  Event-based neuromorphic systems provide a low-power solution by using
artificial neurons and synapses to process data asynchronously in the form of
spikes. Ferroelectric Tunnel Junctions (FTJs) are ultra low-power memory
devices and are well-suited to be integrated in these systems. Here, we present
a hybrid FTJ-CMOS Integrate-and-Fire neuron which constitutes a fundamental
building block for new-generation neuromorphic networks for edge computing. We
demonstrate electrically tunable neural dynamics achievable by tuning the
switching of the FTJ device.
