Tactile Neuromorphic Ion-Gated Vertical Transistor Displays Enabling Dual-Output Reservoir Computing

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Authors: Seung Jun Lee, Woojoong Kim, Jioh Yoo, G Y Kim, Seong-Jin Park, Junhyeok Song, Ning Li, Shengyou Li, HoYeon Kim, 하제봉, J J Jang, KB Huh
+3 more Jungjae Park, Changhoe Lee, Cheolmin Park
Cited by: 1
References: 62

Abstract

Integrating tactile sensing, neuromorphic processing, and visual emission within a single device is essential for next-generation intelligent interfaces. Although tactile neuromorphic displays have advanced significantly, further advances in brightness, stable continuous emission, and gate-tunable optical modulation would substantially broaden their applicability. Here, we present a tactile neuromorphic ion-gated vertical transistor display (TN-VTD) that integrates pressure sensing, ion-mediated synaptic plasticity, and electroluminescence within a compact vertical structure. Mechanical deformation of a hemispherical elastomeric gate modulates ion penetration through a permeable nanoporous Al electrode, inducing pressure-dependent n-type doping and band bending within the Super Yellow emissive layer. This ion-coupled design enables continuous and stable DC emission (∼46 cd m-2 at VDS = 3 V) for over 24 h and strong gate-enhanced brightness (∼427 cd m-2 at VG = 9 V), with the emissive area expanding proportionally with applied pressure. Pressure-dependent ionic accumulation further tunes synaptic relaxation time, generating nonlinear fading-memory electrical and optical responses that evolve along distinct temporal dynamics. From a single input, concurrent conductance and brightness outputs provide complementary state variables that expand the reservoir state dimensionality beyond single-observable operations. Leveraging this multidimensional state encoding, TN-VTD achieves 93.5% spoken-digit classification accuracy, substantially outperforming conductance-only operation (82.3%). These results establish TN-VTD as a unified platform capable of simultaneous sensing, neuromorphic processing, and visual output.

Fields of Study & Subjects

Advanced Memory and Neural Computing Neural Networks and Reservoir Computing Ferroelectric and Negative Capacitance Devices

Publication details

Journal / source
ACS Nano
Publisher
American Chemical Society (ACS)
Volume
20
Issue
27
Pages
19458–19473
Publication date
1 July 2026
Language
EN