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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