Analog Synapses Based on Nonvolatile FETs with Amorphous ZrO2 Dielectric for Spiking Neural Network Applications

In this article, an analog synapse based on a nonvolatile field-effect transistor with amorphous ZrO2 dielectrics has been fabricated and demonstrated. The conductance modulation properties of the devices have been systematically evaluated. Due to the polarization switching dynamics of the ferroelectric-like amorphous ZrO2 dielectric, which is attributable to the voltage-driven oxygen vacancies and negative charges dipoles, the proposed ZrO2-based devices exhibit superior synaptic characteristics, including good symmetry and linearity for both potentiation and depression, with small cycle-to-cycle variations. The ratio of maximum conductance and minimum conductance (G(max)/G(min)) of devices reaches 130, with conductance states over 30. Also, spike-timing-dependent plasticity (STDP) has been mimicked in the devices successfully. Furthermore, based on the experimental STDP characteristics and conductance modulation properties of potentiation and depression, a spiking neural network architecture constructed by the proposed ZrO2-based synapses has been simulated. High offline and online learning accuracy of 94% and 87%, respectively, on the handwritten digits dataset, has been achieved.