Recognizing Spatiotemporal Features by a Neuromorphic Network with Highly Reliable Ferroelectric Capacitors on Epitaxial GeSn Film

Epitaxial GeSn (epi-GeSn) shows the capability to form ferroelectric capacitors (FeCAPs) with a higher remanent polarization (Pr) than epi-Ge. With the interface engineering by a high-k AlON, the reliability of the epi-GeSn-based FeCAPs is enhanced. Using the highly reliable FeCAP in series with a resistor as the synapse and axon, a simplified neuromorphic network based on a differentiator circuit is proposed. The network not only holds the leaky integrate-and-fire (LIF) function but is also capable of recognizing the spatiotemporal features, which sets it apart from other LIF neurons arising from the FeCAP-modulated leaky behavior of the potential on the axon by spiking-time-dependent plasticity. Furthermore, it is more energy efficient to operate, nondestructive to read, and simpler to fabricate by employing FeCAPs, making it eligible for emergent spiking neural network hardware accelerators.