Multi‐Terminal Operability in Van Der Waals Ferroelectric Field‐Effect Memtransistors for Logic‐in‐Memory and Neuromorphic Computing

Abstract Ferroelectric‐based non‐volatile memories (NVMs), which can merge logic and memory functionalities within a single device, represent a promising solution for future in‐memory computing architecture. Although various types of ferroelectric‐based NVM are demonstrated, a device concept integrating compact structure, reconfigurable operation and superior performance that can meet the demands of the emerging in‐memory computing remains to be explored. Here, a new type of device termed ferroelectric field‐effect memtransistor (FeFEMT) is reported, which features a multifunctional device operation scheme using the proposed multi‐terminal operability. In this device, multi‐level non‐volatile conductance switching based on the ferroelectric polarisation switching and the multidomain structure can be achieved with either gate‐ or drain‐voltage control. The device operates with control voltage inputs from both drain and gate terminals, enabling a single‐transistor structure two‐input Boolean logic‐in‐memory gate. Furthermore, the drain‐voltage controlled multidomain structure enables the FeFEMT to function as a two‐terminal synaptic transistor, showing excellent analogue conductance switching with over 7‐bit conductance states. The demonstrated synaptic properties consequently facilitate the simulation of implementation of a convolutional neural network, offering a superior inference performance. These findings highlight the prospects of the FeFEMTs as a suitable device technology for diverse and high‐efficiency in‐memory computing hardware platform.

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Publication Details

Journal
Advanced Functional Materials
Published
2025-10-07
DOI
https://doi.org/10.1002/adfm.202523298
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Multi‐Terminal Operability in Van Der Waals Ferroelectric Field‐Effect Memtransistors for Logic‐in‐Memory and Neuromorphic Computing

Zheng‐Dong Luo, Xuetao Gan, Fei Xue, Fei Xiao et al.
Advanced Functional Materials
Advanced Memory and Neural Computing
article

Multi‐Terminal Operability in Van Der Waals Ferroelectric Field‐Effect Memtransistors for Logic‐in‐Memory and Neuromorphic Computing

Zheng‐Dong Luo, Xuetao Gan, Fei Xue, Fei Xiao, Genquan Han, Yue Hao, Yinshui Xia, Marin Alexe, Yan Liu, Dawei Zhang, Wenchao Chen, Junpeng Zhang, Dongxin Tan, Liang Tian, Qiyu Yang, Zhufei Chu
article en

Abstract

Abstract Ferroelectric‐based non‐volatile memories (NVMs), which can merge logic and memory functionalities within a single device, represent a promising solution for future in‐memory computing architecture. Although various types of ferroelectric‐based NVM are demonstrated, a device concept integrating compact structure, reconfigurable operation and superior performance that can meet the demands of the emerging in‐memory computing remains to be explored. Here, a new type of device termed ferroelectric field‐effect memtransistor (FeFEMT) is reported, which features a multifunctional device operation scheme using the proposed multi‐terminal operability. In this device, multi‐level non‐volatile conductance switching based on the ferroelectric polarisation switching and the multidomain structure can be achieved with either gate‐ or drain‐voltage control. The device operates with control voltage inputs from both drain and gate terminals, enabling a single‐transistor structure two‐input Boolean logic‐in‐memory gate. Furthermore, the drain‐voltage controlled multidomain structure enables the FeFEMT to function as a two‐terminal synaptic transistor, showing excellent analogue conductance switching with over 7‐bit conductance states. The demonstrated synaptic properties consequently facilitate the simulation of implementation of a convolutional neural network, offering a superior inference performance. These findings highlight the prospects of the FeFEMTs as a suitable device technology for diverse and high‐efficiency in‐memory computing hardware platform.

Advanced Functional MaterialsVol. 36(18)
Ningbo University (CN), Xidian University (CN), Northwestern Polytechnical University (CN), University of Warwick (GB), Zhejiang University-University of Edinburgh Institute (CN), Zhejiang University (CN), Ministry of Industry and Information Technology (CN)
Openalex Percentile: Top 72%
Advanced Memory and Neural Computing
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