  Ferroelectric tunnel junctions (FTJ) based on hafnium zirconium oxide
(Hf1-xZrxO2; HZO) are a promising candidate for future applications, such as
low-power memories and neuromorphic computing. The tunneling electroresistance
(TER) is tunable through the polarization state of the HZO film. To circumvent
the challenge of fabricating thin ferroelectric HZO layers in the tunneling
range of 1-3 nm range, ferroelectric/dielectric double layer sandwiched between
two symmetric metal electrodes are used. Due to the decoupling of the
ferroelectric polarization storage layer and a dielectric tunneling layer with
a higher bandgap, a significant TER ratio between the two polarization states
is obtained. By exploiting previously reported switching behaviour and the
gradual tunability of the resistance, FTJs can be used as potential candidates
for the emulation of synapses for neuromorphic computing in spiking neural
networks. The implementation of two major components of a synapse are shown:
long term depression/potentiation by varying the amplitude/width/number of
voltage pulses applied to the artificial FTJ synapse, and
spike-timing-dependent-plasticity curves by applying time-delayed voltages at
each electrode. These experimental findings show the potential of spiking
neural networks and neuromorphic computing that can be implemented with
hafnia-based FTJs.
