journal article·2026-04Open access

All‐Ferroelectric Memtransistors for Brain‐Inspired Computing

Jinhua Zeng, Chenyu Ye, Guangjian Wu, Huiting Wang, Qianru Zhao, Shuaiqin Wu, Xudong Wang, Tie Lin, Jun Ge, Hong Shen, Junhao Chu, Jianlu Wang

Advanced Functional Materials· Volume 36· Issue 34

Abstract

ABSTRACT In‐memory computing is pursued to overcome the memory and power walls inherent to the von Neumann architecture. However, heterosynaptic memtransistors with higher modulation dimensionality and enhanced memory capability still suffer from a limited conductance dynamic range and few gate‐controlled states, constraining learning precision. Here, an all‐ferroelectric memtransistor is demonstrated that synergistically combines a P(VDF‐TrFE) ferroelectric gate dielectric with an α‐In 2 Se 3 ferroelectric semiconductor channel. As the third‐terminal modulator, the P(VDF‐TrFE) gate sets the channel Fermi level via out‐of‐plane polarization reversal, while the channel's in‐plane polarization at the pre‐ and post‐synaptic drain and source asymmetrically tunes the contact Schottky barriers. The coupling of these two distinct ferroelectric effects generates four well‐separated nonvolatile conductance states in fully polarized configurations, introduces 12 third‐terminal states via ferroelectric‐gate domain control, and enables 100 intermediate states in the ferroelectric channel through source–drain pulses. The device emulates heterosynaptic regulation, enabling global enhancement or suppression of synaptic features. Compared with conventional designs, it offers a dynamic range of up to 331.91 and 12 gate‐controlled states. An adaptive neural network implemented with measured device characteristics achieves 95.68% pattern recognition accuracy, with gate pulses selecting optimal operational regimes. This work provides an effective device platform for high‐performance brain‐inspired computing.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Ferroelectric and Negative Capacitance Devices · Advanced Memory and Neural Computing · 2D Materials and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Infrared Physics Shanghai Institute of Technical Physics Chinese Academy of Sciences Shanghai China

University of Chinese Academy of Sciences Beijing China

College of Integrated Circuits and Micro‐Nano Electronics State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai China

Funding

National Key Research and Development Program of China · National Natural Science Foundation of China

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