Oxide-Based Synaptic Transistors for Neuromorphic Systems

Abstract

Inspired by the energy-efficient and cognitive computational ability of a biological brain, neuromorphic computing is an attractive computation paradigm that complements the von Neumann architecture. Hardware implementations of synapses, dendrites and spiking neural networks represent a promising computational paradigm for solving complex pattern recognition and sensory processing tasks. Here, artificial electronic synapses and dendrites are proposed based on the oxide-based electrical-double-layer transistors. Strong electrostatic coupling effect and electrochemical doping were observed due to proton migration in the P-doped SiO2 electrolyte films. Protons in the P-doped SiO2 electrolyte and oxide channel conductance were regarded as the neurotransmitter and synaptic weight, respectively. Spike-timing dependent plasticity, short-term plasticity, including paired-pulse facilitation, dynamic filtering was mimicked. Most importantly, dendritic arithmetic and spiking pH sensors with extremely low energy dissipation of 0.5pJ are also demonstrated in a simple artificial synapse with multiple pre-synaptic inputs. Our oxide-based protonic/electronic hybrid artificial synaptic transistors are potential building blocks for brain-inspired computers and neuromorphic systems. [1] L. Q. Zhu, C. J. Wan, L. Guo, Y. Shi, and Q. Wan*. Nature Communications, 5, 3158, 2014. [2] C. J. Wan, L. Q. Zhu, J. M. Zhou, Y. Shi, Q. Wan*. Nanoscale. 6, 4491, 2014. [3] C.J. Wan, L. Q. Zhu, Y. H. Liu, Y. Shi, and Q. Wan*. IEEE Electron Device Letters. 35, 672, 2014. [4] L.Q. Guo, Q. Wan*, C. J. Wan, L. Q. Zhu, Y. Shi. IEEE Electron Device Letters. 34,1581, 2013. [5] M.Z. Dai, Q. Wan*. Nano Letters 11, 3987, 2011.