Fully solution-processed ferroelectric thin film transistor based on PZT and its application in neuromorphic computing

As a promising alternative to conventional computing paradigms, the neuromorphic computing has been demonstrated by using various artificial synaptic devices. Due to the excellent capability for the conductance modulation, the ferroelectric thin film transistors (FeTFTs) have been shown as one of the promising candidates for artificial synaptic devices. In this work, the FeTFTs based on the lead zirconate titanate (PZT) thin films were integrated by the fully solution process. Prior to the integration of the FeTFTs, a lanthanum nickelate (LNO) thin film was prepared as the seed layer. The introduction of the LNO has been demonstrated to improve the crystallinity of the PZT thin films. It is confirmed that the channel conductance of the FeTFTs can be precisely modulated by adjusting the amplitude, duration, and number of the pulses. The potentiation and depression (P-D) characteristics of the FeTFTs have been demonstrated, and the P-D curve shows low nonlinearity and small cycle-to-cycle variations. Based on the P-D characteristics of the FeTFTs, an artificial neural network has been constructed for the pattern recognition, and a recognition accuracy of 93.1% has been achieved. These results suggest that the fully solution-processed FeTFTs based on PZT are the promising candidate for the artificial synaptic devices.

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Publication Details

Journal
Applied Physics Letters
Published
2025-04-21
DOI
https://doi.org/10.1063/5.0263232
Citations
5
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
3.65

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article

Fully solution-processed ferroelectric thin film transistor based on PZT and its application in neuromorphic computing

Wenlan Xiao, Chunyan You, Fukai Shan, Guangtan Miao et al.
5 citations
Applied Physics Letters
Advanced Memory and Neural Computing
3.65
article

Fully solution-processed ferroelectric thin film transistor based on PZT and its application in neuromorphic computing

Wenlan Xiao, Chunyan You, Fukai Shan, Guangtan Miao, Dong Yao, Guoxia Liu
article en
5 citations

Abstract

As a promising alternative to conventional computing paradigms, the neuromorphic computing has been demonstrated by using various artificial synaptic devices. Due to the excellent capability for the conductance modulation, the ferroelectric thin film transistors (FeTFTs) have been shown as one of the promising candidates for artificial synaptic devices. In this work, the FeTFTs based on the lead zirconate titanate (PZT) thin films were integrated by the fully solution process. Prior to the integration of the FeTFTs, a lanthanum nickelate (LNO) thin film was prepared as the seed layer. The introduction of the LNO has been demonstrated to improve the crystallinity of the PZT thin films. It is confirmed that the channel conductance of the FeTFTs can be precisely modulated by adjusting the amplitude, duration, and number of the pulses. The potentiation and depression (P-D) characteristics of the FeTFTs have been demonstrated, and the P-D curve shows low nonlinearity and small cycle-to-cycle variations. Based on the P-D characteristics of the FeTFTs, an artificial neural network has been constructed for the pattern recognition, and a recognition accuracy of 93.1% has been achieved. These results suggest that the fully solution-processed FeTFTs based on PZT are the promising candidate for the artificial synaptic devices.

Applied Physics LettersVol. 126(16)
Qingdao University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Shandong Province, National Key Research and Development Program of China
Openalex Percentile: Top 7%
Advanced Memory and Neural Computing
3.65
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