ferroelectric decoupling enables independently programmable channel and contact modulation in multifunctional 2D ferroelectric transistors.
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