Flexible and Energy-efficient Synaptic Transistor with Quasi-linear Weight Update Protocol by Inkjet Printing of Orientated Polar-electret/High-k Oxide Hybrid Dielectric

Abstract

Artificial synapse by inkjet printing is promising in cost-effective and flexible applications, but remains challenging in emulating synaptic dynamics with a sufficient number of stable and effective conductance states under ultra-low voltage spiking operation. Hence, for the first time, a synaptic transistor gated by inkjet-printed hybrid dielectric of electret polyvinyl pyrrolidone (PVP) and high-k Zirconia oxide (ZrOx) is proposed and thus synthesized to solve this issue. Quasi-linear potentiation/depression characteristics with large variation margin of conductance states are obtained through the coupling of these two dielectric components and the facilitating of dipole orientation, which can be attributed to the orderly arranged molecule chains induced by the carefully designed microfluidic flows in droplets. Crucial features of biological synapses including long-term potentiation/depression (LTP/D), spike-timing-dependence-plasticity (STDP) learning rule, “Learning-Experience” behavior, and ultralow energy consumption (< 10 fJ/pulse) are successfully implemented on the device. Simulation results exhibit an excellent image recognition accuracy (97.1 %) after 15 training epochs, which is the highest for printed synaptic transistors. Moreover, the device sustained excellent endurance against bending tests with radius down to 8 mm. This work presents a very viable solution for constructing the futuristic flexible and low-cost neural systems.