High-Performance Organic Synaptic Transistors with an Ultrathin Active Layer for Neuromorphic Computing.

In recent years, much attention has been focused on two-dimensional (2D) material-based synaptic transistor devices because of their inherent advantages of low dimension, simultaneous read-write operation and high efficiency. However, process compatibility and repeatability of these materials are still a big challenge, as well as other issues such as complex transfer process and material selectivity. In this work, synaptic transistors with an ultrathin organic semiconductor layer (down to 7 nm) were obtained by the simple dip-coating process, which exhibited a high current switch ratio up to 106, well off state as low as nearly 10-12 A, and low operation voltage of -3 V. Moreover, various synaptic behaviors were successfully simulated including excitatory postsynaptic current, paired pulse facilitation, long-term potentiation, and long-term depression. More importantly, under ultrathin conditions, excellent memory preservation, and linearity of weight update were obtained because of the enhanced effect of defects and improved controllability of the gate voltage on the ultrathin active layer, which led to a pattern recognition rate up to 85%. This is the first work to demonstrate that the pattern recognition rate, a crucial parameter for neuromorphic computing can be significantly improved by reducing the thickness of the channel layer. Hence, these results not only reveal a simple and effective way to improve plasticity and memory retention of the artificial synapse via thickness modulation but also expand the material selection for the 2D artificial synaptic devices.