Black Phosphorus/Ferroelectric P(VDF-TrFE) Field-Effect Transistors with High Mobility for Energy-Efficient Artificial Synapse in High-Accuracy Neuromorphic Computing

The neuromorphic system is an attractive platform for next-generation computing with low power and fast speed to emulate knowledge-based learning. Here, we design ferroelectric-tuned synaptic transistors by integrating 2D black phosphorus (BP) with a flexible ferroelectric copolymer poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)). Through nonvolatile ferroelectric polarization, the P(VDF-TrFE)/BP synaptic transistors show a high mobility value of 900 cm² V^-1 s^-1 with a 10³ on/off current ratio and can operate with low energy consumption down to the femtojoule level (∼40 fJ). Reliable and programmable synaptic behaviors have been demonstrated, including paired-pulse facilitation, long-term depression, and potentiation. The biological memory consolidation process is emulated through ferroelectric gate-sensitive neuromorphic behaviors. Inspiringly, the artificial neural network is simulated for handwritten digit recognition, achieving a high recognition accuracy of 93.6%. These findings highlight the prospects of 2D ferroelectric field-effect transistors as ideal building blocks for high-performance neuromorphic networks.