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 (P-r) than epi-Ge. With the interface engineering by a high-k AION, 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.

Automated summary

Epitaxial GeSn shows higher polarization capabilities than epi-Ge, and when combined with high-k AION for interface engineering, it enhances the reliability of FeCAPs. The simplified neuromorphic network, functioning as a differentiator circuit, not only performs LIF functions but also recognizes spatiotemporal features efficiently. This energy-efficient network, utilizing FeCAPs, is suitable for emerging spiking neural network hardware accelerators.