Work

Nanoarchitectonics for Non‐Volatile Ternary STDP Synapse Using Anti‐Ferroelectric Carbon Nanotube Devices

Year: 2026

Type: article

Abstract: Anti‐ferroelectrics (AFEs) offer unique properties such as double hysteresis window, high endurance, and low latency, making them appealing for neuromorphic computing architectures. This study introduces a novel, compact, and energy‐efficient neuromorphic circuit for spike‐timing‐dependent plasticity (STDP) synapse using AFE field‐effect transistors (AFeFETs). Although AFeFETs are volatile and unsuitable for storing synaptic weights, carbon nanotube field‐effect transistors (CNTFETs) are employed with multi‐threshold operation to achieve nonvolatility by shifting polarization‐electric field (P‐E) characteristics. By leveraging the tunable hysteresis characteristics and negative differential resistance (NDR) effect of AFeCNTFETs, a nonvolatile ternary weight storage latch is demonstrated to store STDP‐governed synaptic weights. Simulation results show that this synapse improves power efficiency by 30% and saves 93% of energy compared to previous works while remaining immune to power outages. This efficient neuromorphic building block paves the way for enhanced neuromorphic learning architectures.

Source: Advanced Electronic Materials

DOI: 10.1002/aelm.202500304

Authors: Mohammad Khaleqi Qaleh Jooq, Fereshteh Behbahani, Amirali Amirsoleimani, Mostafa Rahimi Azghadi, Saeed Afshar

Institutions: Western Sydney University, York University, James Cook University

Language: English

Topic: Advanced Memory and Neural Computing

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,560

Funder: Georgia Institute of Technology